Manhattan Scientist 2015

The Manhattan Scientist Series B Volume 2 Fall 2015

A journal dedicated to the work of science students

The Manhattan Scientist Series B

Volume 2

Fall 2015

ISSN 2380-0372

Student Editors Sana Saeed Biology Paul Markaj Chemistry Gregory Zajac Mathematics Thomas Reid Physics Faculty Advisor and Editor in Chief

Constantine E. Theodosiou, Ph.D.

Manhattan College

4513 Manhattan College Parkway, Riverdale, NY 10471 Student Handbook manhattan.edu

Series B

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Volume 2 (2015)

A note from the dean The present Volume includes twenty four papers, covering all disciplinary subjects of the School of Science at Manhattan College. These activities continue to be aligned with the College’s mission, to “provide a contemporary, person-centered educational experience that prepares graduates for lives of personal development, professional success, civic engagement, and service to their fellow human beings.” The quality of the projects is indicative of our students and faculty and their commitment to research as part of the students’ educational experience. The participants ranged from a High School summer intern, to primarily undergraduate students of all our majors, to graduate students in Mathematics. I would like to particularly express our gratitude to the faculty who willingly provided critical mentoring to our students and future colleagues. Most of the faculty received minimal or no compensation for these efforts.

This work would not have been possible without the availability of substantial financial support for our students. This support came from the School of Science Research Scholars Program, the Jasper Scholars Program of the Office of the Provost, the Catherine and Robert Fenton endowed chair in Biology, the Linda and Dennis Fenton ’73 endowed biology research fund, the Michael J. ’58 and Aimee Rusinko Kakos endowed chair in Chemistry, and Jim Boyle, ’61.

The student editors, all volunteers, worked hard to bring, from very diverse author styles, some uniformity and the proper scientific style to the manuscripts, necessary for publishing in professional journals. I would like to express my deep appreciation for their efforts. We are all honored to showcase our students’ and colleagues’ continuing contributions to the body of scientific knowledge. It is, therefore, with great pleasure that the editors present the publication of Series B, Volume 2, of The Manhattan Scientist.

Constantine Theodosiou Dean of Science and Professor of Physics

ISSN 2380-0372

Series B

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Volume 2 (2015)

Table of Contents Biology Detection of human intestinal parasites in kangaroo rat (Dipodomys Merriami) feces Inas Abuhaikal and Christopher Annabi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Analysis of bending stresses of terminal tree branches Domenick Avanzi and Katherine Petrizzo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Rates of bark formation on surfaces of saguaro cactus plants Lauren Barton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 Irregular stem growth in Artemisia trdendata var wyomingensis Tiffany Kharran . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 Prevalence of human intestinal parasites in Atlantic oysters (Crassostrea virginica) Steven Michael Kowalyk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 Effects of Batrachochytrium dendrobatidis and urbanization on P. cinereus in lower New York State Andrew Paramo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 A pathway of development: The impact of knocking down the kv2.1 and FAK protein coding genes in zebrafish embryos Olivia Payne . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 Microhabitat use by an urban salamander population Mary Portes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 Metabolism as a bioassay of environmental stressors: Hemigrapsus sanguineus as a model organism Zachary Scheid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 Xylem conductivity in twenty-two cactus species of South America Kristen Skonieczny . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 Evidence of Cryptosporidium spp. in three bivalve species collected from Orchard Beach, New York Freda Fafah Ami Tei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95

Chemistry and Biochemistry A density functional study of proton acidity in the thiazolium ring Anthony DiProperzio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 Quenching of Ru(bpy)3 2+ emission by binding to Ag nanoparticles Matthew Feliciano . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111 Luminescence response of ruthenium(II) diammine complexes to polyanionic carrageenans and heparins Matthew Feliciano and Marisa Kroger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 Crystal sructure refinement of ZSM-18 Corine LaPlanche . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 Strategies for the remediation of ground water containing hexavalent chromium: Insoluble . . .

Paul Markaj . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 New synthetic uses for thiazolium salt derivatives Joseph Mozdzierz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 Trash to treasure: Utilization of waste shells for biodiesel synthesis Adrienne Perea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148

Computer Science Monte Carlo investigations of ideal two dimensional linear polymers Adam J. Barillas and Tylor Borgeson . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151

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Mathematics Visualization of xylary rings of stems of Artemisia tridentata spp. Wyomingensis.

Michael Scarinci and Katherine Encarnacion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157 Statistical modelling and the college experience.

Greg Zajac . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165

Physics Study of Higgs boson production in different channels at the Large Hadron Collider Dylan Gray . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171 Fractal analysis of diffraction and interference patterns Cristina Hibner . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181 Limits on Higgs Boson couplings in Effective Field theories Thomas Reid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187

On the cover: The framework of ZSM-18 with the trisquat in the middle of the large cavity.

Atoms shown are N (in blue), C (yellow), H (gray), Si (purple), and O (red). For clarity, the H atoms on the arms of trisquat are not shown. Calculations performed using the facilities of the Kakos Center for Scientific Computing.

Detection of human intestinal parasites in kangaroo rat (Dipodomys Merriami) feces Inas Abuhaikal∗ Department of Chemistry and Biochemistry, Manhattan College Christopher Annabi∗ Fordham Preparatory School, Bronx, NY 10458 Abstract. Parasites pose health risks to both humans and animals. While some parasites infect only animals, the majority are zoonotic, capable of being transmitted from animals to humans. Dipodomys merriami, also known as kangaroo rats, are commonly found in arid areas in the southwestern United States and Mexico. Although they are primarily found in the wild, kangaroo rats have been increasingly observed in public parks. To determine whether kangaroo rats could be used to sample the environment for human parasites, fecal samples were collected from 69 individual kangaroo rats between May and September 2014 in a public park in Las Cruces, New Mexico. DNA was isolated from each of the samples and analyzed for the presence of three human intestinal parasites by the polymerase chain reaction using primers specific for Cryptosporidium parvum, Toxoplasma gondii, and Giardia lamblia, respectively. We found that 4/69 of the samples were positive for Cryptosporidium spp., resulting in a 5.8% prevalence of Cryptosporidium spp. Likewise, 6/69 of the fecal samples were positive for G. lamblia, resulting in 8.69% prevalence.

Further, we observed genetic heterogeneity among the Giardia isolates detected in the kangaroo rats. We observed the zoonotic assemblage B in 3 fecal samples. In addition, the host-specific assemblage E was also detected. Surprisingly, the common assemblage A was not observed in our study. In contrast, T. gondii was not detected in the sample tested.

In summary, kangaroo rats are a good model system for sampling the environment for human intestinal parasites.

Introduction Wild animals, including rodents, are often infected with a wide range of microbes. They also play an important role in the enzootic and zoonotic cycles of eukaryotic microbes. Recently, the California kangaroo rats, Dipodomys californicus, was shown to be the preferred host for Borrelia californiensis, the agent of Lyme disease [1]. Several groups have investigated the ectoparasites associated with small rodents and have uncovered fleas and ticks of the genus Ixodes as common to kangaroo rats [2, 3, 4, 5, 6]. However, very little is known about the endoparasites of kangaroo rats.

Additionally, the role of these rodents in the maintenance of human intestinal parasites has not been explored. In the United States, protozoans of the genus Giardia, are very common. In an aquatic environments, beavers play an important role in the transmission of Giardia. Most human intestinal parasites are responsible for serious diseases in humans and can be transmitted from animals to humans. Toxoplasma gondii is responsible for the disease toxoplasmosis, which is devastating to pregnant women and those with a weakened immune system. Likewise, Cryptosporidium parvum, a zoonotic parasite, classified as bioterrorism agents causes the disease cryptosporidiosis, which is debilitating to individuals with a compromised immune system. Giardiasis is a very common intestinal disease caused by Giardia lamblia. These three parasites have a zoonotic life cycle ∗

Research mentored by Ghislaine Mayer, Ph.D.

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Figure 1. Life Cycle of T. gondii

Figure 2. Life Cycle of Giardia lamblia

Figure 3. Life Cycle of C. parvum

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Figure 4. Collection site and sample used in this study

(Figs. 1-3). It is imperative to identify to investigate the transmission cycle of these parasites by determining the role of rodents as potential hosts. The polymerase chain reaction (PCR), although not commonly used for parasite detection, is highly sensitive and reliable. The goal of current study is to determine whether rat kangaroos (Dipodomys merriami) are suitable terrestrial bio-sentinels for the human intestinal parasites Toxoplasma gondii, Cryptosporidium parvum, and Giardia lamblia by assessing their exposure to these parasites.

Materials and Methods Stool samples were collected from 68 Dipodomys merriami individuals in Las Cruces, NM (Figs. 4-5). DNA was purified from stool samples using the Qiagen Stool DNA kit (Qiagen, Valencia, CA). The purified DNA was quantitated using a UV spectrophotometer (Shimatzu, Tokyo, Japan). Parasite specific primers at 20 pmol/µL in a final volume of 25 µL were used.

To detect G. lamblia, nested-PCR was performed using primers that target the β-giardin gene following a previously described protocol [7]. The forward primer for the first reaction was Gia7 (5’-AAGCCCGACGACCTCACCCGCAGTGC-3’) and the reverse primer was Gia759 (5’GAGGCCGCCCTGGATCTTCGAGACGAC-3’). The nested PCR reaction was amplified using the forward primer (5’-GAACGAACGAGATCGAGGTCCG-3’) and the reverse primer (5’CTCGACGAGCTT CGTGTT-3’). The genotype was assessed by digesting the amplicons with the restriction endonuclease HaeIII. Briefly, 20 µL of the total volume PCR reactions were di-

Figure 5. Dipodomys meriammi

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gested with 10 unit of HaeIII for 4 h at 37 ◦ C. To detect the presence of C. parvum DNA, PCR was performed using the LAX primer pairs previously described to specific for C. parvum [8, 9].

The primer sequences are as follows forward: LAX469F 5’-CCGAGTTTGATCCAAAAAGTT ACGAA-3’, and LAX869R 5’-TAGCTCCTCATATGCCTTATTGAGTA-3’. The following conditions were used: 94 ◦ C for 3 min, 94◦ C for 45 s, 52◦ C for 45 s, and 72◦ C for 1 min, a final extension at 72◦ C for 7 min [9]. T. gondii DNA was detected by using the T. gondii GRA6 primer sets (forward 5’-GTAGCGTGCTTGTTGGCGAC- 3’, reverse primer, 5’ACAAGACATAGAGTGCCCC3’). The PCR reactions were performed as described by Fazaeli et al. [10]. Purified DNA from each parasite was used as a positive control. Water was used as a negative control. PCR products were detected by agarose gel electrophoresis. G. lamblia was genotyped by restriction fragment length polymorphism using the HaeIII enzyme (New England Biolabs).

Results and Discussion To determine the prevalence of C. parvum DNA in kangaroo rat feces, PCR analysis was conducted using genus-specific primers. We found a 5.8% (4/68) prevalence of C. parvum in the samples collected (Table 1 and Fig. 6). The prevalence of G. lamblia DNA was 8.8% (6/68) (Table 1 and Fig. 6), indicating exposure of the kangaroo rats to C. parvum oocysts and G. lamblia parasites. In contrast, none of the samples tested positive for T. gondii. We observed a case of coinfection with C. parvum and G. lamblia in one of the sample collected in Las Cruces, NM. Genetic variation is frequent in G. lamblia parasites [11, 12]. Seven genotypes are established as distinct evolutionary lineages by restriction fragment length polymorphism (RFLP) [13]. They differ in metabolism, drug sensitivity, and host preference [12, 13]. G. lamblia assemblages A and B only infect humans and cats, while assemblages C and D infect dogs. Cows and other hoofed animals are infected by assemblage E [13]. Moreover, assemblage F infects cats only, while assemblage G only infects rodents [13]. We were able to determine the genotype of 5/6 G. lamblia-positive samples. We found that 50% of the G. lamblia-positive samples were of the B assemblage, with an overall prevalence of 4.4% (Fig. 6). On the other hand, 33% of G. lamblia-positive samples belonged to assemblage E, with an overall prevalence of 2.9% (Fig. 7). These data suggest that the source of the contamination might either be humans, cats, or hoofed animals. Interestingly, we did not detect assemblage G, the rodent-specific genotype in our samples. Our data indicate that kangaroo rats have the potential to be a good bio-sentinels for terrestrial environment. In the future, we will determine whether there is change in the prevalence of these three human intestinal parasites over time. We will also assess whether temporal variation in the parasites genotypes.

Table 1. Prevalence of human intestinal parasites in kangaroo rats (Dipodomys merriami) from Las Cruces, NM. Kangaroo rats fecal samples

Cryptosporidium spp.

G. lamblia

T. gondii

(4/68) 5.8%

(6/68) 8.8%

(0/68) 0%

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Figure 6. PCR analysis of DNA isolated from Dipodomys merriami feces . A) Detection of C. parvum DNA . First Row: Lane 1: 100 bp marker, Lane 2: positive control, Lane 3-20 Dipodomys merriami DNA samples. Second Row: Lane 1: 100 bp marker, Lane 2-4 Dipodomys merriami sample DNA. Lane 5: Empty, Lane 6: negative control. B) Detection of T. gondii DNA. First Row: Lane 1: 100 bp marker, Lane 2-15: Dipodomys merriami DNA samples.

Second Row: Lane 1: 100 bp marker, Lane 2-5: Dipodomys merriami DNA samples, Lane 6: positive control, Lane 7: Empty, Lane 8: negative control. C) Detection of G. lamblia DNA. Lane 1: 100 bp marker, Lane 2-20: Dipodomys merriami DNA samples. Second Row: Lane 1: 100 bp marker, Lane 2-5: Dipodomys merriami DNA samples, Lane 6: positive control 1, Lane 7: positive control 2, Lane 8: empty, Lane 9: negative control.

Figure 7. RFLP analysis of G. lamblia assemblages. Lane 1: 100 bp marker, Lane 2: sample 215, assemblage B, Lane 2:-sample 225, assemblage B, Lane 3: sample 227, assemblage E, Lane 4: sample 228, assemblage E, Lane 5: sample 224, assemblage B, Lane 6: ND. ND: Not determined.

Conclusions We have demonstrated the presence of C. parvum and G. lamblia DNA in fecal samples collected from kangaroo rats in Las Cruces, New Mexico. Our study is the first report of these protozoan human intestinal parasites in these small rodents. This might have implications for public health.

Acknowledgement The authors would like to thank Dr. Ghislaine Mayer for guididance and support during this project.

References [1] Peavy, C.A., Lane, R.S., Kleinjan, J.E. “Role of small mammals in the ecology of Borrelia burgdorferi in a peri-urban park in north coastal California.� http://www.ncbi.nlm.nih.gov

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/pubmed/9291589 Exp. Appl. Acarol. 1997, 21, 569-84.

[2] Brown, R.N., Peot, M.A., Lane, R.S. http://www.ncbi.nlm.nih.gov /pubmed/16892634 Sylvatic maintenance of Borrelia burgdorferi (Spirochaetales) in Northern California: untangling the web of transmission. J. Med. Entomol. 2006, 43, 743-51.

[3] Salkeld, D.J., Eisen, R.J., Antolin, M.F., Stapp, P., Eisen, L. http://www.ncbi.nlm.nih.gov /pubmed/16859106 Host usage and seasonal activity patterns of Ixodes kingi and I. sculptus (Acari: Ixodidae) nymphs in a Colorado prairie landscape, with a summary of published North American host records for all life stages. J. Vector Ecol. 2006, 31, 168-80.

[4] Tabor, S.P., Williams, D.F., Germano, D.J., Thomas, R.E. http://www.ncbi.nlm.nih.gov /pubmed/8433341 Fleas (Siphonaptera) infesting giant kangaroo rats (Dipodomysingens) on the Elkhorn and Carrizo Plains, San Luis Obispo County, California. J. Med. Entomol. 1993, 30, 291-4.

[5] Waudby, H.P., Petit, S., Dixon, B., Andrews, R.H. Waudby, H.P., Petit, S., Dixon, B., Andrews, R.H. http://www.ncbi.nlm.nih.gov/pubmed/17611781Hosts of the exotic ornate kangaroo tick, Amblyomma triguttatum Koch, on southern Yorke Peninsula, South Australia.

Parasitol. Res. 2007, 101,1323-30. Epub 2007.

[6] Brown, R.N., Lane, R.S. http://www.ncbi.nlm.nih.gov/pubmed/1604318Lyme disease in California: a novel enzootic transmission cycle of Borrelia burgdorferi. Science. 1992, 256,143942. Brown, R.N., Lane, R.S. http://www.ncbi.nlm.nih.gov/pubmed/1604318Lyme disease in California: a novel enzootic transmission cycle of Borrelia burgdorferi. Science. 1992, 256,1439-42.

[7] Hong, S.H.,Anu, D.,Jeong Y.I.,Abmed, D.,Cho, S.H.,Lee, W.J.,Lee, S.E. Molecular characterization of Giardia duodenalis and Cryptosporidium parvum in fecal Samples of individuals in Mongolia. Am. J. Trop. Med. Hyg. 2014, 90, 43-7.

[8] Laxer, M. A., B. K. Timblin, R. J. Patel. 1991. DNA sequences for the specific detection of Cryptosporidium parvum by the polymerase chain reaction. Am. J. Trop. Med. Hyg. 1991, 45, 688–694.

[9] Rochelle, P.A., De Leon, R., Stewart, M.H., Wolfe, R.L. Comparison of Primers and Optimization of PCR conditions for detection of Cryptosporidium parvum and Giardia lamblia in water. Applied and Environmental Microbiology. 1997, 63, 106-114.

[10] Fazaeli, A., Cartera, P.E., Dardeb, M.L., Pennington, T.H. Molecular typing of Toxoplasma gondii strains by GRA6 gene sequence analysis. Int. J. Parasitol. 2000, 30, 637-642.

[11] Andrews, R.H., Adams, M., Boreham, P.F., Mayrhofer, G., Meloni, B.P. Giardia intestinalis: electrophoretic evidence for a species complex. Int. J. Parasitol. 1989, 19, 183–190.

[12] Monis, P.T., Caccio, S.M., Thompson, R.C.A. Variation in Giardia: towards a taxonomic revision of the genus. Trends Parasitol. 2009, 25, 93–100. 1016/j.pt.2008.11.006.

[13] Lalle, M., Pozio, E., Capelli, G., Bruschi, F., Crotti, D., Simone M. Caccio, S.M. Genetic heterogeneity at the β-giardin locus among human and animal isolates of Giardia duodenalis and identification of potentially zoonotic subgenotypes. Int. J. Parasitol. 2005, 35, 207-213.

Bending Stress Characteristics of Terminal Tree Branches Dominick Avanzi∗ Department of Mechanical Engineering, Manhattan College Katherine Petrizzo∗∗ Department of Biology, Manhattan College Abstract. Trees have an almost infinite array of morphologies. Tree branch morphologies are the result of natural bending stresses in response to the physical and mechanical properties of the branch. The mechanical properties of tree branches were analyzed using Finite Element Models (FEM) in which models were created and simulated using Abaqus FEM software. Terminal branches were sampled from 22 species of trees and large shrubs exhibiting various bending stress configurations. Six individual experiments were conducted to study bending stresses. As branch length was increased, the bending stress increased. As branch stem diameter was increased, the bending stress increased.

When a branch’s natural curvature was reduced or eliminated, overall bending stress decreased. On average, a branch’s stress without leaves was 0.094 times smaller than when leaves were present. As side-branch angle was increased, the maximum bending stress increased. Only when the side-branch was orthogonal to the main-branch did the maximum bending stress decreased. As leaf mass was artificially increased, the bending stress proportionally increased with a one to one ratio. When artificial leaves were placed between each pair of actual leaves, the bending stress increased on average by 1.9 times. These results provided understanding into branch stresses with regard to geometry, sizing, natural bending, weight and location of leaves, and overall branch morphology.

Introduction Land plants have a wide range of growth forms with distinctive morphologies. The evolution of land plants favors species that can provide maximal growth, whether vertically or horizontally, in order to maximize leaf area; larger leaf areas can obtain more light absorption for photosynthesis.

Different growth forms are attributed to branch arrangement which affects the development and reproduction capabilities of the tree. These morphologies are directly impacted by material and mechanical properties, most notably are branch geometries.

Material and mechanical properties of branches are directly related to the natural bending stress of the branch. Material properties include density while mechanical properties include Modulus of Elasticity (MOE) and Poisson’s ratio.

A previous study focused on a theoretical analysis of tree branch geometries (Shahbazi et al., 2015). The previous study described six testable cases with varying branch geometry and material differences. The main purpose of the current study was to test these theoretical findings with tree branches. Actual tree branches exhibit a variety of geometric and material differences including: circular, elliptical, curvy, or tapered cross sections and non-uniform material properties throughout the branch (MOE and density). ∗

Research mentored by Zahra Shahbazi, Ph.D. Research mentored by Lance Evans, Ph.D.

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Leaves have the ability to alter the location of maximum bending stress as they add considerable weight to the branch. The stress they add to the branch depends on factors such as leaf mass, stem diameter and branch length. Leaf morphologies vary greatly among species. Larger leaves provide higher surface area for photosynthesis but consequently add more stress to the branch.

It was important to verify the predictions made previously through the use of Finite Element Analysis (FEA) software (Shahbazi et al., 2015). As a result, the use of FEA was paramount in order to draw conclusions. Using a fully developed method, tree branches were found, cut, measured, simulated and analyzed (Shahbazi et al., in preparation).

The current study was designed to determine relationships between (1) branch bending stresses as a function of branch lengths, (2) branch bending stresses as a function of branch diameter per segment mass, (3) branch bending stress as a function of branch geometries, (4) branch bending stresses with and without the presence of leaves, (5) branch bending stresses as a function of sidebranch angles, and (6) branch bending stresses as a function of leaf masses and placements.

Materials and Methods General Methods Tree species used in this experiment were selected from trees from the Manhattan College Campus in the Bronx, NY from early June to early August 2015. Branches were selected from angiosperm trees that showed significant growth at branch terminals (between 13 - 40 cm in length).

Specifically, these terminal branch samples had no bark formation. Tree species (Table 1) were identified using Kershner et al. (2008) and Little et al. (1980). All branch terminals used for this study were horizontal. Branches were removed from trees for analysis. Photographs of sampled trees and of the branches were archived. The location of each tree was recorded. The branches obtained had normal characteristics for the species. Once samples were brought to the laboratory, additional photographs were archived.

Leaves were numbered from the tip toward the base of each branch. Leaf areas were obtained with a leaf area meter (LI-Cor 3100c, Li-Cor Corporation, Lincoln, NB) to the nearest 0.01 cm2 .

The mass of each leaf was obtained with a balance (OHAUS Adventurer, www.ohaus.com) to the nearest 0.01 grams. Many diameter measurements were taken along the branch with a digital caliper (Fisher Scientific Catalog number S405032D, www.FisherSCI.com) to the nearest 0.01 mm. In order to determine the MOE and to calculate bending stress, the branch was held horizontally at the base from a ring stand with a clamp over a piece of paper and points were made where each node was located using a plumb bob. This procedure provided x and y distances of the branch. The z distance was recorded as the measured height from the paper to the branch. A known weight was hung off the tip of the branch which measured the deformation angle of the branch. The branch was cut at each internode so all internode masses and total mass of the branch were obtained. Data were analyzed with Microsoft Excel (www.microsoft.com).

The characteristics of each species can be seen in Table 1. Since no bark was present on the terminal branches tested, a uniform density and MOE were assumed throughout the lengths of

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Table 1. Characteristics of terminal branch segments of several tree species Genus

Species

Acer Catalpa Hamamelis Juglans Liriodendron Malus Morus Prunus Tilia Ulmus

platanoides speciosa virginiana nigra tulipifera angustofolia rubra pensylvanica americana americana

1,2

Authority

Phyllotaxy

Number of Leaves

Average Density (kg/m3 )

Average MOE (109 )

L. Warder.

L. L. L. Michx.

L. L. L. L.

Opposite Alternate Alternate Alternate Alternate Alternate Alternate Alternate Alternate Alternate

4/4 11/12 15/15 24/22 8/8 14/15 8/10 12/11 8/8 10/10

539/570 1059/991 1310/1121 1260/1140 880/726 1130/1230 1090/814 760/756 683/698 937/794

1.76/1.93 7.06/0.77 4.62/22.7 4.83/5.89 1.07/0.74 3.36/5.03 1.70/1.01 2.50/2.63 0.72/0.25 1.81/1.15

For several species listed above there are two samples

branches tested (Mencuccini et al., 1997). Since branches were relatively short and only included tissues without bark, our assumption of uniform density and MOE are good approximations. Assuming a uniform density and MOE helped to simplify the Abaqus (Dassault Syst`emes Simulia Corp., 2013) calculations. In this study branches were treated similarly to cantilever beams, in that they were fixed at the basal end and exposed to point loads across the length of the branch.

The bending stresses (σ) were calculated using the following equation for cantilever beams σ=

Mc I

(1)

where M is the bending moment, c is the radial distance measured from the neutral axis of the branch, and I is the moment of inertia around the neutral axis (Shames et al., 2000). The moment of inertia, I, was calculated by 1 (2) I = M R2 2 where M is still the bending moment and R is the radius of the branch. Using dimensional analysis for the above formulas stress can be rewritten as 1 σ ∼ L2 ρE r

(3)

where L is the length of the branch, r is branch radius, ρ is density, and E is young’s modulus (MOE). This was significant because it provides strong theoretical insight to see how stress was affected by certain properties. However, it must be noted that this experiment utilized Finite Element Method (FEM) analysis (Widas, 1997), which employed an alternative method to calculate bending stress. Eq. (3) was useful when determining how much impact each physical/material property holds when calculating bending stress.

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Finite element method (FEM) is a computerized method used to predict how a branch will react to physical effects such as mechanical stress. FEM uses a complex system of points called nodes which form a grid called a mesh. The model contains the material and structural properties which define how the structure will react to certain loading conditions. The models are assigned a certain density throughout the material depending on the expected stress levels of a particular area (Widas, 1997). Abaqus software uses FEM and is capable of creating three-dimensional models and calculating mechanical properties including stress, strain, and deformation. For this study, a three-dimensional volumetric wire model was created using experimental branch data through a previously developed method (Shahbazi et al., In preparation). Leaves were represented as concentrated, static, point loads at each node. A gravitational force was applied across the entirety of the branch to ensure a proper approach. Branches were fixed at their bases ensuring that the branch could not be displaced or rotated. Each model was exposed to finite element analysis to determine bending stresses.

Bending stresses versus branch lengths The first objective was to determine branch bending stresses as a function of branch lengths.

Species considered for analysis were selected from the initial data collection. Only species used for this analysis needed relatively similar density, elasticity, and MOE throughout their branches.

For each selected branch, data along four stem segments were selected by restricting the amount of data along each branch. Each branch was subjected to a second, identical FE analysis. The second FE analysis was run to obtain the maximum bending stresses at the new lengths for the branch with and without leaves.

Bending stresses and diameters per branch segment mass The second objective was to determine branch bending stresses as a function of diameter per unit mass. In a similar manner as the case above, all selected branches were compared for similar diameters, MOE’s, and densities. As done above, each case was subjected to FE analysis with their averaged MOE and density values. The stress values were recorded and plotted using a ratio of diameter per unit mass. Considering stem diameters per unit segment mass was vital, allowing for a scale comparison among all species tested.

Bending stresses versus branch geometries The third objective was to determine bending stress as a function of a variety of branch geometries. For these analyses branch curvatures or natural bends were considered.

Theoretical analyses The purpose of these initial analyses was to understand the parameters involved with considering varieties of geometries. For these analyses, physical and material properties were considered to be constant. Artificial branch models were created using Abaqus software and simulated for bending stress. All simulated branches were 31.9 cm and had varied branch geometries. For each

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analysis a single 14 degree bend was considered at 1 cm, 11 cm, and 21 cm from the base of the branch.

Experimental Comparisons Thereafter, branch bends were analyzed. Using Abaqus software, bending stresses were measured for three branches. The second step involved the removal of a single bend to determine bending stresses. The bending stresses with and without the natural bends were then compared.

Bending stresses with and without leaves The fourth objective was to determine the effects the presence and absence of leaves have on natural bending stresses of branches. The contribution of leaves to bending stresses of branches was quantified with a ‘stress factor’ was found using the equation nA = 1 −

σB − σA σB

(4)

where σB is the stress at the leaf node with leaves and σA is the stress at the leaf node without leaves. However, a logarithmic scale allowed for a more precise stress factor. Using the experimental data collected, the new stress factor, rA was found using the equation rSF = 1 − 10[log(σB −σA )−log σB ] .

(5)

The stress factor was then multiplied to the experimental bending stresses of a branch with leaves to find the theoretical bending stress without leaves σ T , σ T = σ B × rA .

(6)

These calculations were carried out for three branches. The average value for rA was calculated and also plotted for each branch.

Bending stresses considering side-branches The fifth objective was to determine the effect of side-branches on main-branch bending stress and vice-versa. Twelve artificial branches were generated and simulated in Abaqus software.

Branches had a main branch length of 4 cm with a side branch length of 2 cm. The branches consisted of a MOE of 1×109 and density of 1×103 . The angle of the side-branch relative to the main branch was varied. The angles used were 90◦ , 88◦ , 86◦ , 84◦ , 82◦ , 80◦ , 76◦ , 64◦ , 45◦ , 34◦ ,

Figure 1. Top view schematic of main and side-branch used in FE analysis. FE analysis was completed on these branches with varying ϕ: 90◦ , 88◦ , 86◦ , 84◦ , 82◦ , 80◦ , 78◦ , 76◦ , 64◦ , 45◦ , 34◦ , and 18◦ . Note that 90◦ denotes that the side-branch is orthogonal to the main branch.

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and 18â—Ś degrees (Fig. 1). Note that 90â—Ś denotes the side-branch orthogonal to the main branch.

Bending stress values were measured along the length of the main-branch and the side-branch for each model. Profile stresses for each angle were calculated and maximum stress as a function of angle was measured.

Theoretical bending stresses considering changing leaf masses and the addition of leaves Changing leaf masses The sixth objective was to determine how changes in leaf masses affect bending stresses along branches. For this experiment, leaf masses were modified. Original branches had their leaf masses multiplied by 4, 2, 0.5, and 0.25. These values were referred to as multiplied leaf factors. The modified branches were exposed to Abaqus’ FE analysis to determine modified stresses. Modified stresses were compared with original stresses.

Adding leaves In the second portion of this experiment artificial leaves were added to three branches. The artificial leaves were placed at one-half the distance between each pair of actual leaves on the Abaqus model. Artificial leaf masses were calculated by taking the average mass of the pair of actual leaves. The new branches were exposed to FE analysis and the modified stresses were recorded. Modified stresses were compared with original stresses.

Results Bending stresses versus branch lengths The first objective was to determine branch bending stresses as a function of branch lengths.

For all species tested, bending stresses increased linearly with increased branch length (Fig. 2).

From regression analysis the slopes of these linear relationship varied from 7,100 to 30,000 Pa among the five species tested. When leaves were absent, slopes varied from 1,000 to 5,800 Pa/cm.

Figure 2. Relationships between maximum bending stresses as a function of branch segment length for several tress species. A, species with leaves. B, species without leaves. Symbols: Large squares -Hamamelis virginiana; Diamonds - Morus rubra; Circles - Juglans nigra; Triangles - Ulmus americana; Small squares-Malus angustofolia.

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Figure 3. Relationships between bending stresses as a function of stem diameters for several tree species. A, species with leaves; B, species without leaves. Symbols: Large squares – Hamamelis virginiana; Diamonds – Morus rubra; Circles – Juglans nigra; Triangles – Ulmus americana; Small squares- Malus angustofolia.

Branches with leaves showed six to ten times higher bending stresses than branches without leaves.

In all cases, linear relationships with r2 values above 0.72 were obtained.

Bending stresses and diameters per branch segment mass The second objective was to determine branch bending stresses as a function of diameters per unit mass. Data in Fig. 3 demonstrated that bending stresses increased as branch diameter per unit segment mass increased. For the species tested slopes ranged from 920 to 51,100 Pa. Moreover, the slopes of branches with leaves had bending stresses twenty times greater than when leaves were absent.

Bending stresses versus branch geometries The third objective was to determine bending stresses as a function of branch geometries, particularly, curvatures along the branch. Three theoretical models were considered. Natural bends near branch bases were 1.5 times greater than when the natural bends were near the midpoints of branches and three times greater than when the natural bends were near branch terminals (Fig. 4).

For this theoretical analysis stress values ranged from 2.38×102 to 7.3×102 Pa. Results suggest that natural bends are a major contributing factor to overall bending stresses along branches.

Experimental analyses were compared with the theoretical results. Bending stress was 1.5 times greater for a naturally bending branch of Catalpa speciosa near the stem terminal compared with bending stress when the bend was removed (Fig. 5). Bending stress was 1.5 times greater for a naturally bending branch of Ulmus americana when the bend was midway along the branch compared with bending stress when the bend was removed. Bending stress was 1.4 times greater for a naturally bending branch of Malus augustofolia when the bend was near the branch base along the branch compared with bending stress when the bend was removed. Analyses show that

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Figure 4. Theoretical relationships between branch bend stresses and length along a branch. A, Location of bends types. B, Stresses along the branch for each bend type.

Figure 5. Three plots of bending stresses along branch lengths for three tree species of modified and unmodified branches. Yellow shading: stresses of unmodified branches. Purple shading: stresses of modified branches. For the modified branches, a single bend was removed along the branch using FE modeling and analysis resulting in lower stresses. A, Malus angustofolia; B, Ulmus americana; C, Catalpa speciosa; A, branch tip modified; B, branch middle modified; C, branch base modified.

bending stresses decreased when bends were removed and that stress concentrations near the base added more stress on the branch compared with other locations.

Bending stresses with and without leaves The fourth objective was to determine the effects that the presence and absence of leaves have on natural bending stresses of branches. The average stress factor for all eleven species (rA ) was 0.094 (Table 2). Comparing species-specific stress factors rs , with the average stress factor (rA ), the error was 30.9%. Fig. 6 illustrates the similarities between the species specific stress factor and the average stress factor of two different species. Maximum stresses along the length of the branch for two branch samples of M. angustofolia (Figs. 6A and 6B) ranged from 1.86 × 104 to 8.03 × 104 Pa. Maximum stresses along the length of the branch for two different branch samples of M. rubra (Figs. 7A and 7B) ranged from 4.30×104 to 1×105 Pa. Stresses of the branch without leaves using the average stress factor provided similar values to the experimental natural bending stresses. These data suggest that the average stress factor of 0.094 was an accurately estimate of bending stresses of branches without leaves.

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The Manhattan Scientist, Series B, Volume 2 (2015) Table 2. Multiplying stress factors for several tree species Species Acer Catalpa Juglans Liriodendron Malus Morus Prunus Tilia Ulmus Mean

platanoides speciosa nigra tulipifera angustofolia rubra pensylvanica americana americana

Multiplying Stress Factor

Theoretical Percent Error

0.12 0.10 0.07 0.12 0.05 0.08 0.09 0.07 0.14

26.59 10.58 23.17 75.82 51.42 5.78 4.57 21.14 48.92

0.09

30.89

Figure 6. Bending stresses as a function of branch length. Squares: stresses with leaves. Circles: stresses without leaves. Diamonds: theoretical stresses without leaves using species specific stress factor. Triangles: theoretical stresses without leaves using average stress factors. Two individual branches are shown in A and B for Malus angustofolia. C and D, two branches of Morus rubra.

Figure 7. Bending stresses as a function of branch length. Squares: stresses with leaves. Circles: stresses without leaves. Diamonds: theoretical stresses without leaves using species specific stress factor. Triangles: theoretical stresses without leaves using average stress factors. Two individual branches are shown (A and B) of Morus rubra.

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Bending stresses considering side-branches The fifth objective was to determine the effect that side-branch angles had on branch bending stresses. The maximum bending stress along the side-branch at 90◦ was 5×10−10 Pa while the maximum bending stress along the side-branch at 76◦ was 5×10−3 Pa. The maximum bending stress for a side-branch at 76◦ was 9 × 106 times greater than the maximum bending stress at 90◦ .

The maximum stress for a side-branch at 18◦ was 3 × 106 times larger than the side-branch at 90◦ (Fig. 8). The maximum bending stress increased from 76◦ to 18◦ . The maximum stress for the 76◦ side-branch was 3.3 times greater than the maximum stress of a side-branch at 18◦ .

Figure 8. Theoretical maximum bending stresses for main and side-branches as a function of the angle ϕ. A, maximum stress along the side branch. B, maximum stress along the main branch. As ϕ increased between the main and side branch, maximum stresses increased.

Maximum bending stress increased as the angles increased until the side-branch became orthogonal to the main-branch (Fig. 9). The bending stresses drastically decreased at a branch angle 90◦ . For this reason, the side-branch fixed at 90◦ was treated as a special case. The orthogonal geometry affects bending stress differently than if the side-branch’s angle was less than 90◦ .

Figure 9. Theoretical bending stresses as a function of side-branch lengths for angles 90◦ (blue), 88◦ (black), 84◦ (green), and 78◦ (red). The 88◦ , 84◦ , and 78◦ had similar stress patterns along the length of the branch (See Fig. 8). The 90◦ angle had significantly lower bending stresses due to its orthogonal geometry to the main-branch.

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Bending stress considering changing leaf mass and the addition of leaves Changing leaf masses When leaf masses were multiplied by four, the average modified stresses were 3.7 times greater than the original stresses. When leaf masses were multiplied by 0.25, the average modified stresses were 0.33 times greater than the original stresses. Fig. 10 displays the relationship between the multiplied leaf factor and the calculated stress ratios for three species of branches.

Each branch trend line contained similar slopes. The Ulmus americana, Malusrubra, and Juglans nigra had slope values of 0.86, 0.88, and 0.95 respectively. The trend lines suggest that bending stress is linearly proportional to leaf mass.

Figure 10. Bending stress ratios versus multiplied leaf factor for tree species. A, Ulmus americana. B, Malus augostofolia. C, Juglans nigra. Multiplied tree factors were 0.25, 0.50, 2, and 4. The multiplied leaf factor is the value in which all leaves were multiplied by for the FE analysis. The stress ratio is the average of the measured stress divided by the original stress.

Adding leaves When artificial leaves were added, modified bending stresses increased by 1.9 times compared to the original branch stresses. Fig. 11 shows the relationship between the original branch and modified branch bending stresses. At each location where an artificial leaf was added, there is

Figure 11. Plots of bending stress along the length of the branch for three species. A, Ulmus americana; B, Malus augostofolia; C, Juglans nigra. The solid line represents the bending stresses for unmodified branches. The dotted line represents the bending stresses in which one artificial leaf was added between each pair of actual leaves. When all leaves were pooled, bending stress increased on average 1.9 times the original bending stress.

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a small rise in stress. This suggests that branches with more leaves not only increases overall bending stress, but create stress concentrations where they lie along the branch.

Discussion

Trees have an almost infinite array of morphologies. For example, spruce and fir trees have a single main stem with mostly secondary branches (Schweingruber et al., 2006). In contrast, most dicot trees have a spreading morphology in which many secondary branches are as long as the main stem is tall (Schweingruber et al., 2006). This variability in morphologies is difficult to explain but trees and individual tree branches need to follow some basic mechanical principles should define shapes and contours and diameters of individual branches (Niklas, 1992). The purpose of this study was to investigate the mechanical properties of some of shapes, contours and diameters.

Thus, overall plant structure is dependent upon the mechanical properties of tree branches.

The mechanical and physical properties of tree branches are important especially when plants are exposed to external forces like strong winds, the impacts of solid objects, snow loads, etc.

Individual branches may experience mechanical failure when stresses reach a material’s maximum allowable stress. Knowing how much stress a branch can handle before failure is important to arborists, urban foresters and many others (Kane et al., 2008). Branch failure may cause damage and harm which can be both dangerous to human lives and expensive to maintain.

Do longer branches have higher bending stresses than shorter branches? The results of these experiments with five species showed a direct relationship between branch length and bending stresses. In all species, bending stresses increased with increased branch length. The slopes of these relationships varied from 7,000 to 30,000 Pa/cm. The variety of slopes may be due to differences in natural morphology, various mechanical properties including density, MOE, and Poisson’s ratio. These and many other factors may contribute to variability among species. Nevertheless, stress increased linearly with length of branches.

Do stem diameters affect bending stresses? Theory states that smaller diameters should yield higher stresses (Shahbazi et al., 2015). However, our data show the contrary. For all species of this study, bending stresses increased as diameter per unit length increased. Slopes of these relationships varied from 920 to 51,100 Pa/cm. Once again, the variance can be explained by the changing physical properties for each species. The base of the branch must support the cumulative weight. Our results may have been contrary to theory because theory did not take the weight of the branch into account. If branches with various diameters had been studied, the results may have differed. For instance, if we had compared primary branch diameters to side branch diameters, alternate relationships may have been found.

Does geometry affect bending stresses? In theory, our results showed that branch bends and their locations are vital in the formation of bending stresses. A bend at the base puts more stress on the branch because the base must support a longer branch segment, and a bend at the tip supports a smaller length of the branch. The experimental data did not support the theory. The artificial models used in the theoretical experiment contained a single bend. The experimental branches used

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contained numerous bends and curvatures. These bends were responsible for variance in bending stress values. However, natural curvatures along branches will always increase stress along the branch. Future experiments could explore this issue further in which branches could have bends in several places along the branch that could be removed one at a time. Clearly, changes in stresses at natural bends are an important aspect of branch mechanics.

More leaves, higher bending stresses? Leaves are extremely significant factors for adding weight and stress along branches. Even though leaves have relatively low masses compared to the branch mass, their accumulation drastically impacts stress.

This study suggests that leaves, regardless of species, add a similar amount of stress to any given branch. This experiment found a single value which could accurately determine stresses of a branch without leaves. The average stress factor was 0.094. This value was applied to nine branches with promising results. The average percent error for all branches used in the study was 31%. Most of the error was due in part to the varying bending stress at the base. The experimental stress at the base was always different than the theoretical stress at the base. Every other point along the branch had similar theoretical and experimental stress values. Using the average stress factor is an efficient method to calculate stresses on branches without leaves.

Do side-branch angles affect bending stresses? Why does orthogonal geometry have less stress? This experiment has real world applications in the forestry and public works industries.

Being able to locate a branch that can potentially cause damage before it fails can save money and reduce risk of injury (Kane, 2008). Side-branches with smaller angles are less likely to fail under extreme loading. However, a special case exists when the side branch becomes orthogonal to the main-branch. Stresses along the side-branch dropped tremendously due to the existing geometry.

Arborists and public workers now have instruction on what kind of branches should be cut to avoid potential failure.

Leaf masses add a proportional amount of stress to branches whether more mass is added for individual leaves or leaf mass is reduced for individual leaves. How does the addition of leaves to a branch affect bending stress? Across three species, the average increase in stress when artificial leaves were added was 1.9 times greater. This value of 1.9 could be checked by repeating the experiment with more branch species. In theory, this experiment doubled the amount of leaves per branch, and the results concluded that the stress is also doubled. This confirms that the addition of leaf mass, whether it be by adding leaves or just increasing the weight of each leaf is proportional by a one to one ratio.

Acknowledgement The authors are indebted to the Catherine and Robert Fenton Endowed Chair to Dr. Lance Evans for financial support. They also thank Dr. Zahra Shahbazi and Dr. Lance Evans for their constructive insight and ideas.

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References Kane, B., R. Farrell, S. Zedaker, J. Loferski, and D. Smith (2008). Failure Mode and Prediction of the Strength of Branch Attachments, Arboriculture & Urban Forestry 34: 308-316.

Kershner B., and C. Tufts (2008). National Wildlife Federation Field Guide to Trees of North America. Sterling Pub: New York.

Little E., S. Bullaty, and A. Lomeo (1980). The Audubon Society Field Guide to North American Trees. 14th ed. Knopf: New York.

Mencuccini M., J. Grace, and M. Fioravanti (1997). Biomechanical and Hydraulic Determinants of Tree Structures in Scots Pine: Anatomical Characteristics, Tree Physiol 17: 105-113.

Niklas, Karl J. (1992). Plant Biomechanics: An Engineering Approach to Plant Form and Function, Chicago Press: Chicago.

Schweingruber, F. H., A. B¨orner, and E. Schulze (2006). The Structure of the Plant Body. Atlas of Woody Plant Stems: Evolution, Structure, and Environmental Modifications. Berlin: Springer.

30-31.

Shahbazi Z., A. Kaminski, and L. S. Evans (2015). Mechanical Bending stress Analysis of Tree Branches. American Journal of Mechanical Engineering 3, 32-40.

Shahbazi Z., D. Keane, D. Avanzi, and L. S. Evans. Automated Finite Element Analysis on Tree Branches. (in preparation).

Shames, Irving H., and James M. Pitarresi (2000). Introduction to Solid Mechanics. Pearson. 3rd ed.

Widas, P. (1997). Introduction to Finite Element Analysis. Virginia Tech Material Science & Engineering. http://www.sv.vt.edu/classes/MSE2094 NoteBook/97ClassProj/num/widas/history.html

Rates of bark formation on surfaces of Saguaro Cactus plants Lauren Barton∗ Department of Biology, Manhattan College Abstract. Extensive bark formation, or epidermal browning, has been found on twenty-one species of tall, longlived columnar cactus species in the Americas. It has been noted that for each species, bark formation begins on equatorial-facing surfaces. Additionally, controlled experiments using UV-B irradiation show the initial stages of bark formation as well. Both of these facts suggest that UV-B irradiation is primarily the cause of this sunlight-induced bark formation. Sunlight-induced bark is detrimental to cacti and leads to premature morbidity and mortality. This study focused on bark formation rates on twelve cactus stem surfaces. Bark formation rates were compared using logistic curves. Typically, logistic curves are best fit to the data using least squares analysis. Least squares analysis allows for the least amount of error in the graph. For the present, south-facing crest surfaces of saguaro cacti in Arizona show bark before other surfaces, so bark formation rates on the south crests were compared to the bark formation rates on eleven other surfaces. Results indicate that east crests are the first surfaces to show bark formation about three years after bark formation on south-facing crests. West crests are next to follow delayed by about 8 years with the north crests following with a delay of 15 years. After the crests begin to show bark formation, the troughs begin to bark as well. The delay of the bark formation on the south, east, west, and north troughs from their respective crests were about 4, 5, 10, and 15 years, respectively.

Introduction Epidermal browning, the bark injuries found on the stem surfaces of Carnegiea gigantea (Engelm.) Britt and Rose (saguaro cacti) have been analyzed and observed in several publications (Duriscoe and Graban, 1992; Evans et al.,1994a; 1994b, 1994c, 1995; 2005; Turner and Funicelli, 2000; Evans and Macri, 2008). These bark injuries are relatively new with few injuries prior to the 1950’s. (Evans et al., 1992). Typically, young saguaro cacti do not exhibit any epidermal bark injuries (Duriscoe and Graban, 1992; Evans et al., 1994a; 1994b). An aggregation of epicuticular waxes is the first microscopic manifestation of stem surface injuries (Evans et al., 1994a; 1994b). An accessory to this accumulation of epicuticular waxes is reduced gas exchange through the stomata of cacti (Evans et al., 1994a; 1994b). This buildup of epicuticular waxes has been shown to correlate directly with fading of color in the typically green stems of the cactus. Similarly, controlled experiments of UV-B light exposure have also shown an identical accumulation of epicuticular waxes in cacti; this UV-B light exposure occurs with normal sunlight exposures (Evans et al., 2001). This also causes a fading the green color of cacti. This fading of green color eventually gives way to orange and brown discolorations. Overtime, a visible bark is present (Evans et al., 1994a; 1994b). Bark formation is caused by repeated cell divisions of epidermal cells (Gibson and Nobel, 1986; Evans et al., 1994a). Extensive bark formation leads to inevitable death in many of the saguaros that exhibit this (Evans et al., 2005; 2013).

Epidermal browning, or bark formation, is found on twenty-one different species of tall, columnar cactus species in the Americas (Evans, 2005; Evans and Macri, 2008; Evans et al., 1994a; ∗

Research mentored by Lance Evans, Ph.D.

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1994b; 1994c). This bark formation begins first on equatorial-facing surfaces; thus, columnar cacti like saguaros, found in the Northern Hemisphere show bark formation first on south-facing surfaces (Evans et al., 1992; 1994a); bark formation progression has been studied extensively and quite specifically on saguaro cacti found in Arizona (Duriscoe and Graban, 1992; Evans et al., 1994a; 1994b, 1995, 2005; 2013; Turner and Funicelli, 2000; Evans and DeBonis, in press). Typically, these studied saguaro cacti that show bark progression are tall. Since the age of the cactus correlates with the height, this suggests damaged cacti are much older.

It has been shown in previous experimental results that bark formation on saguaros highly paralleled morbidity and mortality. This study began in 1993-4 when 50 permanent plots were established in Tucson Mountain Park, Pima County Parks and Recreation Department, Tucson AZ (Evans et al., 1995). Within these 50 permanent plots in 1993-4, 1149 adult saguaros taller than 3.5 m were evaluated based of external bark injuries. Over a 16 year period (1994-2010), 36% of these cacti died (Evans et al., 2013). In addition, the number of cacti without bark decreased by about 1.6% per year over that 16 year period. In a previous study, a machine learning algorithm was created that predicted mortality and morbidity rates (Evans et al., 2013). A second algorithm was also created to predict the characteristics of saguaro stems that would lead to death during the next 4-year period; this was done with 86% accuracy (Evans and DeBonis, in press).

The purpose of this current study was to determine bark formation rates on stem surfaces on saguaro cacti over a 16-year period. Bark percentages on crests, right troughs and left troughs each for south, east, west and north-facing surfaces were analyzed. The necessary approach for this study was to treat the occurrence of bark formation as an abiotic disease. This was essential because many animal/human diseases have been characterized by logistic curves, thus this study could be analyzed using logistic curves as well. These logistic curves have three stages: an ‘initial’ stage, a ‘manifest’ stage, and a ‘morbid’ stage prior to death (Truett et al., 1967; Boyd et al., 1987; Le Gall et al., 1993; Marshall et al., 1995; Biondo et al., 2000; Kologlu et al., 2001) and were very helpful in determining bark formation rates for this study.

Materials and Methods Field conditions Saguaro cacti (Carnegiea gigantea (Engelm.)) Britt and Rose were observed and analyzed over a 16-year period. The field plots used in this study was established in Tucson Mountain Park in 1993-4. Over a period of two years, 50 permanent plots were established in Tucson Mountain Park; within these 50 plots, the location of 1149 cacti were established and analyzed in 1993-4 (Evans et al., 1995), 2002 (Evans et al., 2005) and 2010 (Evans et al., 2013). The plots chosen for this study within Tucson Mountain Park expressed certain characteristics; these characteristics have been described elsewhere in great detail (Evans et al., 2005).

Data sets used Data of percent bark areas included crests, right troughs and left troughs each for south, east, west and north-facing surfaces (twelve surfaces) for all cacti; these percent bark areas were then

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analyzed. Some of the data that was analyzed in 1993 - 4, 2002, and 2010 have been presented elsewhere (Evans et al., 1995; 2005; 2013). An Excel spreadsheet (Microsoft Inc.) was used to document the percentages of barked area on each of the twelve surfaces observed. The numbers of these cacti used for each surface are shown in Table 1.

Table 1. Statistics of the logistic curves produced for this study for Carnegiea gigantea.

Surface South Crests South Right Troughs South Left Troughs East Crests East Right Troughs East Left Troughs West Crests West Right Troughs West Left Troughs North Crests North Right Troughs North Left Troughs Mean Standard deviation

Number of samples1

a2

Coefficients b2 c2

597 781 797 631 776 734 724 792 829 715 802 769 746 70

0.0079 0.0085 0.0083 0.0085 0.0087 0.008 0.008 4 0.0092 0.0095 0.0085 0.0079 0.0093 0.0086 0.0005

26.3 23.0 23.0 21.9 25.1 23.4 22.2 24.3 25.1 23.2 23.3 24.8 23.8 1.32

11.6 14.3 14.0 13.2 15.3 14.7 14.5 16.7 15.0 12.7 15.5 11.3 14.1 1.6

RMSE3 7.17 8.15 8.36 8.30 7.51 8.06 8.81 7.90 7.92 8.12 8.30 7.67 8.02 0.43

20%

Rate of barking4 50% 80% Maximum

4.17 3.97 3.81 3.71 4.37 4.04 3.75 4.46 4.74 3.96 3.69 4.61 4.11 0.36

10.4 9.93 9.53 9.28 10.9 10.1 9.38 11.2 11.8 9.90 9.23 11.5 10.3 0.90

16.7 15.9 15.3 14.8 17.5 16.2 15.0 18.8 19.0 15.8 14.8 18.4 16.5 1.5

19.9 18.9 18.2 17.7 20.8 19.2 17.9 21.2 22.4 18.8 17.6 21.9 19.5 1.7

1

The number of cactus plants in which data were used to determine the logistic curve for each surface.

The meaning of each coefficient is given in the Materials and Methods 3 RMSE is defined as the sample standard deviation of the differences between predicted values and observed values.

4 Rates of bark formation in units of percentage coverage per year. Rates of bark formation were estimated at 20%, 50%, 80% initial bark coverage levels and the maximum overall rate.

2

Theory of the use of logistic curves Logistic curves have been shown to successfully determine rates of disease progression in humans (Truett et al., 1967; Boyd et al., 1987; Le Gall et al., 1993; Marshall et al., 1995; Biondo et al., 2000; Kologlu et al., 2001) and thus it was a natural choice for showing the increase in area of bark formation on the twelve cactus surfaces. The intention of this study was to determine average bark formation rate on cactus surfaces; this model included crests and troughs for south, east, west and north-facing (twelve) surfaces. Data of the twelve surfaces were analyzed over a 16year period (1993-4, 2002, and 2010). These data sets appeared to show three fundamental stages of a logistic curve in terms of areas of bark formation. The first fundamental stage, referred to as the ‘initial’ stage, involved surfaces of any cactus that showed no bark in 1993-4, and progressed minimally over time. This minimal bark formation was less than 25% bark formation by 2010. The second stage, referred to as the ‘manifest’ stage, showed cacti that had bark formation rates that increased in a linear fashion from 1993-4 to 2010. The third stage, the ‘morbid’ stage, included

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cactus surfaces with more than 75% bark for all three sampling dates. After careful analysis, it was determined that for these three stages of bark formation a logistic model fit the data much better than the linear models or the polynomial models.

Although a logistic model was a better fit for this data, the basic logistic curve described by Draper and Smith (1998) was not entirely sufficient since a basic logistic curve has an inherit symmetry in the growth curve. The data did not show an inherit symmetry. Thus, it was essential that a more generalized logistic curve be selected y = 100/{1 + exp[−b(t − c)]}a

(1)

This generalized curve has three parameters a, b, and c, which are determined by the method of least squares (Gottschalk and Dunn, 2005). This curve allowed for asymmetric behavior. Asymmetry means that the lower part of the S-curve may be different for the upper half and the point of inflection can occur anywhere between the minimum (0%) and maximum (100%) values.

Still, the curve described above was not entirely sufficient in producing a successful model. As stated previously, individual cacti were at different stages in their bark formation rate. Thus, cacti were asynchronous to each other with respect to time. Another method needed to be implemented to synchronize the three stages of bark percentages across all surfaces of cacti; this was essential to determine an average cactus’ bark formation rate on each surface. A natural choice to synchronize these models with respect to time is one that is used to synchronize wireless signals (Wang et al., 2011). This synchronizing method had two important factors: (1) least squares analysis needed to be used on the generalized logistic curve, and (2) the square of the errors in the times of the data points needed to be minimized and the curve would need to fit to these data points. This new method yielded R2 > 0.95 on all twelve surfaces of the cacti that were being studied.

Theory of synchronizing logistic curves among cactus surfaces Next, it was necessary to synchronize the logistic curves for all twelve surfaces to make a time sequence; e.g., the logistic curve of the south crests needed to be synchronized to that of the east crests. This synchronization should show a time difference between south and east crests because at any instance of time there were higher bark percentages on south crests than on east crests. Thus, this synchronization provided an estimate of the time delay between the logistic curves for the two surfaces. This was done between pairs to determine time delays for all twelve surfaces.

Method for fitting the data is an asymmetric logistic curve As previously stated, data of park percentages were collected in 1994, 2002, and 2010 for about 1000 cacti. Data for these years for all twelve surfaces were designated b1, b2, and b3 so that it could be processed as an ordered triple (b1, b2, b3). This procedure was implemented using Matlab (www.mathworks.com) where custom programs were written to perform the required tasks.

Preprocessing of the data was a necessary task that needed to be done before the accurate curve fit could be obtained. Three types of triples needed to be removed to obtain this accurate fit:

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(1) Triples with missing data; (2) Triples which had all equal values, since they would not provide any information regarding bark formation rate; and (3) Triples in which the bark percentage of (a) b1 > b2 + 10 or (b) b2 > b3 + 10, because such data had illogical errors (since cacti could not decrease in bark percentage over time).

Next in the prescreening of the data, each triple was divided into the three classes: Initial, Manifest and Morbid. Given a triple (b1, b2, b3), if b3 ≤ 25, then it belonged to the Initial class. If b1 ≥ 75, then it is put in the Morbid class. All other triples are assigned to the Manifest class.

We used an iterative method to produce a curve fit for each surface of a cactus. This process was repeated 33 times with different initial conditions and the “best” fit for the data was selected.

The reason for repeating the process and choosing the best fit arose from a lack of knowledge regarding the actual time delay (time spread) (Table 2).

Table 2. Various initial conditions of the three classes of data used in determine the asymmetric logistic fit for each of the twelve sides of a cactus. Of the 33 initial conditions the “best” fit was selected. Carnegiea gigantea

Spread 1 Spread 2 ...

Spread 32 Spread 33

Initial Relative Time

Manifest Relative Time

Morbid Relative Time

-16, -8, 0 -15, -7, 1 ...

-1, 7, 15 0, 8, 16

0, 8, 16 0, 8, 16 ...

0, 8, 16 0, 8, 16

16, 24, 32 15, 23, 31 ...

1, 9, 17 0, 8, 16

Each of the 33 iterations proceeded in the following fashion: (1) Using “spread” times (Table 2), find the best asymmetric logistic fit to the data; (2) data are then shifted horizontally to give the best least squares fit to the chosen logistic curve; (3) using the shifted data in step (2) find the best asymmetric logistic fit to the data; (4) repeat steps (2) and (3) until the best fit in step (3) stabilized (e.g., the values of a and b no longer changed to a four decimal place accuracy). This process allowed for the production of a logistic fit that yielded the lowest sum of p-values for a and b (Table 1). The model among the 33iterations that provided the highest R2 value and the lowest root mean squared error was chosen as the “best” fit for each comparison.

Method for synchronizing the logistic curves Once a logistic fit was established for each of the twelve surfaces under investigation, it was necessary to synchronize them to determine time delays. This procedure was done with pair-wise comparisons to determine the time shifts between data of two different surfaces. Four independent methods were used to determine this. The final estimate was the average of the four methods.

First method: For each pair of surfaces, the percentages of bark were compared using the logistic fits for each of the two surfaces under consideration. The corresponding time differences

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were calculated using the inverse of the logistic curve T = c − (1/b) ln[(100/B)(1/a) − 1],

(2)

where B is the bark percentage and T is the corresponding time. Then, it was necessary that we compute the difference in times for data of 1994, 2002 and 2010. The average of these computations was our first estimate of the time difference.

Second method: given any two surfaces we looked at how the data had been shifted in time when we created our logistic fits. Thus, for each cactus we determined the difference in times of the resulting time shifted data for years 1994, 2002, and 2010. The average became our second estimate of the time difference.

Third and Fourth methods: given two surfaces, we again analyzed how the data had been shifted in time when we created our logistic fits. Using shifted times for one surface; we fit the logistic curve of another surface to the data using these specific time shifts and the method of least squares. We now had the logistic curve for one particular surface and this resulting fit of the second logistic curve to the shifted data. We then gauged the time difference between the two logistic curves at the 50% barking level using the formula presented in the first method. For instance, the time differences between Methods 1, 2, 3, and 4 for east crests versus north crests were 3.35, 3.48, 3.58, and 5.1 hours, respectively. The mean of the four values, 3.9 hours, was used as the final estimate. The time shifts of right and left troughs versus crests were determined in a similar manner.

Table 3. Computed time shift in bark formation logistic curves between pair-wise comparisons for crests of Carnegiea gigantea Time Shift (hours) Crest

South Crest

East Crest

West Crest

North Crest

South East West North

0

3.67 0

3.95 0.50 0

8.19 3.90 3.46 0

Since we analyzed twelve different surfaces, a large variety of pair-wise comparisons were possible. The data in Table 3 show pair-wise comparisons among all crests. The time difference from south crest to east crest was 3.67 years. The time difference from south crest to west crest was computed in two ways: (1) south directly to west: 3.95 years, or (2) south to east, then east to west: 3.67 + 0.50 = 4.17 years. The mean of these two values was 4.06 years. The time difference from south crest to north crest was computed four ways: (1) south directly to north: 8.19 years, or (2) south to east, then east to north: 3.67 + 3.90 = 7.57 years, or (3) south to west, then west to north: 3.95 + 3.46 = 7.41 years, or (4) south to east, then east to west, then west to north: 3.67 +

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0.50 + 3.46 = 7.63 years. The mean of the four computations (7.70 years) was used to estimate the time shift. Therefore, a variety of methods were used to determine time shifts among the twelve surfaces.

Results First, it was essential to construct entire logistic curves of bark formation for all surfaces.

As stated previously, each cactus possessed initial, manifest, and morbid portions of their logistic curve. Each cactus had three timed data points (1994, 2002, and 2010) for each of the twelve surfaces. These timed data points were used to construct logistic curves for all surfaces; an example of a logistic curve is shown in Fig 1. Open circles represents 0 to 30% bark percentages - the ‘initial’ portion of the curve. Grey-filled circles from approximately 0 to 100% bark percentage show the data used for the manifest portion of the curve while dark, closed circles between 70 and 100% bark percentage show the morbid samples that contributed to the curve. The method of least squares analysis was used to fit these three portions of the logistic curve together.

Figure 1. Logistic curve of percent of bark formation on stem surfaces versus relative time on eastfacing right troughs for injury groups of initial (open circles), manifest (grey-filled circles) and morbid (closed circles) Carnegiea gigantea

Figure 2. Logistic curves for south (solid line), east (large dashes), west (small dashes) and north-facing (dots) crest surfaces stems of Carnegiea gigantea as a function of relative time with south crests as the basis of comparison. Note the similar relative time delays for both east and west-facing crests and the longer delay for north-facing crests.

The next step implemented was the comparing of logistic curves, specifically looking at the synchronicity for south, east, west, and north-facing crest surfaces (Fig. 2). The time shifts were only determined between the south-facing crest and one other crest for each analysis; thus, three separate analyses were performed. For instance, to determine the time-shift between south and east-facing crests, data of the south-facing crests were chosen first while data for the east-facing crests were paired to those of the south crests. Two logistic curves were produced from this comparison of data and the difference in time between the two curves was calculated. This same

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procedure was used among all paired crest surfaces and average time differences among the four surfaces were determined (Fig. 2).

Figure 3. Logistic curves for crests (solid line), right troughs (dots) and left troughs (dashes) on south-facing surfaces of stems of Carnegiea gigantea as a function of relative time with south-crests as the basis of comparison. Note the relatively similar time delay curves for the two troughs.

Figure 4.

Logistic curves for crests (solid line), right troughs (small dashes) and left troughs (large dashes) on east-facing surfaces of stems of Carnegiea gigantea as a function of relative time with east-crests as the basis of comparison. Right troughs that have a north-facing inclination had a shorter time delay than left troughs that have a south-facing inclination.

The third step necessary for this study was to determine the synchronicity for the two troughs of each individual crest. The data in Fig. 3 show the south-facing crest compared with its two troughs. In this particular instance, the time-shifts for south right troughs and south left troughs relative to the south crest were similar. The data in Fig. 4 show the east-facing crest compared with its two troughs. Conversely to south-facing surfaces, east-facing surfaces had two different time-shifts for each trough; the time-shift of bark on the left trough was similar to the crest but bark formation on the right trough was delayed.

The data in Fig. 5 show the time-shift synchronization among all twelve surfaces. Again, all of the time-shifts were relative to south-facing crests since data has shown that south-facing crests show more bark than any other cactus surface. In comparison to the south-facing crests, east-facing crests had between a three and five-year time-shift. West-facing crests, conversely, had approximately a six-year time-shift at 20% bark percentage to a nine-year shift at 80% bark percentage compared with south-facing crests. North-facing crests had the longest time-shift of all crest surfaces with a seven-year time shift at 20% bark percentage to a 21-year time-shift at 80% bark percentage relative to south crests. The surface with the longest time-shift compared with south-facing crests was the north right troughs. This time-shift from south-facing crests to north right troughs was about 35 years.

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Figure 5. Time- shifts of bark formation rates among the twelve surfaces of stems of Carnegiea gigantea cacti based upon logistic curves. South-facing crests are represented by the green zero line at y = 0. Each line represents the time-shift relative to south-facing crests from 20% to 80% bark levels (manifest portion of logistical curve) on surfaces. Green solid line- south crests, green dash line- south left troughs, green dot line- south right troughs, red solid line- east crests, red dash line- east left troughs, red dot line- east right troughs, blue solid line- west crests, blue dash linewest left troughs, blue dot line- west right troughs, yellow solid line- north crests, yellow dash line- north left troughs, yellow dot line- north right troughs.

Discussion The purpose of this study was to determine bark formation rates from three sets of data collections, from 1994, 2002, and 2010, on twelve different surfaces of the same cacti. A typical logistic function is symmetrical; the lower portion of the curve is the same as the upper portion of the curve and the inflection point is at 50% (Draper and Smith, 1998). Bark formation, however, does not follow this typical logistic function since there is a higher initial rate found at the lower part of the curve than the morbid rate located at the upper part of the curve; and the point of inflection of all twelve surfaces was never at 50%. Because of this, a more generalized logistic curve was selected y = 100/{1 + exp[−b(t − c)]}a

(3)

in which parameters a, b and c are determined by the method of least squares (Gottschalk and Dunn, 2005). This new, more generalized curve allows for asymmetric behavior and varied points of inflection. The parameter denoted by a is the quantity which generates this asymmetric behavior and allows for varying points of inflection; without the parameter a we are reduced to the standard logistic curve. The parameter denoted by b is the bark formation rate and the parameter denoted by c is a simple horizontal shift for the logistic curve. As expected the bark formation rate, or the slope of the manifest portion of all logistic curves, decreased from south to east to west to north.

Bark formation, or epidermal browning, found on these studied saguaros does not occur on small cacti. Bark typically occurs on decades-old cactus plants that have been exposed to sunlight for a much longer period of time.

Also, as shown in prior studies, bark formation primarily occurs on saguaros on south-facing surfaces before any other surfaces. Thus, for this study, the timing of bark formation on other surfaces was expressed as time after bark began to accumulate on south-facing crests. Consistent with past results, bark occurred first on east crests. Bark formation on east crests occurred three years prior to the beginning of bark formation on south crests. Along with this, east crests also

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showed bark prior to complete bark formation on south-facing troughs. In the case of the eastfacing surfaces, the left troughs have a south inclination, thus they exhibited bark formation within three years after east crests. Conversely, east right troughs (with their north inclination) exhibited an eight-year delay in bark formation compared to their crests. West-facing crests are delayed about 8 years from the south crests and north-facing crests are delayed by about 15 years. In turn, bark formation on south, east, west and north troughs was delayed by 4, 5, 10, and 15 years, respectively. On average, all stem surfaces at 1.7 m height should have complete bark within 35 years.

As stated previously, over an annual cycle, sunlight exposures on columnar cacti at 32â—Ś latitude, at the latitude of Tucson AZ, should have about four times more sunlight on south-facing surfaces than on north-facing surfaces (Geller and Nobel, 1984). Thus the shape of the curve of this increase in bark from 20 to 80% can be explained by the fact that south- facing surfaces receive so much more direct sunlight exposure than other surfaces. The data in Fig. 5 show comparably horizontal lines for south and east surfaces. However, west and north-facing surfaces show more complex functions. North crests show the steepest slope among the surfaces suggesting that the rate of bark formation was slow from 20 to 80%. Conversely, initial bark formation on north right troughs was much delayed and does not begin until some 15 years after bark formation on south crests. However, once bark formation begins on north right troughs, it occurs rapidly. This rapid bark formation rate is unique to north right troughs. This is because almost the entire cactus surface at 1.7 m height is bark covered before the north right troughs even begins to show any bark formation. Earlier results showed that north right troughs were the last surface to have complete bark cover. Therefore, it is not surprising that the amount of bark on north-facing right troughs alone could predict cactus mortality with 89% accuracy.

It has been noted that saguaro cacti may live to over 200 years of age (Pierson and Turner, 1998); documented rates of bark formation shown herein state that stems at 1.7 m have complete bark coverage on all surfaces within 35 years after the start of bark formation of south crests are inconsistent with the 200 potential years it has to live. Turner (1992) demonstrated that for two field plots at Saguaro National Park, saguaro mortality averaged 2% per year. Turner and Funicelli (2000) showed that 16.5% of all saguaros in their plots at Saguaro National Park died from 1990 to 2000. Furthermore, these rates of bark formation are consistent with mortality rates of 2.3% (Evans et al., 2005) and 2.1% (Evans et al., 2013) per year over the past several decades among adult saguaros (Evans et al., 2005). More recently, O’Brien et al. (2011) showed that for 20,372 saguaros that surveyed, the oldest cactus was only 110 years of age. Overall, this indicates that the high rates of bark formation and the relatively high mortality rates are consistent with lack of older saguaros in the Tucson, AZ area compared with past years.

The overall mortality rates of adult saguaros of more than 2% per year (Evans et al., 2005, 2013; Turner and Funicelli, 2000) coupled with fact that the oldest saguaro as of now at Saguaro National Park was only 110 years old in 2010 (O’Brien et al., 2011) suggest there are some long range changes for adult saguaros in the Tucson area resulting in premature death. The fact that

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surveys of saguaros at Saguaro National Park (Turner and Funicelli, 2000; O’Brien et al., 2011) do not acknowledge that bark formation (epidermal browning) is the cause of the mortality and the change in height structure is surprising. If a young saguaro cactus starts bark formation prior to being 100 years old, and the bark process takes 35 years, and causes imminent mortality to this barked cactus, it is easy to conclude that in the future there will be no older, taller cacti in the region of Tucson, Arizona.

Acknowledgements

The author is indebted to the Catherine and Robert Fenton Endowed Chair to Dr. Lance Evans for financial support for this research. She is also grateful to Drs. M. DeBonis and L. S. Evans for extensive help with this study.

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Boyd, C. R., M.A. Tolson, and W.S. Copes. 1987. Evaluating trauma care: The TRISS method.

Trauma Score and the Injury Severity Score. J. Trauma 27: 370–378.

Draper, N.R. and H. Smith. 1998. Applied Regression Analysis. 3rd ed. John Wiley & Sons. New York.

Duriscoe D. M. and S. J. Graban. 1992. Epidermal browning and population dynamics of giant saguaros in long-term monitoring plots, p. 237-262. In C.P. Stone and S. Bellantoni [eds]. Proceedings of the Symposium of Research in Saguaro National Monument. Southwest Parks and Monuments Association. Tucson, AZ. Evans, L. S. 2005. Stem surface injuries to Neobuxbaumia tetetzo and Neobuxbaumia mezcalaensis of the Tehuacan Valley of Central Mexico. J. Torrey Bot. Soc. 132: 33-37.

Evans, L. S. and N. Abela. 2011. Stem surface injuries of 20 species of succulent Euphorbia (Euphorbiace) from South Africa. Environ. Exp. Bot. 74: 205–215.

Evans, L. S., and M. DeBonis. in press. Predicting Morbidity and Mortality of Saguaro Cacti (Carnegiea gigantea) J. Torrey Bot. Soc Evans, L. S. and A. Macri. 2008. Stem surface injuries of several species of columnar cacti of Ecuador. J. Torrey Bot. Soc. 135:475-482.

Evans, L. S., K.A. Howard and E. Stolze. 1992. Epidermal Browning of Saguaro Cacti (Carnegiea gigantea): Is it new or related to direction? Environ. Exp. Bot. 32: 357-363.

Evans, L.S., V.A. Cantarella, K.W. Stolte and K.H. Thompson. 1994a. Phenological changes associated with epidermal browning of saguaro cacti at Saguaro National Monument. Environ. Exp. Bot. 34: 9-17.

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Evans, L. S., C. McKenna, R. Ginocchino, G. Montenegro, and Roberto Kiesling. 1994c. Surficial injuries to several cacti of South America. Environ. Exp. Bot. 35: 105-117 Evans, L. S., V. Sahi, and S. Ghersini. 1995. Epidermal browning of saguaro cacti (Carnegiea gigantea): Relative health and rates of surficial injuries of a population. Environ. Exp. Bot. 35: 557-562.

Evans, L. S., J. Sullivan and M. Lim. 2001. Initial effects of UV-B radiation on stem surfaces of Stenocereus thurberi (organ pipe cacti). Environ. Exp. Bot. 46: 181-187.

Evans, L. S., A. J. Young, and Sr. J. Harnett. 2005. Changes in scale and bark stem surface injuries and mortality rates of a saguaro (Carnegiea gigantea) cacti population in Tucson Mountain Park. Can. J. Bot. 83: 311-319.

Evans, L. S., P. Boothe and A. Baez. 2013. Predicting morbidity and mortality for a saguaro cactus (Carnegiea gigantea) population. J. Torrey Bot. Soc. 140: 247-255.

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3-11. In C.P. Stone and E.S. Bellantoni [eds.], Proceedings of the Symposium on Research in Saguaro National Monument. Southwest Parks and Monuments Association. Tucson, AZ. Turner, D. and C. Funicelli. 2000. Ten-year resurvey of epidermal browning and population structure of saguaro cactus (Carnegiea gigantea) in Saguaro National Park.

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Characterization of eccentric growth in stems of Artemisia tridentata Nutt. ssp. wyomingensis Beetle & Young Tiffany Kharran∗ Department of Biology, Manhattan College Abstract. Artemisia tridentata Nutt. ssp. wyomingensis stems have an eccentric growth pattern which causes death in localized areas of the stems. Normal growth occurs in all other locations along the stem since the eccentricity only occurs in specific areas. Three stems of Artemisia tridentata Nutt. ssp. wyomingensis presented similar characteristics such as diameters, ring numbers, and stem areas which were studied. Samples were taken along each stem over a distance of 550 mm and had a time difference of more than 26 years in age. All the three stems, exhibited eccentricity.

The results imply that individual stems of Artemisia tridentata Nutt. ssp. wyomingensis will not have exactly the same pattern of eccentric growth although the characteristics of the stems are similar. Data obtained from parameters such as non-sector specificity of eccentric growth and the start of eccentric growth support the randomness of the eccentricity.

More than 13% of segments exhibited a decrease of more than 10 xylem rings from segment to segment which is indication of extreme localization of eccentricity along a stem. Bizarre wood shapes are viewed in cross section due to the expansion of xylem cells adjacent to localized areas which experience a lack of xylem cell production. To the author’s knowledge, this is the first publication that documents the frequency of eccentricity along Artemisia stems and the variation of its results.

Introduction The Central Basin and Range Ecoregion encircles close to 343,000 km2 amidst most of Nevada and a part of Utah. (Soulard, 2012). Artemisia tridentata is among the predominant shrubs of the Great Basin Desert. Species of Artemisia inhabit non-saline sections of the Great Basin Desert.

(Daubenmire, 1970; MacMahon, 1985; Bilbrough and Richards, 1991; Welsh, 2005). Throughout the range, subspecies of Artemisia tridentata are present and contribute to the ecological system.

The eccentric growth of Artemisia stems has been previously described (Diettert, 1938; Ferguson and Humphrey, 1959; Ferguson, 1964). Current findings illustrate that several Artemisia tridentata subspecies have naturally occurring eccentric growth in primary stems at nodes that produce flowering branches. On the contrary, eccentric growth is not produced at nodes that produce vegetative branches along primary stems. (Evans et al., 2012).

Woodiness, a characteristic of Artemisia stems, seems to be a primitive feature of several flowering plants. (Kim et al., 2004). The long evolution (Labandeira et al., 1994) of species that exhibit woodiness is apparent although wood in plants display sophistication. The descent from herbaceous ancestors may be responsible for abnormalities such as eccentric growth and interxylary cork (Moses 1940), which are evident in the wood of shrub species.

Eccentric growth of Artemisia tridentata stems has been documented such that it appears as early as second- year stem production in nodal areas of flowering growth. (Evans et al., 2012). ∗

Research mentored by Lance Evans, Ph.D.

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An in depth representation of eccentric growth along individual stems of Artemisia is lacking although eccentric growth has been previously described. The purpose of the research presented in this paper was to document (1) characteristics of xylary growth along Artemisia branches, (2) changeability of growth patterns that exhibit eccentricity in stem segments and in radial sectors of stem segments, (3) fortify the idea that eccentricity in stems is localized, and (4) analyze the results for wood production in stems of Artemsia tridentata spp. wyomingensis.

Methods Artemisia tridentata spp. wyomingensis stems were collected from plants located near Fremont Canyon, Utah (40.0â—Ś N, 112.1â—Ś W). These stems were kindly sent by Dr. Stanley Kitchen.

The stems obtained were typical to the plants among this region. The Artemisia stems were cut, packed, and shipped to Manhattan College. According to a similarity in diameters along Artemisia stems, three stems were selected for further analysis. For each of three stems, the most important pattern was a diameter that ranged from 4 mm at the tip to 27 mm at the base. In Table 1, the characteristics of each of these three stems are presented. Most of the bark was extracted from Table 1. Comparisons of largest numbers of rings, areas and total length among three branch samples of Artemisia tridentata spp. wyomingensis. For each species, the tip-most and base-most stem segments had stem diameters of approximately 4 and 27 mm, respectively.

Stem sample number Tip-most sample Number of rings Area (mm2 ) Base-most sample Number of rings Area (mm2 ) Total branchlength (mm)

1

2

3

8 9.6

6 6.4

8 13.4

34 754 550

38 727 545

35 603 370

each of the stems. For proper orientation of each of the stem segments, a vertical line was drawn along each stem sample with permanent Sharpie marker (www.Sharpie.com). Therefore, the stem could be reconstructed once all the segments were cut. Each stem segment (cross sections) was obtained using a Dewalt DWHT20541 flush cut pull saw (www.dewalt.com). The average thickness for each segment was approximately 7.8 mm. A digital caliper (Fisher model #14-648-17, Fisher Scientific Inc. Pittsburgh PA) was used to obtain the measurement of the thickness of each segment to an accurate 0.01 mm. Using a Canon PowerShot ELPH100HS camera (www.canon.com), images of cross section stem segments were captured, through a Leica EZ4 microscope (www.leciamicrosystems.com). ImageJ (imagej.nih.gov/ij) was used to collect all the measurements. In each image, zero degree was assigned to the black line drawn on the stem prior to the cutting of the segments. Ten sectors, each 36 degrees apart, were then drawn and rings were traced in Microsoft Paint (Fig. 1). Various segments were cut from stem #1 and #2 but only segments from the tip and

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Figure 1. Three different images of segment 31 from stem #1 (Artemisia tridentata spp. wyomingensis) are presented. Image A illustrates the segment with no alterations immediately after the sawing process. The black mark is evident in this image on the upper left hand portion on the segment. Image B illustrates the lines which were drawn to create the equally separated sectors on the segment. Zero degrees is assigned to the black mark line while the remaining lines are drawn every 36 degree interval clockwise from the previously drawn line. Image C illustrates the tracing of the xylem rings on the segment. Note the eccentricity of this stem segment.

base were cut for stem #3. Comparisons between the three stems were done using the tip-most and base-most segments. Sixty-two segments were cut along stem #1 and eight segments were cut from stem #2. Stem #2 segments were used as a duplicate stem for stem #1. A stem segment was deemed to have eccentric growth if the standard deviation of the number of rings or the area calculations of sectors was more than or equal to 25% of the mean value (Evans et al., 2012).

Table 2. Comparison of the characteristics stem # 1 and stem #2 with diameters between 12 and 18 mm segment number

diameter (mm)

area (mm2 )

largest number of rings

smallest number of rings

Stem #1

23 29 36 38

12.1 14.0 17.0 16.5

93 158 151 205

19 19 19 20

2 2 5 1

Stem #2

4 5 6

12.3 18.4 17.7

160 157 170

20 22 23

6 6 2

Results Comparability of the characteristics for three stem samples The segments located at the tip and base for stems #1 through #3 had similar characteristics (Table 1). At 4 mm in diameter, the three tip-most segments produced six or eight xylem rings.

(Table 1). At 27 mm in diameter, the base-most segments produced between 34 and 38 xylem

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Figure 2. A function of stem area of the number of xylem rings per stem segment for the three samples of Artemisia tridentata spp. wyomingensis used in this study. Diameters from 15 to 18 mm were measured from stem segments of the three stems. Lines are used to guide the eye. For each sample, a linear regression analysis was completed. The upper line (squares) results from stem #2 having an equation of y = 0.063x + 17.0 and an R2 value of 0.17. The middle line (triangles) results from stem #3 with an equation of y = 0.034x + 15.0 and R2 = 0.54. The lower line (diamonds) results from stem #1 having an equation of y = 0.029x + 18.5 and R2 = 0.91.

rings (Table 1). 29 years was the average age difference from the tip to the base for all three stems.

The data further expressed that the number of xylem rings per unit of stem was similar for all three of the stems. (Fig. 2). A further detailed comparison between stem #1 and stem #2 was made including characteristics of stem diameters between 12 and 17 mm. Respectfully, the largest number of rings ranged from 19 to 23 and the smallest number of rings ranged from 1 to 6 for stems #1 and #2. The data expresses the similarity between the three stems.

Figure 3. Example of two cases of eccentricity among segments from stem #1 (Artemisia tridentata spp. wyomingensis) presented in this study. Respectively, segments 57, 56, and 55 are depicted in image A through image C. The ruler lines evident in each image are one mm apart. Image D through image F are stem segments 33, 32, and 31, respectfully. The ruler lines evident in each of these images are 2.4 mm apart. In each of the six images, the black mark is present on the upper left portion in order to maintain the proper orientation of each segment.

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General characteristics of eccentric growth In Fig. 3, two examples of eccentric growth are presented for stem #1. The black mark which indicates 0 degrees is located on the upper left hand region of each image. This was the black line that was drawn along the full length of the stem prior to sawing segments. The black mark in each of the images provides a point in which each image can be compared to each other. Respectively, images 3A-3C were from stem segments 58, 57, and 56 (Appendix 1). The differences in the number of rings in sector 72-108 for segments 58 through 56 best represents the eccentric growth caused by the death of the vascular cambium in localized areas of the stem. Respectively, the number of rings were 29, 7 and 27 in sector 72-108 for segments 58 through 56. The expansion of rings in sector 36-72 is evident in segment 58 to segment 57. This expansion is caused by the vascular cambium’s death after the seventh year of growth. Segment 56 illustrates a large expansion in sector 36-72 which also carries over to section 72-108. In sector 72-108, segment 56 had 27 rings.

The examples used above were present in older stem segments. The same bizarre growth patterns are evident in younger stem segments. For example, eccentric growth is distinct in sector 252-288 in segment 33, 32, and 31 (images 3D-3F). The sector 252-288 in segments 33, 32, and 31 had 16, 8, and 13 rings, respectively. Additionally, considerable differences of 3, 17, and 5 rings were present for these three segments in sector 288-324.

Characteristics of stem sample #1 Eccentricity was displayed in every tissue segment of stem #1 which had more than 10 xylem rings. Over the 550 mm length of the entire stem, there was a range of 9 to 754 mm2 for the segment areas, and the largest number of rings ranged from 8 to 34 rings which indicates that the stem had an age difference of 26 (34 minus 8) years (Table 3). A large range of the number of xylary rings were present within each of the stem segments. Respectively, the number of rings differed from 4 to 7, 5 to 18, and 2 to 34 for segments 1, 24 and 62. The data from all of the stem segments indicates that 17 (28%) segments only had one ring while 43 (66%) had less than five Table 3. Characteristics of several stem segments along the length of stem #1 of Artemisia tridentata ssp. wyomingensis. Segment 1 is the tip-most and segment 62 is the base-most sample for the sampled stem.

Stem segment

Cummulative distance (mm)

Segment area (mm2 )

Largest number of rings

Smallest number of rings

1 8 16 24 32 40 48 56 62

0 47 98 159 219 292 373 449 550

9.6 23 34 98 128 151 232 246 754

8 9 14 18 16 19 25 27 34

4 6 1 5 3 5 1 1 2

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Figure 4. The largest number of rings (triangle) and the smallest number of rings (circles) for the 62 stem segments along stem #1 of Artemisia tridentata spp. wyomingensis of this study. The equation that resulted of the line for the largest number of rings was y = 3.08x + 0.37 with an R2 value of 0.87. The equation that resulted of the line for the smallest number of rings was y = 0.0005x + 3.41 with an R2 value of 0.014.

rings present. Largest and smallest number of rings is shown from the data in Fig. 4 for each of the 62 segments. This is clearly a wide selection of values for each segment.

The analyses carried out determined the differences in number of rings along the stem. As previously mentioned, when the growth of flowering branches kills the vascular cambium in late 1st year or early 2nd year the stems only have one xylem ring. 60 sectors (9.7%) of all of the 620 sectors (62 stem segments multiplied by ten sectors for each segment) for stem #1 only showed one xylary ring (Appendix 1). Hence, only a small portion of segments experienced the vascular cambium’s death early in growth.

Table 4. Number of occurrences where the number of xylary rings differed by 0-2, 3-10, or more than 10 rings from segment to segment within sectors within stem segments of stem #1 of Artemisia tridentata ssp. wyomingensis. There were 62 stem segments evaluated so the values in each sector add to 62 unless a ring was not present for that sector.

Sector Number of changes

036

3672

72108

108144

144180

180216

216252

252288

288324

324360

Mean

S.D.

S.D./ Mean

0 to 2 3 to 10 > 10

24 28 10

30 22 10

20 24 18

27 26 9

28 27 4

30 28 4

36 24 2

31 25 6

21 30 11

19 26 17

26.6 26.0 9.1

5.5 2.4 5.4

20.7 9.1 58.9

Note: On a percentage basis, the changes for samples with 0 to 2, 3 to 10, and more than 10 rings, were 42.9%, 42.4%, and 14.7%, respectively.

Additional analysis was conducted in order to determine differences in number of rings in sectors of segments and among successive segments. The number of xylem rings with changes of 0 to 2 rings, 3 to 10 rings and more than 10 rings among the successive 62 stem segments varied greatly for stem #1 (Table 4). There was a variety of a difference of 0 to 2 ring change from an eminent 36 of 62 stem segments in sector 216-252 to as small as 19 of 62 segments in sector 324-260. On another instance, in which stem segments had a difference of more than 10 rings, sector 72-108 had a high of 18 rings while sector 216-252 had a low of only 2 of the 62 segments.

Chiefly in stem #1, the segment percentages of 0-2, 3 to 10 and with a difference of more than 10 rings among the successive 62 segments were 42.9, 42.4 and 14.7%. An identical analysis was

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conducted to obtain the differences among sectors within each of the segments from stem #1. The ten sectors of each segments had average changes for 0 to 2, 3 to 10 and more than 10 rings at 5.4, 3.2 and 1.4 (i.e. 54.3%, 31.9% and 13.7%), respectively. Overall, more than 13% of segment sectors had a difference of more than 10 xylem rings when calculated using two different methods.

Further analyses were conducted in order to identify whether a low number of rings was continued from segment to segment. If this were the case from segment to segment, the results would imply that eccentric growth patterns are maintained as the stem continues to growth. The result would suggest eccentric growth to be localized in specific locations and not maintained as the stem continues to grow granted that a small number of rings is not maintained from one segment to another. In order to determine the number in which a low number of rings occurred in two successive segments from sector to sector along stem #1 (Table 5), an analysis was completed. The result of the analysis indicates that the number of occurrences with low number of rings in two successive stem segments had a range from 1 to 4 times and had a mean of 2.5 times per sector among the 62 segments of stem #1. Of all the 620 sectors there were only 25 occurrences in which a low number of rings are present. Hence, it is not common for a maintaining of a low number of rings for two successive segments to occur. The data proposes that eccentric growth is extremely localized. In addition to the number of rings present, areas of segments differed considerably as the stem enlarges (Fig. 5). A comparison was done between three successive segments with segments 35 being the youngest of the group and segment 37 being the oldest in the group of three.

Enlarged areas of the xylem rings mostly displayed uniformity from segment 35 to segment 36.

On the contrary, ring areas enlarged considerably from segment 36 to segment 37, chiefly above ring 12.

Table 5. Number of occurrences in which the number of xylary rings deceased by 10 and more than 10 rings for two consecutive segments within sectors of stem #1 of Artemisia tridentata ssp. wyomingensis. There were 62 stem segments evaluated so the values in each sector add to 62 unless a ring was not present for that sector.

Sector Number of occurences

036

3672

72108

2 4 4 Total number of occurrences = 25

108144

144180

180216

216252

252288

288324

324360

Mean

S.D.

S.D./ Mean

2

1

1

2

3

2

4

2.5

1.2

47%

The eccentric pattern of xylem areas throughout stem #1 were also displayed among sectors in segments. In segment 37 of stem #1, the date from three adjacent sectors were compared (Fig. 6). Sector 108-144 had a presence of 17 small rings while sector 144-180 had a presence of only 9 rings with small rings. As opposed to smaller areas, sector 72-108 had a presence of 21 rings with areas that were considerably larger. A similar pattern was present when an older segment with more xylary rings was analyzed. For this segment, sector 144-180 displayed smaller rings. In contrast, the xylem areas for sector 108-144 and 72-108 were similar from each sector to the other

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Figure 5. Comparison of xylem ring areas per sector for sector 72-108 for segments 37 (circles), 36 (squares), and 35 (diamonds) along stem #1 of Artemisia tridentata spp. wyomingensis of this study.

Figure 6. Comparison of xylem ring areas within a sector for sectors 72-108 (circles), 108-144 (squares), and 144-180 (diamonds) for segment 37 of stem #1 of Artemisia tridentata spp. wyomingensis of this study.

Figure 7. Comparison of xylem ring areas within a sector for sectors 72-108 (circles), 108-144 (squares), and 144-180 (diamonds) for segment 31 of stem #1 of Artemisia tridentata spp. wyomingensis of this study.

having larger areas (Fig. 7). The data proposes that non-uniform growth is present in the stem even among areas in which rings were present.

Characteristics of stem sample #2 As a replica of stem #1, a smaller number of segments were cut from stem #2. Among the 12 stem segments all but the first had a maximum of six rings, and all of the segments displayed eccentric growth (Table 6, Appendix 2). Table 7 illustrates the differences from sector to sector in segment 6. Respectively, the number of rings were 23, 10, and 12 for sectors 72-108, 108-144 and 144-180. Furthermore, all the ring in these three sectors had ratios of S.D./mean percentages of more than 9% while four of these rings had percentages above 25%. The data presented in Table 8 expresses a considerable variation of areas per rings in three segments for sector 144-180. There were S.D./mean ratios between 17 and 79% for all rings that had available data (nine rings).The data expressed for stem two displayed eccentric growth patterns similar to stem #1.

Discussion Segments of each stem were subdivided into 10 sectors for the purpose of quantification of eccentricity. Growth can be considered eccentric when there is number of rings or areas with a

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Table 6. Characteristics of several stem segments along the length of stem #2 of Artemisia tridentata ssp. wyomingensis. Segment 1 is the tip-most and segment 8 is the base-most sample.

Stem segment

Cummulative distance (mm)

Segment area (mm2 )

Largest number of rings

Smallest number of rings

1 2 3 4 5 6 7 8

0 258 276 294 306 321 537 545

6 107 110 160 157 170 236 727

6 19 19 20 22 23 23 38

3 6 7 6 6 2 2 1

standard deviation of 25% or more of the mean value for each of the ten sectors in a segment.

The criterion used was extremely similar to the one used by Love et al. (2009). For this study, the criterion used allowed for comparisons between successive stem segments of a stem and between sectors in individual segments.

Table 7. Areas (in mm2 ) within several sectors from segment 6 of Stem #2 of Artemisia tridentata ssp. wyomingensis.

Sectors Ring

72-108

108-144

144-180

Mean

Standard Deviation

S.D./ Mean (%)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Total

0.09 0.70 0.46 0.70 1.57 0.48 0.79 0.72 1.49 1.24 1.81 0.72 1.26 1.04 2.62 1.72 1.20 1.25 0.91 0.76 0.68 0.46 0.16 22.82

0.08 0.56 0.38 0.84 1.73 0.51 1.10 0.49 0.38 0.11 – –

0.10 0.33 0.29 0.71 1.06 0.30 0.81 0.49 0.89 0.78 0.60 0.67

0.09 0.53 0.38 0.75 1.45 0.43 0.90 0.57 0.92 0.71

0.10 0.19 0.08 0.08 0.35 0.11 0.17 0.13 0.56 0.57

11 35 23 10 24 26 19 23 60 80

6.18

7.02

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Table 8. Ring areas (in mm2 ) within sector 144-180 from several stem segments from Stem #2 of Artemisia tridentata ssp. wyomingensis.

Sector number Ring number

4

5

6

Mean

Standard Deviation

S.D./ Mean (%)

1 2 3 4 5 6 7 8 9 10 11 12 Mean Total

0.02 0.11 0.40 0.72 0.31 0.90 0.58 0.31 0.45 – – – 0.42 3.80

0.04 0.08 0.30 0.25 0.72 0.39 0.77 0.43 0.54 0.60 0.82 – 0.45 4.94

0.10 0.33 0.29 0.71 1.06 0.30 0.81 1.06 0.89 0.78 0.60 0.67 0.63 7.60

0.05 0.17 0.33 0.56 0.70 0.53 0.72 0.60 0.63

0.42 0.14 0.06 0.27 0.38 0.32 0.12 0.40 0.23

78 79 18 48 54 61 17 67 37

Mentioned previously, research has expressed that Artemisia tridentata stems display extensive eccentricity (Diettert, 1938; Moss, 1940; Ferguson and Humphrey, 1959; Ferguson, 1964; Miller and Shultz, 1987). This eccentric growth is a result of the death experienced by the stem’s vascular cambium causing a decrease of secondary xylary growth in localized areas (Evans et al., 2012). The results (Evans et al., 2012) exhibit that eccentricity is localized at nodes along main stems having flowering branches which appear early in the second year or late in the first year of the stem’s growth.

In the current study, eccentricity was defined in the three A. tridentata ssp. wyomingensis branches by having similar lengths and diameters. These stems had similar degree of eccentricity and number of xylem rings. These two eccentric components of the stem were present in the two stems that were studied in detail. It seems that no stems of Artemisia tridentata will have identical patterns of eccentric growth although the eccentric characteristics of all three branches in this study were similar in relativity to the frequency in which rings were loss and the amount of growth experienced within the remaining rings. Furthermore, the amounts of eccentricity for small and large stems and from sector to sector had data which illustrates that eccentric growth is not specific to certain sectors and seem to be a random phenomenon. To the author’s knowledge, this is the first publication which documents the frequency of eccentricity along Artemisia stems and the variation of its results.

In this study, every stem segment which had more than ten xylem rings presented eccentricity.

Essentially 10% of all eccentric growth began towards the end of the first year or the start of the second year. Hence, eccentric growth also appears after the first and second year. No defined cause or causes can be concluded for the death of the vascular cambium after the first or second year of

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growth. A possibility is that the vascular cambium’s death might be a result of localized freezing of water at or near the vascular cambium which is caused by predominance of exfoliating bark present in Artemisia. (Provenza et al., 1987). Several other possibilities should be considered as a cause for this phenomenon.

Taking all the 620 sectors of stem #1 in account, a decrease of 10 or more rings were present in more than 13% of all segments. A difference of 10 rings or more is quite considerable since the oldest segment of stem #1 had 36 rings as the maximum of xylary rings for this stem. Additionally, a significant decrease in the number of rings that were maintained from one segment to an adjacent segment only occurred in 25 cases out of the 620 sectors per segments in this study.

As mentioned above, woodiness is considered to be primitive amid some plants that are flowering (Kim et al., 2004).The lengthy evolution (Labandeira et al., 1994) of plant species with woodiness (Carlquist, 1980) produce specialized woods with several woody species. By contrast, the unusual production of interxylary cork and the eccentric growth pattern in species such as Artemisia may have been a result of having herbaceous ancestors (Lundberg, 2009). Furthermore, the presence of these abnormal characteristics of wood production which could otherwise be attributed to plant height might be compromised in order to facilitate the production of a generous amount of seed-bearing Artemisia stems each growing season for reproduction. Compromise such as sacrificing individual growth for species reproduction is common among plants.

Ferguson (1964) expressed analyses of big sagebrush’s (Artemisia tridentata ssp tridentata) xylem rings. Ferguson (1964) presented several images of stems of big sagebrush which determined the age of the plants. The primary purpose expressed in this study was to determine age and the growth status of this plant throughout its region of growth. An extensive set of methods which were well detailed was used for cross-dating the age of the plant. Ferguson (1964) was attentive to the possibly of having false rings in the plant. Ferguson (1964) described skillful techniques that set a high standard when it came to determining the xylem rings for species of Artemisia tridentata.

In the present study, the stems exhibited distinct xylem rings having interxylary cork that helped in determining the characteristics of the rings.

Previous results indicated that eccentric growth started during the end of the first year or at the beginning of the second year for stems of Artemisia tridentata ssp tridentata that were young (Evans et al., 2012). Additionally, that study mentioned that several stems of other Artemisia subspecies exhibit eccentricity in the first and second year. The results in this study further those results to illustrate that Artemisia tridentata ssp wyomingensis has extensive eccentric growth throughout the tissues of its stem.

Acknowledgement

The author kindly appreciates the financial support for this research provided by the Catherine and Robert Fenton Endowed Chair to Lance S. Evans. The author thankfully appreciates the samples of the stems from plants found near Fremont Canyon, Utah supplied by Dr. Stanley Kitchen, Scientist-in charge, Desert Experiment Station, Rocky Mountain Research Station, Provo, Utah.

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The author would also like to thank Jason Durney from the Manhattan College Carpentry Shop for expertly providing the sawing of the Artemisia stem segments.

References Bilbrough, C.J. and J.H. Richards. 1991. Branch architecture of sagebrush and bitterbrush: Use of a branch complex to describe and compare patterns of growth. Can. J. Bot. 69: 1288-1295.

Carlquist, S. 1980. Further concepts in ecological wood anatomy with comments on recent work in wood anatomy and evolution. Aliso 9:499-553.

Daubenmire, R. 1970. Steppe vegetation of Washington. Technical Bulletin 62. Washington State Agricultural Station, College of Agriculture. Washington State University. Pullman, WA. Diettert, R.A. 1938. The morphology of Artemisia tridentata Nutt. Lloydia 1:3-14.

Evans, L. S., A. Citta and S.C. Sanderson. 2012. Flowering branches cause injuries to secondyear main stems of Artemisia tridentata Nutt. subspecies tridentata. Western North American Naturalist 72: 447-456.

Ferguson, C.W. 1964. Annual rings in big sagebrush. Papers of the Laboratory of Tree-Ring Research No 1. University of Arizona Press. Tucson, AZ. Ferguson, C.W. and R.R. Humphrey. 1959. Growth rings of sagebrush reveal rainfall records.

Progressive Agriculture in Arizona. 1959.3.

Kim, S.T., D.E. Soltis, P.S. Soltis, M.J. Zanis and Y.B. Suh. 2004. Phylogenetic relationships among early-diverging eudicots based on four genes: were the eudicots ancestrally woody?

Molecular Phylogenetics and Evolution 31: 16-30.

Labandeira, C.C., D.L. Dilcher, D.R. Davis and D.L. Wagner. 1994. Ninety-seven millionyears of angiospeerm-insect association: paleobotanical insights into the meaning of coevolution.

Proceedings of the National Academy of Sciences. USA 91: 12278-12282.

Love, J.S., J. Borklund, M. Vahala, J. Hertzberg, J. Kangasjarvi, and B. Sundberg. 2009.

Ethylene is an endogenous stimulator of cell division in Populus. Proceedings of the National Academy of Science. 106: 5984-5989.

Lundberg, J. 2009. Asteraceae and relationships within Asterales. Pages 157-169 in V.A. Funk, A.Susanna, T.F. Steussy and R.J. Bayer, editors. Systematics, evolution and biogeography of Compositae. International Association for Plant Taxonomy, Institute of Botany. University of Vienna, Vienna, Austria.

MacMahon, J. A. 1985. Deserts. The Audubon Society Nature Guides. Alfred A. Knopf. New York, 638 p.

Moss, E.H. 1940. Interxylary cork in Artemisia with a reference to its taxonomic significance.

American Journal of Botany 27: 762-768.

Provenza, F. D., J.T. Flinders, and E. Durant McArthur. 1987. Proceedings: Symposium on Plant Herbivore Interactions. Snowbird, Utah. August 1985. Intermountain Research Station, Forest Service, U.S. Dept. of Agriculture, 1987 - Biotic communities - 179 pages

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Soulard, C. E. 2012. Central Basin and Range Ecoregion 2012. in Status and Trends in the Western United States – 1973 to 2000 (Edited by B. M. Sleeter, T. S. Wilson and W. Acevecb) US Geological Survey Professional Paper 1794-A. Welsh, B. 2005. Big sagebrush: a sea fragmented into lakes, ponds, and puddles. General Technical Report RMRS-GTR-144. Fort Collins, CO. Appendix 1. Number of xylary rings for the 10 sectors for each of the 62 segments of Stem #1 of Artemisia tridentata ssp. wyomingensis. Segment 1 is the tip-most and segment 62 is the base-most sample for the stem #1.

Sector Segment 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

036

3672

72108

108144

144180

180216

216252

252288

288324

324360

S.D./Mean (%)

8 7 2 7 8 4 9 7 9 10 9 10 11 14 3 3 15 21 18 17 19 16 18 16 10 18 20 16 20 17 16 13 7 11 18 20

8 7 2 4 4 8 9 9 9 10 9 10 11 14 14 15 15 16 18 13 9 6 18 16 18 19 4 9 20 17 15 19 16 19 18 13

5 7 3 7 4 8 9 9 9 1 9 9 11 14 8 5 2 7 6 6 3 15 17 4 18 2 19 6 20 17 12 18 19 19 6 6

5 4 6 5 4 8 9 9 9 10 10 11 11 13 1 3 2 6 3 2 4 10 10 2 13 17 15 7 15 14 8 2 19 17 14 6

5 7 6 3 8 8 9 7 6 7 10 1 5 8 8 2 2 6 3 2 6 9 10 8 9 10 10 7 11 10 8 7 3 7 13 7

6 7 6 5 8 7 9 6 6 7 10 9 3 6 5 2 2 6 3 2 1 7 10 8 9 11 11 7 11 9 6 7 8 15 20 18

8 5 6 7 8 8 8 7 5 7 9 10 1 3 4 2 2 5 3 2 1 6 10 8 7 8 7 16 8 1 5 7 13 9 9 20

8 5 3 7 8 8 9 9 5 9 9 10 1 2 3 2 2 6 5 2 1 6 5 7 7 13 6 17 6 5 5 13 8 16 7 7

8 5 4 7 8 8 9 9 9 10 9 10 1 2 3 2 2 10 14 7 1 6 5 14 11 2 20 17 11 5 5 17 3 9 16 10

8 7 4 7 8 8 9 9 9 10 9 10 2 5 3 2 3 21 19 17 1 10 18 16 17 5 20 10 6 17 3 17 5 8 3 7

21 20 40 26 27 17 3 15 24 36 5 32 83 64 73 105 116 62 77 91 124 41 43 53 37 60 48 42 44 54 54 49 63 36 37 52

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8 20 8 7 20 8 20 26 22 26 25 28 28 28 24 7 30 9 30 34 33 26 33 35 34 34

20 20 19 1 20 23 8 7 22 26 25 27 28 16 11 29 30 27 18 22 20 17 33 35 29 21

20 20 19 22 6 9 6 4 22 20 16 23 22 5 10 26 8 20 18 27 7 29 28 28 15 4

8 20 14 18 1 1 5 2 1 1 1 22 21 3 6 24 16 8 11 6 12 3 13 15 10 1

19 16 5 10 1 1 5 3 1 1 1 13 16 4 3 13 11 1 7 6 4 7 10 21 5 1

1 14 5 4 1 1 5 4 1 1 1 5 8 6 6 10 1 1 16 13 13 17 10 16 4 1

11 11 11 6 1 1 5 4 1 1 1 1 4 16 13 7 1 1 10 12 13 13 15 13 3 8

21 5 13 9 1 3 5 5 3 1 1 1 4 24 17 9 1 1 10 12 10 13 12 15 2 7

21 5 19 13 1 5 4 13 10 1 1 1 7 24 19 9 1 1 7 14 14 11 24 26 3 16

Kharran 17 20 14 19 2 24 26 26 22 14 1 17 15 28 24 10 7 3 10 29 28 20 33 24 34 12

48 41 43 64 145 122 86 99 9 121 143 80 61 67 56 59 108 128 51 56 58 51 48 36 96 101

Appendix 2. Number of xylary rings for the 10 sectors within each of the 8 segments of Stem #2 of Artemisia tridentata ssp. wyomingensis. Segment 1 is the tip-most and segment 8 is the base-most sample for Stem #2.

Sector Segment

036

3672

72108

108144

144180

180216

216252

252288

288324

324360

S.D./Mean (%)

1 2 3 4 5 6 7 8

6 19 19 20 22 23 23 38

6 19 19 20 22 23 23 4

6 7 7 16 13 16 23 4

6 6 7 8 9 10 12 5

6 6 7 8 6 11 10 1

3 6 7 6 6 11 12 1

6 6 7 6 6 11 12 1

6 6 7 9 8 2 20 25

6 19 19 16 8 18 2 38

6 19 19 20 22 23 2 38

16.6 58.7 52.5 46.9 57.9 47.4 58.5 110

Prevalence of human intestinal parasites in Atlantic oysters (Crassostrea virginica) Steven Michael Kowalyk∗ Department of Biology, Manhattan College Abstract. Bivalves, such as the Atlantic oyster, are excellent bio-indicators of marine environments. By filter feeding, these organisms often ingest various pollutants and parasites, providing an overall picture of the health of a marine habitat. Toxoplasma gondii and Giardia lamblia are intestinal protozoan parasites that can lead to serious complications in immunocompromised individuals. Surprisingly, T. gondii and G. lamblia have been found recently in many marine organisms. The goal of this study is to determine the prevalence of T. gondii and G. lamblia in Atlantic oysters. Oyster samples were collected from Orchard Beach in New York in the fall of 2014 and 2015 during low tide. Tissues were harvested from the oysters prior to DNA isolation. To determine whether the collected samples were infected with T. gondii and G. lamblia, a polymerase chain reaction (PCR) was performed using primers specific to those parasites. We found that none of the tested samples from 2014, 0/10, were positive for T. gondii. However, a 60% prevalence of G. lamblia was found in these samples. It was determined that the G. lamblia-positive samples were of the assemblage A genotype. In contrast, a 33% prevalence of G. lamblia DNA was found in the samples collected in 2015, indicating approximately a two-fold decrease from 2014. We will be screening for T. gondii in the samples collected in 2015. The results indicate that Atlantic oysters are excellent bio-indicators of human intestinal parasites and of contamination of Orchard Beach with these parasites.

Introduction The overall health of marine ecosystems is not only of importance to marine organisms, but also to human health. Thus, it is necessary to carefully monitor marine ecosystems for the presence of various pollutants, both biological and chemical. A variety of strategies to assess water quality have been developed, including the use of bivalves as bio-indicator organisms. Bivalve mollusks, which include clams, mussels, oysters, and other organisms, are filter feeders. As such, bivalves obtain and accumulate various particles from their environment. Heavy metal and pesticide contamination in marine environments have long been studied using bivalves as bio-indicators (Miller et al., 2005). More recently, bivalves have been used to assess bioaccumulation of bacteria, viruses, and protozoan parasites (Graczyk et al., 2002).

The use of bivalves in the detection of waterborne protozoan parasites, such Toxoplasma gondii and Giardia lamblia, is of particular interest in regard to human health. T. gondii is an intracellular protozoan parasite that causes the disease toxoplasmosis in infected humans. T. gondii infection in humans is widespread, but most healthy individuals are asymptomatic (Dubey, 2004).

Some people may experience mild-flu like symptoms. However, in immunocompromised individuals such as those with AIDS and in pregnant women and newborns the disease can lead to complications including blindness and seizures (Dubey, 2004). Studies have even shown a potential link between toxoplasmosis and a variety of psychiatric disorders such as schizophrenia ∗

Research mentored by Ghislaine Mayer, Ph.D.

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and bipolar disorder (Jones et al., 2014). The definitive hosts of T. gondii are felids, which shed the environmentally resistant oocysts of the parasite through their feces leading to the infection of intermediate hosts (Jones et al., 2012). The feces along with the oocysts can then enter marine environments through untreated sewage or storm-water, exposing marine organisms (Conrad et al., 2005). Thus consumption of raw oysters for example, or the accidental ingestion of contaminated water, could expose an individual to T. gondii infection.

G. lamblia is an intestinal flagellated protozoan parasite that infects a wide array of vertebrate hosts (Lalle et al., 2005). The parasite results in the disease giardiasis, which manifests itself with gastrointestinal symptoms such as nausea, weight loss, acute or chronic diarrhea, and abdominal pain (Fletcher et al., 2012). Diarrhea is particularly dangerous in young children, especially in developing nations. The source G. lamblia cysts in marine environments are attributed to wastewater or agricultural runoff that has been contaminated with human or animal feces containing cysts (Fayer et al., 2004). This contamination exposes marine wildlife as well as humans to infection.

Furthermore, bivalves also have been shown to be susceptible to G. lamblia infection (Fayer et al., 2004). G. lamblia possesses multiple genotypes, including assemblages A, B, C, D, and E. Humans are infected primarily with assemblage A and sometimes B, however these assemblages are also present in cats, gods, and cattle (Lalle et al., 2005).

The goal of this study was to utilize the bivalve Crassostrea virginica, or Atlantic oyster to assess the water quality of the marine environment of Orchard Beach, NY, by investigating the prevalence of the protozoan parasites T. gondii and G. lamblia. Additionally, the temporal prevalence of G. lamblia infection in the oysters was assessed.

Materials and Methods Collection of Oysters and DNA Extraction Atlantic oysters were collected at Orchard Beach in Bronx, NY during low tide in the fall of 2014 and the fall of 2015 as part of a larger study that involved three other species of bivalves.

On September 9, 2014, 10 oysters were collected. On October 5th 2015, 9 oysters were collected.

Each oyster was dissected and five tissue types harvested: the abductor muscle, digestive gland, foot, gills, and mantle. The dissected tissues were then stored at -80 ◦ C prior to DNA extraction.

DNA extraction was carried out using the DNeasy Blood and Tissue Kit (Qiagen, Valencia, CA). In brief, DNA extraction involved the cutting up of 0.25 grams of each tissue sample, the addition of buffer and the enzyme proteinase K, and incubation in a water bath set to 56 ◦ C for 1 hour for lysis. Following incubation, the samples were vortexed and transferred to a mini spin silica DNA column. The samples were then washed with buffers and eluted, yielding purified DNA. DNA purity of each of the samples was quantified using a UV spectrophotometer. Extracted DNA samples were then stored at -20 ◦ C prior to further analysis.

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Detection of Parasites using Polymerase Chain Reaction T. gondii DNA was detected using primer sets targeting the GRA6 gene. The sequences used were as follows: forward primer, 5’-GTAGCGTGCTTGTTGGCGAC- 3’, and reverse primer, 5’TACAAGACATAGAGTGCCCC-3’ (Fazaeli et al., 2000). The following conditions were used for the PCR reaction: 95◦ C for 5 minutes for one cycle, 94◦ C for 30 seconds for 35 cycles, 60◦ C for 1 minute, 72◦ C for 2 minutes, and one cycle for the final extension at 72◦ C for 7 minutes (Fazaeli et al., 2000). Purified T. gondii DNA was used as a positive control in the PCR reaction, while water was used as a negative control. PCR products were analyzed using a 1.6% agarose gel stained with ethidium bromide under UV G. lamblia DNA was detected using a nested-PCR protocol previously described using primer sets targeting the β-giardin gene (Lalle et al., 2005). Purified G. lamblia DNA was used as a positive control, while water was used as a negative control in the PCR reaction. PCR products were analyzed using a 1.5% agarose gel stained with ethidium bromide visualized under UV light. The genotype of G. lamblia DNA was assessed by restriction fragment length polymorphism (RFLP) analysis using a previously described protocol (Lalle et al., 2005).

Results A total of 10 oyster samples were collected from Orchard Beach, NY on September 9th , 2014 during low tide. Following the PCR reactions and gel visualization, we found that none of the oyster samples tested positive for T. gondii (Table 1). However, 6/10, or 60% of the oyster samples tested positive for G. lamblia (Table 1) Among the 6 G. lamblia positive samples, a total of 12 individual tissues were infected (Table 2). All tissue types except the foot were found to be infected (Table 2.) RFLP analysis of the 12 infected tissue types from the 6 samples revealed that all of the G. lamblia DNA belonged to the genotype assemblage A (Table 2). Fig. 1 shows the 12 individual tissue samples, each showing the banding pattern associated with assemblage A. Table 1. T. gondii and G. lamblia infection status in C. Virginica samples from 2014 Sample Number

T. gondii infection

G. lamblia infection

1 2 3 4 5 6 7 8 9 10

Absent Absent Absent Absent Absent Absent Absent Absent Absent Absent

Absent Present Absent Present Absent Present Absent Present Present Present

We tested the oyster specimens collected in 2015 for the presence of G. lamblia DNA. A total of 9 oyster samples were collected from Orchard Beach, NY on October 5th during low tide. PCR

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Table 2. C. virginica tissues infected with G. lamblia and RFLP analysis data for 2014 Sample Number

Tissue Type

Assemblage Type

2 4 6 6 8 8 8 8 9 9 9 10

Abductor Muscle Digestive Gland Abductor Muscle Mantle Abductor Muscle Digestive Gland Gills Mantle Digestive Gland Gills Mantle Digestive Gland

A A A A A A A A A A A A

Table 3. G. lamblia infection status in C. Virginica samples from 2015 Sample Number

G. lamblia infection

1 2 3 4 5 6 7 8 9

Absent Present Present Absent Absent Absent Present Absent Absent

Table 4. C. virginica tissues infected with G. lamblia in 2015 Sample Number

Tissue type infected

2 3 17

Foot Foot Foot

reactions and gel visualization to determine the presence of G. lamblia showed that (3/9), or 33% of the oyster samples tested positive for G. lamblia (Table 3). Among the 3 infected oyster samples, a total of 3 individual tissues were found, all belonging to the foot (Table 4). Thus, there was an approximately two-fold decrease from 2014 to 2015 in the prevalence of G. lamblia in the samples analyzed.

Discussion In summary, we have found that the oyster samples collected in 2014 had a prevalence of 60% for G. lamblia, indicating contamination of Orchard beach with G. lamblia. No particular tissue seemed to have a higher prevalence of infection than others. Furthermore, RFLP analysis has shown that the infected samples belong to the G. lamblia genotype assemblage A, as evidenced by the expected fragments at 201, 150, 110, and 50 bp (Fig. 1). Studies have shown that assemblage A has been detected in humans (Lalle et al., 2005). Thus, it is reasonable to propose that the source of G. lamblia in Orchard Beach is from sewage containing human feces. The results have also

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shown that none of the oyster samples collected at Orchard Beach. NY in 2014 tested positive for T. gondii DNA. This indicates that Orchard Beach is not contaminated with T. gondii.

Figure 1. RFLP gel for C. virginica tissues infected with G. lamblia

The oyster samples collected in 2015 at Orchard Beach have shown a prevalence of 33% for G. lamblia, approximately a two-fold decrease from the 60% prevalence of G. lamblia infection found in the 2014 oyster samples (Fig. 2). Interestingly, the 3 infected tissues from the 3 oyster samples all belonged to the foot. Oysters use their foot to attach to substrates, thus it is possible that their increased exposure to seawater makes them more susceptible to infection. Ongoing work is being done to genotype the G. lamblia detected in the oysters in 2015 to determine which assemblage they belong to. Additionally, work is being done to determine the prevalence of T. gondii infection in the 2015 oyster samples.

This study has indicated that bivalves, specifically Crassostrea virginica are excellent tools for assessing the water quality of marine environments. We demonstrated that C. virginica was able to accumulate G. lamblia cysts. The temporal prevalence of G. lamblia infection in the oysters, which showed a two-fold decrease of prevalence, is interesting in light of recent local news reports concerning orchard beach. A report from the news station News 12 Bronx (2012) stated that Orchard Beach was closed in August of 2015 due to contamination of the water with sewage and storm water runoff, including fecal matter (News 12, 2015). This supports our data that showed115 the beach was contaminated with G. lamblia. Future studies using Crassostrea virginica with increased sample sizes will further illustrate the usefulness of bivalves as bio-indicator organisms.

Figurre 2

Figure 2. Change in prevalence of G. lamblia infection over time

Prevalance of G. lamblia in Oysters

70% 60% 50% 40% 30% 20% 10% 0%

2014

2015 5

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Acknowledgements I would like to thank the Manhattan College School of Science for funding the research. I would like to thank Dr. Mayer, my research advisor, for assisting in and supervising the research project, as well as my fellow student colleagues Freda Tei, Jhenelle Reid, and Matthew Presta for the work they did to assist in the project. I would also like to thank Dr. Judge, who aided in the collection of the bivalve samples.

References Conrad, P. A., et al. (2005). “Transmission of Toxoplasma: clues from the study of sea otters as sentinels of Toxoplasma gondii flow into the marine environment.” International journal for parasitology 35(11), 1155-1168.

Dubey, J. P. (2004). Toxoplasmosis–a waterborne zoonosis. Veterinary parasitology 126.1: 57-72.

Fayer, R., J. P. Dubey, and D. S. Lindsay (2004). Zoonotic protozoa: from land to sea. Trends in parasitology 20(11), 531-536.

Fazaeli, A., et al. (2000). Molecular typing of Toxoplasma gondii strains by GRA6 gene sequence analysis. International journal for parasitology 30.5: 637-642.

Fletcher, S. M., et al. (2012). Enteric protozoa in the developed world: a public health perspective.

Clinical microbiology reviews 25.3: 420-449.

Graczyk, T., et al. (2003). Accumulation of human waterborne parasites by zebra mussels (Dreissena polymorpha) and Asian freshwater clams (Corbicula fluminea). Parasitology research 89.2: 107-112.

Jones, J. L., and J. P. Dubey (2012). Foodborne toxoplasmosis. Clinical Infectious Diseases: cis508.

Jones, J. L., M. E. Parise, and A. E. Fiore (2014). Neglected parasitic infections in the United States: toxoplasmosis. The American journal of tropical medicine and hygiene 90.5: 794-799.

Lalle, M., et al. (2005). Genetic heterogeneity at the β-giardin locus among human and animal isolates of Giardiaduodenalis and identification of potentially zoonotic subgenotypes. International journal for parasitology 35.2: 207-213.

Miller, M. A., et al. (2002). Coastal freshwater runoff is a risk factor for Toxoplasma gondii infection of southern sea otters (Enhydra lutris nereis). International journal for parasitology 32.8: 997-1006.

Miller, W. A., et al. (2005). Clams (Corbicula fluminea) as bioindicators of fecal contamination with Cryptosporidium and Giardia spp. in freshwater ecosystems in California. International journal for parasitology 35.6: 673-684.

News 12 Bronx (2012). http://bronx.news12.com/news/officials-orchard-beach-closed-to-swimmers- due-to-contamination-1.10781543

Effects of Batrachochytrium dendrobatidis and urbanization on P. cinereus in lower New York State Andrew Paramo∗ Department of Biology, Manhattan College Abstract. The chytrid fungus Batrachochytrium dendrobatidis is currently afflicting amphibian populations globally, however few studies document its presence within New York State (NYS). Some studies suggest some amphibian populations may differ in their ability to resist this emerging disease. This study aims to investigate the prevalence of B. dendrobatidis in lower NYS, and to compare symbiotic microfloral resistance to B. dendrobatidis between urban and rural amphibian populations. Between the months of June and August of 2015, 14 amphibians were collected and swabbed for Bd in Van Cortlandt Park, NYC, and in Harriman State Park. DNA was extracted from these swabs and subject to Polymerase Chain Reaction (PCR), and compared to a positive sample. All 14 samples tested negative for B. dendrobatidis, and all collected microfloral cultures await challenging against the pathogen. Further sampling is required in our rural field site, and further investigation is required with regards to cutaneous symbionts.

Introduction Anthropogenic habitat fragmentation, climate change, and disease are the greatest threats to amphibian species across the globe; amphibian declines currently exceed those of all other vertebrate groups (Hof et al., 2011). Amphibian conservation is imperative, as they are strongly linked to ecosystem dynamics involving trophic cascades, detritus food webs, predator-prey relationships and nutrient recycling (Davic et al., 2004). Amphibians are also valuable as indicator species due to their sensitivity to environmental conditions; their health reflecting that of their habitat (Welsh and Droege, 2001).

Amphibian chytridiomycosis caused by the chytrid fungus, Batrachochytrium dendrobatidis, is a major emerging threat to amphibian populations. This infectious fungal disease was first recognized in 1997, and has contributed to the decline or extinction of over 200 amphibian species worldwide (Fisher et al., 2009). B. dendrobatidis afflicts keratinized cells of the amphibian epidermis, and can cause hyperkeratosis, hyperplasia, weight loss, and death (Brucker et al., 2008). This hyperkeratosis and hyperplasia effectively interferes with osmoregulation and cutaneous respiration, which are both indispensable function to amphibians for survival (Ruiz and Rueda-Almonacid, 2008). Significant efforts have been made to map the prevalence of B. dendrobatidis in natural populations. Diagnosis of chytridiomycosis is possible through histological and immunohistochemical analysis of toe clips, as well as through less invasive methods such as PCR analysis of skin swabs (Boyle et al. 2004). Though qPCR is the more popular method of PCR analysis, endpoint PCR has been deemed equally effective at detecting the presence of zoospores (Windstam and Olori, 2014). Due to limited sampling within the region, few studies document the presence of B. dendrobatidis in New York State (Windstam and Olori, 2014). ∗

Research mentored by Gerardo Carfagno, Ph.D.

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Some symbiotic microflora present on amphibian skin secrete anti-fungal metabolites, which assist individuals in resisting Bd (Harris et al., 2006). One example is the antifungal strain of Janthinobacterium lividum, which has been isolated from the skin of P. cinereus, and shown to produce the antifungal metabolites 3-carboxaldehyde, and violacein (Brucker et al., 2008). Though urbanization is generally attributed with amplifying the decline of amphibian populations, some studies suggest that urban environments may actually serve as a refuge against B. dendrobatidis.

This is suspected to be due to differences in symbiotic bacteria present on amphibian skin between such populations (Saenz et al., 2015). The Eastern Redback Salamander, Plethodon cinereus, was chosen as an ideal study subject due to its high prevalence in northeastern North America and because they are an entirely terrestrial species (Moore and Wyman, 2010). Considering this species’ wide distribution, role as an indicator species, and importance to forest ecology, it is clear that their health deserves special attention (Moore and Wyman, 2010).

Our goal was to investigate the prevalence of Batrachochytrium dendrobatidis infections in amphibian populations of lower New York State, and to compare symbiotic bacterial resistance to B. dendrobatidis between urban and rural environments. We expected to see increased symbiotic resistance to B. dendrobatidis from urban microflora, in comparison to rural microflora.

Materials and Methods Field-sites and Amphibian Collection Between the months of June and August 2014, 50.25 man-hours were spent sampling for amphibians in several NYS field sites, primarily focusing on Van Cortlandt Park and most recently Harriman State Park. Located in New York City, Van Cortlandt served as the urban field site, while Harriman State Park, located fifty miles out of New York, NY, served as an urban field site.

Both sites had similar superficial characteristics in their habitats, however it cannot be claimed to be a perfect urban to rural gradient. The primary species being pursued was the Eastern Redback Salamander P. cinereus, a species commonly found in eastern temperate deciduous forest; however amphibians belonging to other species were also swabbed for Bd. Data Collection Once located, subjects were rinsed twice in sterile dechlorinated water to remove any transient bacteria, and handled with sterile nitrile gloves. The species of the subject was then identified and photographed. Subjects were then swabbed ten times on the lateral, dorsal, and ventral surfaces.

Swab tips were clipped and stored in 1.5 mL microcentrifuge tubes containing 70% ethanol and stored on ice (Windstam and Olori, 2014). Cutaneous microfloral cultures were collected on three upstate subjects by swabbing in the same fashion, and streaking the swab onto a plate containing Difco R2A media. The individual’s weight and dimensions were then measured, as well as the dimensions of the cover object, canopy cover, temperature and GPS location, for use in a concurrent study. All gloves were changed between individuals, and all materials were properly sterilized using high concentration ethanol or bleach.

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DNA Extraction DNA was extracted from swabs using the Qiagen Blood & Tissue DNA Kit (Qiagen, Valencia, CA). This kit was chosen due to its fidelity and reputation for removing DNA degrading contaminants such as Hiatic Acid. The kit was used following Qiagen’s protocol: DNA Purification from Buccal Swabs (Spin Protocol), instead of the provided protocol since it was necessary to extract DNA from the swabs, not individual tissue samples. Swabs were first transferred to 2 mL microcentrifuge tubes; 400 µL of PBS were then added. 20 µL of Qiagen Protease stock solution and 400 µL of Buffer AL were added to the sample, and immediately vortexed for 15 s. Samples were incubated in a water bath at 56o for ten minutes. 400 µL of 100% ethanol were then added, followed by vortexing, and centrifugation to remove drops from the lid. 700 µL of the mixture were then transferred to the QIAmp Mini spin column and centrifuged at 6000 g for 1 min. The 2 mL collection tube containing filtrate was discarded, and another collection tube was used. The remaining mixture from step four was then added to the spin column and centrifuged once again.

The spin column was then treated with 500 µL of Buffer AW1 and centrifuged at 6000 x g for 1 min. The collection tube with filtrate was discarded once again. 500 µL of Buffer AW2 was then added followed by centrifugation at full speed (20,000 g) for 3 min. The spin column was then placed in a clean 1.5 mL centrifuge tube and 100 µL of Buffer AE was then added, followed by incubation at room temperature for 1 min, and centrifugation at 6,000 g for 1 min. DNA was then quantified using a spectrophotometer at 260 nm.

PCR Amplification and Gel Electrophoresis Endpoint PCR was used to detect the presence of B. dendrobatidis zoospores. Purified B. dendrobatidis DNA was provided by Pisces Molecular (Boulder, CO) at several concentrations to serve as a positive control. Each PCR contained 10 µL of molecular grade water, 12.5 µL of Invitrogen master mix, 1.25 µL of forward primer ITS1-3 Chytr (5’-CCTT GATATAATACAGTGTGCCATATGTC-3’; Life Technologies; Table 1), and 1.25 µL of reverse primer 5.8S Chytr (5’- AGCCAAGAGATCCGTTGTCAAA-3’; Life Technologies; Table 1), for a total volume of 25 µL (Windstam and Olori 2014). The PCR protocol was as follows: initial denaturation at 95o C for 4 min, followed by 50 cycles of denaturing at 95o C for 30 s, annealing at 55o C for 30 s, and extension at 72o C for 45 s (Windstam and Olori 2014). Each PCR was conducted including a positive B. dendrobatidis DNA control, and a negative control containing only PCR cocktail and sterile molecular grade water. 2.5 µL of each PCR tube was mixed with loading dye and loaded into a 2% agarose gel in 1X TAE buffer. The positive control yielded an expected band of 146 bp (Windstam and Olori 2014). A 100 bp ladder was used to determine bp size.

Table 1: Primers used for Bd detection Forward Primer (ITS1-3 Chytr)

50 -CCTTGATATAATACAGTGTGCCATATGTC-30

Reverse Primer (5.8S Chytr)

50 -AGCCAAGAGATCCGTTGTCAAA-30

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Fig 1: P. cinereus

Fig 2: A. opacum

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Fig 3: P. cinereus microflora

Results and Discussion We successfully sampled primarily P. cinereus (Fig. 1), however other species, such as the marbled salamander Ambystoma opacum, (Fig. 2), were also captured and swabbed. Microflora from P. cinereus (Fig. 3), and microflora from A. opacum (Figs. 4 and 5) were successfully cultured.

These cultures contain a variety of bacterial species, but have several bacterial species in common.

The red colonies depicted in Fig. 3 can also be visualized in cultures obtained from A. opacum salamanders (Figs. 4 and 5). Despite having been obtained from Harriman State Park during the same season, it is interesting that the cultures obtained from the two marbled salamanders have much in common with each other, but are generally comprised of colonies not seen in P. cinereus microflora (Fig. 3). The number of microfloral cultures collected are too few to claim to see any trend, however the amount of variation in salamander microflora between species and its impact on their resistance is a question to consider.

How much variation is there between salamander microfloral species, and could this make some species of amphibians more resistant to B. dendrobatidis than others? Ultimately, we intend to challenge these and additional microfloral cultures against B. dendrobatidis under controlled conditions to measure levels of inhibition. These challenges will be conducted on 1% tryptone agar plates uniformly streaked with B. dendrobatidis. Respective microflora will then be streaked at the center and observed for levels of inhibition. These levels of inhibition will be recorded and compared between salamander symbionts collected from urban and rural environments. This challenge awaits the successful growth and establishment of our B. dendrobatidis stock culture from its zoospores (Fig. 6). We expect to see increased resistance to the pathogen in microflora collected from urban environments, as some studies suggest differences in symbiotic bacteria from isolated habitats may increase resistance (Saenz et al., 2015).

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Fig 4: A. opacum microflora

Fig 5: A. opacum microflora

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Fig 6: B. dendrobatidis zoospores

Of the 14 cutaneous swabs collected, none tested positive for B. dendrobatidis. Fig. 7 depicts the results of the PCR conducted on all 14 swabs; preceded by the bp ladder, negative control, and positive control with the characteristic band at 146 bp in the third lane. Though all samples tested negative, as expected for lower NYS, this does not mean that B. dendrobatidis was not present in the population. The sensitivity of this analysis has yet to be determined in regards to concentration of zoospores, thus it is not possible to conclude that these amphibians were not infected. There is no guarantee that minute quantities of B. dendrobatidis zoospores will always be included in the DNA extraction aliquot subject to PCR. It is possible that minute amounts of the pathogen’s DNA eluded detection due to it comprising only a low percentage of DNA extracted for the swabs. The efficacy of the DNA extraction kit is also a factor to consider. It is possible that B. dendrobatidis zoospores present in minute quantities were not fully extracted during the spin column extraction. Therefore, these factors must be considered in this analysis and require further investigation. Additional sampling will also be necessary in order to establish a better sample size for our rural field. In order to reach any conclusions regarding urbanization and resistance to chytridiomycosis, we require a better-equilibrated sample size between our urban and rural field sites. This preliminary study established how to sample and test for this infectious disease. We expect that sampling for B. dendrobatidis will continue from this foundation as an ongoing study.

Figure 7: PCR gel results of 14 cutaneous swabs for B. dendrobatidis detection Lane #: 1: 100 Bp Marker; 2: (-) Control; 3: (+) Control; 4-17: Samples

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Acknowledgements The author thanks the Jasper Summer Research Scholars and the Department of Biology for financial support; Dr. Longcore, at the U. of Maine Chytrid Laboratory, for the live cultures of B. dendrobatidis; Dr. Wood, at Pisces Molecular Lab, Boulder CO, for the positive controls and expertise in chytrid research; Drs. G. Mayer and Q. Machingo for guidance during lab analyses; Dr. G. Carfagno and Mary Portes for affording me the privilege of working with them.

References Boyle, Dg, Db Boyle, V. Olsen, Jat Morgan, and Ad Hyatt. “Rapid Quantitative Detection of Chytridiomycosis (Batrachochytrium dendrobatidis) in Amphibian Samples Using Real-time Taqman PCR Assay.” Diseases of Aquatic Organisms 60 (2004): 141-48.

Brucker, R. M., R. N. Harris, C. R. Schwantes, T. N. Gallaher, D. C. Flaherty, B. A. Lam, and K. P. C. Minbiole. “Amphibian Chemical Defense: Antifungal Metabolites of the Microsymbiont Janthinobacterium Lividum on the Salamander Plethodon Cinereus.” J Chem Ecol Journal of Chemical Ecology 34.11 (2008): 1422-429. Web. Davic, R. D., and H. H. Welsh. “On The Ecological Roles Of Salamanders.” Annual Review of Ecology, Evolution, and Systematics 35.1 (2004): 405-34.

Fisher, M. C., Trenton W.J. Garner, and S. F. Walker. “Global Emergence of Batrachochytrium dendrobatidis and Amphibian Chytridiomycosis in Space, Time, and Host.” Annual Review of Microbiology 63.1 (2009): 291-310.

Harris, R. N., T. Y. James, A. Lauer, M. A. Simon, and A. Patel. “Amphibian Pathogen Batrachochytrium dendrobatidis is Inhibited by the Cutaneous Bacteria of Amphibian Species.” EcoHealth 3.1 (2006): 53-56.

Hof, C., Ara´ujo, M. B., Jetz, W. and Rahbek, K., “Additive threats from pathogens, climate and land-use change for global amphibian diversity,” Nature, 480 (2011): 516–519 Moore, J-D., and R. L. Wyman. “Eastern Red-backed Salamanders (Plethodon cinereus) in a Highly Acid Forest Soil.” The American Midland Naturalist 163.1 (2010): 95-105.

Ruiz, A., and J. V. Rueda-Almonacid. “Batrachochytrium dendrobatidis and Chytridiomycosis in Anuran Amphibians of Colombia.” EcoHealth 5.1 (2008): 27-33.

Saenz, D., T. L. Hall, and M. Kwiatkowski. “Effects of Urbanization on the Occurrence of Batrachochytrium dendrobatidis: Do Urban Environments Provide Refuge from the Amphibian Chytrid Fungus?” Urban Ecosystems 18.1 (2015): 333-40.

Welsh, H. H., and S. Droege. “A Case for Using Plethodontid Salamanders for Monitoring Biodiversity and Ecosystem Integrity of North American Forests.” Conservation Biology 15.3 (2001): 558-69. Web. Windstam, S. T., and Olori, J. C. 2014. “Proportion of hosts carrying Batrachochytrium dendrobatidis, causal agent of amphibian chytridiomycosis, in Oswego County, NY in 2012.” Northeastern Naturalist, 21(1) NENHC-25-34.

A Pathway of Development: The impact of knocking down the kv2.1 and FAK protein coding genes in zebrafish embryos Olivia Payne∗ Department of Biology, Manhattan College Abstract. In this project we studied the facilitation of convergent extension (CE) in developing zebrafish embryos. We hypothesized that kv2.1 and FAK interact to facilitate CE and are in the same genetic pathway. We also hypothesized that kv2.1 serves a structural role rather than a functional role or a combination of the two in facilitating CE. We used morpholinos to knock down the genes coding for kv2.1 and FAK separately and simultaneously and observed the resulting phenotypes to study the relationship between the two. We used Guangxitoxin to eliminate kv2.1 pore function and compared these mutants to those lacking structure and pore function in order to study kv2.1’s role in CE. We found that kv2.1 and FAK do interact and that kv2.1 does have a functional role in CE. A fuller understanding of the relationships and functions of these proteins will provide us with a better understanding of vertebrate development and can potentially illuminate the mechanisms behind developmental disorders. Further research will be conducted to expand the population numbers and to test the impact of different concentrations of the two morpholinos to better understand the relationship between kv2.1 and FAK and kv2.1’s role.

Introduction Convergent extension (CE) is a key patterning process in early embryonic development, characterized by the intercalation and elongation of mesodermal cells that form the anterior posterior (AP) body axis and develop into the notochord and other midline structures (Gilbert, 2006). Cells collectively move toward the middle of the embryo, lining up or intercalating and elongating to form the narrow notochord that runs from the anterior end to the posterior end of the embryo (Gilbert, 2006). When CE is prevented in zebrafish embryos, mutants possess shortened AP body axes and an undulating and widened notochord. The abnormalities observed in the mutants are fatal to embryos because development of the spinal cord, which is induced by the formation of the notochord, cannot proceed. Two molecules, kv2.1 and FAK (Focal Adhesion Kinase), are hypothesized to interact in embryos to facilitate CE. Kv2.1 is the first molecule found to impact CE. It is a delayed rectifying potassium channel located on cell membranes and controls the flux of potassium ions into and out of the cell. Previous experiments in Dr. Machingo’s lab identified kv2.1 as an integral molecule to CE. The knock down of kv2.1, accomplished by preventing its expression with morpholinos, was found to inhibit CE in developing embryos. Morpholinos block translation or transcription, by binding to a target site like the AUG start codon, in order to prevent the formation of a protein from DNA. The prevention of CE in the absence of kv2.1 indicated that the channel facilitated CE. FAK is the second molecule believed to impact CE. FAK is an enzyme that helps cells adhere to their environment and other cells, also guiding cell migration during CE. At the neuronal level, ∗

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FAK has been shown to interact with kv2.1 (Wei, 2008). In this same experiment, kv2.1 enhanced FAK phosphorylation, or activation, and therefore the knockdown of kv2.1 ultimately hindered directed cell migration (Wei, 2008). This relationship suggests that the two molecules may interact at the developmental level as well to facilitate CE. In this project, we studied the relationship between kv2.1 and FAK at the developmental context.

In the first experiment of this project we investigated the relationship between the kv2.1 and FAK. We hypothesized that FAK and kv2.1 interact to facilitate CE and that they are in the same genetic pathway, which is characterized by a series of expression of multiple genes that leads to one phenotypic trait. We tested this by injecting embryos with either kv2.1 morpholino, FAK morpholino, or simultaneously injecting an embryo with both kv2.1 and FAK morpholinos. If our hypothesis is supported and the two are in one genetic pathway, eliminating the pathway at any point should lead to an identical phenotype, regardless if the embryos were treated with either morpholino alone or both simultaneously. If different phenotypes are found between the treatments then the molecules are playing different roles outside of a pathway.

In the second experiment of this project, we studied the specific role kv2.1 plays in facilitating CE. It is unclear from the previous experiments whether kv2.1 serves a structural role by providing scaffolding for cells to aggregate around, a functional role by guiding cell migration by controlling the flux of potassium ions, or if it both structurally and functionally facilitates CE. We also hypothesized that kv2.1 facilitates CE through a structural role, rather than a functional role or some combination of structural and functional roles. This was tested using a peptide toxin, Guangxitoxin, isolated from spider venom that binds to and blocks kv2.1 to prevent ion flux, its pore function. If this hypothesis is supported, the embryos in which kv2.1’s function is eliminated will be phenotypically wild type. If this hypothesis is not supported, then the embryos without functional kv2.1 proteins will have some or all of the abnormalities as the mutants treated with the morpholino.

Materials and Methods Danio rerio, or zebrafish, was the model organism used in this project. In the first experiment, ptk2.1 morpholino was used to knockdown FAK and either kcnb1 or kv2.1 morpholinos were used to knockdown kv2.1. Before the eight cell stage, the embryos were treated via microinjection of consistent volume. The single treated embryos, those treated with either ptk2.1 or kcnb1/kv2.1, were injected with varying concentrations of the morpholinos, ranging from 3ng to 6ng per embryos. All double treated embryos were injected with 2ng of each morpholino for a total of 4ng of morpholino per embryo. Photos were taken around the 2 to 6 somite stage. In the second experiment, Guangxitoxin was used to eliminate kv2.1 pore function. The embryos were manually dechorionated and treated with 250nM, 500nM, or 750nM concentrations of the toxin. Again, photos were taken around the 2 to 6 somite stage.

Mutations in notochord width and undulation were quantified in both experiments by taking five measurements equally spaced along the notochord of individual embryos (Fig. 1). The stan-

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Figure 2.

dard deviation of those five measurements was found and compared between treated embryos and wild type embryos.

Mutations to the notochord were also quantified by measuring the anterior posterior body axis angle. This measured the angle between the anterior end and the posterior end from the center of the yolk of the developing embryo (Fig. 2). The greater the angle between the points, the shorter the body axis and the greater the mutation. The axis measurements of treated embryos were compared to those of wild type.

Microinjections were performed under a microscope with glass needles made in the lab. A peddle connected to a nitrogen tank was used to force the morpholino out of the needle and into the embryo. It is difficult to inject consistently because the process requires a lot of skill. Similarly, manual dechorionation is performed under a microscope with two sets of sharpened forceps to cut the chorion, the outer shell covering the embryo, and tear it off without perforating the embryo.

This also required a lot of skill. Therefore, to account for human error during injections and potential inefficacy of the morpholinos and the toxin, a statistical method was used to isolate the mutant treated embryos in the data sets from the wild type treated embryos. The embryos were separated by calculating the average and standard deviation of the wild type embryos, those treated embryos that possessed AP axes that were one standard deviation greater than the average of the control were considered to be mutant treated embryos while the others were considered to be wild type treated. The wild type and wild type treated were combined into the control embryos for the statistical analysis of the mutant treated embryos.

Results Fig. 3 shows dorsal images of wild type, FAK, kv2.1, and double (FAK and kv2.1) treated embryos. The notochord is very clear in the wild type embryo, it is narrow and straight, but in the three treated embryos the notochord is widened and undulates. The three treated starkly contrast the wild type, but there is little variation among them. Fig. 4 shows lateral images of each type of embryo. Similar to Fig. 3, the wild type embryo has a small AP angle, corresponding to a longer

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Figure 3. Photographs of dorsal morpholino treated embryos

Figure 4. Photographs of lateral morpholino treated embryos

Figure 5. Photographs of dorsal toxin treated embryos and kcnb1 treated embryos

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Frequency of mutants in morpholino treated

notochord length, while the three treated have larger angle, shorter notochords, and show little variation. Fig. 5 shows dorsal images of wild type, toxin treated, and kv2.1 morpholino treated embryos. The wild type image has a very straight and narrow notochord while the treated images both appear to have widened and malformed notochords. The toxin and morpholino treated show little variation. Fig. 6 graphically demonstrates the frequency of mutants in morpholino injected and control embryos. The lower portion of the bar shows the number of embryos possessing statistically mutant anterior posterior body axes while the upper portion shows the embryos with statistically wild type axes. The entire bar, with both upper and lower portion together, shows the total number of embryos injected.

Table 1 shows the statistical analysis of the notochord widths of wild type, ptk2.1, kcnb1 and double injected embryos. The table shows the p value calculated from a TTest of the wild type with each treatment and the average standard deviation, which was used in the TTest. Table 2 shows the analysis of the AP axis measurements for injected embryos. This shows the p value and the average AP measurement, used to compare the wild type and treatment. Table 3 shows the quantification of the FAK morpholino treated embryos at 4 ng and 6 ng concentrations. 4 ng showed strong significance while 6ng showed significance, and 4 ng showed a larger percent mutants than 6 ng.

Table 4 shows the quantification of the kv2.1 morpholino treated embryos at 3 ng, 4 ng, and 5 ng concentrations. 3 ng and 5 ng did not show significance while 4 ng showed strong significance.

Table 1. Quantification of notochord width data of injected embryos Treatment P value Average Standard Deviation

Wild Type (9 embryos) -

FAK (19 embryos) p > 0.05

Kv2.1 (10 embryos) p < 0.01

5.941

8.052

21.705

Double (7 embryos) p < 0.05 14.664

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Table 2. Quantification of anterior-posterior data of injected embryos Wild Type (124 embryos) -

Treatment P value Average AP Angle

FAK (7 embryos) p < 0.01

104◦

Kv2.1 (7 embryos) p < 0.01

131◦

Double (23 embryos) p < 0.05

140◦

131◦

Table 3. Quantification of FAK morpholino injections at different concentrations Treatment % Mutant P value Average AP Angle

Wild Type (21 embryos) -

FAK 4 ng injected (7 embryos) 58% p < 0.01

FAK 6 ng injected (2 embryos) 29% p < 0.05

104◦

131◦

126◦

Table 5 shows the AP analysis for the toxin treated embryos at 250 nM, 500 nM, and 750 nM. This table shows that 250 nM and 750 nM were significant treatments but 500 nM was not.

Table 4. Quantification of kv2.1 morpholino injections at different concentrations Treatment % Mutant New T Test Average AP Angle

Wild Type (48 embryos) 102◦

Kv2.1 3 ng injected (2 embryos) 40% p > 0.05

Kv2.1 4 ng injected (7 embryos) 37% p < 0.01

Kv2.1 5 ng injected (2 embryos) 22% p > 0.05

99◦

140◦

111◦

Discussion In the first experiment, the results confirm our hypothesis that FAK and kv2.1 interact and that they are located in the same genetic pathway. The hypothesis is supported by both qualitative and quantitative data. In the dorsal images in the Fig. 3, the double injected embryo had a visually similar notochord compared to the single treated embryos. The double injected embryos appear to have the same widening and undulation of the notochord that is apparent in the single treated embryos and it contrasts with the straight narrow wild type notochord. The widening and undulation were quantified in the analysis of the deviation in notochord width within individuals, shown in Table 1. This quantitative analysis supports the hypothesis as well. The standard deviation among width measurements in individual double treated embryos was significantly different than the deviation in wild type embryos, as was the deviation in kcnb1 treated embryos but not in ptk2.1 treated embryos.

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Table 5. Quantification of anterior-posterior data of toxin treated embryos Treatment P value Average AP Angle

Wild Type (22 embryos) -

250 nM toxin treated (2 embryos) p < 0.05

500 nM toxin treated (2 embryos) p > 0.05

750 nM toxin treated (3 embryos) p < 0.05

87◦

135◦

116◦

120◦

These results partially confirm the hypothesis, since the double treated embryos developed the same significant abnormality as the kv2.1 mutants, but the FAK mutants did not have this significant abnormality quantitatively. A very small population of embryos was used in these calculations, which may have created errors that could account for the fact that the ptk2.1 treated, FAK mutant embryos did not show a significant difference from the wild type.

The hypothesis was further supported quantitatively by the measured anterior posterior body axis angles. Fig. 6 displays the frequency of statistically mutant embryos among injected embryos for each treatment. The figure shows that the majority of injected embryos did not have statistically mutant axes, but there is a population within each treatment that was mutant. The AP axis analysis for the mutant embryos from Fig. 6 is shown in Table 2. The angles of the double treated and single treated embryos were significantly greater than those of the wild type. This supports the hypothesis that the double treated embryos, like the FAK and kv2.1 mutants, had shortened notochords characteristic of prevention of CE. Tables 3 and 4 show the p values at different concentrations, contrasting Table 2 and Fig. 6 in which only 4 ng treated embryos were used in the calculations. The numbers were separated because 4 ng treatments of single morpholino were consistent with the double treatments, which were all 4 ng. They were also separated because there were greater numbers of 4 ng injected, making them a more reliable population to analyze. Table 3 shows that 6 ng injections of FAK was significant while 4 ng was strongly significant. Table 4 shows that only 4 ng treatments were significant while 3 ng and 5 ng were insignificant. This variation may be due to the small sample sizes.

When varying concentrations of either of the single morpholinos were injected to test the efficacy of the morpholinos, 3ng injections seemed to be ineffective at knocking down the protein and preventing CE, while 4ng injections and higher seemed to be effective at producing the mutant phenotype. This could potentially be a source of error in the data from the double injected embryos, since they were injected by 2ng of both morpholino, below the observed threshold for mutation.

Although the double injected embryos did show the phenotype and were significantly different from the wild type, the injections with 2ng of each may not have effectively knocked down the genes compared to the efficacy of 4ng of both morpholinos.

In the second experiment in this project, the results do not support the hypothesis that kv2.1 only serves a structural role in facilitating CE. The results are based on a small population of

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embryos, but the preliminary data does indicate that the elimination of pore function does prevent CE from proceeding normally. Fig. 3 shows that the notochord of the toxin treated embryo is widened and barely formed, appearing very abnormal compared to the wild type, but similar to the notochord of the morpholino treated embryo. The similarities between the toxin treated embryo that only lacked kv2.1 pore function and the embryo in which kv2.1 was knocked down structurally as well as functionally indicate that function does play a role in kv2.1’s facilitation of CE. The quantitative results shown in Table 5 also do not support the hypothesis. This table shows that there was a significant difference between the AP axes of the 250 nM and the 750 nM treated embryos, but not the 500 nM treated ones. The variation may be the result of extremely low population numbers. Overall, these results indicate that kv2.1 plays a functional role in CE and that our second hypothesis was not supported.

Conclusion These experiments examined the relationship between kv2.1 and FAK in facilitating CE and the mechanism through which kv2.1 mediates CE. In the first experiment, when morpholinos were used to simultaneously knock down both kv2.1 and FAK, embryos that possessed phenotypically abnormal body axis measurements were found to be statistically different from wild type and control treated embryos. These results support the hypothesis that the two proteins function in the same genetic pathway.

In the second experiment statistical analysis indicates a significant difference between the statistical mutants that did not possess functional kv2.1 protein and the control and wild type mutant embryos. This does not support the hypothesis that kv2.1 serves only a structural role, but indicates that kv2.1 plays a functional role in addition to a structural role.

Further research will be conducted to test the impact of different morpholino concentrations to better understand the relationship between kv2.1 and FAK. Further research will also be conducted to expand the numbers of embryos treated with different concentrations of Guangxitoxin to better understand kv2.1’s functional role in CE.

Acknowledgement The author thanks the School of Science Research Scholars Program for financial support during this research.

References Gilbert, Scott F. Developmental Biology. 8th ed. Sutherland, MA: Sinauer Associates, 2006.

Wei, Jian-Feng, Ling Wei, Xin Zhou, Zhong-Yang Lu, Kevin Francis, Xin-Yang Hu, Yu Liu, WenCheng Xiong, Xiao Zhang, Naren L. Banik, Shu-Sen Zheng, and Shan Ping Yu. ”Formation of Kv2.1-FAK Complex as a Mechanism of FAK Activation, Cell Polarization and Enhanced Motility.” J. Cell. Physiol. Journal of Cellular Physiology 217.2 (2008): 544-57.

Microhabitat Use by an Urban Salamander Population Mary Portesâ&#x2C6;&#x2014; Department of Biology, Manhattan College Abstract. Amphibians play an important role in our ecosystems as well as the food web. It is pertinent to know as much information about these animals. Knowing more about their habits and how they are affected by their environment can provide insight on the actions a population can undertake to save our ecosystem and even how to improve overall human health. This study focuses on quantifying microhabitat variables of the Red-Backed salamander (Plethodon cinereus) found in Van Cortlandt Park in Bronx, NY and comparing collected data with a comparably pristine environment to determinine the habitat preferences of this species. It was found that the sampled salamanders preferred closed canopy locations over open canopy. All other microhabitat variables were found to be statistically insignificant, showing that salamanders in this location did not significantly prefer the other variables. Our results showed that there is no clear distinction between whether healthier salamanders are found in cooler or warmer temperatures. Future plans include collecting data from Harriman State Park and comparing disturbed, urban environment already studies with the upstate New York pristine environment.

Introduction Amphibians have been on the planet for millions of years. However, population numbers have begun to decline worldwide due to habitat destruction, disease, climate change, introduction of new species of amphibians to non-native locations and exploitation of the species by humans for food and medicinal research. Given their semi-permeable skin and access to both aquatic and terrestrial environments, amphibians are considered important indicator species of environmental health. Therefore, the decline of these species is alarming, and understanding the causes of these declines could be crucial for understanding potential effects on both ecosystem and human health (Blaustein and Wake, 1995; Gardner, 2001; Wyman and Hawksley-Lescault, 1987; AmphibiaWeb, 2015). It is essential to gain a better understanding of the health of amphibian populations in a variety of locations to identify potential environmental problems.

The Red-Backed salamander (Plethodon cinereus) is a widespread species that is abundant in New York State forests (Breisch and Ducey, 2003). They are an easy species to identify and sample because they are a terrestrial species, but is still dependent on moist environments. This species also plays an important role in forest ecosystems and are located in variable habitats, allowing one to compare populations from disturbed locations, like in and near New York City, and less disturbed habitats like those found in upstate New York (Sulgaski, 1997).

This study focused on quantifying microhabitat use by an urban population of Red-Backed salamander. It was predicted that there would be differences in microhabitat use between our urban study population and salamanders that would be found in a more pristine habitat. â&#x2C6;&#x2014;

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Materials and Methods Sampling for the Red-Backed Salamander occurred during the months of June-August of 2015. Sampling was conducted during the mid-morning to afternoon hours at Van Cortlandt Park, in the Bronx, New York, throughout the summer. Once salamanders were found, they were weighed and their Snout-to-Vent length (SVL) and total length (TL) were recorded. At salamander locations, several environmental measures were also recorded. These variables included distance to the nearest mature tree from the cover object, diameter of said tree, length and width of the cover object, canopy and ground coverage as well as air and ground temperature. These same measurements were then recorded at a random distance and direction from each salamander site for comparison. This was used to test for significant microhabitat preferences by salamanders.

The Mann-Whitney U-Test (Mann and Whitney, 1947) was used to test for significant differences among the different microhabitat variables. A chi-squared goodness-of-fit test was used for differences in proportions of ground and canopy coverage. A Pearsonâ&#x20AC;&#x2122;s correlation index was used to see if there was a correlation between ground temperature and body fitness. Salamander fitness itself was estimated using a ratio of mass versus Snout-to-Vent Length of the salamander.

Results

500 400 350 300 250 200 150 100 50 0

Salamander

300 200 100

50 40 30 20 10 0

Random

Figure 1.

Average maximum length (A) and width (B) of cover object in salamander locations vs. random sites

20 15 10 5

Salamander

Random

35

(B)

50

(B)

30

40 30 20 10

25 20 15 10 5 0

0

Salamander

25

0

Air Temperature (°C)

(B)

30

Random

60

60

(A)

35

0

Salamander Diamter of Nearest Mature Tree (cm)

Maximum Width Cover Object (cm)

400

Random

70

40

(A)

500

Ground Temperature (°C)

(A)

450

Distance to Nearest Mature Tree (cm)

Maximum Lenth of Cover Object (cm)

After using the Mann-Whitney U-Test to analyze the microhabitat variables, they were found statistically insignificant. All U values for variables measured were greater than the critical value of 23. As seen in Figs. 1-3, salamander location values were not significantly different when com-

Salamander

Random

Figure 2.

Average Distance to the nearest mature tree (A) and diameter of the nearest mature tree (B) in salamander locations vs. random sites

Salamander

Random

Figure 3.

Average air temperature (A) and ground temperature (B) in salamander locations vs. random sites

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pared with random locations. This indicates that salamander locations were not significantly different from locations randomly sampled. Data that involved percentage values, i.e. canopy coverage and ground coverage, were analyzed using the chi-squared goodness-of-fit test. This test showed that salamanders significantly preferred locations with greater canopy closure compared to random sites (X 2 = 0.224, Table 1). However, the proportion of ground coverage at salamander locations were not significantly different from those observed at random locations (X 2 = 0.504, Table 2). To find a correlation between body condition and ground temperature, the Pearson’s Correlation Index was used. As seen in Fig. 4, there is a very slight negative correlation between body condition and ground temperature. However, the R2 value of 0.0756 is too small to consider this correlation to be significant.

Table 1. Chi-Squared Goodness-of-Fit Summary for Canopy Coverage Closed Canopy

Open Canopy

71.6% 68%

28.4% 32%

Salamander Location Random Location

Table 2. Chi-Squared Goodness-of-Fit Summary for Ground Coverage

Salamander Location Random Location

Plant

Log

Rock

Leaf

30.75% 28.4%

19% 12.4%

1.3% 40%

48.95% 18.8%

Body Condition (g/cm)

0.3

y = -0.0079x + 0.3123 R² = 0.0756

0.2

0.1

0.0 13

15

17

19

21

23

25

Ground Temperature (°C)

Figure 4. Pearson’s Correlation comparing Body Condition and Ground Temperature

Discussion

Since random locations were generally not significantly different than salamander sites, we can conclude the salamanders at Van Cortlandt Park do not show any obvious preference for the microhabitat variables measured. This might be due to the relative instability of Van Cortlandt Park,

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as it is a disturbed, urban environment. In disturbed environments it expected to observe habitats of relatively low quality, which could force salamanders to occupy less than ideal locations. To further test this idea, we wish to quantify the same variables in a less disturbed environment. For example, Harriman State Park located in Rockland and Orange counties, New York. Once this new data is obtained, it can then be compared to the data obtained at Van Cortlandt Park in order to draw conclusions on what kind of variables these salamanders prefer to live in. If it is indeed true that Van Cortlandt Park, as a disturbed environment, does not present salamanders with a good quality microhabitat, then when compared to Harriman State Park, we would expect significant differences in microhabitat use among sites as well as preference for certain variables over others.

Salamanders did significantly prefer more closed canopy locations as opposed to open ones.

This is because the microhabitats found under closed canopies are less exposed to the sunlight and remain moist. One way to test salamander preference for closed canopy locations in the future is to measure soil moisture in relation to canopy closure. We could also move salamanders from closed to open canopies and test whether they will return to the closed canopies. It was also found, although not significant, that salamanders tended to be found in locations with higher leaf and less rock ground coverage. This could be due to the fact that leaf litter contains potential food items for salamanders, as opposed to rocky ground. Riedel et al. (2012) found in their study of the Red-Backed Salamander in West Virginia, that ”salamanders in non-forest habitats may be subject to greater rates of desiccation, which in turn limits foraging intake and therefore overall physical condition, reproductive potential, and survivorship,” confirming that canopy coverage may be essential to the survivorship of this species. However, more data would need to be obtained in order to confirm that leaf coverage is significantly preferred over rock coverage.

As Jakob et al. (1996) describe in their article, physical body condition is used by ecologists to estimate the nutritional state of an organism”... to provide a snapshot of an animal’s physiological state.” Physical body condition itself can be a determining factor in an individuals’ fitness as well (Riedel et al., 2012). In this study, it was predicted that salamanders that had a higher body condition index would be found in cooler temperatures. The reason for this is that salamanders are known to live in cool, moist climates. It is hypothesized that healthier salamanders will have chosen better habitats and therefore be found in these cool habitats. However, with the data obtained, there was no strong correlation between these two variables. Also, the data obtained showed that there was very little variation in temperatures where we sampled. Perhaps if we sampled across more variable conditions we might see a more clear pattern.

This study provided insight on the possible variables favored by salamanders in terms of habitat. It also confirmed that a comparison between our urban environment location and a relatively pristine environment is needed in order to determine what differences are present and what may contribute to the choice of salamanders of certain habitats. This can also inform us of suitable environments for this species, assist in integral conservation decisions, and ultimately help us determine what can be done to prevent not only salamander populations from declining, but amphibian populations as well.

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Acknowledgement The author would like to thank the School of Science Research Scholars Program for financial support during the performance of the present research and the School of Science for supplying the materials needed to conduct the research. She thanks Dr. Gerardo Carfagno for dedicating his time and effort to mentoring and supporting her, and Andrew Paramo for his help and collaboration in this project.

References AmphibiaWeb: “Information on amphibian biology and conservation.” [web application]. 2015.

Berkeley, California: AmphibiaWeb. (Accessed: Web. 24 Feb. 2015.) (http://amphibiaweb.org /declines/declines.html).

Blaustein, Andrew R., and David B. Wake. “The Puzzle of Declining Amphibian Populations.”

Scientific American 272.4 (1995): 52-57.

Breisch, Alvin, and Peter K. Ducey. ”Woodland & Vernal Pool Salamanders of New York State.” New York State Conversationalist (2003): n. pag. New York State Department of Environmental Conservation, June 2003. Web. 26 Feb. 2015.

Gardner, T. “Declining Amphibian Populations: A Global Phenomenon in Conservation Biology.”

Animal Biodiversity and Conservation 24.2 (2001): 25-44.

Jakob, E. M., Marshall, S. D., Uetz, G. W., “Estimating fitness: a comparison of body condition indices.” Oikos 77 (1996): 61–67.

Mann, Henry B.; Whitney, Donald R. (1947). “On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other.” Annals of Mathematical Statistics 18 (1): 50–60.

Riedel, Breanna L., Kevin R. Russell, and W. Mark Ford. “Physical Condition, Sex, and AgeClass of Eastern Red-Backed Salamanders (Plethodon cinereus) in Forested and Open Habitats of West Virginia, USA.” International Journal of Zoology (2012): 1-8. BioOne. Web. Sugalski, Mark T., and Dennis L. Claussen. “Preference for Soil Moisture, Soil PH, and Light Intensity by the Salamander, Plethodon cinereus.” Journal of Herpetology 31.2 (1997): 245-50.

Wyman, Richard L., and Dianne S. Hawksley-Lescault. “Soil Acidity Affects Distribution, Behavior, and Physiology of the Salamander Plethodon cinereus.” Ecology 68.6 (1987): 1819-27.

Metabolism as a bioassay of environmental stressors: Hemigrapsus sanguineus as a model organism Zachary Scheid∗ Department of Biology, Manhattan College Abstract. Metal toxicity is an important abiotic factor when looking at the limitations of invasive species. Nickel is an abundant heavy metal in urban settings. Oxygen consumption, Isocitrate dehydrogenase activity, and Lactate dehydrogenase activity are useful in revealing a stress response through looking at the metabolism. This project looks to determine the metabolic activity at three levels of study when exposed to nickel (II) chloride hexahydrate.

Oxygen consumption indicates significant decrease in rate at moderate concentration (10 mg/L) of nickel but not at high concentration. Isocitrate dehydrogenase activity followed a similar trend to oxygen consumption but without significance in performing ANOVA. Lactate dehydrogenase increased significantly at high concentration (100 mg/L) of nickel indicating a stress response.

Introduction Since H. sanguineus’ first observation (in 1988) in Townsend Inlet, New Jersey (McDermott, 1991), it is now observed from South Carolina to Maine (Epifanio, 2013). With a predilection for open-coast rocky intertidal regions, the grapsid crab has displayed a rapid increase in its population. The sympatric mud crab, E. depressus, has since declined in abundance by 95% from 1998-2005 (Kraemer et al., 2007). The three other species of crabs located just off the coast of Long Island include C. irroratus (Atlantic rock crab), C. maenas (green crab), and L. emarginata (spider crab) have also been observed as having a substantial decrease in abundance in recent years (Epifanio, 2013). Its abundance has also resulted in a decline many commercially important bivalves inhabiting the intertidal regions (Epifanio, 2013). Nascent establishment of invasive animal populations are commonly introduced through human activity and thrive by their ability to consume a broad spectra of eligible prey (Carlton and Geller, 1993).

Invasive species are often noted to be highly affected by biotic factors within the food chain and often upset the relative stability of native habitats. However, the influence of abiotic factors on invasive species is infrequently mentioned in literature. Factors such as temperature, salinity, substrate size, inorganic compounds, and pollutants often play a role in the limiting the span by which an invasive species can occupy (Elton, 1958). With the recent influx of the non-indigenous species Hemigrapsus sanguineus occupying many intertidal and subtidal regions along the U.S. East Coast, the grapsid crab has invaded a number of urban habitats (Jenson, 2002). Non-invasive species often upset the stable dynamic of the native inhabitants through their ability to tolerate a variety of different conditions (Elton, 1958). Nascent establishment of invasive animal populations are commonly introduced through human activity and thrive by their ability to consume a broad spectra of eligible prey (Carlton and Geller, 1993). ∗

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Metals accumulation in aquatic systems has a propensity to create problems for many aquatic animals living in close proximity to urban areas. Increasing concentrations of heavy metals have resulted from the discharge of many waste products into streams and rivers as a result of industrial activity (Moorthikumar and Muthulingam, 2011). Studies indicate that heavy metals can impact the species diversity of a community (Heath, 1987) . A number of organic and inorganic compounds proliferate as they move through the ecological food chain, affecting many species within a community (Moorthikumar and Muthulingam, 2011). Metals such as nickel are often found in high concentrations in urban areas and pose a number of problems for species that are not well adapted to its toxicity.

In a similar paper, Xuan et al. (2013) investigated stress responses of a freshwater crab when exposed to cadmium. The paper used myriad of different methods to quantify the rate of aerobic and anaerobic respiration at the organismal and enzymatic level. Oxygen consumption is valuable for the study of the rate of aerobic respiration at the organismal level. Enzymes from the Kreb’s cycle such as isocitrate dehydrogenase (IDH) provides information on the rate of aerobic respiration at the molecular level. Glycolytic enzymes (Cori cycle) such as lactate dehydrogenase (LDH) are useful in our assessment of stress responses resulting from toxins exposed to aquatic organisms (Matozzo et al., 2001). Through these methods the determination of LC50 ’s may be avoided through the use of a less pernicious alternative.

In order to understand the resilience of this species, it is imperative to take measurements of its tolerance level to many environmental factors, including temperature, salinity, pH, and the presence of inorganic or organic compounds. Without this knowledge, we will lack an effective method of controlling this species.

In the study it was hypothesized that nickel (II) chloride hexahydrate will decrease aerobic activity at the organismal and enzymatic levels. The second hypothesis states that anaerobic respiration will increase as a result of being exposed to nickel (II) chloride hexahydrate.

Methods and Materials Collection Adult male crabs were collected at Clason Point, South Bronx (N40◦ 480 23.8500 , W73◦ 500 54.4700 ). Over the months of June, July, and August, at low tide, batches of 25 − 35 crabs were collected during each visit. Crabs were returned to lab in aerated tubs for 24 − 48 hours prior to experimentation. Collection tubs held seawater at a temperature around 20 ± 3 ◦ C. Salinity was held constant at 30 ppt.

Acute Nickel Treatment The treatment groups were exposed to Nickel (II) chloride hexahydrate for the standard 96hour period for acute sublethal toxicity exposure. Treatment took place in 1 L mason jars filled to a volume of 0.5 L (30 ppt) with one control and two treatment groups used: (1) 0 mg/L, (2) 10 mg/L, and (3) 100 mg/L. Sublethal nickel concentrations for Asian shore crabs were selected using

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Figure 1: Clason Point, South Bronx

previous LC50 estimates for Palaemonetes pugio of similar body size (Judge, Bringley, Spellman and Mahony, 2015, unpublished).

A body mass range of 30 − 35 grams (∼ 3 − 5 crabs) was selected to keep accumulation of the metal consistent with each treatment batch. Small and large individuals were often combined in this study to avoid confounding variables.

Exposure trials were performed in Percival 36LL incubator with temperature at 22◦ C and light/dark periods at 14 hours/10 hours, respectively (Fig. 2).

Figure 2: Mason jars were used in holding groups of crabs exposed to different concentrations of nickel in a Pervical incubator.

Crabs were randomized in treatment placement.

Oxygen Consumption After the completion of the acute treatment crabs were immediately transferred to individual respiration chambers (500 mLs). Wet body mass of each individual was calculated prior to oxygen trials. Conditions matched the treatment applications (nickel concentration) and abiotic factors (30 ppt, 22 ◦ C) used beforehand. A dissolved oxygen meter (YSI 5100) was used to measure the change in dissolved oxygen in the respiration chamber over a thirty-minute time interval. The formula for oxygen consumption is as follows: Oxygen consumption (mg O2 ) = [O2 initial – O2 final](mg/L)×500 mL/g of tissue/min.

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Enzyme Activity Assays Subsequent to the oxygen consumption trials all individuals were transferred to a segmented storage container and immediately placed into an −80◦ C freezer for 24 hours. After thawing a total of 150 mg of tissue was dissected from both claw appendages for each individual for the IDH (50 mg) and LDH (100 mg) assays, respectively. The following procedures were taken from the Sigma Aldrich manuals (MAK 066 and MAK 062) and modified to fit a marine species (ie. change in temperature). The absorbance of the enzymatic product (NADH) was measured using a Bio-Rad 96 well plate spectrophotometer at the wavelength of 450 nm for both enzymes. The formula for the activity of LDH and IDH are as follows: Enzyme Activity = nmol NADH (product formed)/min/mL.

Results Oxygen Consumption Fig. 3 contains data on the consumed oxygen in varying nickel concentrations. A 2-way ANOVA was performed on nickel concentration and size. In the post-hoc analysis, Tukey’s HSD multiple comparison test revealed a significant depression in the metabolism at 10 mg/L (F2,71 = 6.236, p < 0.05) when compared to the control group (marked by letters a and b). There was no significance found between the control and the highest concentration of Ni (100 mg/L). There was also significance between the two sizes of individuals (F 2,71 = 20.937, p < 0.05).

Figure 3: Metabolic rate measured as the rate of oxygen consumed. Letter a, indicates no significance of both large and small groups (combined) with respect to the control. Letter b, indicates significant difference in both large and small group (combined) with respect to the control.

Figure 4: Isocitrate dehydrogenase activity by protein kinetics analysis.

Figure 5: Lactate dehydrogenase activity by protein kinetics analysis. Letter a, indicates no significance of both large and small groups (combined) with respect to the control. Letter b, indicates significant difference in both large and small group (combined) with respect to the control.

Enzyme Kinetics Fig. 4 shows data taken from the enzyme activity of IDH, and aerobic enzyme. A similar depression is seen at 10 mg/L of nickel. However, large individuals appear to be increasing their

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aerobic respiration as nickel concentration increases. ANOVA did not find significance in either categorical variable.

Fig. 5 represents data taken from the anaerobic activity of LDH. Different letters indicate significant differences between groups. A Tukey HSD Multiple Comparison discovered significance at the highest concentration of nickel.

Discussion This study looked at three response levels of the organism to best understand its change in metabolism when exposed to certain concentrations of nickel. Oxygen consumption was found to have decreased at 10 mg/L of nickel providing a converse comparison with Xuan, 2013. The reason for this paradigm is uncertain but the pattern is analogous with Fig. 2, IDH activity.

Oxygen consumption and IDH activity were both used in order to evaluate aerobic respiration through the comparison of the similarities displayed between the two studies. The decline at 10 mg/L in oxygen consumption appears to be in concordance with IDH activity. Both methods of analysis were performed in order to affirm the level of aerobic respiration and to determine the precision of the two means. A confirmation leads one to conclude that the data may not have been a result of error. This provides promising evidence of a stressful response to nickel but will require future efforts of this experiment and ones similar to it, which will take place later in the academic year. However, Fig. 4 (IDH activity) did not show significance in its trend - the depression at 10 mg/L of Ni. Insufficient data leads to the assertion that further study on this research should be performed to fully grasp the mechanism behind the stressor. An increase in IDH activity was positively associated with nickel concentration in large individuals hinting at consistencies with the report by Xuan in 2013.

An increase or decrease in LDH activity was important for indicating a shift from aerobic to anaerobic respiration (or vice versa) and was useful in concluding that an organism was undergoing a fair amount metabolic stress (Xuan, 2013). A higher LDH activity at a high concentration of nickel was discovered from ANOVA, suggesting a stress response resulted.

The low standard error found in the analysis of oxygen consumption but not in either IDH or LDH denotes a smaller signal-to-noise ratio at the organismal level than at the enzymatic or molecular level. This suggests that oxygen consumption in this experiment was a better tool in the measurement of metabolism.

In 2013, Xuan performed a similar experiment that is seen here but on a freshwater species and with a different metal. Although some consistencies were found in each of the two papers there were some disparities, which suggest differences in the two systems. A notable difference found in marine systems is the number of ions in comparison to a freshwater system. Ions such as chloride are noted to form a complex with metals in marine systems (Moorthikumar and Muthulingam, 2011) not often seen in freshwater. Complexation with metals is a natural occurrence in aquatic systems and could explain differences in metabolic activity.

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The data provides a sufficient understanding in H. sanguineusâ&#x20AC;&#x2122; tolerance when exposed to metal. Nickel, being a fairly nontoxic substance, was fairly tolerated in the experiment. This perhaps could explain its sheer abundance in urban settings such as what is seen along the coast of the East River. Since nickel is not often cited in literature on aquatic systems, this study could give insight into its effect on many metabolic enzymes related to those used in this experiment.

Its relative tolerance to the metal may lead to conjecturing that nickel has a marginally low to moderate influence on metabolic enzymes.

Acknowledgement The author is grateful for the financial support of the Mahony endowment and for useful discussions with Drs. J. Mahony, Q. Machingo, and G. Mayer.

References Carlton, J.T., and J.B. Geller. 1993. Ecological roulette: The global transport of nonindigenous marine organisms. Science 261:78-82.

Elton, C.S., 1958. The ecology of invasions by animals and plants. Methuen, London.

Epifanio, C.E. 2013. Invasion biology of the Asian shore crab Hemigrapsus sanguineus: A review.

Journal of Experimental Marine Biology and Ecology 441: 33-49.

Heath A. G. 1987. Water Pollution and Fish Physiology. CRC press Inc. Boca Raton, FL, U.S.A. Jenson, G. C., McDonald, P. S., and D. A. Armstrong. 2002. East meets west: Competitive interactions between green crab Carcinus maenas, and native and introduced shore crab Hemigrapsus spp.. Marine Ecology Progress Series 225:251-262.

Kraemer, G.P., Selberg, M., Gordon, A., and J. Main. 2007. Eight-year record of Hemigrapsus sanguineus (Asian Shore Crab) invasion in Western Long Island Sound estuary. Northeastern Naturalist 14:207-224.

Matozzo, V., Ballarin, L., Pampanin, D.M., Marin, M.G.,2001. Effects of copper and cadmium exposure on functional responses of hemocytes in the clam, Tapes philippinarum. Arch. Environ.

Contam. Toxicol. 4, 163-170.

McDermott, J. M. 1991. A breeding population of the western Pacific crab Hemigrapsus sanguineus (Crustacea: Decapoda: Grapsidae) established on the Atlantic Coast of North America.

Biological Bulletin 181:195-198.

Moorthikumar, K. and Muthulingam, M. 2011. Impact of heavy metal nickel chloride on enzyme succinate dehydrogenase of freshwater fish Labeo rohita. International Journal of Current Research Vol. 3 (7): 115-119.

Xuan R. et al. 2013. Oxygen consumption and metabolic responses of freshwater crab Sinopotamon henanense to acute and sub-chronic cadmium exposure. Ecotoxicology and Environmental Safety 89: 29-35.

Xylem Characteristics and Xylem Conductivity in Stems of North American Cactus Species Kristen Skonieczny∗ Laboratory of Plant Morphogenesis, Department of Biology, Manhattan College Abstract. Cactus plants are found in both deserts and arid environments. These areas are characterized by having limited water availability, which in turn is a limiting factor for plant growth. Under such circumstances, the plant species that use water more efficiently may persist over the plant species that use water less efficiently. This research focused on comprehending vessel (conduit), vascular bundle, and xylem conductivity features in stem terminals among several morphologies of cactus species. These morphologies were explicitly columnar, prostrate, terminal branch, and globose. Characteristics of stem terminals were examined from Arizona, U.S.A. Xylem vessel cells are organized within vascular bundles. Average conduit diameters in the most basal stem sections were 38.8, 33.4, 18.7 and 17.9 µm for columnar, prostrate, terminal branch and globose species, respectively. Average quantities of conduits in the most basal stem sections for the species tested were 9080, 3420, 2410 and 984 for columnar, prostrate, globose and terminal branch cacti, respectively. Vascular bundle ring diameters were found to be 23% of stem sample diameters. The numbers of bundles were well associated with stem sample diameters. Average xylem conductivities of the most basal sections were calculated to be 0.56, 0.70, 13.5, and 80.0 g cm MPa−1 s−1 for terminal branches, globose, prostrate, and columnar species, respectively. The smallest xylem conductivity value was 0.04 g cm MPa −1 s−1 for the terminal branches of Cylindropuntia arbuscular, while the largest xylem conductivity value was 344 g cm MPa −1 s−1 for the columnar stem of Carnegia gigantea. The cumulative stem surface areas of the species previously mentioned spanned from 1.18 to 202 mm2 , respectively. Even with the diversity indicated above, when data from all cacti sampled were combined, xylem conductivities were well correlated with both cumulative stem volumes and cumulative stem surface areas. These data propose that water conducting features of cactus species are well proportioned to the size and dimensions of the stems for each species.

Introduction Cactus plants are commonl in arid environments (Figs. 1-3). The extent of the Earth’s land surface that is considered arid is approximately twenty percent (Mauseth, 1988; MacMahon, 1992; Anderson, 2001). Arid climates are described as having evapo-transporation rates that exceed precipitation rates (Bender, 1982). Relatively low precipitation rates result in limited water supply in these areas. Therefore, water use efficiency is a key issue for cacti and other plants living in these arid climates (Nobel, 1988). Cactus species native to the Americas have an extensive diversity of morphologies (Bensen, 1982; Anderson, 2001). Some of the morphologies include tall, columnar species (Fig. 1), prostrate species that possess several branches growing along the ground (Fig. 2), shrubby, vastly branches species (Fig. 3), and small globose species (Fig. 4) among other cactus morphologies.

In order to avoid dehydration during periods with little precipitation, cactus plants must conserve water when it becomes obtainable. A number of cactus species are able to survive for prolonged periods of time with little to no precipitation (Anderson, 2001). Due to cactus stems ∗

Research mentored by Lance Evans, Ph.D.

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Figure 1. Image of a plant of Pachyceresus schotti on the property of Robert Webb and Toni Yocum. Note the columnar nature of individual stems.

Skonieczny

Figure 2. Image of a portion of a plant of Stenoceresus gummosus. Note relative prostrate nature of individual stems. Photo from http://calphotos.berkeley.edu. Photo by Wynn Anderson near Hermosillo, Sonora, Mexico, February 24, 2015.

possessing both thick epidermal and hypodermal layers, along with thick cuticles, they are able to inhibit water loss(Gibson and Nobel, 1968; Evans et al., 1994, Evans and Cooney, 2015). Cells containing chlorophyll for photosynthesis are oriented internal to the epidermal and hypodermal cells. Looking further inward, many parenchyma cells and vascular bundles are present (Gibson, 1973; Mauseth, 1993a).

The features of secondary xylem in over one hundred cactus species were characterized by Gibson (1973). Mauseth (1993a;b) contributed an evolutionary insight regarding xylem anatomy for cactus species. In cactus stems, vascular tissues are contained within vascular bundles which are present in a ring configuration (Fig. 5) (Gibson, 1973; Gibson and Nobel, 1968; Mauseth, 2004). Vascular bundles are organized as distinct vertically-aligned rings inside terminal sections of cactus stems (Fig. 6). Bundles may contain vessel cells, tracheids, wide-band tracheids, and fibers (Gibson, 1973; Mauseth, 2004). Cactus stems can possibly have medullary (cortical) bundles dispersed throughout stems (Mauseth & Sajeva, 1992; Mauseth, 1993b); however, bundles in the vertical ring configuration are accountable for the transportation of water from roots to tips. As a result, the vertically-aligned vascular bundles are continuous throughout the stems (Fig. 7).

Both xylem conduits and xylem conductivity have been studied relative to morphological appearances (Hacke and Sperry, 2001; McCulloch and Sperry, 2005; Sperry et al. 2006; McCulloh et al., 2009, 2010). Xylem conductivity ought to follow Murrayâ&#x20AC;&#x2122;s Law (Murray, 1926; Sherman,

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Figure 3. Image of an entire plant of Cylindropuntia ramosissima showing the highly branched nature of the plant.

Photo from http://calphotos.berkeley.edu.

Photo by Thomas Stoughton at the Aza Borrego Desert, San Diego County, CA, March 06, 2010.

Figure 5. Image of fresh stem section showing the ring of vascular bundles from a stem segment of Pachycereus pringlei at 205 mm from terminal.

Figure 4. Image of a portion of a plant of Mammillaria grahamii. Note the relative bulbous nature of individual stems.

Photo from http://calphotos.berkeley.edu.

Photo by Barry Rice within Organ pipe National Monument, Pima County, AZ, June 2013.

Figure 6. Image of a stem segment of Stenoceresus alamosensis showing the ring of vascular bundles. Bar = 200 Âľm.

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Figure 7. Theoretical diagram depicting continuous vascular bundles from the fifth section in stem sections to the terminal sections of cactus stems. Normally, the number of vascular bundles does not change from stem terminals to more basal sections. Figure taken from Evans and Skonieczny (2015).

Skonieczny

Figure 8. Diagram of stem tissue sampling depicted along stems. The first, terminal sample, was usually within five mm from the terminal.

Other samples were taken at a variety of distances from the terminal. See data in Table 2 for details.

Figure taken from Evans and Skonieczny (2015).

1981) with respect to water distribution (McCulloh et al., 2009). The pertinence of Murray’s Law to plants is distinctive, contrasting the application in animals, since extensive water transport in plants takes place only inside xylem cells. Xylem-specific conductivity was associated with plant heights and leaf areas (Gleason et al., 2012). Overall, water transport phenomena are accounted for with xylem conductivity parameters (Gleason et al., 2012).

Particularly large cactus plants possessed vessel lengths greater than 300 µm with diameters beyond 65 µm. Prostrate columnar and caespitose species possessed vessel lengths below 250 µm with diameters less than 42 µm (Gibson and Nobel, 1986). This research was conducted in order to comprehend vessel (conduit), vascular bundle, and xylem conductivity features in stem terminals amid cactus species of several stem morphologies. The morphologies examined include columnar, prostrate, terminal branch and globose. The particular intentions of these experiments were to determine (1) the features of conduits and vascular bundles of cactus species, (2) if vascular bundle ring diameters were associated with stem diameters among species, (3) if vascular bundles were arranged alike among species, (4) if quantities of conduits were correlated among cactus species, (5) if xylem conductivities were strongly associated with both stem volumes and stem surface areas for individual cactus species, and (6) if collective maximum xylem conductivities were strongly correlated with stem volumes and/or stem surface areas within terminal stem sections among cactus species. If comparable xylem characteristics are revealed in cactus species between

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the four morphological groups, the outcome would propose that xylem conductivity features are similar for all cactus species and are autonomous of morphology. If resemblances occur, these xylem characteristics may elucidate features of water use in a morphologically assorted taxonomic group.

Materials and Methods

Cactus samples were acquired from multiple sources (Table 1). Five sections per stem (branch) were sampled to determine variations in conduits, vascular bundles, and xylem conductivity from cactus stem tips to more mature tissues. Table 2 displays the characteristics of the various sampled stems. Terminal sections and four supplementary cross-sectional stem sections were attained for each sampled stem (Fig. 8). This process for sampling was formerly used (Evans and Skonieczny, 2015). After the most terminal section was sampled, a stem section was cut and discarded (discarded segment #1). Next, an additional tissue section for examination was cut (tissue sample #2) while a second segment was discarded (discarded segment #2). This method of discarding segments between segments used for analysis was performed until five samples for analysis were obtained (Fig. 8). Each stem segment was photographed after sampling (Fig. 5). A ruler was placed next to each section for the photographs to yield a scale. The total stem sample length was measured from the tip to the bottom of the most basal sample.

Parameters determined from fresh tissue segments The techniques used in this portion have been previously used (Evans and Skonieczny, 2015).

Measurements of stem sample diameters and vascular bundle ring radii were determined from photographs using ImageJ (www.rsb.info.nih.gov/ij/) and a scale. The area of each stem crosssection was generated by tracing the perimeter with ImageJ. Resulting area values were divided by Ď&#x20AC;. The radius was calculated by taking the square root of the resultant value. Diameters were calculated from resulting radii values.

Cumulative stem volumes were determined for each stem that was sampled. Five measurements, one for each stem section, of cumulative stem volume were calculated for each stem. The first measurement only consisted of the volume of the terminal section and was calculated as the volume of a circular cone V = Ď&#x20AC;r2 h/3, where h is the height of the terminal section only. The second quantity of cumulative stem volume comprised the contributions of the volumes of discarded segment #1 joined with that of sample section #2 (Fig. 8). The volume consisting of discarded segment #1 and sample segment #2 was calculated as the volume of a cylinder (V = Ď&#x20AC;r2 h). In this fashion, the volume contributions of all stem fragments were added to provide five data points for each stem sample. The five values were summed to give the final cumulative stem volume.

Cumulative stem surface area was determined similarly. The first measurement only consisted of the surface area of the most terminal segment. The surface area of a right cone S.A.= rhl (http://calculator.tutorvista.com/math/43) where r is radius of the base, h is the height of the section and l is the slant height of the sample, was used to estimate the surface area. The second measurement of surface area encompassed the surface areas of discarded segment #1 and sample segment

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Table 1. Cactus species sampled. Location of collection and pertinent data from The New Cactus Lexicon (NCL).

Genera are assigned to Tribes as per NCL. Each entry lists Genus; Species; Location; GPS; References in The New Cactus Lexicon (NCL). All species were identified by Robert Webb.

NCL Vol 1 (pages)

NCL Vol 2 (illustrations)

(Eng) B+R 1908/JNYBG 9: 188.

36

35.1-35.4, 36.1

216 217 217

28.5, 29.1, 29.2 30.3, 30.4, 31.1 32.3, 32.4

217

none

private property

S. thurberi ssp. thurberi

(DC) B+R 1909/CUSNH 12: 421.

(Wats) B+R 1909/CUSNH 12: 422.

(Eng) Hunt 1987/Brdl. 5: 93; 096832 (H.E.Gates) P.V.Heath Calyx 2(3): 107 (1992) (Weing.) P.V.Heath Calyx 2(3): 107 (1992) (Cltr) Gibs+Horak 1979/AMBG 65(4): 1006; 11017.

(BgeT) Gibs+Horak 1979/AMBG 65(4): 1007.

(BgeT) Gibs+Horak 1979/ AMBG 65(4): 1007.

(Eng) Buxb 1961/BStud 12: 101.

Aridlands Greenhousesa private propertyd private property private property

Myrtillocactus geometrizans Echinocereus pensilis

Genus/species

Authorities

Subfamily Cactoideae Tribe Echinocereeae Carnegia gigantea Pachycereus marginatus P. pringlei P. schotti P. schotti var. monstrosus P. schotti f. miekleyanus

265

53.3, 53.4

Aridlands Greenhouses Desert Survivorsb

266

46.1, 46.2

Desert Survivors

266

46.3, 43.5

Desert Survivors

267

52.3, 52.4

(Pf) Cons 1897/BOBP 10.

(BgeK) Purp 1908/MfK 18: 5.

192 86

43.2 to 43.4 54.1

Aridlands Greenhouses Desert Survivors Desert Survivors

Tribe Cacteae Mammillaria grahamii sp. grahamii M. laui ssp. subducta

Eng 1856/SynC 262; 1857/PAA 3: 262; 1859/CMB 7, t. 6.

(Hunt) Hunt 1997/MP 6: 7; 02715

158

405.4, 406.1

Desert Survivors

163

422.3

Desert Survivors

Subfamily Optuntioideae Tribe Cylindropuntiieae Cylindropuntia arbuscula C. fulgida C. kleiniae C. ramosissima C. versicolor Grusonia bradtiana

(Eng) Knuth 1936/K-ABC 123.

(Eng) Knuth 1936/K-ABC 126.

(DC) Knuth 1936/K-ABC 123.

(Eng) Knuth 1936/K-ABC 122.

(Cltr) Knuth 1936/K-ABC 125.

(Cltr) B+R 1919/CBR 1: 215.

70 71 72 72 73 126

477.1, 477.2 476.1, 476.2 477.4, 477.5 478.4, 478.5 474.4 481.5, 481.6

County Propertyc County Property Desert Survivors Desert Survivors Desert Survivors Desert Survivors

Stenocereus alamosensis S. eruca S. gummosus

published since NCL

Commercial Source

All names conform to the New Cactus Lexicon series (Hunt et al. 2006: Hunt 2013).

Aridlands Greenhouses, 3560 W. Bilby Rd. Tucson, AZ 85746 U.S.A. (32.20◦ N, 110.98◦ W).

Desert Survivors Native Plant Nursery, 1020 W Starr Pass Blvd, Tucson, AZ 85713. U.S.A. (32.20◦ N, 110.98◦ W). c County Property (32.07o N, 111.25o W) is near West Ava road near junction with Sierrita Mountain Road, (near Three Points) Tucson, AZ U.S.A. d private property of Robert Webb and Toni Yocum, Tucson, AZ

a b

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Table 2. Stem characteristics of the cactus plants studied.

Morphology Species

Total length of stems (cm)

Total Stem sample length1 (cm)

Average distance between stem samples2 (cm)

Globose Mammillaria grahamii sp. grahamii M. laui ssp. subducta Mean Standard Deviation

13.0 7.71 10.4 3.74

7.0 5.0 6.0c,3 1.41

1.75 1.0 1.4c 0.53

Prostrate Echinocereus pensilis Stenocereus alamosensis S. eruca S. gummosus Mean Standard Deviation

25.8 25.6 41.8 33.4 31.7 6.65

23.8 18.0 15.5 19.9 19.3a,b 3.50

5.95 3.60 3.10 3.98 4.16a,b 1.25

Terminal branches Cylindropuntia arbuscula C. fulgida C. kleiniae C. ramosissima C. versicolor Mean Standard Deviation

15.5 15.0 20.0 19.9 23.0 18.7 3.02

5.2 9.0 19.6 19.8 9.5 12.6b,c 6.67

1.30 2.25 3.92 3.96 1.90 2.67b,c 1.21

Columnar Carnegia gigantea Grusonia bradtiana Pachycereus marginatus P. pringlei P. schotti P. schotti var. monstrosus P. schotti f. miekleyanus Stenocereus thurberi ssp. thurberi Myrtillocactus geometrizans Mean Standard Deviation

41.3 17.8 24.2 40.0 66.5 25.9 36.7 38.4 40.9 36.9 14.0

26.2 17.7 17.0 29.0 21.0 18.1 18.9 29.0 27.0 22.7a 5.08

5.24 4.43 3.40 5.80 5.25 3.62 3.78 4.83 5.40 4.64a 0.87

1

This includes the length from the terminal to the base of the fifth stemsample which included (the depths of the discarded stem segments).

2 These values were the mean depths of the discarded stem segments so the reader can determine the overall sampling pattern for each species and each group.

3 Within each parameter, mean values followed by a different letter are statistically significant (p â&#x2030;¤ 0.05). Mean values followed by the same letter are not statistically significant.

Statistical analyses were performed using ANOVA followed by a multiple range test (Systat 10).

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#2. The surface area of these two segments was equal to 2πrh + 2πr2 (http://www.aaamath.com).

In this fashion, the stem surface areas of further stem portions were added to produce five data points for each stem sample.

Histological Procedures Immediately after photographs were taken, sections were fixed in FAA (Jensen, 1962) for 24 hours. After fixation, samples were dehydrated through a series of tert-butanol solutions. Tissues were then treated in paraffin (Paraplast X-tra Tissue Embedding, McCormick, Lecia Biosystems, Richmond, Inc., Richmond, IL). All tissues were embedded, microtomed at 30 µm, stained with safranin, and cover-slipped with Canada balsam. All measurements recorded via microscopy were standardized with a stage micrometer, allowing for calculations to be made with ImageJ. The number of vascular bundles found in each species was calculated using two or more stem sections. To calculate the number of vascular bundles per section, distances between the centers of adjacent bundles (Fig. 6) for around ten pairs of bundles were recorded. Distances were determined using a caliper and dissecting microscope with slides from the numerous sections. Numbers of vascular bundles were calculated as a function of perimeter of the vascular bundle ring divided by the average distance between two bundles (Fig. 6). The number of vascular bundles was constant among all sections for a species.

The overall number of conduits in each stem section was determined by calculating the average number of conduits per bundle multiplied by the number of bundles. For each stem section, the number of conduits in about ten randomly selected bundles was determined. For this study, only vessel cells were considered conduits (Mauseth, personal communication), no wide-band tracheids (Mauseth, 2004) were evaluated for this particular study. Xylem conductivity was calculated for each stem section using the following formula: Conductivity = (π × total number of conduits × conduit radius4 )/(8 × 109 )

(1)

with units of g cm MPa−1 s−1 (McCulloh and Sperry, 2005). The average of two diameter measurements of each conduit was used to determine the radius. Individual conduit radii were raised to the fourth power for the xylem conductivity calculations. The weighted average conduit radius (McCulloh, 2005) was calculated from the average of about fifty conduits per stem sample. The processes used in this section have been formerly used (Evans and Skonieczny, 2015).

Results The purpose of this research was to comprehend xylem conduit characteristics, vascular bundle characteristics, and xylem conductivity values for a variety of cactus species that possessed different morphologies. Tissues that were sampled near stem tips had relatively few conduits. As stems matured, additional conduits were added toward the outside of the stems. This caused bundles to expand as new conduits developed. In several cases, additional conduits produced wider

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vascular bundles. This progression of bundles becoming wider ultimately led to bundles becoming more closely associated in mature stem sections.

Cactus species in each of the groups displayed variation among vascular bundle shapes (Fig. 9). All species possessed rings of vertically-aligned vascular bundles, with a small number of conduits near stem tips and additional conduits in stem sections farther from stem tips (Fig. 10).

Quantities of conduits per bundle varied noticeably as a function of distance from the stem tips among the cactus species of this research (Fig. 11). This relationship of number of conduits per bundle and distance from the stem tip had slopes that ranged from 0.099 for P. schotti var. monstrosus to 0.70 for M. laui ssp. subducta among the four species displayed. Average numbers of conduits in the most mature stem sections examined were 9080, 3420, 2410 and 984 for columnar, prostrate, globose and terminal branch cacti, respectively. Numbers of conduits for both columnar species and prostrate species were statistically larger than that of globose and terminal branch species. Conduit diameters varied strikingly among the four cactus morphologies studied (Table 3). In the most basal stem sections, average conduit diameters were 38.8, 33.4, 18.7 and 17.9 µm for columnar, prostrate, terminal branch and globose species, respectively. Statistically, columnar and prostrate species were most different relative to the remaining two groups. For select species, conduit diameters changed by less than two times in length when progressing from stem tip to base. In contrast, some species had diameter measurements that increased more than five times along the stems sampled (Fig. 12). An investigation of variance indicated that slope values for columnar species were greater when related to both terminal branch species and globose species.

The cacti examined varied in relation to vascular bundle ring diameters, stem diameters, and number of vascular bundles (Table 3). Among these particular samples, the vascular bundle ring diameters were well correlated with stem diameters (Fig. 13). The equation of the line representing this relationship, y = 0.23x + 0.85, R2 = 0.87, reveals vascular bundle ring diameters to be 23% of diameters. In a similar fashion, the numbers of vascular bundles were associated with stem diameters (Fig. 14). Given the equation of the line, y = 2.32x + 0.98, R2 = 0.75, the number of vascular bundles increased approximately 2.3 bundles per mm change in diameter. The numbers of vascular bundles differed among the four morphological groups. Columnar species possessed an average of 198 bundles in the largest stem section, while terminal branch species averaged 23 bundles in the largest stems sections (Table 3).

For individual species, xylem conductivity was strongly associated with cumulative stem volume (Fig. 15). All individual species possessed R2 values above 0.70. The relatively low xylem conductivity values for terminal branch and globose species are worth noting. Among the most basal stem sections of the cactus species examined for this research, the number of conduits ranged from 547 to 32,800, while the xylem conductivities ranged from 0.04 to 378 g cm MPa−1 s−1 (Table 3). Despite this wide range of values for the two previous parameters, the xylem conductivity values were strongly correlated (R2 = 0.96) with the number of conduits (Fig. 16).

When species were analyzed collectively, xylem conductivity values were also strongly correlated (y = 0.000085x − 10.76; R2 = 0.88) with cumulative stem volumes (Fig. 17). Among

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Figure 9. Images of three stem segments that illustrate vascular bundles from cactus species with several stem morphologies. A: Stem section 73 mm from the terminal of Cylindropuntia ramosissima (terminal branch cactus species).

B: Stem section 20 mm from the terminal of Mammillaria laui (globose cactus species). C: Stem section 155 mm from the terminal of Stenocereus eruca (prostrate cactus species). Bars = 200 Âľm.

Figure 10. Images of four stem segments that illustrate changes in numbers of xylem conduits in stem segments of Carnegia gigantea (columnar cactus species). A: Stem section 95 mm from the terminal. B: Stem section 150 mm from the terminal. C: Stem section 210 mm from the terminal. D: Stem section 262 mm from the terminal. Bars = 200 Âľm.

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Figure 11. Intraspecific scaling of the number of conduits per bundle in four cactus stems as a function of distance from the stem terminals. Data of Cylindropuntia arbuscula (triangles) [y = 0.70x â&#x2C6;&#x2019; 3.5; R2 = 0.98] as an example of a terminal branch species; Pachycereus schotti var. monstrosus (diamonds) [y = 0.37x+3.3; R2 = 0.97] as an example of a columnar species; Mammillaria laui ssp. subducta (circles) [y = 0.25x + 0.64; R2 = 0.97] as an example of a globose species; and Stenocersus alamosensis ((squares) [y = 0.098x + 0.19; R2 = 0.97] as an example of a prostrate species.

Figure 12. Intraspecific scaling of the increase in mean conduit diameter as a function of distance from the stem terminals for all species of this study.

Slopes values for columnar species were higher compared with both terminal branches and globose species but were not different for prostrate species.

No other comparisons were statistically significant.

Figure 13. Interspecific scaling of vascular bundle ring diameter as a function of stem diameters for the most basal stem segment of all the stems of this study. The equation of the line was y = 0.229x + 0.851 with an R2 of 0.87.

Figure 14. Interspecific scaling of the number of vascular bundles as a function of stem diameters for all the stems of this study. The equation of the line was y = 2.32x + 0.98 with an R2 of 0.75.

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Table 3. Stem characteristics of the cactus plants studied.

Morphology Plant name

Number of bundles1 (cm)

Largest Largest Largest Cumulative Cumulative Vascular xylem number stem stem stem bundle conductivity of diameter1 surface volume ring conduits1 (cm) (g cm (103 mm3 ) (103 mm2 ) diameter1 MPaâ&#x2C6;&#x2019;1 sâ&#x2C6;&#x2019;1 ) (cm)

Globose Mammillaria grahamii sp. grahamii M. laui ssp. subducta Mean Standard Deviation

73

53.2

7.57

2250

15

14.5

0.90

77 75b 3.33

31.4 42.3a,b 15.5

10.3 8.94b 1.93

2570 2410a 227

278 197b,c 61.7

5.46 9.98c 6.36

0.50 0.70b 0.28

Prostrate Echinocereus pensilis Stenocereus alamosensis S. eruca S. gummosus Mean Standard Deviation

54 80 99 102 84 b 22

33.2 38.6 42.6 39.7 38.5b 3.95

5.60 7.40 6.81 7.77 6.90b 0.95

1300 4020 5410 2990 3430a,b 1740

138 182 200 210 183b 61.7

17.3 37.5 26.4 42.5 30.9b 11.3

9.21 11.5 26.8 6.38 13.5a 9.13

Terminal branches Cylindropuntia arbuscula C. fulgida C. kleiniae C. ramosissima C. versicolor Mean Standard Deviation

23 26 32 11 25 23c 7.64

8.39 23.2 9.53 10.1 10.8 12.4c 6.11

3.20 11.5 4.55 1.60 3.10 4.79b 3.88

547 1070 1270 594 1440 984b 399

2.51 33.5 13.5 11.6 8.13 13.8b 11.7

1.18 8.90 6.67 8.46 4.79 6.24c 3.15

0.04 0.78 0.36 0.05 1.55 0.56b 0.63

257 49 153 255 260 224 169 292

143 42.7 53.6 97.2 102 52.5 59.3 82.4

31.0 9.02 13.1 24.3 28.6 15.3 16.8 16.5

32800 2170 5500 5510 8210 4320 4600 13300

3400 158 313 1740 1360 327 440 1290

202 20.2 32.0 141 74.7 80.3 40.4 115

378 3.10 35.7 69.7 75.6 13.5 12.8 83.2

127 198a 79.2

68.1 77.9a 31.9

22.6 19.7a 7.35

5150 9070a 9460

792 1090a 1030

69.4 86.1a 58.2

48.4 80.0a,b 115

Columnar Carnegia gigantea Grusonia bradtiana Pachycereus marginatus P. pringlei P. schotti P. schotti var. monstrosus P. schotti f. miekleyanus Stenocereus thurberi ssp. thurberi Myrtillocactus geometrizans Mean Standard Deviation 1

Measurements were taken from the most basal stem segment.

Statistical analyses were performed using ANOVA followed by a multiple range test (Systat 10).

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Figure 15. Intraspecific scaling of xylem conductivity as a function of cumulative stem volumes for stems of this study. Data for Carnegiea gigantea were not included so that data for most species would be more visible. The slope of the line corresponding to Carnegiea gigantea was similar to the other species shown.

Figure 16. Interspecific scaling of xylem conductivity as a function of the number of conduits for the most basal stem segment of all the stems of this study. The equation of the line was y = 0.0115x − 21.5 with an R2 of 0.96.

Figure 17. Interspecific scaling of xylem conductivity as a function of the cumulative stem volumes of all the stems of this study. The equation of the line was y = 0.000085x − 10.76 with an R2 of 0.88.

Figure 18. Intraspecific scaling of xylem conductivity as a function of cumulative stem surface areas for stems of this study. Data for Carnegiea gigantea were not included so that data for most species would be more visible. The slope of Carnegiea gigantea was similar to the other species shown.

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the four morphologies of cacti, average xylem conductivities of the most basal sections were 0.56, 0.70, 13.5, and 80.0 g cm MPa−1 s−1 for terminal branches, globose, prostrate, and columnar species, respectively. Due to a great amount of variability in xylem conductivity values for columnar species, no statistically significant differences regarding xylem conductivities among all four groups were apparent. Xylem conductivity was associated with cumulative stem surface area for individual species (Fig. 18). All distinct species possessed R2 values above 0.70.

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When species were united, xylem conductivities for the most basal sections were well associated (y = 0.00123x â&#x2C6;&#x2019; 23.1; R2 = 0.72) with cumulative stem surface areas (Fig. 19).

Figure 19. Interspecific scaling of xylem conductivity as a function of the cumulative stem surface areas of all the stems of this study. The equation of the line was y = 0.00123x â&#x2C6;&#x2019; 23.1 with an R2 of 0.72.

Discussion The main reason for conducting this research was to comprehend vascular bundle characteristics and xylem conductivity values in cactus species that possessed variability in morphologies that ranged from small terminal branches of shrub species to large stems of columnar species. This study was to be a general survey in which forthcoming researchers may want to put emphasis on the individual cactus groups mentioned.

Research involving xylem characteristics and xylem conductivity in plants is fairly new. For most woody plants, conduits make a noteworthy impact on mechanical properties in stems (Hache and Sperry, 2001; Weitz et al., 2006; Zach et al., 2010). McCulloh et al. (2009) studied xylem conductivity in petioles and petiolules of leaves and suggested that these tissues provide little mechanical support. The reasonably small quantities of conduits in terminal stem portions of cacti possibly provide little mechanical support due to the conception that quantities of xylem tracheids and fibers are more than ten times the quantity of xylem conduits in cactus stems (Gibson and Nobel, 1986). Therefore, the primary function of xylem conduits in terminal portions of cactus stems is water transport. The comparable xylem conductivity relationships presented here further support the notion that xylem conduits are predominantly involved in water transport rather than mechanical support.

The concentration of this study was to determine if there are any generalities concerning vascular bundles, xylem conduits and xylem conductivity for cactus species with several distinct morphologies. Numbers of conduits per bundle differed strikingly as a function of distance from the stem tips among all cactus species of this research. Differences in stem diameter were most apparent among the four groups, and significant differences were present regarding the numbers of conduits and numbers of vascular bundles among the four groups.

As anticipated, slopes of xylem conductivity versus both cumulative stem volumes and cumulative stem surface areas differed markedly among cactus species analyzed. Even though the values

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differed over several orders of magnitude, xylem conductivity was correlated to all morphological parameters when the species were grouped together.

Acknowledgements The author is grateful to the Catherine and Robert Fenton Endowed Chair to Lance S. Evans for financial support for this research. The author thanks Robert H. Webb and Toni Yocum for assistance with the scientific names for all species and their donation of stems for this study from their private property.

References Anderson, E. (2001). The Cactus Family. Timber Press, Portland, Oregon.

Bender, G.L. (1982). Reference Handbook on the Deserts of North America. Greenwood Press.

Westport, CT. Bensen, L. (1982). The Cacti of the United States and Canada. Stanford Univ. Press. Stanford, CA. Coomes, D.A., Heathcote, S., Godfey, E.R., Shepard, J.J. & Sack, L. (2008). Scaling of xylem vessels and veins within the leaves of oak species. Biol. Letters 4: 302-306.

Evans, L. S., Cantarella, V.A., Kaszczak, L., Krempasky, S.M. & Thompson, K.H. (1994). Epidermal Browning of Saguaro Cacti (Carnegiea gigantea). Physiological Effects, Rates of Browning and Relation to Sun/Shade Conditions. Environ. and Exp. Botany 34: 107-115.

Evans, L.S. and Margaret L. Cooney. 2015. Sunlight-induced bark formation in long-lived South American Columnar Cacti. Flora. 217:33-40.

Evans, L. S. and K. Skonieczny. 2015. Xylem Conductivity in Terminal Stems of 20 Species of Columnar Cacti of South America. Bradleya.33:108-118.

Gibson, A. C. (1973). Comparative anatomy of second xylem in Cactoideae (Cactaceae). Biotropica 5: 29-65.

Gibson, A. C. & Nobel, P.S. (1968). The cactus primer. Harvard Univ. Press. Cambridge, MA. Gleason, S. M., Butler, D.W., Ziemiriska, K., Waryszak, P. & Westoby, M. (2012). Stem xylem conductivity is key to plant water balance across Australian angiosperm species. Functional Ecology 26: 343-352.

Hacke, U., & Sperry, J. (2001). Functional and ecological xylem anatomy. Perspectives in Plant Ecology, Evolution and Systematics 4: 97-99.

Hunt, D. 2013. The New Cactus Lexicon Illustrations. dh Books. Milborne Port, UK. Hunt, D., Taylor, N, Charles, G. 2006. The New Cactus Lexicon. Two volumes. dh Books. Milborne Port, UK Jensen, W.A. (1962). Botanical Histochemistry. â&#x20AC;&#x201C; Principles and Practice. W.H. Freeman. San Francisco, CA MacMahon, J. A. (1992). Deserts. National Audubon Society. New York.

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Mauseth, J. D. (1988). Plant Anatomy. The Blackburn Press. Caldwell, NJ. Mauseth, J. D. (1993a). Water-storing and cavitation. Annals of Botany 72: 81-89.

Mauseth, J. D. (1993b). Medullary bundles and the evolution of cacti. Amer. J. Bot. 80: 928-932.

Mauseth, J. D. (2004). Wide-band tracheids are present in almost all species of Cactaceae. J. Plant Res. 117: 69-76.

Mauseth, J. D., & Sajeva, M. (1992). Cortical in the persistent, photosynthetic stems of cacti. Ann. Bot. 70: 317-324.

McCulloh, K.A., & Sperry, J. S. (2005) Patterns in hydraulic architecture and their implications for transportation efficiency. Tree Physiology 25: 257-267.

McCulloh, K.A., Sperry, J. S., Meinzer, F.C., Lachenbruch, B., & C. Arala, C. (2009). Murray’s law, the ‘Yarrum’ optimum, and the hydraulic architecture of compound leaves. New Phytologist 184: 234-244.

McCulloh, K.A., Sperry, J.S., Lachenbruch, B., Meinzer, F.C. & Reich, P. (2010). Moving water well: comparing hydraulic efficiency in twigs and trucks of coniferous, ring-porous, and diffuseporous saplings from temperate and tropical forests. New Phytologist 185: 1-12.

Murray, C. D. (1926). The physiological principle of minimum work. I. The vascular system and the cost of bold volume. Proc Natl. Acad. Sci. 12: 207-214.

Nobel, P.S. (1988). Environmental Biology of agaves and cacti. Cambridge University Press. New York.

Sherman, T. F. (1981). On connecting large vessels to small. J. Gen. Physiol. 78: 431-453.

Sperry, J. S., Hacke, U.G., & Pitterman, J. (2006). Size and function of conifer tracheids and angiosperm vessels. Amer. J. Bot. 93: 1490-1500.

Weitz, J., Ogle, K., & Horn, H. (2006). Ontogenetically stable hydraulic design in woody plants.

Functional Ecology 20: 191-199.

Zach, A., Schuldt, B., Brix, S., Horna, V. & Culmsee, H. (2010). Vessel diameter and xylem hydraulic conductivity increase with tree height in tropical rainforest trees in Sulawasi, Indonesia.

Flora 205: 506-512.

Evidence of Cryptosporidium spp. in Three Bivalve Species Collected from Orchard Beach, New York.

Freda Fafah Ami Tei∗ Department of Biology, Manhattan College Abstract. Bivalve mollusks as filter-feeders play an important role in the integrity of estuarine ecosystem. Mussels and oysters are raised commercially and are part of our everyday diet. They are either bottom-dwellers or spend their lives attached to substrates. Bivalves have been shown to be infected with the human intestinal parasites of the genus Cryptosporidium, which causes cryptosporidiosis in humans and other vertebrates. Thus, bivalves could be used as biosentinels for human parasites in aquatic environment. The goal of this study is to determine the prevalence of Cryptosporidium species from mollusks of New York City using a polymerase chain reaction (PCR)–based assay.

Four bivalve species were collected at low tide from Orchard beach New York in September 2014. For this study, we will focus on three out of four, which are Mytilus edulis, Mya arenaria, and Geukensia demissa. We found that the prevalence of Cryptosporidium species in Mytilus edulis was 1% and 16% in Geukensia demissa. Surprisingly, 50% of the collected specimens of Mya arenaria tested positive for Cryptosporidium infection.

Introduction Evaluation of water quality has been done conventionally by testing for the pH, and presence of chemicals such as nitrate and bacteria in the water. Water systems are normally contaminated with rainfall and sewage runoff which increases the number of coliforms (Ferguson et al., 1996).

Testing of water quality usually depends on monitoring the increase in bacterial indicators such as coliforms and fecal coliforms to determine the level of contamination in the water. These indicators are not very reliable for predicting the presence of protozoan enteritis parasites like Cryptosporidium and others like Giardia, which are some of the common protozoan in aquatic environments (Rose et al., 1988).

Cryptosporidium is a protozoan of the genus Apicomplexa. It causes enteritis which is accompanied by diarrhea (Semie et al., 2014). Cryptosporidiosis is an intestinal disease that affects humans and vertebrates (Semie et al., 2014). The mode of transmission of Cryptosporidium is through contaminated water and food or having direct contact with an infected host. According to the CDC, Cryptosporidium is the leading cause of water-borne disease among humans in the United States. Cryptosporidium is exposed to the environment through the deposit of fecal matter containing the oocysts. The oocysts have a thick shell that helps it to survive for long periods of time until it infects a definitive host. The use of disinfectant will not kill the oocysts in water. The oocysts are also not inactivated by chlorine. This contributes to the spread of the parasite (Korich et al., 1990). Cryptosporidiosis greatly affects individuals with a compromised immune system.

Cryptosporidium has been isolated from patients with Acquired Immune Deficiency syndrome ∗

Research mentored by Ghislaine Mayer, Ph.D.

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(AIDS) and it is linked to severe symptoms axhibited in people with AIDS due to their depressed immune function (Cozon et al., 1994).

There are many chemicals and pollutants that are introduced into aquatic environments due to human activities, therefore bio-indicators are needed to assess aquatic environment and are thus an integral component of public health (Martinez, 2007). Bio-sentinels such as bivalves have been used by many researchers to test for toxins in the environment (Koh et al., 2013). Bivalves acquire nutrients by filter feeding, which allows them to pick up particles from their aquatic environments.

This makes bivalves very good candidates in testing for human pathogens in aquatic environments. This mechanism allows one to detect the organism present in aquatic environment since the oocysts can persist for long periods. The use of bivalves as bio-sentinels for the detection of Cryptosporidium spp. is very important because bivalves are commercially raised and sometimes are eaten raw (Graczyk et al., 2008). They have previously been used to monitor aquatic environments for human enteric parasites (Graczyk et al., 2008). The goal of this research is to determine which of the bivalve species collected at Orchard Beach, New York will be a good bio-sentinel for Cryptosporidium species.

Materials and Methods Sample collection and DNA isolation Four species of bivalves were collected in Orchard Beach, New York on September 9th, 2014 at low tide. The species collected are as follows: Mya arenaria (8) Crassostrea virginica (10), Geukensia demissa (44) and Mytulis edulis (97). The digestive tract, the gills, the foot, and the mantle were dissected from each individual. DNA was isolated from each tissue using the Qiagen DNA tissue kit (Qiagen, Valencia, CA). The quantity and purity of DNA was determined using a UV spectrophotometer. Briefly, 0.25 grams of each individual tissue was obtained and cut into tiny pieces to ensure a more efficient lysis, the tissue was further placed into one hundred and eighty uL of lysis buffer. The addition of the buffer was to break down the tissue. Twenty uL of proteinase K was added and the mixture was vortexed to ensure that the mixture was thoroughly mixed. It was then incubated for 1 hour in a water bath at 56◦ C until the tissue was completely lysed. After an hour, the lysed tissue was removed from the water bath; the tissue was vortexed for 15 minutes to ensure a uniform dispersion of the sample. The lysate was transferred into a DNeasy Mini spin column for DNA isolation. Following washes, the DNA was eluted and stored at -20◦ C prior to analysis.

Polymerase Chain Reaction and agarose gel The prevalence of Cryptosporidium spp. was determined by using the primer sets that target the 18S ribosomal RNA subunit gene of Cryptosporidium parvum (forward primer: 50 CCGAGTTTGATCCAAAAAGTTACGAA30 ; reverse primer: 50 TAGCTCCTCATATGCCTTATTGAGTA30 ) with the following conditions: 35 cycles at 94◦ C for 1 min, 52 ◦ C for 2 min, and 72◦ C for 3 min with a final extension at 72 ◦ C for 5 min (Rochelle et al., 1996). The PCR products were detected using a 1.5% agarose electrophoresis stained with ethidium bromide.

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Results Detection of Cryptosporidium spp. DNA in Mya arenaria To determine the presence of Cryptosporidium in Mya arenaria, tissues from 8 collected specimens were analyzed by PCR. As shown in Fig. 1 and Table 1 specimens 1, 3, 4 and 5 were positive for Cryptosporidium spp. The tissues that were infected for all the specimen were: digestive gland in specimen 1 and 3, the foot in specimen 4 and 5 an the siphon in specimen 3 (Table 2). We found that 50% of tested samples were positive for Cryptosporidium spp (Fig. 1 and Table 1).

Figure 1. Mya arenaria infection with Cryptosporidium spp. Top Lane 1: 100 bp marker, Lane 2: positive control, Lane 3-16: Mya arenaria tissue DNA, Bottom Lane 1: 100 bp marker, Lane 2-15 : Mya arenaria tissues DNA, Lane 20: negative control.

Figure 2. Geukensia demissa infection with Cryptosporidium spp. Top Lane 1: 100 bp marker, Lane 2: positive control, Lane 3-18: Geukensia demissa tissue DNA. Bottom Lane 1: 100 bp marker, Lanes 2-18: Geukensia demissa tissue DNA, Lane 20: negative control.

Detection of Cryptosporidium spp. DNA in Geukensia demissa The presence of Cryptosporidium spp. DNA was assessed by PCR in 44 specimens of Geukensia demissa. Cryptosporidium DNA was detected in specimens 34, 35, 36, 37, 38, 39, 40 of Table 1. Infection status of Mya arenaria

Table 2. Mya arenaria infected tissues

Species name

Specimen Number

Cryptosporidium spp DNA

Specimen Number

Mya arenaria Mya arenaria Mya arenaria Mya arenaria

1 2 3-5 6-8

Present Absent Present Absent

1 3 4 5

Tissue Type Digestive gland Siphon Digestive gland Foot Foot

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Geukensia demissa (Fig. 2 and Table 3). The infected tissues were: The foot in specimens 34, 36, 38, 39 and 40, the digestive gland in specimens 34, 36 and 40, the mantle in specimens 35, 37 and 38 and lastly specimens 37 and 38 showed infection in the gills (Table 4). Overall the prevalence of Cryptosporidium spp in Geukensia demissa was 16% (Fig. 2 and Table 3).

Table 3. Infection status of Geukensia demissa Species name

Specimen Number

Cryptosporidium spp DNA

Geukensia demissa Geukensia demissa Geukensia demissa

1-33 34-40 41-44

Absent Present Absent

Table 4. Geukensia demissa infected tissues Specimen Number 34 35 36 37

38 39 40

Tissue Type Foot Digestive gland Mantle Foot Digestive gland Mantle Gills Foot Mantle Gills Foot Foot Digestive gland

Detection of Cryptosporidium spp. DNA in Mytilus edulis Ninety seven Mytilus edulis mussels were tested for infection with Cryptosporidium. Out of the ninety seven, only specimen 29 was found to be infected (Fig. 3 and Table 5). The infected tissues were the gills and foot (Table 6). This study reveals a prevalence of 1% of Cryptosporidium in Mytilus edulis (Fig. 3 and Table 5).

Discussion Based on the results Cryptosporidium spp was found in all of the bivalve species that were tested. There was no apparent pattern in the tissues infected from bivalve species collected at Orchard beach. It seems that each tissue was equally infected. Fifty percent (4/8) Mya arenaria were infected with Cryptosporidium spp. Sixteen percent (7/44) Geukensia demissa were infected

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Figure 3. Mytilus edulis infection with Cryptosporidium spp. Top Lane 1: 100 bp marker, Lane 2: positive control, Lane 3-18: Mytilus tissue DNA. Bottom Lane 1:100 bp marker, Lane 2- 19: Mytilus tissue DNA, Lane 20: negative control.

Table 5. Infection status of Mytilus edulis

Table 6. Mytilus edulis infected tissues

Species name

Specimen Number

Cryptosporidium spp DNA

Specimen Number

Geukensia demissa Geukensia demissa Geukensia demissa

1-28 29 30-97

Absent Present Absent

29

Tissue Type Gills Foot

with Cryptosporidium spp. and 1% (1/97) Mytilus edulis were infected with Cryptosporidium spp. Our results indicate that bivalves are excellent model systems to monitor for the presence of Cryptosporidium in the marine environments they inhabit. They have successfully been used to detect the presence of Cryptosporidium in Oahu (Asahina et al., 2009). The parasites that they pick up during filter feeding also persist for a long period of time (Villegas, E. 2014). From the data, Mya arenaria seems to be the best bio-sentinel for Cryptosporidium spp. detection even though the sample size was very small. In the future it will be better to screen a wide variety of specimens.

The source of pollution at Orchard beach is currently unknown but over the summer News 12, a local TV station, reported that Orchard Beach was shut down due to contamination with sewage.

This report supports our research that Orchard Beach is contaminated with Cryptosporidium. Biosentinels as a way of detecting pollutants in the environment allow researchers to determine the duration of the pollution in that particular environment as opposed to current chemical screenings conducted to test the water quality which provides only a snapshot of the aquatic environment. In the future, we will determine the species of Cryptosporidium present in the infected tissues. We will also determine the source of infection.

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Acknowledgement The author thanks the School of Science Research Scholars Program for financial support during this research.

References Asahina, A. Y., Y. Lu, C. Wu, R. S. Fujioka, and P. C. Loh (2009). Potential biosentinels of human waste in marine coastal waters: Bioaccumulation of human noroviruses and enteroviruses from sewage-polluted waters by indigenous mollusks. J. Virol. Methods. 158:46-50.

Cozon G., Biron F., Jeannin M, Cannella D, Revillard JP (1994). Secretory IgA Antibodies to Cryptosporidium parvum in AIDS patients with Chronic Cryptosporidiosis, The Journal of Infectious Disease. 3: 696-699.

Ferguson C., Coote B., Ashbolt N., and Stevenson I (1996). Relationships between indicators, pathogens and water quality in an estuarine system. Water Research, 30:2045- 2054.

Graczyk, T. K., and D. B. Conn. (2008). Molecular markers and sentinel organisms for environmental monitoring. Parasite 15:458-62.

Koh, Wan, Peta L. Clode, Paul Monis, and RC A. Thompson (2013). Multiplication of the waterborne pathogen Cryptosporidium Parvum in an aquatic biofilm system. Parasit. Vectors. 6:2.

Korich DG, Mead JR, Madore MS, Sinclair NA, and Sterling CR (1990). Effects of ozone, chlorine dioxide, chlorine and chloramines on Cryptosporidium parvum oocyst viability. Appl. Environ.

Microbiol. 56:1423-1428.

Martinez, V. (2007). Helminths and Protozoans of Aquatic Organisms as Bioindicators of Chemical Pollution. Parassitologia. 49:177-84.

Rochelle, P.A. (199). Comparison of primers and optimization of PCR conditions for detection of Cryptosporidium parvum and Giardia lamblia in water. Applied and Environmental Microbiology. 63: 106-114.

Rose, Joan B., Darbin, Hamid and Charles P. Gerba (1988). Correlations of the protozoa, Cryptosporidium and Giardia, with water quality variables in a watershed. Water Science and Technology, 20:271- 276.

Semie H., Kim K., Yoon S., Park, W., Sim S., and Yu J (2014). Detection of Cryptosporidium parvum in environmental soil and vegetables. The Korean Academy of Medical Sciences 29: 1367-1371.

Villegas, E. (2014). Using Bivalves as Biosentinels to Detect Cryptosporidium spp. and Toxoplasma gondii Contamination in aquatic environments. The 89th Annual Meeting of the American Society of Parasitologists. 89: 117-18.

Department of Chemistry and Biochemistry, Manhattan College Bronx, NY 10471, USA *Kakos Summer Research Fellow

A density Abstract:

functional study of proton acidity in the thiazolium ring

Mozdzierz et al. recently synthesized a series of thiazolium rings with a variety of Anthony DiProperzioâ&#x2C6;&#x2014; substituents.8 B3LYP/6-311++G** density functional calculations were done to study interesting Department of specifically Chemistry and Biochemistry, College properties of these compounds, why the removal Manhattan of a hydrogen from ring carbon number 2 is favored over the removal of any other hydrogens. (See text.) These calculations Mozdzierz al. recently synthesized a series of thiazolium ringssynthesized with a variety of substituents ring [1]. We were Abstract. done to study theetinteresting electronic properties of the thiazolium as well performed B3LYP/6-311++G** density functional calculations to study interesting properties of these compounds, as the series of halogen substituted analogs. specifically why the removal of a hydrogen from ring carbon number 2 is favored over the removal of any other hydrogens. These calculations were done to study the interesting electronic properties of the synthesized thiazolium Introduction: ring as well as the series of halogen substituted analogs.

Introduction Thiazolium is a 5-membered heterocyclic zwitterion that contains sulfur and nitrogen.

Thiazolium a 5-membered heterocyclic by zwitterion thatdelocalization. contains sulfurC5 andis nitrogen.

The The ring is planar,is aromatic, and characterized pi electron the primary ringfor is electrophilic planar, aromatic, and characterized electron C5substitution. is the primary site site substitution, and C2 is by the pi primary sitedelocalization. for nucleophilic It has for electrophilic andaC2 is the primary site forB1, nucleophilic substitution.

It has and many many interesting substitution, uses, including component of Vitamin dyes, fungicides, pesticides, 9 interesting uses, including component of Vitamin B1, dyes, fungicides, pesticides, and even in even in the firefly chemicalaluciferin. the firefly chemical luciferin [2].

8 Mozdzierzetetal.al.[1] synthesized a thiazolium ring thatthat waswas a zwitterion andand unstable.

TheThe Mozdzierz synthesized a thiazolium ring a zwitterion unstable. purpose was to investigate why the proton removal leading to the formation of the zwitterion was purpose was to investigate why the proton removal leading to the formation of the zwitterion was favored of one one of of the the protons protonsfrom fromthe theR-group.

R-group. favored over over the the removal removal of

Diagram 1. Synthesized Thiazolium Ring Figure 11 displays is the thiazolium is ring synthesized

by Mozdzierz.

Note Note that the Diagram the thiazolium ring synthesized

by Mozdzierz. thatthe thenitrogen the nitrogen positively charged, and that the carbon at the 2 position has a negative charge, thus making the is positively charged, and that the carbon at the 2 position has a negative charge, thus making the molecule molecule aa zwitterion. zwitterion.

Theoretical Details Density Functional calculations were performed on the modified thiazolium rings using Spartan 14, B3LYP correlation functional, and the basis set of 6-311++G**. Every calculation included Electrostatic [3], Mulliken [4], and Natural Population Analysis (NPA) [5]. Diagrams 2-8 display the configurations we studied. All structures were geometry-optimized and vibrational frequencies 1were calculated to ensure that the energy minima were obtained. â&#x2C6;&#x2014;

Research mentored by Joseph Capitani, Ph.D.

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Diagram 2 Addition of Carbonyl to Thiazolium Derivative

2

H

4

N

3

H 1'

O

H X

2'

X

Diagram 3 Diagram 4 Addition of a Nitro Group to Addition of Halogens to the Benzene Ring the Benzene Ring (X = F, Cl, Br)

Diagram 6 Diagram 7 Halogen substitution on Replacement of H’s on the the Thiazolium Ring. (X1, Thiazolium Ring with X2 = H, F, Cl, Br) Methyls.

(X1, X2, and X3 = H, CH3)

DiProperzio

Diagram 5 Replacement of the RGroup at N3 with a C. (X = H, F, Cl, Br)

Diagram 8 Addition of Halogens to the 2' position.

(X1 , X2 = hydrogens; X’s at 2' = F, Cl, or Br)

The goal wasDetails: to make the hydrogens at 10 more acidic than the hydrogen at C2. Calculations Theoretical were performed comparing the acidities of the hydrogen at C2 and those at 10 . A nitro group was Functional calculations performed on the modified thiazolium In rings using Spartan added to the Density benzene ring para to C20 were and the calculations were repeated. attempt to make 14, B3LYP correlation functional, and the basis 0 set of 6-311++G**. Every calculation included the hydrogen at C2 more acidic than those at 1 , halogens were added to the benzene ring in Electrostatic, Mulliken, and Natural Population Analysis (NPA). All structures were geometry optimized the ortho and para positions.

Graphs of electronegativity versusminima chargewere were generated for the and vibrational frequencies were calculated to insure that the energy obtained.

Electrostatic, Mulliken and Natural Population Analysis (NPA) charges. Because the hydrogen at The goala was to make the the hydrogens at 1’ more acidic than the hydrogen at C2.nitrogen Calculations C2 still maintained higher acidity, R-Group attached to the positively charged of the were performed comparing the acidities of the hydrogen at C2 and those at 1’. A nitro group was added thiazolium ring was replaced by a methyl. Calculations on the acidity of the hydrogen at C2 were to the benzene ring para to C2’ and the calculations were repeated. In attempt to make the hydrogen at done each with three than hydrogens, fluorines, chlorines, and three C2 more acidic those at three 1’, halogens werethree added to the benzene ringbromines. in the ortho and para positions. of electronegativity charge were generated Electrostatic, Mulliken and Interest wasGraphs then directed upon theversus electron delocalization of for thethe thiazolium ring.

The hydroNatural Population Analysis (NPA) charges. Because the hydrogen at C2 still maintained a higher acidity, gens atthe C4R-Group and C5attached were replaced by the same halogens previously. replacement to the positively charged nitrogenasofused the thiazolium ringAlso, was replaced by a of either the hydrogen at C4 or at C5 with a halogen was performed to look deeper into the electron methyl. Calculations on the acidity of the hydrogen at C2 were done each with three hydrogens, three fluorines, of three andthe threehydrogens, bromines. including the hydrogen at C2, on the thiazolium delocalization thechlorines, ring. All ring were replaced with methyls to see how the acidities of the hydrogens attached to the methyls Interest was then directed upon the electron delocalization of the thiazolium ring. The compared theC5hydrogen at C2. calculation repeated by replacing only the at C4toand were replaced

by This the same halogens was as used previously.

Also, replacement of hydrogen either the at C2 withhydrogen a methyl.

The portion of this featured addition to the 20 carbon. at C4 or atfinal C5 with a halogen wasresearch performed to look deeper intoof thehalogens electron delocalization of the ring. All the hydrogens, including the hydrogen at C2, on the thiazolium ring were replaced with

Results

In reference to Diagram 2, Table 1 shows that the hydrogen at C2 proved to be more acidic Pagethan 2 0 the hydrogens at 1 , even though they were structurally closer to the strong electron-withdrawing

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oxygen. As can be seen in Table 2 and in Diagram 3, the hydrogen at C2 proved to be the most acidic, even though it appeared that the hydrogens at 10 were in much better proximity to the electron-withdrawing groups.

Table 1. Carbonyl Addition to R-Group (Diagram 2) Charge

Hydrogen at C2

Hydrogen at 10

Hydrogen at 20

Electrostatic Mulliken Natural

0.280 0.306 0.269

0.233 0.262 0.249

0.236 0.200 0.239

Table 2. Nitro Group and Carbonyl Additions to the R-Group (Diagram 3) Charge

Hydrogen at C2

Hydrogen at 10

Hydrogen at 20

Electrostatic Mulliken Natural

0.283 0.304 0.268

0.238 0.261 0.252

0.239 0.198 0.241

The significance of Table 3 and Diagram 4 is that the more electronegative halogen replacement led to making the hydrogens at 10 more acidic than when there was the carbonyl substitution.

However, the hydrogen at C2 was still more acidic than the hydrogens at 10 , even though the hydrogens at 10 were structurally closer to the halogenated benzene, and should have been made more acidic due to the inductive effect.

Table 3. Addition of Halogens to Ortho and Para Positions of Benzene (Diagram 4) Charge

Difluoro (hydrogen at C2)

Dichloro (hydrogen at C2)

Dibromo (hydrogen at C2)

Electrostatic Mulliken Natural

0.276 0.305 0.268

0.292 0.305 0.267

0.292 0.306 0.268

Charge

Difluoro (hydrogen at 10 )

Dichloro (hydrogen at 10 )

Dibromo (hydrogen at 10 )

Electrostatic Mulliken Natural

0.273 0.230 0.251

0.234 0.153 0.249

0.235 0.180 0.248

Charge

Difluoro (hydrogen at 10 )

Dichloro (hydrogen at 10 )

Dibromo (hydrogen at 10 )

Electrostatic Mulliken Natural

0.268 0.273 0.255

0.239 0.232 0.258

0.242 0.237 0.260

In reference to Diagram 4, the significance of Fig. 1 is that the charge of the hydrogen at C2 decreased with increasing electronegativity, while the charges of the hydrogens at 10 increased with

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Figure 1. Charge vs. electronegativity using Electrostatic

Figure 2. Charge vs. electronegativity using Mulliken

DiProperzio

Figure 3. Charge vs. electronegativity using Natural Population Analysis

increasing electronegativity.

For Fig. 2 and Diagram 4, the Mulliken charge displayed similar trends for the hydrogens at 1 ; however, the charge of the hydrogen at C2 seemed to remain constant.

0

The NPA (Fig. 3) displayed unexpected results for the ortho and para halogen substitutions on the benzene ring (Diagram 4), as one of the hydrogens at 10 decreasing with increasing electronegativity, while the other increasing. However, the charge of the hydrogen at C2 still remained constant.

As can be seen from Table 4 but also with reference to Diagram 5, the acidity of the hydrogen at C2 increased as the halogens became more electronegative. The methyl hydrogens made the hydrogen at C2 the least acidic according to NPA, because hydrogen is not as electronegative as the halogens. However, the Electrostatic and the Mulliken charges both displayed hydrogen as having greater electron-withdrawing effects than both chlorine and bromine, and in one case, fluorine.

Table 4. Hydrogen at C2 Charge Upon Replacement of R-Group with Methyl (Diagram 5) Charge Type

Hydrogens

Fluorines

Chlorines

Bromines

Electrostatic Mulliken Natural

0.265 0.289 0.261

0.258 0.311 0.284

0.229 0.274 0.280

0.185 0.258 0.278

According to Table 5, replacement of the thiazolium hydrogens with the halogens (Diagram 6) led to the same trends as seen in Table 1. Replacement of the hydrogens in the ring with

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Table 5. Replacement of Thiazolium Hydrogens with Halogens (See Diagram 6) Charge Type

Hydrogens

Difluorine

Dichlorine

Dibromine

Electrostatic Mulliken Natural

0.265 0.289 0.261

0.314 0.297 0.265

0.271 0.322 0.263

0.258 0.296 0.262

Charge Type

Hydrogens

Fluorine at C4

Chlorine at C4

Bromine at C4

Electrostatic Mulliken Natural

0.265 0.289 0.261

0.297 0.299 0.264

0.280 0.328 0.262

0.263 0.306 0.262

Charge Type

Hydrogens

Fluorine at C5

Chlorine at C5

Bromine at C5

Electrostatic Mulliken Natural

0.265 0.289 0.261

0.288 0.290 0.262

0.263 0.296 0.262

0.252 0.289 0.260

two identical halogens increased the acidity of the hydrogen at C2 as the electronegativity of the halogen substituents increased. For the single halogen replacements on the ring, the halogens at C4 seemed to make the hydrogen at C2 slightly more acidic than the halogen replacements at C5.

This could have been due to the electron delocalization present in the ring.

For some of the results, hydrogen seemed to mimic the bromine in electron pulling power, which may be due to the similarity in electronegativity values: 2.2 for the former versus 2.96 for the latter.

The significance of Table 6 is that the methyl hydrogens on the ring (Diagram 7) were not as acidic as they were with the ortho and para halogen replacements on the benzene. Also, the hydrogens at 10 lost much more charge than was expected. This may be due to the slight electronegativity effects of carbon, or to the fact that there were no very electronegative substituents in proximity to the hydrogens at 10 .

Table 6. Thiazolium with all Hydrogens on Ring Replaced with Methyls (See Diagram 7) Charge

Methyl Hydrogen on Thiazolium

Methyl Hydrogen on Thiazolium

Methyl Hydrogen on Thiazolium

Hydrogen at 10

Hydrogen at 10

Electrostatic Mulliken Natural

0.263 0.200 0.253

0.265 0.221 0.259

0.245 0.218 0.244

0.155 0.208 0.246

0.159 0.195 0.247

As can be seen from Table 7 and also as a modification to Diagram 7, replacement of only hydrogen at C2 with a methyl group seemed to increase the acidity of the hydrogens at 10 slightly.

Also, the hydrogens on the replacement methyl seemed to be more acidic when only one carbon

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Table 7. Thiazolium with Hydrogen at C2 Replaced with Methyl (Diagram 7) Charge

Methyl H on Thiazolium

Methyl H on Thiazolium

Methyl H on Thiazolium

Hydrogen at 10

Hydrogen at 10

Electrostatic Mulliken Natural

0.280 0.224 0.265

0.257 0.213 0.248

0.282 0.204 0.254

0.204 0.223 0.245

0.202 0.207 0.247

was attached to the thiazolium ring. It seemed that the attached carbons were having somewhat of an electron withdrawing effect on the ring.

Figs. 4 - 6 indicate the effect on the three critical hydrogens when two identical halogens where added to the 20 position (Diagram 8). The data presented in Fig. 4 indicate that the charge of the hydrogen at C2 increased with increasing electronegativity, while the charges of both the hydrogens at 10 decreased.

Figure 4. Charge vs. electronegativity using Electrostatic

Figure 5. Charge vs. electronegativity using Mulliken

Figure 6. Charge vs. electronegativity using Natural Population Analysis

As can be seen in Fig. 5 and Diagram 8, the Mulliken charge showed that all three hydrogens increased in acidity when the electronegativity of the halogen substituents increased.

Based on the NPA charges in Fig. 6, all the hydrogens seemed to decrease in charge with increasing electronegativity, but the hydrogen at C2 still maintained a higher charge magnitude (see Diagram 8).

Discussion The initial part of this research emphasized the use of the principle of the inductive effect to make the hydrogens at 10 more acidic than the hydrogen at C2 of the ring. The principle states that

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a more electronegative atom or group can withdraw electrons to itself through sigma bonds [6]. As seen in Diagram 2, the hydrogen at C2 proved to be more acidic than the hydrogens at 10 , despite the fact that the hydrogens at 10 were closer to the carbonyl at 20 . The significance of Fig. 2 is that the hydrogen at C2 proved to be more acidic than the hydrogens at 10 , even though the hydrogens at 10 were vicinal to a stronger electron-withdrawing group. As seen in Diagram 3, adding a nitro group to the benzene ring in the para position gave the repeated trend.

The data in Fig. 3 illustrate that addition of a second electron-withdrawing group did not make the hydrogens at 10 more acidic than the hydrogen at C2. Addition of identical halogens to the ortho and para positions of the benzene ring (Diagram 4), showed that adding multiple electronwithdrawing groups to the benzene ring would not make the hydrogen at C2 less acidic than those at 10 . The significance of the data from Tables 1 - 3 indicate that electron-withdrawing groups can affect the acidity of the protons, but that the hydrogen at C2 cannot be made less acidic than the hydrogens at 10 . When X = fluorine, the acidities of the three hydrogens were about the same value (Table 3). When X = chlorine or bromine, the acidity of the hydrogen at C2 increased, even though fluorine is the more electronegative atom.

It was even more unusual to see the acidities of the hydrogens at 10 drop significantly when the heavier halogens were added. Seeing the results in Figs. 1 - 3, and also that the principle of electronegativity was being violated, it seemed plausible that this molecule was governed by the electronic parameters of thiazolium ring. The thiazolium ring seemed to be governed by different electrostatic properties than the R-Group. For example, the data from Figs. 1 - 3 revealed that the charge of the hydrogen at C2 seemed to remain constant when the electronegativity of the electron withdrawing group increased. On the other hand, the charge of the hydrogens at 10 seemed to change more dramatically when exposed to changing electronegativity. It was assumed that the positively charged nitrogen behaved as a barrier that protected the hydrogen at C2 from the intruding electronegative forces.

The second part of this research thus emphasized an investigation of the electronic properties of the thiazolium ring. Table 4 emphasized that the more electronegative atoms made the hydrogen at C2 more acidic than when there were only hydrogens attached to the carbon, but there were more unlikely results. When X = hydrogen, the hydrogen at C2 proved to be more acidic than when X was either bromine or chlorine (Diagram 5). Bromine and chlorine are much more acidic than hydrogen. This is counterintuitive to the fundamental laws of chemistry if understood from the perspective of the inductive law. The replacement of the R-group suggested that the thiazolium ring was governed by its own interior electron placement. If taken from the perspective of the electronic behavior of the thiazolium ring, the previous results seemed to coincide more with the laws of chemistry and physics. First, it was demonstrated that the positive charge on the thiazolium nitrogen does not serve as the electron sink to stabilize the negative formal charge on the carbon when the hydrogen at C2 is removed [7]. On the contrary, sulfur acts as the electron sink when it is a formally neutral atom. It was shown that upon deprotonation of the hydrogen at C2, the pi bonds of the thiazolium ring were polarized away from carbon 2 toward both the sulfur and nitrogen

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atoms of the ylide, while the nitrogen increased in charge by 0.0905 units [8]. An electron sink is a group that can pull electrons from another group and stabilize it. Because the hydrogen at C2 is attached to the carbon adjacent to sulfur, it seems that the carbanion will remain stable despite having a negative formal charge because sulfur reduces the negative charge load. Since the hydrogen at C2 is directly linked to an aromatic ring, it seems that the charge density of the ring is spread out so as to compensate for any loss of atoms.

Putting electron withdrawing groups directly onto the thiazolium ring (Diagram 6) gave a different perspective on how withdrawing groups affected the stable aromaticity of the thiazolium ring. By the term aromatic ring is meant that the ring is unusually stable. Table 5 revealed that putting halogens directly on the ring made HC1 more acidic than having them indirectly bonded as was seen in Table 4. When X1 and X2 were both fluorines, the hydrogen at C2 was the most acidic. When they were both chlorines, the hydrogen decreased in acidity. It was interesting to note that the acidity of the hydrogen stayed the same when X1 and X2 were both either hydrogens or bromines. When X2 was a halogen and X1 a hydrogen, the hydrogen at C2 maintained a slightly greater acidity than when X1 was a halogen and X2 a hydrogen. Adding halogens to C4 and C5 affected the electronic parameters more than the methyl attached previously to the nitrogen.

Aldrich, Alworth, and Clement et al. indeed demonstrated that the pi bonding for the ring is extensively delocalized, which means that the electrons are shared between more than two atoms.

Hence, the largest amount of pi localization is in the C4 and C5 portions of the ring, and that the N-CH-S fragment is a separate delocalized pi network [8]. It was also shown that addition of substituents on the thiazolium ring affects only the electronic parameters of the ring. Because the ring is aromatic, it is thus very stable [9].

When X1 and X2 were both halogens, there seemed to be maximum electron delocalization.

When there was only one halogen substitution, there was not as much electron delocalization.

Because of the slight difference in acidities with respect to the placement of the single halogen, it was discovered that the thiazolium ring has two different delocalized pi networks. Though the N-CH-S is a separate delocalized pi network, it donated electrons to the electron deprived C=C to stabilize the ring. The N-CH-S portion was thus electrostatically more positive, thus increasing the acidity of the hydrogen at C2. Adding an R-group to the positive nitrogen did not have the same effect because the electronegative forces were being applied to a positive charge that protected the aromaticity and stability of the ring. To affect the stability of the ring more effectively, it is necessary to place proper substituents where the electrons are found. The C4 halogen replacements from Table 5 were slightly more acidic than the C5 replacements because the former were closer to the hydrogen at C2. The replacements at C5 were not only farther from the hydrogen at C2, but also closer to sulfur, the electronic sink, which stabilized the ring by donating some of its electrons to the intruding force.

Tables 6 and 7 indicate that the methyl replacements on the carbons of the ring did not affect the electronic parameters of the ring like the halogens because carbon has a lower electronegativity than the halogens. As can be seen in Fig. 7, acidity seemed to be higher when only X3 was replaced

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with a methyl rather than when all the hydrogens directly bonded to the ring were replaced with methyls. The only case where the hydrogen at C2 had greater acidity over the hydrogens at 10 was replacement of the hydrogens bonded to the adjacent carbon with halogens (Diagram 8). More specifically, the hydrogen at C2 was less acidic than the hydrogens at 10 only when both X’s were fluorines. As indicated by Fig. 4, the charge of the hydrogen at C2 increased with increasing electronegativity. Though the hydrogens at 10 had a greater positive charge than the hydrogen at C2, their acidity decreased with increasing electronegativity until their charge intersected with that of the hydrogen at C2. According to the Mulliken charges, all three hydrogens started with the same acidity, but as the electronegativity increased, the hydrogen at C2 seemed to gain the most charge. For the NPA, all three hydrogens decreased in charge, but the hydrogen at C2 still maintained itself as most acidic.

Conclusion From these calculations, it is concluded that the hydrogen at C2 is almost always more acidic than the hydrogens at 10 possibly due to the resonance and electronic parameters of the thiazolium ring. The thiazolium ring is its own separate electron sink entity and has a positively charged nitrogen to guard against unwanted forces that are seeking to steal the electronic charge of the ring.

To affect the electronic parameters of the ring, it is necessary to place substituents on the carbon portion of the ring, but the ring has the electronic sink called sulfur to nullify the withdrawing of electrons. The two separate electron delocalization entities also stabilize the molecule because if one is affected, the other will contribute electrons to protect the stability of the ring. It seemed very plausible that the nitrogen behaved as an electronic barrier towards the substituents, because no matter the electronegative power of the substituents, the approximately same charge seemed to be placed on hydrogen at C2. Furthermore, the inductive effect had no significance in this study because both hydrogen at C2 and those at 10 were on separate regions of a molecule that were governed by different electronic parameterizations.

Acknowledgements The author would like to thank the Michael ’58 and Aimee Rusinko Kakos Endowed Chair to Joseph F. Capitani for financial support. He also thanks Professor J. F. Capitani for guidance and helpful discussions during this research. Helpful discussions with Mr. J. Mozdzierz, and Drs. J. Regan and C. E. Theodosiou are all gratefully acknowledged.

References [1] J. Mozdzierz, Private Communication.

[2] J. A. Zoltewicz and L. W. Deady, “Quaternization of heteroaromatic compounds. quantitative aspects.” Advances in Heterocyclic Chemistry 22, 71–121 (1978).

[3] L. E. Chirlian and M. Francl, “Atomic charges derived from electrostatic potentials: A detailed study.” Journal of Computational Chemistry 8, 894-905 (1987).

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[4] R. S. Mulliken, “Electronic population analysis on LCAO-MO molecular wave functions.” J. Chem. Phys. 23, 1833-1840 (1955).

[5] A. E. Reed, R. B. Weinstock, and F. Weinhold. “Natural population analysis.” J. Chem. Phys.

83, 735 (1985).

[6] E. V. Anslyn and D. A. Dougherty. Modern Physical Organic Chemistry. University Science Books. Sausalito, California. pp15-17 (2006).

[7] D. B. DuPr´e and J. L. Wong. “Topological analysis of the electron density in model azolium systems for thiamin structure.” J. Phys. Chem. 109, 7606-7612 (2005).

[8] H. S. Aldrich, W. A. Alworth, and N. R. Clement. “Electronic structures of azolium ions and their ylides.” J. Am. Chem. Soc. 100(8), 2362-2365 (1978).

[9] S. Belaidi, R. Mazri, H. Belaidi, T. Lanez, and D. Bouzidi. “Electronic structure and physicochemical property relationship for thiazole derivatives.” Asian Journal of Chemistry, 25, 9241-9245 (2013).

Quen nching off Ru(bpy))32+ Emisssion by B Binding tto Ag Naanoparticc

Quenching of Ru(bpy)3 2+ emission by binding to Ag nanoparticles Matth hew Felician no* Dep partment of Chemistry C an nd Biochemi istry, Manhaattan Collegee ∗

Matthew Feliciano Department of Chemistry Manhattan A Abstract. Silveer nanoparticle es (Ag-NPs) co oatedand withBiochemistry, citraate as a cappin ng agent College were synthesized. Itt was found thh

sstrongly quencch the fluoresccence of tris(2 2,2’-bipyridyl)rruthenium(II), Ru(bpy)32+, inn aqueous soluution. The Stee qquenching con nstant was meeasured under three differen nt conditions which yield cconsistent resuults with an a Abstract.6 Silver nanoparticles (Ag-NPs) coated with citrate as a capping agent were synthesized. It was found that f a new absorrption 2+ 99.28±0.18x10 M-1. There is a direct opticcal evidence o band located at 540-5580 nm indicaat 0 Ag-NPs strongly quench 2+ the fluorescence of tris(2,2 -bipyridyl)ruthenium(II), Ru(bpy)3 , in aqueous solution. The fformation of [R Ru(bpy) NP(citrate)] ag ggregates in different th he solutions viiawhich electrostatic c attraction tween the posi 3 -Ag Stern-Volmer quenching constant was measured under three conditions yield consistent results bet with 6 ccomplex and th heof negative cittrate capping a a directThese aevidence of a are beelocated responsible ffor static energg an average 9.28±0.18×10 M−1 . There isagent. optical aggregates new believed absorption to band at 540-580 2+ 2+ qquenching of the t ofexcited staate ofof[Ru(bpy) Ru(bpy) . The specctroscopic ations yield the maximum ratio, i.e., the n nm indicative the formation aggregates intitra the solutions via electrostatic attraction 3 )3-AgNP(citrate)] 2+ between the positive metal complex and the negative citrate capping agent.

These aggregates are believed to be R Ru(bpy) vs. the t number of Ag-NPs, in th he aggregate to be around 400 0:1.

3 responsible for static energy transfer quenching of the excited state of Ru(bpy)3 2+ . The spectroscopic titrations yield the maximum ratio, i.e., the number of Ru(bpy)3 2+ vs. the number of Ag-NPs, in the aggregate to be around 400:1.

Introduction n

Introduction 2+ ItItisisknow wn that (2,2’-bipyrid dyl)ruthenium m(II),Ru(bpy) Ru(bppy) esses strong g absorption// 0 2+3 , posse known thattris( tris(2,2 -bipyridyl)ruthenium(II), , possesses strong absorp3 pproperties in n UV/visible and d region, its photo-in excitted state is astate potent oxiddizing/reduci i tion/emission properties inregion, UV/visible and nduced its photo-induced excited is a potent oxw which has th he potential of o splitting wpotential to prod duce fuelwater hyddrogen gas. fuel Many studieesgas. have beenn idizing/reducing agent which has the water of splitting to produce hydrogen oon utilizing it i in energy conversion c systems s and as photosen sors.

Many studies have been focused on utilizing it in energy conversion systems and as photosensors.

On the other hand, the nanoparticles of metals and semimetals have attracted more and more attention novelthe properties such as of theirmetals Plasmon resonance absorption On thedueother o to their hand, nanopaarticles msize, surface and semimetals have attrac cted more a and largerdue surface area to volume ratio. catalystsPla inasmon energyreson conversion aattention e to their no ovel propert tiesThey suchareasswildly their used size,assurface nance absorpp cycles, biosensors in medical field as well in many other areas. llarger surfacce area to volume v ratio o. They are wildly usedd as catalyssts in energyy conversionn

Recentin havefie found noble metals such as gold, silver and platbbiosensors nstudies medical eld asthat wellthein nnanoparticles many otherr of areas. inum can greatly affect the emissive properties of Ru(II) diimmine compounds by enhancing Recent sttudies have found that the t nanopartticles of nobble metals su ucheither as gold, , silver and or quenching the emission depending on the size, shape of the nanoparticles and the distance of enhaa ccan greatly affect the emissive e prroperties of Ru(II) diim mmine comppounds by either fluorophoresthe the nanoparticles [1,2]. qquenching t fromemission n depending g on the size, shape of the nannoparticles aand the diss This study investigates the effect of[1,2]. silver nanoparticles (Ag-NPs) on the emission properties ffluorophores s from the naanoparticles 2+ of This Ru(bpy) solution. areeffe interested in finding out whether the Ag-NPs canthe quench the prop stud investiga atesWethe ct of silver nanoparticl les (Ag-NPs s) on em mission p 3 dy in 2+ ∗ R Ru(bpy) nmentored solution.by We WJianwei are intere ding out wheether the Ag--NPs can quuench the em m 3 in Research Fan,ested Ph.D.in find 2+ R Ru(bpy)3 and a the role the capping g agents play y. Since thee capping aggent used too stabilize A nnegatively ch harged citraate some deg gree of interraction betw ween the Agg-NPs and caationic Ru(bb

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emission of Ru(bpy)3 2+ and the role the capping agents play. Since the capping agent used to stabilize Ag-NPs is negatively charged citrate some degree of interaction between the Ag-NPs and cationic Ru(bpy)3 2+ is expected. Indeed, UV-visible absorption spectroscopy confirmed an association between the Ag-NPs and the ground state of Ru(bpy)3 2+ . Steady-state fluorescence spectroscopy also demonstrated the strong quenching effect of Ag-NPs on the excited state of Ru(bpy)3 2+ .

Materials and Methods Materials. 2,2 -bipyridal (Aldrich), cis-bis(2,20 -bipyridine)dichlororuthenium(II) hydrate (Aldrich), silver nitrate (Fisher), sodium borohydride (Strem), trisodium citrate (Fisher) and polyethylene glycol (Alfa Aesar) were used as received. All solutions were prepared with distilled, deionized water.

0

Syntheses. Ru(bpy)3 Cl2 . 2H2 O was synthesized from cis-(bpy)2 RuCl2 and 2,20 -bipyridal in 1:1.2 ratio according to the literature method. Silver nanoparticles with citrate capping agent were synthesized by reducing silver nitrate with sodium borohydride in the presence of trisodium citrate as follows [3]. A solution composed of 10 mL of 0.50 mM sodium citrate and 10 mL of 0.50 mM AgNO3 was stirred for 30 seconds, and 1.2 mL of 10 mM NaBH4 prepared in de-areted water was added. The solution was stirred for another 30 seconds, and was allowed to sit for 30 minutes before use.

Physical Measurements. A series of mixture solutions were prepared in the following way: 2 mL of Ru(bpy)3 2+ (8×10−5 M) was mixed with different volumes (0.5 − 2.5 mL) of Ag-NPs (1.2×10−7 M) in a volumetric flask, and then diluted to a total of 5.0 mL with distilled water, respectively. The UV/visible spectra (200-800 nm) of Ag-NP, Ru(bpy)3 2+ and the mixture solutions were recorded on Agilent 8453 UV/visible photodiode array spectrophotometer. The emission spectra (500-800 nm) of all solutions were taken on Photon Technology International (PTI) spectrofluorometer with the excitation wavelengths set at 286 nm and 452 nm, respectively.

Results Calculation of the molar concentration of Ag-NP solution. The molar concentration of the nanoparticles was calculated by the initial concentration of AgNO3 dividing the average number of atoms per nanoparticle. Assuming each nanoparticle is spherical in shape, the number of atoms per nanoparticle (N) is calculated from the equation [4] N = (πρd3 /6M )NA

(1)

where d is the diameter of the nanoparticle, ρ is the density of silver metal (10.49 g/cm3 ), M is the molar mass (107.87 g/mole) and NA is Avogadro’s number. The size of the nanoparticle is obtained from its visible spectrum. Since the maximum wavelength is 392 nm, the diameter of the nanoparticle is taken as 10 nm [5]. The molar concentration of the stock solution of Ag-NP is thus calculated to be 8.16 × 10−9 M.

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1.5

Absorbance

at 392nm  at 450nm

1.0

at 286nm

0.5

0.0 0.E+00

2.Eâ&#x20AC;?08

4.Eâ&#x20AC;?08

[Agâ&#x20AC;?NP]Â (M) Figure 1. UV/visible absorption spectra of Ru(bpy)2 3+ (black, B) and Ag-NPs (red, A)

Figure 2. Calibration curves for Ag-NP (citrate) solution

Determination of the extinction coefficients of Ag-NP in aqueous solution. The Plasmon absorption band of Ag-NPs (392 nm) has some overlap with MLCT band of Ru(bpy)2 3+ (452 nm) (Fig. 1). However, at L-L* band of Ru(bpy)2 3+ (286 nm), Ag-NP has the least absorption. Considering the inner filter effect, i.e., the competition of photons by Ag-NPs at the excitation wavelengths of Ru(bpy)2 3+ , the molar extinction coefficients of Ag-NPs at 286 nm, 392 nm and 452 nm were determined. A series of standard solutions (8.16 Ă&#x2014; 10â&#x2C6;&#x2019;9 M to 3.26 Ă&#x2014; 10â&#x2C6;&#x2019;9 M) were prepared from the stock solution of the Ag-NP by series dilution. The UV/visible absorption spectra of these solutions were recorded, and the calibration curves (absorbance vs. concentration) were plotted (Fig. 2). The molar extinction coefficients were determined from the slopes of curves (Table 1).

Table 1. Molar extinction coefficients ( ) of Ag-NP(citrate) and Ru(bpy)3 2+ in aqueous solution. Îť (nm) â&#x2C6;&#x2019;1

â&#x2C6;&#x2019;1

(M cm ) of Ag-NP (Mâ&#x2C6;&#x2019;1 cmâ&#x2C6;&#x2019;1 ) of Ru(bpy)3 2+

286

392 7

5.16 Âą 0.34 Ă&#x2014; 10 8.70Ă&#x2014;104

3.60Âą0.20 Ă&#x2014; 10

452 8

1.02 Âą 0.33 Ă&#x2014; 108 1.26Ă&#x2014;104

Stern-Volmer quenching constant. A series of mixture solutions with fixed Ru(bpy)3 2+ concentration (8.0 Ă&#x2014; 10â&#x2C6;&#x2019;5 M) and variable Ag-NP concentrations (1.2 Ă&#x2014; 10â&#x2C6;&#x2019;8 M to 6.0 Ă&#x2014; 10â&#x2C6;&#x2019;8 M) were prepared for emission quenching measurement. The Stern-Volmer constant was measured under three different conditions. First, the excitation wavelength of light for Ru(bpy)3 2+ was set at 286 nm since at which the co-absorption by Ag-NPs is minimum (Fig. 1). The emission intensity *Research mentored by Jianwei Fan, Ph.D. of Ru(bpy)3 2+ at 610 nm decreases as the concentration of Ag-NPs added increases (Fig. 3). The emission intensities were fitted with Stern-Volmer equation I0 /Iem = 1 + KSV [Q]

(2)

The Manhattan Scientist, Series3.B,Em Volume 2 (2015) Feliciano F Figure mission Specctra of Ru(bp py)32+ with in ncreasing coon

114

I0/I

1.8 8 1.6 6 1.4 4 1.2 2 1.0 0 0.8 8 0.6 6 0.4 4 0.2 2 0.0 0 0.E+00

Ksv = 9.46 9 106

2.E‐08

‐1

4.E‐08

[Ag‐‐NP] M Figure 3. Ru(bpy)3 2+ emission spectra with increasing concentration of Ag-NPs (λex = 286 nm)

Figure 4. Stern-Volmer plot corresponding to Fig. 3

F Figure 4. ern-Volmer plot p correspo onding to Fig gure 3 (ex = (λexSte = 286 nm)

where I0 and Iem are the emission intensities of Ru(bpy)3 2+ in the absence and presence of Ag-NPs, respectively, and [Q] is the concentration of Ag-NPs. The Stern-Volmer constant, KSV , obtained from the slope of curve is 9.46 × 106 M (Fig. 4).

The emission spectra of these solutions were also measured with the excitation light of 451 nm which corresponds to MLCT band of Ru(bpy)3 2+ (Fig. 5). It can be seen that as the concentration of Ag-NPs increases the emission intensity of Ru(bpy)3 2+ decreases in a larger degree compared with those measured with the excitation at 286 nm. Since Ag-NPs have co-absorption at 451 nm of light which could cause the apparent diminishing of the emission intensity of Ru(bpy)3 2+ (the inner filter effect), a correction factor should be used in order to get the true Stern-Volmer constant.

The Stern-Volmer constants obtained under the three different conditions described are quite consistent with each other (Table 2).

Table 2. Summary of Stern-Volmer constants measured under three different conditions. λex = 286 nm KSV (M−1 ) Average KSV (M−1 )

9.46 × 106 9.28 ± 0.18 × 106

λex = 452 nm, after correction for inner filter effect

λex = 452 nm, with very low concentration of Ag-NP

9.30 × 106

9.10 × 106

Spectroscopic titration. The UV/visible spectrum of the mixture solution showed a new peak at 540 nm after the addition of Ag-NP to Ru(bpy)2 3+ . To monitor the growth of this new peak, variable volumes of Ag-NP (1.2×10−7 M) in 100 microliter interval was added to 2 mL of Ru(bpy)2 3+ (8×10−5 M) placed in a cuvet, and the absorption spectrum of the solution was recorded after each addition until very little spectral change at 540 nm was observed (Fig. 5). The spectral titration was

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Figure 5. Overlay of UV/vis absorption spectra of the mixed solutions recorded after each addition of 1.2 × 10−7 M Ag-NP (100 microliter interval, 3 mL total) to 2 mL 8.0 × 10−5 M Ru(bpy)3 2+ in a cuvet

also performed in an opposite direction, i.e., variable volumes of Ru(bpy)2 3+ (8 × 10−5 M) were added in 100 microliter interval to 2 ml of Ag-NP (1.2 × 10−7 M) placed in a cuvet. The UV/vis absorption spectrum of the mixture solution was recorded after each addition. The absorbance at 540 nm was plotted against the ratio of two concentrations, i.e., [Ru(bpy)3 2+ ]/[Ag-NP] (Fig. 6), which yields the maximum ratio of the two in the aggregate to be 400:1.

0.6

Absorbance(540 nm)

0.5 0.4 0.3 0.2 0.1 0 0

100

200 300 400 [Ru(bpy)32+]/[Ag‐Np]

500

600

Figure titration 6. Spectroscopic titration showing the increasing absorbance 540 nm as the increasing Figure 6. Spectroscopic curve showing thecurve increasing absorbance at 540 nm as theat increasing molar concen2+ tration ratio of [Ru(bpy) ]/[Ag-NP].ratio of [Ru(bpy)32+]/[Ag-NP]. molar3concentration

Discussions

Discussion The quenching of emission of Ru(bpy) 2+ by Ag-NPs was observed and quantified by Stern-Volmer 3

2+ constant.

Stern-Volmer by was Ag-NPs was measured with the excitation The quenchingquenching of emission of The Ru(bpy) byconstant Ag-NPs observed and quantified

by Stern3 wavelength set at either 286 nm or 451 nm. Although the excitation wavelength of 451 nm produces the 2+ Volmer quenching emissive constant.

The Stern-Volmer constant by Ag-NPs was measured with excited state of Ru(bpy)3 (MLCT) directly, a major concern is the co-absorption of the this exAg-NPs (Figure The451 emission measured withexcitation ex = 451 nm in the presence of citation wavelengthwavelength set at by either 286 nm1).or nm.intensities Although the wavelength Ag-NPs decrease much faster than those measured with 2+ ex = 286 nm under the same condition. This 451 nm produces of the emissive excited state of Ru(bpy) (MLCT) directly, a major concern is indicative of the co-absorption of 451 nm light by 3Ag-NP which causes the apparent diminishing of 2+ is the co-absorption this wavelength

by Ag-NPs (Fig. 1). Before The correcting emissiontheintensities measured (inner filter effect). inner filter effect the theof emission intensity of Ru(bpy) 3 7 -1 Stern-Volmer constant obtained with  = 451 nm was 3.1±0.9x10 M .

After the correction it ex with λex = 451 nm in the presence of Ag-NPs decrease much faster than those measured iswith 6 -1 6 -1

9.30x10 M which is consistent with the value obtained with ex = 286 nm (9.46x10 M ).

The quenching mechanism is likely to be static by forming the aggregates between the positive Ru(bpy)32+ and the negative citrate layer on the surface of Ag-NPs via the electrostatic attraction. The

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λex = 286 nm under the same condition. This is indicative of the co-absorption of 451 nm light by Ag-NP which causes the apparent diminishing of the emission intensity of Ru(bpy)3 2+ (inner filter effect). Before correcting the inner filter effect the Stern-Volmer constant obtained with λex = 451 nm was 3.1 ± 0.9 × 107 M−1 . After the correction it is 9.30 × 106 M−1 which is consistent with the value obtained with λex = 286 nm (9.46 × 106 M−1 ).

The quenching mechanism is likely to be static by forming the aggregates between the positive Ru(bpy)3 2+ and the negative citrate layer on the surface of Ag-NPs via the electrostatic attraction.

The optical evidence is the formation of a new peak at 540 nm after the Ag-NP is added to the Ru(bpy)3 2+ . The other spectral evidence is the observation of at least two isosbestic points located at 340 nm and 470 nm indicative of a dynamic equilibrium system with multiple converting components. Since the absorption bands of the aggregates overlap with the emission profile of Ru(bpy)3 2+ , they provide an effective static quenching pathway to the excited state of Ru(bpy)3 2+ via energy transfer mechanism.

From two independent titration curves, i.e., titration of a fixed volume of Ru(bpy)2 3+ with Ag-NPs or titration of a fixed volume of Ag-NP with Ru(bpy)2 3+ , we got the same result on the maximum number of Ru(bpy)2 3+ ions (about 400) surrounding each Ag-NP in aggregates.

Assuming the shape of Ag-NP is spherical, its surface area is 4πr2 , where r is the radius of the nanoparticle (5 nm). Assuming Ru(bpy)3 2+ ion is spherical, its projected area on the surface of nanoparticle is πr2 , where r is the radius of Ru(bpy)3 2+ (0.54 nm). The number of Ru(bpy)3 2+ surrounding each nanoparticle is calculated to be 343.

Conclusion Our experiment demonstrated the strong quenching effect of Ag-NP coated with citrate on the emission of Ru(bpy)2 3+ . The quenching mechanism is thought to be static energy transfer due to the formation of aggregates of Ag-NPs and Ru(bpy)2 3+ by electrostatic attraction.

Acknowledgements The author would like to thank Dr. Harry D. Gafney of Queens College, CUNY, for the collaboration on the study.

References Huang, T.; Murray, R. W. Langmuir (2002), 18, 7077-7081.

Jagassar, P. S.; Perri, A.; Ibarrola, G.; Gafney, H. G. J. Phys. Chem. C (2013), 117, 1925-1934.

Jana, N. R.; Gearheart, L. and Murphy C. J., Chem. Commun. (2001), 617-618.

Liu X., Atwater M., Wang J. and Huo Q. Colloids and Surfaces B: Biointerfaces (2007), 58, 3-7 [5] Paramelle D., Sadovoy A. Gorelik S., Free P. Hobley J. and Fernig D. G. Analyst (2014), 139, 4855-4861

[1] [2] [3] [4]

Luminescence response of ruthenium(II) diammine complexes to polyanionic carrageenans and heparins Matthew Felicianoâ&#x2C6;&#x2014; and Marisa Krogerâ&#x2C6;&#x2014; Department of Chemistry and Biochemistry, Manhattan College

Abstract. In this study the luminescent properties of ruthenium(II) diammine complexes, tris(2,20 -bypiridine)ruthenium (II), Ru(bpy)3 2+ , and tris(1,10-phenanthroline)ruthenium(II), Ru(phen)3 2+ , were tested with two polyanions of carrageenan and heparin. Luminescence measurements were taken on the mixture solutions of the ruthenium(II) complexes and the polyanions in order to find out if the polyanions will change the emission intensities of the metal compounds. The results show that both enhancement and quenching of the emission by the polyanions occur, depending on the nature of the ruthenium compounds and the polyanions. The results also show that the emission intensity of Ru(phen)3 2+ is more sensitive to polyanions than Ru(bpy)3 2+ , and is a better sensor for the concentration of the polyanions.

Introduction Carrageenan and heparin are macromolecular polyanions which have important applications in food industry or physiology. Carrageenan is a natural food ingredient widely used for their gelling, thickening, and stabilizing properties. Heparin is an anticoagulant that is injected into a patient to thin the blood. Recent studies at St. Johns University found that these polyanions can enhance the luminescence intensity of the positively charged Osmium(II)-phen complexes in ethanol and aqueous solutions [1]. This unique character of the Os(II) complex makes it a useful tool for the detection of these polyanions in commercial products.

We are interested in the investigation of the luminescence response of ruthenium(II) compounds to the polyanions for the following reasons: First, the elements ruthenium and osmium belong to the same group in the Periodic Table and share many similar chemical properties such as high luminescence of their compounds. Second, since ruthenium compounds are less expensive than osmium ones, it would be economically advantageous if we could develop a rutheniumbased sensor to detect the concentration of polyanions. The ruthenium complexes we studied are Ru(bpy)3 2+ and Ru(phen)3 2+ since both are highly emissive. The polyanions used are lcarrageenan and heparin sodium or lithium salts. Furthermore, in order to prove that the interaction between the ruthenium(II) complex ions and polyanions is electrostatic attraction, the luminescence property of a neutral ruthenium compound, cis-dicyanobis(2,20 bipyridine) ruthenium(II), Ru(bpy)2 (CN)2 , is tested with these polyanions. â&#x2C6;&#x2014;

Research mentored by Jianwei Fan, Ph.D.

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Figure 1. Column chromatography using sephadex as the stationary phase and methanol as the eluent.

Experimental Synthesis of Ru(phen)3 Cl2 Ru(bpy)3 Cl2 and Ru(bpy)2 (CN)2 were made by previous research students in this lab.

Ru(phen)3 Cl2 was synthesized based on the published method [2] with slight mortification.

RuCl3 . 3H 2 O (1 mmol) was mixed with (4 mmol) of 1,10-phenanthroline in 50 mL of ethylene glycol. This mixture was refluxed under a nitrogen atmosphere for four hours. Next the mixture was cooled to room temperature and vacuum filtrated. A saturated solution of KCl was added so that it would precipitate as a chloride salt.

Purification The crude product was purified by column chromatography as shown in Fig. 1. Sephadex was used as the stationary phase and methanol was used at the eluent in the column.

Characterization The purified product, Ru(phen)3 Cl2 , was characterized by comparing its spectra of UV/visible (HP 8453 spectrophotometer), emission (PTI spectrofluorometer), FTIR (Nicolet FITR instrument) and NMR (Anasazi) with published spectra. All spectral data are consistent with the literature values. Fig. 2 is the NMR spectra of Ru(phen)3 Cl2 that was synthesized in comparison with its literature NMR spectra [3].

Emission measurements 2 mL of ruthenium compound (2 Ă&#x2014; 10â&#x2C6;&#x2019;5 M) was placed into a cuvette, and either five or ten microliter increment of a polyanion solution (1mg/mL) was added to the cuvette. UV/visible and fluorescence measurements were taken after the mixing. This same process of added equal amounts of polyanion was repeated until no more change in the emission spectrum was observed.

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Figure 2. NMR spectra of Ru(phen)3 Cl2 : synthesized (left) and from Ref. 3 (right)

Results Enhancement of luminescence of Ru(bpy)3 2+ by carrageenan As the concentration of carrageenan increases, the emission intensity of Ru(bpy)3 2+ in aqueous solution increases, as shown in Fig. 3. The plot of the luminescence enhancement ratio F/F0 of Ru(bpy)3 2+ vs. concentration of l-carrageenan is shown in Fig. 4. F is the emission intensity without carrageenan, and F0 is the emission intensity in the presence of carrageenan.

Quenching of luminescence of Ru(phen)3 2+ by carrageenan It was found that both l-carrageenan and heparin quench the luminescence of Ru(phen)3 2+ .

Fig. 5 is the luminescence quenching ratio (F/F0 ) of Ru(phen)3 2+ in aqueous solution vs. the concentration of l-carrageenan.

Figure 3. The emission spectra of Ru(bpy)3 2+ in aqueous solution in the presence of different concentration of lcarrageenan. Black line, pure Ru(bpy)3 2+ ; magenta, 10 µL l-carrageenan added; blue, 20 µL l-carrageenan added; red, 30 µL l-carrageenan added;

23.80952 32.71028

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1.6

F/F0

1.4 1.2 1.0 0.8

0

5

10

15

Concentration (μg/mL)

20

25

Figure 4. Luminescence enhancement ratio F/F0 of Ru(bpy)3 2+ vs. concentration of l-carrageenan.

1.1 1.0

F/F0

0.9 0.8 0.7 0.6 0.5

0

5

10

15

Concentration (μg/ml)

20

25

Figure 5. Luminescence quenching ratio F/F0 of Ru(phen)3 2+ in aqueous solution vs. concentration of l-carrageenan.

Neither quenching nor enhancing of luminescence of Ru(bpy)2 (CN)2 by all polyanions Cis-dicyanobis(2,2’bipyridine)ruthenium(II) is a neutral compound. It was found that heparinlithium salt neither enhances nor quenches the luminescence of Ru(bpy)2 (CN)2 . Fig. 6 is the ratio (F/F0 ) of Ru(bpy)2 (CN)2 in aqueous solution vs. concentration of Heparin-Lithium.

The results of all of the combinations of ruthenium compounds with polyanions made in this experiment are summarized in Table 1. Here, E represents enhancement, while Q represents quenching. The numbers within the parentheses indicate the slope of the line when plotting F/F0 vs. concentration of polyanions for each combination.

Table 1. Summary of the effect of polyanions on the luminescence of Ru compounds

2+

Ru(bpy)3 Ru(Phen)3 2+ Ru(bpy)2 (CN)2

λ-carrageenan

l-carrageenan

Heparin(Na)

Heparin(Li)

E (+0.0097) Q (-0.0300) No effect

E (+0.0074) Q (-0.0319) No effect

Q (-0.0213) Q (-0.0461) No effect

Q (-0.0146) Q (-0.0400) No effect

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F/F0

1.1

1.0

0.9

y = 0.0007x + 1 R² = 0.6588 0

10

20

30

Concentration (Îźg/mL)

40

Figure 6. The ratio F/F0 of Ru(bpy)2 (CN)2 in aqueous solution vs. the concentration of heparin-lithium salt.

Discussion Throughout the experiments, we observed three types of interaction: enhancement, quenching or no effect on the luminescence of ruthenium(II) compounds by the polyanions.

For Ru(bpy)3 2+ the enhancement by carrageenan is observed. This may be due to the fact that the long chains of polyanions with anionic sites on its branches closely surround the positive center of ruthenium complexes by electrostatic force. This shields the solvent molecules from approaching and reduces the collision quenching to the excited state of the complex by the solvent molecules.

For Ru(phen)3 2+ the quenching by carrageenan happens. It is likely that the bulky size of Ru(phen)3 2+ hinders its close contact with polyanions. As a result the polyanions act as a dynamic quencher by collision to the excited state complex.

The neutral Ru(bpy)2 (CN)2 shows neither enhancement or quenching by all polyanions tested.

This is consistent with what we expected since there is no interaction between a neutral molecule and negatively charged polyanions.

The results also show that Ru(phen)3 2+ is more sensitive than Ru(bpy)3 2+ in luminescent response to the concentration of polyanions. This is because that phen is a more rigid ligand than bpy ligand, and the rigidity of the complex favors luminescence decay.

Conclusion The emission properties of the ruthenium compounds tested in this study were affected by polyanions of heparin and carrageenan. Either enhancement or quenching could occur when mixing a ruthenium complex with these polyanions. It depends on the nature of the complexes and the polyanions.

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Acknowledgements The authors thank Dr. Enju Wang at St. Johnâ&#x20AC;&#x2122;s University for the research collaboration, and the Manhattan College School of Science Research Scholars Program for generous support.

References [1] Wu, H.; Wu, J.; Saez, C.; Campana, M.; Megehee, E. G. and Wang, E., Analytica Chimica Acta (2013), 804, 221 [2] Bhuiyan, A. A.; Kudo, S., and Bartlett, J., Journal of Arkansas Academy of Science (2010), 64, 33 [3] Baggott, J. E.; Gregory, G.K.; Pilling, M.J., etc., J. Chem. Soc., Faraday Trans. 2 (1983), 79, 195

Crystal Structure Refinement of ZSM-18 Corine LaPlancheâ&#x2C6;&#x2014; Department of Chemical Engineering, Manhattan College Abstract. Different models for the structure of ZSM-18 have been suggested. A published idealized model needs to be confirmed by an X-ray structure determination. Preliminary refinement of synchrotron x-ray data of as-synthesized ZSM-18 was not successful until the symmetry (P63 /m) of the published model was reduced to P-3. To complete the refinement of the structure of ZSM-18, the trisquat organic templating molecule used in the synthesis must be included in the refinement. Analysis of the electron density in the large cage of ZSM-18 revealed the trisquat was disordered.

To include trisquat in the refinement the lowest energy configuration of trisquat within the large cavity of ZSM-18 was determined by a DFT calculation in Spartan. Procedures to convert Spartanâ&#x20AC;&#x2122;s Cartesian atomic coordinates to crystallographic (fractional) coordinates were developed. Bond distance and angle restraints are needed to allow the trisquat to be refined.

Introduction ZSM-18 is an interesting zeolite synthesized in the research laboratory of Mobil. The name ZSM represents Zeolite SOCONY Mobil, which is a combination of former names of the energy company now known as Exxon-Mobil. The number 18 probably stands for one of many synthesis reactions carried out in the labs of this company. The goal was to make improved catalysts for use in petroleum refining and petrochemical processing. Zeolites are known as minerals with large cavities and pores. Zeolites are used for ion exchange, catalysis, air purifying, molecular sieving, and drying agent. ZSM-18 is unusual in that its published framework topology has a large number of odd-membered rings, including the first example of a 3-ring [1].

The published topology was determined only by model building, and has never been confirmed by an X-ray structure determination. Variations on this model have been suggested [2]. Also, the model contains an unusually long bond along the c axis of the ZSM-18 [3]. The model presumes a high symmetry space group P63 /m.symmetry while others suggest other symmetry.

Experimental Methods ZSM-18 was first synthesized by Ciric using a trisquaternaryammoniun (trisquat) ion template [1]. Sodium aluminate was dissolved in water, then 1.16 N trisquat template and methyl silicate, (CH3 O)4 Si, were added at high temperature. Upon mixing, an aluminosilicate gel was formed which crystallized around the template (a structure directing agent) to produce an aluminosilicate mineral with large pores and big cavities that are characteristic properties of zeolites.

A Merck Molecular Force field in Spartan (2006) [4] was used to calculate to idealize the trisquat position within the large cavity of ZSM-18. Spartan uses Cartesian Coordinates for modeling. These were converted into crystallographic (fractional) calculations using the program BMâ&#x2C6;&#x2014;

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FIT. The results were checked in the graphics program “Atoms” [5]. Using synchrotron data collected by J. M. Bennett the Shelex program [6] was used to refine all atom coordinates. Bond and distance restraints were applied to the idealized trisquat.

Results Using the published model as a starting point, the refinement using Shelex was only successful after reducing the symmetry from P63 /m to P-3. The structure of as-synthesized ZSM-18 consists of the framework and the trisquat. The 3-D framework has cavities with pores as shown in Fig. 1. The framework contains three-, four-, five-, seven- and twelve-membered rings, some are illustrated in Figs. 2 and 3. At this stage of the refinement, a difference Fourier calculation (comparing calculated to experimental electron density maps) revealed two positions for the central nitrogen atom of the trisquat, also shown in Fig. 1. This indicates that trisquat within the cavity is disordered. Trisquat, N [CH2 CH2 N (CH3 )3 ]3 3+ , contains a neutral pyramidal central nitrogen with a lone pair. The trisquat fits in the cavity in two equally probable ways, with the lone pair either pointing up or down along the z axis. The two trisquat orientations are related by a mirror plane. In space group P-3 the three trisquat arms are also symmetrically related to each another.

Each arm (in either disorder model) points into a cavity (pore) formed by a 7-ring. The +1 charge on the outermost N atoms is attracted to the negative lone electron pairs on oxygen atoms in the framework.

Future Work The refinement of the ZSM-18 structure is not yet complete. The disorder model for trisquat needs improvement. The locations of sodium and aluminum ions that were part of the synthesis still need to be determined.

Acknowledgement Thanks to Anthony DiProperzio for assistance in Spartan calculations

References [1] Ciric, Julius et al. “Synthesis And Crystal Structure of 2,3,4,5,6,7,8,9-Octahydro2,2,5,5, 8,8-Hexamethyl-1H-Benzo[1,2-c:3,4-c’:5,6-c’]-Tripyrrolium Tribromide Dihydrate, C18H30N33.3 Br-.2H2O.” J. Am. Chem. Soc. 100.7, 2173–2175 (1978).

[2] J. M. Bennett, private communication.

[3] Lawton, S. L., and W. J. Rohrbaugh. “The Framework Topology of ZSM-18, a Novel Zeolite Containing Rings of Three (Si, Al)-O Species.” Science 247, 1319–1322 (1990).

[4] SpartanWavefunction.Inc., Irvine CA. (2006).

[5] “Atoms” by Shape Software (2011).

[6] “Shelex,” Sheldrick, G.M., Acta Cryst. A64,112-122 (2008).

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Figure 1. Side view of the framework along the c axis showing small cavities in the outer surface and bigger cavities inside. The blue atoms in the center of the large cavities are the two possible positions for the central nitrogen atom of the disordered trisquat.

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Figure 2. This picture represents some rings that are present in the framework. Shown from left to right are twelveand seven- membered rings with their -Si-O-Si-O-. . . bond linkage.

Figure 3. This picture shows the framework of ZSM-18 with the trisquat in the middle of the large cavity. Present are N (in blue), C (yellow), H (gray), Si (purple), and O (red). For clarity the H atoms on the arms of trisquat are not shown.

Strategies for the remediation of toxic groundwater containing hexavalent chromium: insoluble 5,6-O-(substituted methylidene)-L-ascorbic acid Paul Markajâ&#x2C6;&#x2014; Department of Chemistry and Biochemistry, Manhattan College Abstract. Chromium metal has several oxidation states, the most common of which are the hexavalent state and the trivalent state [1]. Hexavalent chromium, more commonly referred to as chromium VI, is used in a variety of industries and can be found in the waste as well. Short term exposure to chromium VI has been known to cause ulcers and prolonged exposure can cause liver and nerve damage and also death [2]. Trivalent chromium is not as mobile and forms chromium (III) oxides that are insoluble in neutral pH. Ascorbic acid can reduce chromium VI to chromium III, but its solubility makes it impossible to remove ascorbic acid and perhaps recycle it. By altering ascorbic acids structure at the C5 and C6 carbons, the hydrophobicity of the molecule can be increased allowing for easy removal and recycling. The benzophenone analog created proved successful at removing the chromium VI from a concentrated solution, but difficulties arose in the recycling phase of the project.

Introduction Chromium is a transition metal that has a variety of chemical properties such as hardness, brittleness, shine and silvery in color, and has multiple oxidation states giving it numerous uses in industry [3]. It has been used in industry to create dyes, and it is one of the minerals responsible for the green color in emeralds and the red color in rubies [3]. It is also used to make yellow and orange dyes as well. The signature luster of chromium is the same brilliant shine found in stainless steel. Chromium is used to make the steel shine and prevent corrosion and rusting. These same attributes are what attracted the use of chromium to the process of electroplating. Utilizing electrical current to create indestructible bonds with chromium and the surface of the original metal, gave the metal an aesthetic shine and prevented damage as well [3]. Chromium has been used to line furnaces due to its hardness, its chemical inactivity, and its heat stability. Chromium is also used in the tanning leather industry as well. Potassium dichromate, K2 Cr2 O7 , has been used in many different photochemical processes such as photography and photoengraving. It is also used in the production of waterproof glues [3]. Other forms of chromium used in the industry are fungicides, wood preservatives, catalysis production, and glass production. Although chromium is used in a vast amount of process, about 60 to 70% of chromium ore are used in alloy production such as stainless steel [3]. Shown below is a table of different industries and industrial processes that use chromium.

All of the process that have been mentioned create some sort of waste material comprised of chromium VI material [3]. Chromium VI is most commonly found in either the chromate ion â&#x2C6;&#x2014;

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Table 1. Industries and Industrial Process That Use Chromium Antifouling pigments Antiknock compounds Alloy manufacturing Catalysts Ceramics Corrosion inhibitors Drilling muds Electroplating Electronics Emulsion hardeners Flexible printing Fungicides Gas absorbers Hardening steel

High Temperature batteries Magnetic Tape Metal finishing Metal Primers Mordants Phosphate coatings Photosensitization Pyrotechnics Refractories Tanning Textile preservatives Textile printing and dyeing Wash primers Wood preservatives

Source: Ref. 3, p. 16

(CrO4 2â&#x2C6;&#x2019; ) or the dichromate ion (Cr2 O7 2â&#x2C6;&#x2019; ) [3]. Often waste management is poor and chromium VI invades the environment and the people in the vicinity. Chromium VI is more mobile than chromium III and it is difficult to remove from water, it is also incredibly more toxic [1]. Chromium VI has been classified as a Group 1 (carcinogenic to Humans) by the IARC [4]. and can even enter the cell and oxidize genetic material. Short term exposure to maximum levels of contamination can cause stomach irritation and ulcers, while long term exposure can lead to dermitis damage to the liver, kidney, nerve tissue, and can cause death. Chromium III does not exhibit the same toxicity.

It is a Group 3 pollutant according to the IARC (not classifiable as its carcinogenicity to humans) [4]. Chromium III not toxic and is an essential micronutrient and participates in the metabolism of glucose and is less soluble in neutral pH [2]. Chromium III can also form insoluble oxides as well.

Many different techniques have been conceived to remediate ground water containing chromium VI. Adsorption is the process where molecules are concentrated on the surface of the sorbent, the driving force for absorption is the ratio of the concentration to the solubility of the compound [2]. There are many benefits to adsorption such as low cost, availability, and ease of operation. The different types of sorbents available, such as activated carbon, biosorbents, and industrial waste sorbents, increases availability even further. But it is not without any drawbacks.

Most forms of adsorption processes reduce chromium VI to chromium III, which then binds to the sorbent [2]. Adsorption is also pH dependent and can be ineffective with the presence of competing anions, adsorption in groundwater has been deemed ineffective.

Another form of remediation is the use of membrane filtration. Various types of membranes are capable of filtering out heavy metals such as chromium [2]. There a vast number of membranes currently in use; inorganic, polymeric, and liquid membranes. Experiments have shown that they are successful at removing chromium from wastewater, inorganic membranes showing

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the most success with a maximum of 96% rejection of chromic acid solution [2]. Pore size of the membrane, pH of the solution, and ionic strength all were deemed to have an influence on the chromium removal efficiency. Chromium VI ions are too small to be successfully removed from wastewater by filtration, unless pretreatment techniques are performed. The issue of the toxicity of the chromium VI is not addressed either.

Ion exchange techniques have also been used to remediate wastewater containing chromium VI. Wastewater is run through a column containing a synthetic ion exchange resin that completely removes the chromium VI [2]. The chromium ionâ&#x20AC;&#x2122;s high affinity for the resin replaces the ion with a much lower affinity, usually the chloride ion or the hydroxide ion [1]. Once the chromium is bound to the resin the resin it is then converted to sodium chromate and removed from the column and the column is regenerated using hydrochloric acid. The pH of the solution has been shown to play a role in the efficiency of the column as well as the possibility of organic fouling. The drawbacks to ion exchange technology is the strenuous four step process, the cost and production of the synthetic resin, the need to replace the resin when the threshold value is exceeded, and the lack of consideration of the toxicity of chromium VI. Electrochemical treatment methods to remove chromium have been developed and studied as well. Examples of electrochemical treatment are membrane electrolysis, electrochemical precipitation, electrokinetics, and vitrification. Membrane electrolysis, utilizes electrical potential to assist in the reduction of soluble chromium VI into insoluble chromium metal. The process requires low pH and high charge conditions, but yields a 98.5% removal rate from wastewater. Electrokinetics applies low concentrations of voltages across soil contaminated with chromium VI in order to mobilize the chromium into an aqueous phase. The collected wastewater is then treated above ground.

The optimal conditions for electrokinetics are low cation exchange capacity, high soil moisture but not saturated, low salinity, low conductivity, and high chromium concentrations [1]. Flushing the system with water is required as it allows for pH balance. This form of remediation is still in the development phase and not ready for on-site remediation. Although the electrochemical methods are successful at removing a majority, if not all, of the chromium VI found in industrial waste none of the methods address the issue of the toxicity of chromium VI and the methods are not as viable as other forms.

Biological remediation methods have also been used to remediate chromium VI waste. Microorganisms, such as bacteria, yeast, and fungi are able to carry out enzymatic reduction and oxidation reactions, referred to as redox reactions, which can convert chromium VI into chromium III. They often require a carbon source of some kind and are not always successful if the chromium reduction is not part of a metabolic pathway. Although biological reduction can be aerobic or anaerobic, reduction reactions are sensitive to oxygen concentrations [1]. Phytoremediation is the use of plants to take up chromium VI from the soil and reduce it to chromium III and store it in its tissue. Plants such as Leptospermum scoparium are found to contain soluble chromium in the leaf tissue as chromium III ions (Cr(Cr2 O4 )3 )3â&#x2C6;&#x2019; . This method is also beneficial to the soil as the roots prevents soil erosion. But, overall phytoremediation has been considered as temporary measure

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Figure 1. Reduction of dichromate ion (chromium VI) to chromium III with using Ascorbic acid

and would need further development [1].

Chemical reduction of chromium VI to chromium III and then the removal of chromium III has been used as method of treating chromium VI waste. This approach both addresses the toxicity of chromium waste and the removal of it from aqueous solution. Electron donors such as sulfur, iron II or iron metal, and others are used at the optimum pH. Some of the electron donors, such as H2 S and SO2 , are known to exhibit toxicity themselves [5]. But when concentrations of chromium VI are high the pH is increased to ensure chromium III will come out of solution. Chromate concentrations are decreased to nondetectable levels and no pumping and above ground treatment costs are required making this method a viable option for chromium remediation [1]. One factor that must always be considered is delivery method for different waste conditions.

According to Xu et al. [5], ascorbic acid has been known to chemically reduce chromium VI to chromium III. Ascorbic acid is most commonly referred to as vitamin C and is an antioxidant. Xu et al. [5] have shown that after adding varying amounts of ascorbic acid to solutions of potassium dichromate for half an hour the chromium VI concentrations had been eradicated, see Fig. 1.

Ascorbic acid though, and the dehydrogenated version, are both soluble in water and this could pose possible consequences as well. To account for this the structure of ascorbic acid could be altered at the C5 and C6 positions, not altering the site of the redox chemistry at the C2 and C3 position, replacing the hydroxyl groups with hydrophobic groups and therefore increasing the hydrophobic character of ascorbic acid, see Fig. 2. This would not only address the issue of the possible consequences of large concentrations of ascorbic acid, but it would also be a conservative method of remediation, as the ascorbic acid analog could then be filtered out and recycled for further remediation, see Fig. 3.

Materials and Methods Benzophenone Ascorbic acid Ketal. Following the experimental procedure of Abushanab et al. [6] the 5 g of the benzophenone dimethyl ketal was combined with 1.5 molar equivalents of ascorbic acid and catalytic amount (0.05 equivalents) of trifluroacetic acid in dimethylformamide.

The solution was allowed to stir at room temperature for 120 hours. The solution was then poured into water with 0.1 equivalents of sodium bicarbonate and the white precipitate was filterd out.

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Heptacosanone Ascorbic acid Ketal. The heptacosanone dimethyl ketal needed was prepared by combining 2.5 g of heptacosanone with 5 molar equivalents of methanol, 4 molar equivalents of trimethylorthoformate, and 1 molar equivalent of camphorsulfonic acid in tetrahydrofuran.

The solution was stirred for 72 hours and then poured into a solution of water with 2 molar equivalents of sodium biocarbonate. The ketal formed was combined with 2 molar equivalents of ascorbic acid and 0.1 equivalents of toluene sulfonic acid in dimethyl formamide. The soluiton was refluxed for 15 hours, and stirred for 24 hours.

Dibenzyl Ether Benzophenone Ascorbic acid Ketal. 1.5 g of Dihydroxy benzophenone was combined with 2.1 molar equivalents of benzyl bromide and 5 equivalents of potassium carbonate in 15 mL of acetone and refluxed for 6 hours. The solution was then poured into ice water and the dibenzyl ether ketone precipitated out. That was then combined with 10 ml of methanol, 4 molar equivalents of trimethyl orthoformate, and 0.5 molar equivalents of toluene sulfonic acid.

The reaction was then stirred overnight.

Diphenyl Benzophenone Ascorbic acid Ketal. 0.5 g of biphenyl-4-carboxaldeyde was combined, in portions, with 5.832 mL of 0.5 M 4-biphenyl Magnesium Bromide in THF (1.05 molar equivalents) and stirred at 0◦ C for 1 hour. The reaction was then quenched with 3mL of isopropanol and taken up in MTBE. The MTBE was washed with 1% sulfuric acid 3 times and then the MTBE layer was concentrated down. The solid was then combined with 4.2mL of 8.25% sodium hypochlorite in two uneven portions in half an mL of glacial acetic acid at 0◦ C for half an hour. The solution was then taken up in ethyl acetate and washed 3 times with water. The ethyl acetate layer was dried with sodium sulfate and then concentrated down.

Chromium VI Reduction. A 12.5 mM solution of potassium dichromate was prepared (2700 ppm) and used. 5 molar equivalents of the analog was combined and the reaction was stirred for half an hour and the yellow solution turned green. After the solution was analyzed by UV-Vis spectroscopy using a 1 : 60 dilution to keep with Beer’s law.

Figure 2. Model of the structural modifications to Ascorbic acid

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Figure 3. Initial analog recycling process

Results and Discussion The benzophenone ascorbic acid ketal was successfully created. It was a solid of melting point 184◦ C−190◦ C that was stable in pH 4 for 2 hours. Acetals that had been attempted to create were not stable leading to the conclusion that ketals were more suited then acetals. The benzophenone ascorbic acid ketal was then used in the chromium reduction experiment and was successful. The 2700 ppm solution of potassium dichromate used is 50,000 times more concentrated then the WHO recommended concentrations of chromium in drinking water, 0.05 ppm. The UV-Vis analysis showed that there was no chromium present due to Solution the lack ofBefore the identifying peak at 372 nm, Absorbance ofVI Chromium(VI) and see Fig. 4.

4

After Treatment with Ascorbic Acid Analog 4

3.5

Absorbance (AU)

3 2.5 2

Reaction Solution(1:60 dilution) Stock Solution(1:60 dilution)

1.5 1 0.5 0 250 260 270 280 290 300 310 320 330 340 350 360 370 380 390 400 410 420 430 440 450

Wavelength (nm)

Figure 4. Spectroscopic results of the Chromium VI reduction experiment

The analog was then attempted to be filtered out, which did not work. The solution was centrifuged which yielded a very low mass recovery. This could be due to the hydration of the dehydroascorbic acid analog which would make the analog much more water soluble, see Fig. 5.

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Figure 5. Hydration of the dehydroascorbic acid analog

In order to circumvent this issue the other, much larger and much more hydrophobic analogs were envisioned, see Figs. 6 and 7. The heptacosanone ketal was successfully formed and the formation of the ketal with ascorbic acid was attempted but the analog was not stable. The dibenzyl ether dimethyl ketal was never created due to electronic properties of the ether. The dimethyl diphenyl bezophenone ketal was successfully created and the development of the diphenyl benzophenone ketal with ascorbic acid is promising. Plans to continue the development of that analog, as well as others, as well as plans to form the ascorbic acid styrene ketal and polymerize it are the next steps to the project. Further research into the recycling steps of the overall remediation process will be pursued.

Figure 6. New analog to address hydrophobic requirements

Figure 7. Diphenyl benzophenone analog (right) and dibenzyl ether analog (left)

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Acknowledgement The author would like to thank the School of Science Scholars Program for financial support to perform this work. He also thanks the Department of Chemistry and Biochemistry at Manhattan College for the materials and the lab space that were made available for use, Dr. Alex Santulli for his help with the UV-Vis spectrophotometer, and Dr. John Regan for his guidance as his mentor.

References [1] Hawley, Elisabeth L., Deeb, Rula A., Kavanaugh, Michael C., and Jacobs, James R.G., 2004.

Treatment Technologies for Chromium (VI). Chromium (VI) Handbook. 273-308 [2] Owlad, Mojdeh, Aroua, Mohamed Kheireddine, Wan Daud, Wan Ashri, and Baroutian, Saeid, 2009. Removal of Hexavalent Chromium-Contaminated Water and Wastewater: A Review.

Water Air Soil Pollution. 200, 59-77 [3] Jacobs, James and Testa, Stephen M., 2004. Overview of Chromium (VI) in the Enviornment: Background and Histroy. Chromium (VI) Handbook. 1-22 [4] World Health Organization, Guidelines for Drinking-Water Quality. 2011. 4th Edition, 340 [5] Xu, X.R., Li, H.B., Li, X.Y., Gu, J.D., 2003. Reduction of Hexavalent chromium by ascorbic acid in aqueous solutions. Chemosphere. 57,609-613 [6] Abushanab, Elie, Vemisheti, Purushotham, Lieby, Robert W., Singh, Haribansh, Mikkilineni, Amarendra B., Wu, David C.-J., Saibaba, Racha, and Panzica, Raymond, 1988. The Chemistry of L-Ascorbic and D-Isoascorbic acids. The Preparation of Chiral Butanetriols and â&#x20AC;&#x201C; tetrols. Journal of Organic Chemistry. 53, 2598-2602

New synthetic uses for thiazolium salt derivatives Joseph Mozdzierzâ&#x2C6;&#x2014; Department of Chemistry and Biochemistry, Manhattan College Abstract. Thiamine, also known as vitamin B1 controls the movement of electrolytes into and out of nerve or muscle cells as well as helping to digest carbohydrates. However, when reacted with benzaldehyde under basic conditions in a laboratory, thiamine undergoes a pinacol rearrangement to form benzoin. Derivatives of thiamine known as thiazolium salts also undergo this particular arrangement, During the reaction, there is a transition state characterized by the formation of a zwitterion. If isolated, this zwitterion could act as a regenerative catalyst to continuously perform this benzoin condensation reaction without the need for additional base or an extensive acidic workup. It was determined that the intermediate zwitterion is too unstable to be isolated. An amino-alcohol compound can be produced via a similar reaction pathway. The trimethyl thiazolium analog when reacted with methyl iodide as an alkylating agent formed a new molecule whose structure has yet to be determined. Purification and recrystallization have been initiated to isolate a single crystal suitable for analyses by x-ray crystallography.

Background Almost everything in our lives is governed by the multitude of organic chemical reactions that take place on a daily basis. One of the most familiar categories of compounds is that of the vitamins. Thiamine (Fig. 1), also known as vitamin B1, proves quite important for many of the chemical reactions that take place in the human body.

Figure 1. Thiamine

These include the flow of electrolytes into and out of nerve/muscle cells as well as the decomposition of carbohydrates in digestion [1]. Scientists discovered that this compound could perform a pinacol rearrangement known as the benzoin condensation when reacted with benzaldehyde. It was later understood that a more basic thiazolium salt derivative performs the same reaction.

General Goals and Hypothesis The purpose of this research is to better understand the structure of thiazolium salts and their role in the benzoin condensation reaction. The goal is to recreate this reaction using modified â&#x2C6;&#x2014;

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substituents of the thiazole ring to create a greener chemical reaction with higher efficiency, and one that produces less waste.

A Better Understanding The thiazolium ring present in the salt has aromatic character which results in stabilization of the pi electrons. Although, there have been many cases in which chemists have been able to perform interesting reactions with this molecule including the production of cyanine dyes and pharmaceuticals such as alagebrium. These compounds are found in nature as a source of luminescence in fireflies resulting in the visible light that we see at night. Nonetheless, despite being aromatic, the presence of nitrogen and sulfur atoms destabilizes the ring and allows for reactivity under mild conditions as compared to the stable benzene aromatic ring. Given that the salt already has a positive charge present on the nitrogen atom upon deprotonation, a carbanion is formed (Fig. 2). This type of molecule is known as a zwitterion or betaine which implies that the compound is electronically neutral due to counter effects from the positive and negative charge. The hydrogen attached to the carbon at the C2 position, adjacent to the nitrogen atom is most acidic. This compound is an intermediate which is not stable enough to be isolated on its own.

Figure 2. Benzoin Condensation with Thiamine

Beginning the Synthesis Theoretically, the betaine intermediate formation is the driving force behind the mechanism of the benzoin condensation. The purpose of our investigation is to understand how substituent groups can affect the formation of this zwitterion. When methyl groups are added to all the carbon atoms within the 5-membered ring, it was unclear whether the methyl hydrogens would be more acidic than the benzylic hydrogens attached to the nitrogen. If deprotonation occurred at the benzylic site, then a betaine intermediate would be formed. However, if one of the methyl hydrogens at C2 was removed, it would form a zwitterion. Having performed the reactions, it was discovered that

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when the conditions were varied slightly, two different attacks occurred, forming two molecules characterized as benzoin and an amino-alcohol derivative of benzoin.

Benzoin The benzoin condensation is normally performed using a thiazolium salt. The conditions are relatively mild - triethylamine (a weak base) is used to deprotonate the ring. As the mechanism suggests, the hydrogen at C2 is removed most likely due to the fact that the both the positively charged nitrogen and electronegative sulfur atom adjacent to the C2 position. There are some theories which propose a possible dimerization between the C2 sites of two different thiazolium molecules followed by a subsequent attack of the benzaldehyde reagent at the same site. It was believed that these dimers reacted more effectively with the aldehyde, although, this idea was later disproved in support of a reaction with a single thiazolium salt [2]. Even though triethylamine is a weak base, it is strong enough to remove a hydrogen that has a partial positive charge. It was also noted on multiple accounts that when deprotonated, the salt forms a zwitterion compound with adjacent opposing charges as an intermediate step. As a preliminary experiment, we attempted to isolate this uniquely neutral compound as a possible stand-alone catalyst for the benzoin condensation. To eliminate any possible equilibrium issues with a weak base, sodium hydride (NaH) was used instead. However, it was speculated that in the presence of any water, the sodium hydride would convert to sodium hydroxide and attack the thiazole ring itself instead of removing the desired proton. After it was determined that the zwitterion could not be isolated as a separate catalyst for the benzoin condensation, we decided to see how different thiazolium compounds reacted under similar conditions.

Experimentation As mentioned previously, the benzoin condensation is a relatively simple reaction run using thiazolium salt derivatives and aldehyde reagents under mild basic conditions. The salt we created was formed using benzyl bromide and 2,4,5-trimethyl thiazole in a 1:1 equivalency due to the fact that both reagents are liquid at room temperature. The benzyl bromide alkylates the nitrogen atom on the thiazole ring creating a positive charge, and the hydrogen atoms attached to the carbons in the thiazole ring have now been replaced by methyl groups (Fig. 3). The base depro- tonates the hydrogen atom attached to one of the carbon atoms present within the thiazole ring. According to Spartan theoretical calculations, the C2 hydrogen is considered to be the most acidic and will be removed under basic conditions [3]. The salt we formed used benzyl bromide and 2, 4, 5-trimethyl thiazole. The benzyl bromide alkylates the nitrogen atom on the thiazole ring creating a positive charge. The hydrogen atoms at the benzyl position are at the same position relative to the positive nitrogen as those at the C2 site, and as such, could theoretically have similar acidities. Also, now that there is a methyl group at the key C2 position, the hydrogens attached to that carbon prove to be less acidic than the benzylic hydrogens. Upon different reactions, the condensation actually occurs as the result of an attack at the newly attached methyl site, not the benzylic site. This opposes the theoretical calculation.Even though it is still somewhat uncertain as to why the methyl

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site is favored in an experimental situation, although homogeneous reaction conditions maybe a contributing factor. A few other bases of varied strengths were used however, they produced miniscule yields of benzoin.

Figure 3. Formation of the N-benzyl Thiazolium Salt

Results When reacted with DBU, the most efficient weak base tested, benzoin was produced in a 2:1 yield when compared with the amount of starting material. The results were based on NMR spectra and it is not surprising that there was some of the original aldehyde remaining because it was added in excess to the reaction in an attempt to force a catalytic reaction with the trimethyl thiazolium derivative as a â&#x20AC;&#x153;replicateâ&#x20AC;? of the traditional benzoin condensation. It appears that large amounts of catalyst would be needed to obtain decent yields [4]. Adding heat to the reaction succeeded in further destroying the N-benzyl salt at a much faster rate. This observation also implies that there are actually two competing reactions taking place within the same flask. One of these reactions is responsible for the formation of the desired benzoin product (Fig. 4) while the other decomposes the catalyst into unwanted organic molecules.

Figure 4. Benzoin Condensation with N-benzyl Thiazolium Salt

Amino-Alcohol Synthesis As explained previously, throughout the course of research, the conditions of the benzoin condensation were varied in order to find the combination that yielded the most promising results.

What we found was that when reacting the N-benzyl salt with benzaldehyde under strongly basic conditions, benzoin was not produced. However, we synthesized an amino-alcohol derivative. The differences in the reaction environment (strong base and heterogeneous solution) obviously did not support the mechanism required to form the benzoin molecule which results from an attack at the C2 methyl site; instead, there was a deprotonation at the benzylic site. This proves to be

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an interesting phenomenon because, again, according to the theoretical calculations, the benzylic hydrogens are more acidic and should not require the use of a strong base to deprotonate. It is possible, though, that the equilibrium produced by the weak base had an effect on where the aldehyde attack occurred. Despite this stark distinction between the two reactions, it is important to note that the two mechanisms are more or less equivalent. The liberation of the nitrogen from the thiazole ring can occur by two different scenarios. The first is the ring is decomposed upon initial reaction with the strong base. The other possibility assumes that upon aqueous workup with hydrochloric acid, the thiazole ring breaks apart and liberates the nitrogen. The true cause is still under investigation although, it is known that during the benzoin condensation, the nitrogen is liberated during the acidic extraction, except the amino-alcohol compound is not produced, instead it is simply benzylamine.

Experimentation: Amino-Alcohol Similar to the methodology behind the formation of benzoin, the process of creating the amino-alcohol was not overly involved. Namely, the same N-benzyl salt was used as a starting material. Once the starting material has been isolated, it is reacted in a 1:1 ratio to both the strong base, in this case sodium hydride (NaH), and benzaldehyde. THF is used as a solvent and does not dissolve the starting material. The amino-alcohol synthesis is nearly identical to the benzoin condensation 18 hours at room temperature. Once the reaction has reached completion, the mixture is extracted with 10% aqueous hydrochloric acid followed by two extractions with water followed by brine solution. Again, it is speculated that the aqueous HCl liberates the nitrogen compound from the thiazole ring. However, it is important to note that this reaction is far from efficient and is under current experimentation to determine the optimal reaction conditions (Fig. 5).

Figure 5. Synthesis of 2-amino-1,2-diphenylethanol

Optimization of Amino-Alcohol Synthesis One of the most notable conclusions drawn following experimentation with the thiazolium salt compounds was that when reacted with strong base such as sodium hydride and benzaldehyde under heterogeneous conditions, an amino-alcohol derivative was formed as opposed to the originally anticipated benzoin compound. It should be noted that the benzylamine carbanion is the formal equivalent of the thiazolium betaine (Fig. 6). We undertook an optimization and isolation of the amino alcohol. Ultimately, the reagents used were kept constant, however, the amounts of

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Figure 6. Benzylamine Carbanion

each were varied along with the time of reaction. In each case, though, the amount of benzaldehyde added was slightly less than both the thiazolium salt compound and sodium hydride to ensure that, provided the reaction runs to completion. Unfortunately, even allowing the reaction to run for multiple days did not provide any useful amount of product to be analyzed. At this point, despite the experiments failure, we began a more in depth investigation.

Understanding the Reaction Formally, the success of the amino-alcohol synthesis reaction hinges on the formation of a benzylamine-like anion as the result of removing a hydrogen from the N-benzyl site on the original thiazolium salt. A negative charge is reacted with a electrophilic aldehyde carbon atom. The understanding is that upon reaction with strong acid, the nitrogen atom present in the thiazolium ring is liberated as a primary amine. The goal was also to determine if an aqueous basic reaction can still perform this same operation. In both cases, the starting material was reacted with excess acid or base. With regards to the acidic reaction, the workup consisted of extraction with ether to remove the excess hydrocarbon material, basicified, and then extracted again with ether. The basic workup required an additional step - a brief exposure with acid to protonate the amine group prior to washing with ether. Unfortunately, in each reaction, the outcome was the same due to the fact that no benzylamine anion was liberated from the thiazolium salt starting material. The overall sequence of side reactions following the decomposition of the thiazole ring is unknown and most definitely intricate, as a result, we are still attempting to fine tune the exact conditions suitable to perform this reaction.

Experimentation: Reaction with Methyl Iodide During our varied exploration of the thiazolium salt compounds and its various constituents, we had attempted to run a reaction involving methyl iodide as an alkylating agent. The initial impetus for running this reaction stemmed from the desire to understand exactly what position on the thiazole ring is attacked by an external nucleophile. Originally, it was believed that this reaction would be more than helpful, providing insight into other condensation reactions. Instead, what we

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found was that an entirely new compound was created, implying that another reaction occurred in place of a simple alkylation.

Judging by information gathered from an NMR spectrum, it appeared the methyl group at C3 was decomposed, or in some cases, removed entirely. Overall, the reaction is quite simple, involving the thiazolium starting material, a strong base (sodium hydride) and methyl iodide in large excess. The entire reaction is stirred and heated in a sealed tube for varied lengths of time.

Interstingly,no matter how long the reaction was run, the completion percentage (as judged by the presence of the methyl group at C3) did not seem to vary much. Given that the interaction of starting material with sodium hydride is a solid-solid reaction, it is possible that, while the surface material is deprotonated, those in sublayers are not, leaving unreacted starting material.

Recrystallization and Structural Determination Generally speaking, salt compounds are characterized by well-organized lattice structures which have anions interspersed with cations. In this particular case, the cation is represented by the positively charged nitrogen in the thiazole ring while the bromide ions present from the original benzyl bromide reagent act as the anions. With this knowledge, it is understood that the new compound created from reaction of the thiazolium salt with methyl iodide would form a salt that has a defined lattice structure that can be determined by X-ray crystallography. However, in order to utilize this method of structural determination, the product must be pure and present as relatively large crystals. The compound created appeared to be powdery, composed of fine crystals as opposed to larger ones. Recrystallizing the solid would remove the impurities present (in this case, excess starting material) but would also help to form larger crystals. The recrystallization of this product was trial and error, utilizing different solid combinations to achieve the best possible crystalline structure. Recrystallization THF proved to produce the nicest crystals. Of course, it was important to separate the dissolved organic salt from the sodium bromide which is also present and insoluble in THF. When looking at the recrystallized compound under a microscope with Dr. Richard Kirchner , it appeared as though there were smaller, black crystals coating the surface of a central white crystal. This discovery is interesting given that salt materials usually have a uniform composition. A better recrystallization system is needed to achieve the best possible salt crystal for analysis via X-ray crystallography.

Conclusions Having studied the thiazolium salts for a few months, it is clear that they are an extremely unique class of compounds. For one, it would appear that the aromatic nature of the ring would stabilize the salt, although, it was seen countless times that a variety of chemical reactions can occur on the thiazole ring. Typically, the basic thiazolium has a single hydrogen attached to each free carbon within the ring at the 2,4, and 5 positions; although, only the C2 position appears to be extremely reactive. Even under mild basic conditions, this proton is pulled from the ring and a zwitterion intermediate compound is formed. As it turns out, substituting methyl groups for

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each of the hydrogen atoms changes the reactivity of the ring slightly, although, certain reactions still take place. For example, the benzoin condensation was performed using a slightly stronger base in DBU coupled with benzaldehyde as a reagent. In addition to this traditional condensation reaction, a similar reaction was discovered which resulted in the formation of an amino-alcohol compound. The mechanism is similar except for the fact that the aldehyde attacks at the benzylic site as opposed to the C2-methyl site. In both cases, an acidic workup is required and it was observed that this extraction results in the liberation of benzylamine previously embedded in the thiazole ring.

Future Research Thiazolium salts are an interesting class of compounds and additional basic research can uncover new discoveries. Optimizing the reactions using the trimethyl thiazolium salt will discover how to react this compound with other aldehydes, ketones, esters and anhydrides. In addition, the simple alkylation with methyl iodide, can be further exploited. As is that case with amino-alcohol syntheses, the decomposition of the thiazole ring can be investigated. Thiazolium compounds are vastly underexplored and can hold the key to new and exciting syntheses down the road.

Acknowledgement This Summer Research Fellowship would not be possible without financial support from Manhattan College, chemical and laboratory support from the Department of Chemistry and Biochemistry, previous research on thiazolium salts by Mr. Shabaz Ali, and Dr. John Regan as a faculty advisor. I am infinitely appreciative of their help and support.

References [1] “Thiamine (Vitamin B1).” Background. The Natural Standard Research Collaboration, 01 Nov. 2013. Web. 28 Sept. 2015.

[2] Breslow, R. and R. Kim. “ChemInform Abstract: The Thiazolium-Catalyzed Benzoin Condensation with Mild Base Does Not Involve a ‘Dimer’ Intermediate.” ChemInform 25.24 (1994): n. pag. Web. [3] DiProperzio, A., Private communication [4] White, M. J. and F. J. Leeper. “Kinetics of the Thiazolium Ion-Catalyzed Benzoin Condensation.” The Journal of Organic Chemistry J. Org. Chem. 66.15 (2001): 5124-131. Web

Trash to treasure: Utilization of waste shells for biodiesel synthesis Adrienne Pereaâ&#x2C6;&#x2014; Department of Chemistry and Biochemistry, Manhattan College Abstract. The utilization of waste shells as heterogeneous catalysts for biodiesel synthesis was investigated in this paper. Biodiesel is an alternative fuel that can be produced from renewable sources by way of a transesterification reaction. Traditionally, this process includes the use of edible oils such as soybean oil and a homogeneous catalyst.

In this study, natural shells such as eggshells, mussel shells, clam shells and oyster shells were used as heterogeneous catalysts. Experimental results show that the reaction of Camelina Sativa oil with ethanol and KOH gave the best yield of 97%. FTIR, Diffuse Reflectance and NMR spectroscopy as well as X-ray crystallography were used to analyze the biodiesel obtained from each reaction, the natural shells and Camelina Sativa oil.

Introduction Diesel fuel is a mixture of hydrocarbons which are obtained from petroleum [1]. It is commonly used to power a third of the entire transportation industry in the United States [2]. Some vehicles that use diesel fuel include school buses, boats, trucks, MTA buses, farm as well as construction equipment, etc. Although used to power important vehicles in society, diesel fuel is toxic and expensive as it is made from the burning of fossil fuels. The burning of fossil fuels also emits carbon dioxide into the atmosphere which contributes to global warming, as well as the release of exhausts that are potential carcinogens.

An environmentally benign alternative to diesel fuel is biodiesel. Biodiesel has become a reasonable alternative fuel due to its fuel properties, as it is biodegradable, reduces CO2 emissions and is non-toxic. It can be used in diesel engines as a blend, i.e. B20 or pure, without requiring engine modifications. Synthesis of biodiesel occurs by way of a transesterification process, in which one ester is converted into another ester [3]. Vegetable oil, a triglyceride, is converted upon the reaction with an alcohol and a catalyst to produce biodiesel as well as its byproduct, glycerol.

The process is shown in Fig. 1 [4].

Figure 1. Transesterification process of triglycerides â&#x2C6;&#x2014;

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This reaction requires an excess of alcohol, either methanol or ethanol, so that a high degree of conversion could be obtained [5]. Methanol is traditionally used, because it is inexpensive, however, it is toxic, as it is commonly derived from non-renewable natural gas [6]. Ethanol is perceived to be a better alternative as it is commonly derived from renewable resources such as corn and sugarcane, however it is more expensive than methanol [6].

Biodiesel can also be produced from various feedstock such as vegetable oils, animal fats and waste oils [7]. In the United States, common oils are soybean, corn, etc. For biodiesel synthesis, soybean oil is commonly used as a starting oil. Soybean oil, otherwise known as vegetable oil, is commonly used in the United States for cooking. However, this poses a food versus fuel controversy. In the event that the demand for vegetable oil exceeds the supply of vegetable oil, a decision would have to be made about the primary use for the oil. In this instance, will it be used solely for food, or for fuel? An alternative that can end this controversy is Camelina Sativa oil, because it is not widely used in the United States for food. Camelina Sativa is a member of the mustard family and its plants grow from one to three feet tall [8]. These plants produce seed pods containing many small, oily seeds that amount to about 400,000 seeds per pound [8]. The seeds are 40 percent oil compared to 20 percent with soybeans [8]. Camelina Sativa is also a good feedstock alternative, because it is adaptable to temperate climate, it is short seasoned and fast growing [9, 10]. In addition, Camelina Sativa has lower water, pesticide and fertilizer requirements and it can be seeded, as well as harvested with conventional farm equipment [8].

There are two types of catalysts known as homogeneous and heterogeneous catalysts. Homogeneous catalysts are in the same phase as the reactants while heterogeneous catalysts are in a different phase than the reactants. Traditionally, homogeneous catalysts such as KOH are used for biodiesel synthesis, but because homogeneous catalysts require a water washing step, they are not very cost-efficient. More environmentally benign catalysts are heterogeneous catalysts in which a water washing step is not required. Instead, heterogeneous catalysts can be filtered and therefore, recovered. Thus, for biodiesel synthesis, it is more cost-efficient to use heterogeneous catalysts opposed to using homogeneous catalysts. The main focus of this paper is to use natural shells as heterogeneous catalysts, because the main component of waste shells is CaCO3 , which decomposes to CaO when calcined. CaO is a basic heterogeneous catalyst that has a higher basicity, lower solubility, lower price and is easier to handle than KOH [11]. Also, every year, approximately 8 to 10 million tons of waste shells are produced and these shells are either dumped either into a landfill or the sea. In developed countries such as the United States, disposal of these waste shells can be very costly. Therefore, the goal of this paper is to alleviate these disposal costs by using natural shells as heterogeneous catalysts as well as Camelina Sativa oil for biodiesel synthesis.

Materials and Methods Materials Camelina Sativa oil was utilized as the starting oil and homogeneous, as well as heterogeneous, catalysts were used. The homogeneous catalyst used was KOH and the heterogeneous catalysts

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used were CaO, eggshells, clam shells, mussel shells, and oyster shells. Methanol and ethanol were employed as both solvents and reactants. All reactions were done using a 1:12 oil to alcohol ratio. The biodiesel obtained from each reaction, as well as the Camelina Sativa oil were analyzed using IR and NMR and the natural shells were analyzed using Diffuse Reflectance (Solid IR) and X-ray crystallography.

Transesterification Reaction with Homogeneous Catalysts The reaction of Camelina Sativa oil, methanol and KOH was placed in a 250 mL round bottom flask at 65◦ C, whereas the reaction with ethanol occurred at 75◦ C. Both reactions ran for two and a half hours. When the reaction was completed, the contents were placed into a separation funnel, so that the biodiesel and glycerol layers could separate. The biodiesel layer was analyzed using spectral analysis.

Transesterification Reaction with Heterogeneous Catalysts The catalysts used, with the exception of CaO, were washed with water and dried at 100◦ C for one hour. All catalysts were then ground into a powder-like form, and calcined in a furnace at 900◦ C for four hours. After calcination, the catalyst was added to a beaker with stirring at 65◦ C for methanol, or 75◦ C for ethanol, for one hour. Once the one hour had passed, the catalyst/alcohol mixture was added to a 250 mL round bottom flask containing the Camelina Sativa oil. Reactions took place with stirring at 65◦ C for methanol, or 75◦ C for ethanol, and were heated from one to five and a half hours. Contents were cooled to room temperature and then vacuum filtered. Once the filtration step was completed, contents were placed in a separation funnel, biodiesel and glycerol layers were separated and the biodiesel was dried with anhydrous sodium sulfate. The biodiesel layer was then analyzed using spectral analysis.

Results Homogeneous Catalyst The reaction with Camelina Sativa oil, methanol and KOH resulted in a 95% yield while the second trial of Camelina Sativa oil, ethanol and KOH resulted in a 97% yield of biodiesel.

Heterogeneous Catalysts In the reaction of Camelina Sativa oil with methanol and CaO, a 93% yield was obtained and the reaction with ethanol and CaO resulted in a 77% yield. The trial with ethanol was yellow orange in color and was gel-like in form. A 67% yield was obtained for the reaction with methanol and eggshells, as some of the biodiesel turned into a gel. The eggshells were recovered as a pure, white powder which were analyzed using X-ray crystallography. The reaction with ethanol and eggshells resulted in a 73% yield. An 81% yield was obtained for the reaction of methanol with mussel shells, and the reaction of methanol with clam shells resulted in a 64% yield. Table 1 summarizes the conversion yields for each reaction and Figs. 2-5 are the spectra obtained for the analysis biodiesel and natural shells.

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Alcohol (12)

Catalyst

Percent Yield

Camelina Oil

Methanol Methanol Methanol Methanol Methanol Methanol Ethanol Ethanol Ethanol

KOH CaO Eggshells Mussel shells Clam shells Oyster shells KOH CaO Eggshells

95 % 93 % 67 % 81 % 64 % 86 % 97 % 77 % 73 %

Figure 2. FTIR spectrum of biodiesel produced by the reaction of Camelina Sativa oil with methanol and mussel shells as a heterogeneous catalyst

Figure 3. NMR spectrum of biodiesel produced by the reaction of Camelina Sativa oil with methanol and oyster shells as a heterogeneous catalyst

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Figure 4. FTIR spectrum of the heterogeneous catalyst eggshells in its phase before (green) and after (red) calcination.

Commander Sample ID (Coupled TwoTheta/Theta)

Figure 5. X-Ray Diffraction graph of the heterogeneous catalyst eggshells in its calcined state

Discussion Potassium Hydroxide as a Homogeneous Catalyst The most commonly used materials for the production of biodiesel are vegetable oil and a homogeneous catalysts such as KOH or NaOH. The overall goal of this project was to show that heterogeneous catalysts, but more specifically natural waste shells, could also be used for biodiesel synthesis. Not only could heterogeneous catalysts be used, but they are more environmentally benign, because the catalysts can be recovered and reused. In addition, the use of a homogeneous catalyst for biodiesel synthesis requires a water washing step which reduces the percent yield, as it results in the formation of soaps. When a heterogeneous catalyst is used, the water washing step is eliminated.

The reactions of Camelina Sativa oil and KOH resulted in a 95% yield when methanol was used as a reactant, and a 97% yield when ethanol was used as seen in Table 1.

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Calcium Oxide as a Heterogeneous Catalyst The reaction of methanol and CaO resulted in a 93% yield of biodiesel. The reaction with ethanol and CaO resulted in a low yield of 77%, because the biodiesel had turned into a gel like form below room temperature. There was a small amount of biodiesel in liquid form that was above the gel like form of the biodiesel. The biodiesel was heated back into the liquid phase so that vacuum filtration could occur. As vacuum filtration occurred, the filtrate began to turn back into a gel at room temperature. Thus, the low yield is attributed to the loss of biodiesel during filtration, as the biodiesel was in the solid phase. It was determined that the biodiesel turned into a gel, because the temperature had dropped below the cloud point and pour point of biodiesel, thus allowing the biodiesel to reach its gel point. The cloud point is the temperature at which paraffin wax crystals begin to form, the pour point is the temperature below which the fuel will not pour and the gel point is when the fuel becomes the consistency of petroleum jelly [3]. The temperature at which biodiesel reaches its gel point depends on the feedstock used [3].

Eggshells as a Heterogeneous Catalyst A 67% yield was obtained during the reaction of methanol and eggshells. In this reaction, the biodiesel also turned into a gel. Biodiesel was left on the filter paper and when the biodiesel was dried with anhydrous sodium sulfate, it turned into a gel while on top of the drying agent.

Therefore, the low yield is attributed to the biodiesel turning into a solid. Despite the low yield obtained for the biodiesel, the recovered eggshells were pure white in color and they were in powder form. The reaction of ethanol and eggshells resulted in a 73% yield.

Mussel Shells as a Heterogeneous Catalyst Mussel shells were used in addition to eggshells, to show that products that are considered waste can be used in an environmentally benign process. One component of shells is CaCO3 , which could be converted to CaO at high temperatures. Therefore, mussel shells were used as a heterogeneous catalyst to show any difference between yield conversions. It was compared with other shells to see if the percentage of CaCO3 in each shell has an effect on the percent yield of biodiesel. In this reaction, methanol and mussel shells were used and a yield of 81% was obtained.

Clam shells as a Heterogeneous Catalyst In addition to mussel and eggshells, clam shells were used. A low yield of 64% was obtained, because some of the biodiesel had turned into a gel while drying in a beaker containing anhydrous sodium sulfate.

Oyster shells as a Heterogeneous Catalyst The reaction of methanol and oyster shells resulted in an 86% yield. This trial was different from the previous reactions according to IR analysis. It was verified that the glycerol layer was less dense than the biodiesel layer in the separation funnel. However, after the filtration step, the recovered oyster shells were pure white.

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Spectral Analysis Camelina Sativa oil and the biodiesel produced from each reaction were analyzed using Fourier Transform Infrared Spectroscopy (FTIR). FTIR is a technique that is used to identify the functional groups of an organic compound [12]. By using this method, the products from each trial were analyzed to verify the conversion of Camelina Sativa oil to biodiesel. This was verified by two sharp peaks around 1200 cm−1 , as seen in Fig. 2. The peaks found in Figure 2 identify the biodiesel as containing a methyl ester. Nuclear Magnetic Resonance (NMR) is another technique that was used to analyze Camelina Sativa oil and the biodiesel produced from each reaction. NMR, like FTIR, is used to identify the functional groups of an organic compound and was used in this experiment to verify the conversion of Camelina Sativa oil to biodiesel. The peaks of interest that verified the conversion to biodiesel are seen around 3.5-3.7 ppm in Figure 3. These peaks show that the biodiesel produced from the reaction of Camelina Sativa oil with methanol and oyster shells, contained a methyl ester.

Diffuse Reflectance (Solid IR) and X-ray crystallography were used to analyze the natural shells before and after calcination, as well as after one reaction. In Diffuse Reflectance, the samples were mixed with 300 mg of KBr, which was used to dilute the sample. In Figure 4 between the 3500 cm−1 to 3000 cm−1 range, the blue line represents the composition of the calcined eggshells with KBr. The middle line (violet) represents the composition of the raw eggshells before calcination, with KBr. Lastly, the bottom line (red) represents the composition of the eggshells after one reaction with Camelina Sativa oil and methanol. X-ray crystallography is scientific method is used to determine the arrangement of atoms of a crystalline solid in three dimensional space [13]. For the purpose of this lab, this method was used to see if the composition of the shells had changed in any way. If the arrangement of the atoms in the shells did not show any major changes in composition, it verified that the catalyst could be reused for multiple reactions. The X-ray Diffraction graph, as shown in Figure 5, displays the peaks found in calcined eggshells. Analysis of this graph showed that the peaks in Figure 5 matched the peaks found in CaO. Therefore, Figure 5 verifies that when eggshells are calcined, the CaCO3 component of the eggshells is decomposed to CaO.

Conclusion The overall goal of this project was to show that natural waste shells could be used as heterogeneous catalysts. In a series of reactions, the catalytic system that resulted in the best conversion of biodiesel was determined. This was determined by the yield of biodiesel obtained. The reaction of Camelina Sativa oil with ethanol and KOH gave the best yield of 97%. Although homogeneous catalysts are commonly used for biodiesel synthesis, heterogeneous catalysts work as well. Natural shells can be used as heterogeneous catalysts in the synthesis of biodiesel, which applies the concept of “Trash to Treasure”. Future work consists of synthesizing biodiesel using shrimp shells as heterogeneous catalysts, finding the optimum conditions to increase biodiesel yield, and analyzing the biodiesel using GC-MS.

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Acknowledgement The author would like to thank the School of Science Research Scholars Program for financial support during the performance of the present research.

References [1] Majewski, W. Addy, and Hannu J¨aa¨ skel¨ainen. “What Is Diesel Fuel.” DieselNet Technology Guide, n.d. Web. 16 Oct. 2015.

[2] About Diesel Fuels. EPA: United States Environmental Protection Agency, n.d. Web. 01 Nov. 2015.

[3] Pahl, Greg. Biodiesel: Growing a New Energy Economy. White River Junction, VT: Chelsea Green Pub., 2005. Print.

[4] Knothe, G. (2001). Historical Perspectives on Vegetable Oil-Based Diesel Fuels. The AOCS Lipid Library. Retrieved August 22, 2014.

[5] Hillion, Gerard, Bruno Delfort, Dominique Le Pennec, Laurent Bournay, and Jean-Alain Chodorge. “Biodiesel Production Using a Heterogeneous Catalyst.” Focus on Catalysts 2003.1 (2003): 636-38. Web. 26 Aug. 2015.

[6] Knothe, Gerhard. “Biodiesel and Renewable Diesel: A Comparison.” Progress in Energy and Combustion Science 36.3 (2010): 364-73. Web. [7] Knothe, Gerhard, Jon Van Gerpen, and Jurgen Krahl. “Introduction.” The Biodiesel Handbook.

Champaign, IL: AOCS, 2005. 1. Print.

[8] “Camelina Information.” Sustainable Oils. N.p., 2009. Web. 01 Nov. 2015.

[9] Cahoon, Edgar. Camelina—An Emerging Biofuel Oil Feedstock. Progress and Prospects for Biotechnological Improvement (n.d.): n. pag. Web. 24 Aug. 2015.

[10] Greenwal, Curt. Camelina Oil in Human Consumption (n.d.): n. pag. Ole World Oils: Camelina Gold. Web. 24 Aug. 2015.

[11] Gnanaprakasam, A. , Sivakumar, V. M. , Surendhar, A. , Thirumarimurugan, M. , & Kannadasan, T. (2013). Recent Strategy of Biodiesel Production from Waste Cooking Oil and Process Influencing Parameters: A Review. Journal of Energy, vol. 2013, Article ID 926392, 1-10.

[12] FTIR Instrumentation and Theory. N.p., n.d. Web. 16 Oct. 2015.

[13] “X-ray Crystallography.” UC Davis- Chemwiki. N.p., 01 Oct. 2013. Web. 16 Oct. 2015.

Monte Carlo studies of ideal two dimensional linear polymers Adam J. Barillas∗ and Tylor Borgeson∗ Department of Computer Science, Manhattan College Abstract. Monte Carlo computer simulation is a useful tool for exploring the properties of ideal two dimensional linear polymers. Monte Carlo simulations provide an opportunity for students to develop their computer skills while deepening their knowledge of the behavior of polymers. The current simulations are in excellent agreement with theoretical predictions.

Introduction In a previous publication in this journal, Zajac and Bishop [1] employed a Monte Carlo growth method to simulate three dimensional ideal linear polymers. They computed many different polymer properties such as the mean-square radius of gyration, < S 2 > and the mean asphericity, < A >, and found excellent agreement with theoretical values. In this work, their Monte Carlo growth method is used to examine ideal linear polymers in two dimensions. A wide variety of properties are computed and compared to theoretical predictions.

Method Two dimensional polymers are constructed on an integer coordinate system. Given the numbers N and M, the simulation is performed by creating M independent samples each containing N units (beads). Two kinds of lattices were studied: a square lattice and a triangular lattice. In both lattices polymer samples are constructed by starting the first bead at the origin (0, 0). In the case of the square lattice subsequent beads are placed by randomly selecting one of four possible directions: North, South, East, or West, whereas in the case of the triangular lattice one of the following six possible directions is chosen: Northeast, East, Southeast, Southwest, West and Northwest. Each bead is placed one unit apart from the previously placed bead. In this study of ideal polymers, a location that has already been used by another bead is allowed to be chosen so that beads can overlap. After each polymer is completely constructed, a number of properties are calculated for that configuration.

One important property of polymers is their shape, which can be determined from the matrix ← → representation of the radius of gyration tensor, T This is a 2 by 2 symmetric tensor with four components but only three are unique. It can be written as T ab (k) = (1/N )

N X i=1

∗

[Qai (k) − Qa CMi (k)] ∗ [Qbi (k) − Qb CMi (k)]; a, b = X or Y

Research mentored by Marvin Bishop, Ph.D.

(1)

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Here, Qi (k) represents the X or Y components of the location of the i-th bead in the k-th sample and QCMi (k) represents the corresponding coordinates of the center of mass: QCMi (k) = (1/N )

N X

Qi (k)

(2)

i=1

← → The eigenvalues of T , λ1 and λ2 , are the components of the radius of gyration along the principal orthogonal axes [2]. They are determined for a given polymer sample by using the standard solution to the quadratic characteristic equation. The λ values of each configuration can be ordered by magnitude. One can envision [3] the polymer as enclosed in an elliptical envelope with semi-major axis λ1 and semi-minor axis λ2 . Rudnick and Gaspari [2] defined the asphericity of the k-th sample of a configuration, A(k), in two dimensions as A(k) = (λ1 − λ2 )2 /(λ1 + λ2 )2 .

(3)

The asphericity ranges from a value of 0 when λ1 = λ2 and the polymer has the shape of a perfect circle, to 1 when λ2 = 0 and the polymer has the shape of a straight rod.

The overall size of a polymer is characterized by its radius of gyration and, in the special case of a linear chain, by its end-to-end distance. The squared radius of gyration of the k-th sample, S 2 (k), is equal to the sum of the diagonal elements of the radius of gyration tensor, S 2 (k) = λ1 + λ2 .

(4)

and the squared end-to-end distance of the k-th sample of linear chains, R2 (k), is R2 (k) = (XN − X1 )2 + (YN − Y1 )2 .

(5)

where N and 1 refer to the last and first bead, respectively.

It is well-known [4] that for large polymers, both < R2 > and < S 2 > follow scaling laws: < R2 >= C1 (N − 1)2ν and < S 2 >= C2 (N − 1)2ν .

(6)

The coefficients, C1 and C2 , are model dependent amplitudes but the exponent, 2ν, is universal and equal to 1.0 for ideal polymers. It is also well-known [4] that < S 2 > / < R2 >= 1/6 for infinitely long ideal linear chains. These universal quantities are independent of dimension for ideal chains.

Results The simulations have been programmed using the GCC C compiler on a Linux machine. All the runs for N = 1001, 1501, 2001, and 2501 employed M = 160,000 polymer samples. The program averages the data over all the samples. Since the polymer growth generation process

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provides independent samples, the mean and standard deviation of the mean of general properties can be computed from the usual simple equations [5] but more care is needed in computing the errors of the ratios. In all the tables the number in parenthesis denotes one standard deviation in the last displayed digit; for example, < λ1 >= 138.96(26) means that < λ1 >= 138.96 ± 0.26.

The < S 2 > and < R2 > data in Tables 1 and 3 were fit by a weighted nonlinear least-squares program [5] to determine the exponent in the scaling laws, Eqs. 6. It was found that 2ν had the value of 1.00 ± 0.01 for < S 2 > and 1.01 ± 0.01 for < R2 > on a square lattice and 1.00 ± 0.01 for < S 2 > and 1.00 ± 0.01 for < R2 > on a triangular lattice. These results are in excellent agreement with the theoretical value of 1.00.

The computer results in the tables are for finite N whereas the theoretical results are for infinite N . Another scaling law for any property P is (7)

P = P∞ (1 − K/N ∆ )

Here P∞ is the value of P for infinite N, K is a constant, and ∆ is the finite scaling exponent.

In the ideal polymer regime ∆ has a value of 1.0. The P∞ value can thus be found by fitting a weighted least-squares line [5] in 1/N to each set of data in the tables.

The error in ratio calculations involving the division of separately averaged quantities which might be correlated has been determined by employing the equations derived by Bishop and Clarke [6]. They related the error in a ratio, to the separate errors in the numerator and in the denominator.

See Zajac and Bishop [1] for the detailed equations.

Table 1. General Properties as a function of N : Square Lattice.

Property

1001

1501

2001

2501

< λ1 > < λ2 > < S2 > < R2 > <A>

138.96(26) 27.75(4) 166.71(27) 997.33(251) 0.397(1)

207.69(38) 41.70(6) 249.39(40) 1491.43(374) 0.396(1)

278.05(51) 55.670(8) 333.72(53) 2001.24(501) 0.397(1)

347.45(63) 69.50(10) 416.95(66) 2502.84(626) 0.397(1)

The ratio results appear in Tables 2 and 4. Then the best linear fit was extrapolated in 1/N to 0 (e.g. N → ∞). The final extrapolated values are presented in Table 5 along with known theoretical results. All of the simulation values reported in Table 5 are well within two standard deviations of the mean, or in the 95% confidence interval. The error bars for the end-to-end distance moments grow larger as the exponent of the moment increases because of the large numerical values present in the quotient.

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Table 2. Ratio Properties as a function of N : Square Lattice.

Property 2

<λ1 >/<S > <λ2 >/<S2 > <S2 >/<R2 > <R2 >/<R>2 <R4 >/<R2 >2 <R6 >/<R3 >2 <R6 >/<R2 >3 <R8 >/<R4 >2 <R8 >/<R2 >4

1001

1501

2001

2501

0.834(1) 0.166(1) 0.167(1) 1.275(1) 2.010(5) 3.429(21) 6.083(48) 6.087(139) 24.588(419)

0.833(1) 0.167(1) 0.167(1) 1.274(1) 2.006(5) 3.411(21) 6.043(47) 6.026(138) 24.243(422)

0.833(1) 0.167(1) 0.167(1) 1.273(1) 2.003(5) 3.419(25) 6.047(53) 6.132(173) 24.604(581)

0.833(1) 0.167(1) 0.167(1) 1.273(1) 2.002(5) 3.419(25) 6.043(54) 6.138(181) 24.606(619)

Table 3. General Properties as a function of N : Triangular Lattice.

Property

1001

1501

2001

2501

< λ1 > < λ2 > < S2 > < R2 > <A>

138.94(25) 27.87(4) 166.81(26) 1001.12(251) 0.396(1)

208.27(38) 41.86(6) 250.13(40) 1497.19(376) 0.396(1)

278.55(51) 55.74(8) 334.29(53) 2005.49(501) 0.397(1)

348.69(64) 69.76(10) 418.45(66) 2506.91(630) 0.397(1)

Table 4. Ratio Properties as a function of N : Triangular Lattice.

Property

1001

1501

2001

2501

<λ1 >/<S2 > <λ2 >/<S2 > <S2 >/<R2 > <R2 >/<R>2 <R4 >/<R2 >2 <R6 >/<R3 >2 <R6 >/<R2 >3 <R8 >/<R4 >2 <R8 >/<R2 >4

0.833(1) 0.167(1) 0.167(1) 1.272(1) 2.003(5) 3.423(21) 6.051(47) 6.095(139) 24.452(418)

0.833(1) 0.167(1) 0.167(1) 1.274(1) 2.008(5) 3.437(24) 6.092(53) 6.179(163) 24.922(532)

0.833(1) 0.167(1) 0.167(1) 1.274(1) 1.999(5) 3.391(24) 5.992(52) 6.037(162) 24.124(533)

0.833(1) 0.167(1) 0.167(1) 1.275(1) 2.012(5) 3.443(21) 6.111(48) 6.139(140) 24.850(422)

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Table 5. Comparison of Simulation and Literature Results

Property 2

<λ1 >/<S > <λ2 >/<S2 > <A> 2 <S >/<R2 > <R2 >/<R>2 <R4 >/<R2 >2 <R6 >/<R3 >2 <R6 >/<R2 >3 <R8 >/<R4 >2 <R8 >/<R2 >4

Square Lattice Extrapolated

Triangular Lattice Extrapolated

Literature

0.832(2) 0.168(2) 0.397(2) 0.167(2) 1.272(2) 2.004(8) 3.416(48) 6.010(78) 6.138(245) 24.433(798)

0.833(2) 0.167(2) 0.398(2) 0.167(2) 1.277(2) 2.010(8) 3.429(32) 6.084(73) 6.124(216) 24.820(661)

0.832938[a] 0.167062[a] 0.3964[b] 0.1667[c] 1.273[d] 2.000[d] 3.395[d] 6.000[d] 6.000[d] 24.000[d]

[a] Ref. 7, [b] Ref. 8, [c] Ref. 4, [d] Ref. 6

Conclusion We have investigated two dimensional ideal linear polymers using a Monte Carlo growth method on both a square and a triangular lattice. Many different properties have been computed.

There is excellent agreement with theoretical results. Modeling projects such as the one described here provide a clear demonstration of some aspects of polymers and thus strongly enhance student understanding and intuition.

Acknowledgements The authors thank the School of Science Research Scholars Program for financial support and the Manhattan College Computer Center for providing time on their machines. They also wish to thank Professor Paula Whitlock for many useful conversations about Monte Carlo calculations.

References [1] G. Zajac and M. Bishop, “Monte Carlo Studies of Ideal Three Dimensional Linear Polymers,” Comp. Educ. J., 5(4) 107 (2014).

[2] J. Rudnick and G. Gaspari, “The Asphericity of Random Walks,” J. Phys. A, 19, L191 (1986).

[3] A. M. Dunn and M. Bishop, “Modeling and Simulation of Two Dimensional Star Polymers with the Pivot Algorithm,” Comp. Educ. J., XVIII (1), 64 (2008).

[4] P. G. de Gennes, Scaling Concepts in Polymer Physics, (Cornell University Press, Ithaca, 1979).

[5] P. R. Bevington, Data Reduction and Error Analysis for the Physical Sciences, (McGraw-Hill, New York, 1969).

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[6] M. Bishop and J. H. R. Clarke, “Investigation of the End-to-End Distance Distribution Function for Random and Self-Avoiding Walks in Two and Three Dimensions,” J. Chem. Phys., 94, 3936 (1991).

[7] G. Wei, “New Approaches to Shapes of Arbitrary Random Walks,” Physica A, 222, 155 (1995).

[8] H. W. Diehl and E. Eisenriegler, “Universal Shape Ratios for Open and Closed Random Walks: Exact Results for all d,” J. Phys. A, 22, L87 (1989).

Visualization of xylary rings of stems of Artemisia tridentata spp.

Wyomingensis.

Michael Scarinci∗ and Katherine Encarnacion∗ Department of Mathematics, Manhattan College Abstract. Plants of Artemesia tridentata are dominant plants in the American southwest. They cover most of Nevada, Utah, Idaho, and Oregon at low elevations. This plant species provides important habitat for many endangered species.

Many species of Artemesia tridentata show extensive eccentric growth, which probably limits it ability to grow tall.

Eccentric growth occurs because the vascular cambien dies and does not continue to produce secondary xylem in stems. The purpose of this study was to create an accurate pictorial representation of xylary rings of an eccentric stem of Artemesia tridentata spp. wyomingensis using computer visualization . Four stem samples from the branch were properly sized and aligned in MATLAB. Three xylary rings were selected in Microsoft Paint and colored for the visualization. The images were aligned in MATLAB beginning from the oldest to youngest of the four samples.

This assembly provided a three dimensional visualization which allowed the discontinuation of the rings from segment to segment to be viewed. The process provides a method of visualizing the xylary rings for tree species in three dimensions.

Introduction The Central Basin and Range Ecoregion ranges nearly 343,000 km2 throughout most of Nevada and a portion of Utah (West, 1999; Soulard, 2012). Prevailing shrubs of the Great Basin Desert includes six species of Artemisia, two species of Chrysothamnus, two species of Atriplex, Sarcobatus vermiculatu, and Ceretoides lanata among others. Species of Artemisia populate most non-saline portions of the Great Basin Desert (Daubenmire, 1970; MacMahon, 1985; Bilbrough and Richards, 1991; Welsh, 2005). Subspecies of Artemisia tridentata are a major contributor to community structure and ecology of the region. Eccentric growth of stems of Artemisia has been documented (Diettert, 1938; Ferguson and Humphrey, 1959; Ferguson, 1964). Many subspecies of Artemisia tridentata produce eccentric growth naturally.

The purpose of this study was to create an accurate pictorial representation of xylary rings of an eccentric stem of Artemesia tridentata spp. wyomingensis using computer programs. Specifically, an accurate pictorial representation of xylary rings from cuts of stem samples was produced.

Sample images will be uploaded into MATLAB. They will be scaled to the same pixel size so that all images are aligned. Processed images will be brought into Microsoft Paint and traced. This trace will create a three dimensional visualization of xylary rings from consecutive wood images.

Materials and Methods Initial preparation of samples from a stem A stem of Artemisia tridentata spp. wyomingensis was obtained from plants near Fremont Canyon, Utah (40.0◦ N, 112.1◦ W) kindly provided by Dr. Stanley Kitchen, Desert Experiment ∗

Research mentored by Angel Pineda,Ph.D. and Lance S. Evans, Ph.D.

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Station, Rocky Mountain Research Station, Provo, Utah. The stem was typical for plants of the region. The stem was cut and shipped to Manhattan College.

Prior to sawing samples, some of the bark was removed from each stem. Once sufficient bark was removed, a vertical line was drawn along each stem with a permanent marker so that the orientation of all stem segments could be reconstructed once segments were cut. Stem segments (cross or transverse sections) were obtained with a Dewalt DWHT20541 flush cut pull saw (www.dewalt.com). The average segment thickness was 7.8 mm. The thickness of each segment was measured with a digital caliper (Fisher model #14-648-17, Fisher Scientific Inc., Pittsburgh, PA) accurate to 0.01 mm. Images of transverse stem segments were obtained from photographs through a Leica EZ4 microscope (www.leica-microsystems.com) with a Canon PowerShot ELPH100HS camera (www.canon.com).

Image alignment process to recreate the correct alignment of stem segments.

To illustrate the process, we use segmet #46 as an example.

1. The image of segment #46 from a stem of Artemisia tridentata spp Wyomingensis. This image does not have the xylary rings labeled or the angles outlined (Fig. 1).

2. The image of the stem segment with its xylary rings labeled and the angles outlined (Fig. 2).

Figure 1. Image of segment 46 taken from a stem of Artemisia tridentata spp. wyomingensis. This is a raw image without xylary rings or the angles labeled.

Loading and scaling the images to the same resolution All images were loaded into MATLAB (www.mathworks.com) using the ‘imread’ function (Fig. 3). The color of all images was changed from RGB (red, green, blue) to gray with the ‘rgb2gray’ function. All eleven images were scaled using the ‘imresize’ function to have the same resolution (154 pixels per millimeter) as image #9 (sample 28) which had the highest resolution of the images.

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Figure 2. Image of stem segment 46 with the xylary rings and angles labeled.

Figure 3. Image for stem segment number 46 of Artemesia tridentata ssp tridentata showing extensive eccentric growth. The first step was to find the biological center (the area of original growth of the stem. In this image, the biological center is located in the lower portion where the four straight lines intersect. The next step was to trace the xylary rings the innermost ring was produced first. The outermost ring was produced last. Twenty-seven xylary rings are present in the sample. The arrow indicates the 0◦ angle that was used to assist in the orientation process to align all the images of the study. Other lines to help orientation were drawn every 36◦ . Image is displayed in the MATLAB program with ‘imread’ function, file size 126 KB.

Aligning the zero degree points and the biological centers.

The next step was to rotate all scaled images horizontally to align the zero degree angle point in a coordinate (horizontal) plane. This was performed with the function ‘imrotate’ in MATLAB (Fig. 4). When necessary, the sizes of images were adjusted so all of the biological centers of the eleven segments were aligned on a 4000 × 4000 matrix. In summary, all eleven images were scaled with the same resolution so that the zero degree angle point and the biological centers were completely aligned.

Ring Visualization Procedures Stem samples 36, 38, 40 and 42 were selected for visualization of individual rings. As stated previously, the stem segments were approximately 7.8 mm apart. Segment 42 had the largest

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Figure 4. Rotation of image in MATLAB using ‘imrotate’ function. Images needed to be rotated so they could be aligned with other images.

diameter (oldest), while segment 36 had the smallest diameter (youngest) among the segments analyzed. Xylary rings 3, 7 and 10 were selected for visualization from the above stem samples. A trace of the desired rings was done in Microsoft Paint. The desired rings were free-form selected and filled with black pixels. The filling was done for the selected rings of the four samples. Then the entire image color was inverted (invert color). Thereafter, the image was adjusted in “image properties” and under “color”, adjusted to black and white. The next step was to return to “image properties” and select “color”. The following step was to go to “invert color” again. At this point, only the image rings were visible and were all black. The black and white images (Fig. 5) were loaded into MATLAB and were adjusted to align zero angles and the biological center for the four images. The images were inserted into a three dimensional matrix. Using the ‘contourslice’ function in MATLAB, a three dimensional figure was created (Fig. 6).

Figure 5. Image of rings 3, 7 and 10 from segment 38. This image was produced by tracing the rings in Microsoft Paint.

Visualizations of rings 3, 7 and 10 for segments 36, 38, 40 and 42 Stem samples 36 and 42 were selected for ring visualizations. The original images were loaded into Microsoft Paint (Figs. 7A, 8A). Rings 3, 7 and 10 were free-form selected and filled with colors

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Figure 6. Image of rings 3, 7 and 10 for the four segments.

Each image was translated, rotated, and scaled. They were put into a three dimensional matrix and the contourslice function was used for the visualization. The x and y axis indicate the pixel range. The z axis indicates the segment numbers.

The upper to lower images are segments 36, 38, 40, and 42, respectively.

(Figs. 7B, 8B). The contourslice image was saved and imported into Microsoft Paint. The chosen rings were free-form selected and filled with colors (Fig. 9). The four images in Fig. 9 show entire rings and eccentric rings for rings 3, 7 and 10. For segment 42, ring 3 was complete, but rings 7 and 10 were incomplete (eccentric). Specifically, ring 7 was approximately 342 degrees of arc, while ring 10 was approximately 216 degrees of an arc. For segment 40, ring 3 was complete, and rings 7 and 10 were incomplete (eccentric). However, the gaps for ring 7 and 10 were remarkably different from those in segment 40 in terms of direction of discontinuities of rings. Segment 38 shows all 3 rings eccentric. Segment 36, the youngest sample, showed very incomplete rings. Specifically, ring 3 was approximately 180 degrees of an arc, ring 7 was approximately 144 degrees of an arc, and ring 10 was approximately 97 degrees of an arc. Clearly, these data document the eccentric nature of every segment analyzed in stems of Artemesia tridentata. The data also show that there were dynamic differences between each segment that were 7.8 mm apart.

Discussion The purpose of this study was to create an accurate pictorial representation of xylary rings of an eccentric stem of Artemesia tridentata spp. wyomingensis using computer visualization. This study produced an accurate pictorial representation of three xylary rings within four stem samples that were separated by 15.6 mm each. In addition we calculated the percent of arc for each of the xylary rings for each of the images. Clearly, the arc percentages varied among samples, indicating that eccentric growth varied remarkably among the stem samples over very short distances. Thus, the eccentric growth is quite localized and the growth rings in one location seemingly have little effect on the growth on nearby locations. Overall, the approaches used accurately documented the relationships between xylary rings inside of the stem samples.

One application of this study would be to create a predictive model of xylary ring growth. Using the (1) locations of complete rings, (2) locations of partial rings, (3) percentages of individual arcs, (4) calculations of ring areas, are all required for an evaluation of stem growth. The current images can be used to illustrate how predictive models might be used. Clearly, the arc locations

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Figure 7. Images of segment 36. A: image with only the rings marked and the several transects. Zero degree transect is at the black arrow. Bar = 3.2 mm. B: image in which ring 3 is colored green, ring 7 is colored blue and ring 10 is colored red. Bar = 3.2mm.

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Figure 8. Images of segment 42. A: image with only the rings marked and the all transects. Zero degree transect is at the black arrow. Bar = 3.2 mm. B: image in which ring 3 is colored green, ring 7 is colored blue and ring 10 is colored red. Bar = 3.2mm.

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Figure 9. Three dimensional visualization of the four stem segments with rings 3, 7 and 10 colored. Ring 3 is colored green, ring 7 is colored blue and ring 10 is colored red. The biological center is a black dot near ring 3. The black arrow indicates the zero degrees transect.

and percentages are different between samples 36 and 42 (Figs. 7B and 8B). For sample 36, the approximate ring areas were 4.2 mm2 , 21.0 mm2 , and 50.2 mm2 , respectively. In contrast, for sample 42, the larger sample (Fig. 8B), the approximate ring areas were 8.0 mm2 , 23.3 mm2 , and 20.4 mm2 . Comparing these two samples, ring 10 for sample 36 was more than twice the area in sample 42, while the area of ring 3 for sample 42 was more than twice the area for sample 36.

Therefore, ring locations, ring arcs, and ring areas were different among these two samples. Such samples may be useful for predicting xylary ring growth.

Acknowledgements The authors appreciate the generous financial support of the Linda and Dennis Fenton â&#x20AC;&#x2122;73 Endowed Biology Research Fund for this work. The authors gratefully appreciate the stem images from Tiffany A. Kharran and Hayley J. Graney. The authors appreciate the guidance by Dr. Angel R. Pineda and Dr. Lance S. Evans.

References Ardekani, B., S. Guckemus, A. Bachman, M. Hoptman, M. Wojtaszek, . 2005. Quantitative comparison of algorithms for inter-subject registration of 3D volumetric brain MRI scans. Journal of Neuroscience Methods 142: 67-76.

Bilbrough, C.J. and J.H. Richards. 1991. Branch architecture of sagebrush and bitterbrush: Use of a branch complex to describe and compare patterns of growth. Can. J. Bot. 69: 1288-1295.

Daubenmire, R. 1970. Steppe vegetation of Washington. Technical Bulletin 62. Washington State Agricultural Station, College of Agriculture. Washington State University. Pullman, WA.

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Diettert, R.A. 1938. The morphology of Artemisia tridentata Nutt. Lloydia 1:3-14.

Ferguson, C.W. 1964. Annual rings in big sagebrush. Papers of the Laboratory of Tree-Ring Research No 1. University of Arizona Press. Tucson, AZ. Ferguson, C.W. and R.R. Humphrey. 1959. Growth rings of sagebrush reveal rainfall records.

Progressive Agriculture in Arizona. 1959.3.

MacMahon, J. A. 1985. Deserts. The Audubon Society Nature Guides. Alfred A. Knopf. New York, 638 p.

Soulard, C. E. 2012. Central Basin and Range Ecoregion 2012. in Status and Trends in the Western United States â&#x20AC;&#x201C; 1973 to 2000 (Edited by B. M. Sleeter, T. S. Wilson and W. Acevecb) US Geological Survey Professional Paper 1794-A. Watkins, K.,T. Paus, J.P.Lerch, A. Zijdenbos, D.L. Collins, P. Neelin, J. Taylor, K.J. WorsleyA.C. Evans. 2001. Structural Asymmetries in the Human Brain: a Voxel-based Statistical Analysis of 142 MRI Scans. Cerebal Cortex 11:868-877lkl.

Welsh, B. 2005. Big sagebrush: a sea fragmented into lakes, ponds, and puddles. General Technical Report RMRS-GTR-144. Fort Collins, CO. West, N.E. 1999. Managing for biodiversity of rangelands. Pages 101-126 in W.W. Collins and C.O. Qualset, editors. Biodiversity in agroecosystems. CRC Press, Boca Raton, FL.

Statistical modeling and the college experience Gregory Zajac∗ Department of Mathematics, Manhattan College Abstract. This study seeks to examine student satisfaction at Manhattan College. In doing so, it explores several factors that were found to be statistically significant in affecting overall satisfaction for certain groups of students. The results were used to provide value-added information to the Manhattan College administration. This information could be used to initiate and or modify policies and programs that would positively impact student satisfaction.

Introduction Institutional research is essential for every college. Its purpose, according to Volkwein [1], is “To maintain and enhance their competitiveness and academic reputations. . . [and to provide] good information about the impact they are having on their students and about the quality of student learning at their institutions.”

Examining data regarding to student satisfaction can provide administrations with value-added information that can be beneficial to both their colleges and their students. Specifically, such information can aid Manhattan College determine whether it is fulfilling its mission; it can help promote and market the college, and it can facilitate changes in areas that are more responsive to student satisfaction.

This study expands on the preliminary results the author obtained regarding student satisfaction while enrolled in MATH 492: Topics in Applied Math: Mathematical Modeling. The goal of this study is to determine if those students who complete an undergraduate program at Manhattan College are satisfied with their experience.

Methods and Materials The sample analyzed was the 2013-14 Senior Class at Manhattan College. This group was chosen because it was decided that seniors would give the most complete view of the undergraduate experience.

Three datasets were then chosen for analysis. The first dataset, the National Survey of Student Engagement, abbreviated NSSE, is a national instrument used gauge student engagement.

“Through its student survey, The College Student Report, NSSE annually collects information at hundreds of four-year colleges and universities about first-year and senior students’ participation in programs and activities that institutions provide for their learning and personal development.

The results provide an estimate of how undergraduates spend their time and what they gain from attending college” [2]. The second dataset, the Graduating Senior Survey, abbreviated GSS, is a ∗

Research mentored by Ira Gerhardt, Ph.D.

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Table 1. Significant Results Who?

Comparison

Percent Difference

More Satisfied?

p-value

Engineers Male Students

Male vs. Female Residents vs. Commuters

+13% from Male to Female -6% from Resident to Commuter

Females Residents

< 0.01 < 0.01

required senior exit survey. The third dataset, the Fall 2013 Banner census information, contains demographic information for all students.

The next step was to develop a new working definition of “overall satisfaction”. There were two questions that appeared in both the NSSE and the GSS with regard to student satisfaction: 1. How would you rate your overall educational experience at Manhattan?

2. If you could do it all over again, would you choose to come back to Manhattan?

The ratings from these questions were averaged across the NSSE and GSS, and fitted to a 0-100 scale, which we gave the title “overall satisfaction.”

With overall satisfaction clearly defined, the larger question of “What makes for a satisfied student?” could be broken down into two smaller questions: “What factors are significant in affecting overall satisfaction?,” and “When comparing two independent groups, who is more satisfied?” To compare satisfaction levels among two independent groups, a two- sample hypothesis test is employed. A sample from each of the two independent groups is examined to determine if there is evidence to show, beyond a reasonable doubt, that one group is truly more satisfied with their experience at Manhattan. To determine which factors are significant in affecting overall satisfaction, multiple regression was utilized. Multiple regression is used to predict the behavior of a single output variable based on multiple input variables; in this case, to predict overall satisfaction. In addition, multiple regression identifies which of the variables are significant in affecting overall satisfaction.

Results After performing numerous two-sample hypothesis tests, claims could be substantiated for various groups, two of which will be discussed: the Female Engineers vs. Male Engineers, and the Male Residents vs. Male Commuters. The results are shown in Table 1, and the actual satisfaction levels and sample size are shown in Figs. 1 and 2. Note that a p-value is simply the probability that our claim is incorrect.

Those who self-identify as Female in the School of Engineering are more satisfied than those who self-identify as Male in the School of Engineering. This result was actually not very surprising. Engineering is, historically, a Male-dominated profession [3].

In light of this fact, it was hypothesized that there may be a special “bond” that exists among Female Engineers. To substantiate this hypothesis, sets of special variables from the NSSE that

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Figure 1. Male Engineers vs. Female Engineers

Figure 2. Resident Males vs. Commuter Males

would be indicative of a social/academic bond were examined. These variables come under the headings Quality of Interactions, Collaborative Learning, Supportive Environment, and StudentFaculty Interactions. The statistically significant results are summarized in Table 2 below.

Of all the variables examined, those that were statistically significant dealt with interpersonal interactions. The existence of a bond among senior female engineers may not be fully supported by the data inasmuch as the variables analyzed were not idiosyncratic to that group.

However, personal observations by this researcher of interactions among the relatively small group of senior female engineers at Manhattan College revealed that a strong bond does indeed exist among them. In this researcherâ&#x20AC;&#x2122;s view, this sufficiently provided one of the bases for the recommended actionable plans.

Recall that we were able to conclude beyond a reasonable doubt that the Male Residents were

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Table 2. Significant Variables: Female Engineers Variable

Male Count

Female Count

Percent Increase from Male to Female

Higher Rating?

p-value

Quality of Interactions

60

25

25%

Females

< 0.01

Quality of Interactions among Students

59

26

7%

Females

0.037

Student-Faculty Interactions

65

30

34%

Females

< 0.01

more satisfied than the Male Commuters. The question now was “what factors are significant in affecting overall satisfaction for Residents and Commuters?” To answer this, numerous models were constructed using multiple regression. The most useful of these models is shown below, in Table 3.

Table 3. Regression Model: Resident and Commuter Males Adjusted R-Squared

Observations

Significance F

0.237

265

< 0.01

Significant Variables

Coefficients

Intercept Satisfaction-Availability of Courses Satisfaction-Space for ’hanging out’, clubs, student govt meetings Satisfaction-Academic Advising (from faculty and Assistant Deans) Satisfaction-Surroundings (Off-Campus) Res/Comm (1 R, 0 C)

41.027 3.335 (+) 2.577 (+) 2.286 (+) 1.991 (+) 4.303 (+)

First, note that all of the variables are significant in the model (p < 0.05). All of the variables observed had positive slopes. A variable with a positive slope indicates that an increase in that variable should lead to an increase in overall satisfaction. Moreover, we see that the adjusted R2 (measure of how well the model explains the variation in the data) is 0.237, which is acceptable given the sample size. Also note that the Significance F < 0.01, implying that the predictions of the model are reliable. Finally, this model demonstrates that Resident Males should be more satisfied than Commuter Males.

It was hypothesized further that the set of variables that are significant in affecting the satisfaction of Resident Males should be different than those that affect the satisfaction of Commuter Males. To test the hypothesis, two regression models were built: one for Resident Males, and one for Commuter Males. The models, shown in Tables 4 and 5 below, confirmed this hypothesis.

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Table 4. Regression Model – Resident Males Adjusted R-Squared

Observations

Significance F

0.237

126

< 0.01

Significant Variables

Coefficients

Intercept Satisfaction-Academic Advising (from faculty and Assistant Deans) Satisfaction-Surroundings (Off-Campus) Satisfaction-Campus Food Services Satisfaction-Campus Ministry & Social Action

40.065 3.323 (+) 2.610 (+) 2.984 (+) 3.154 (+)

Table 5. Regression Model – Commuter Males Adjusted R-Squared

Observations

Significance F

0.281

134

< 0.01

Significant Variables

Coefficients

Intercept Satisfaction-Availability of Courses Satisfaction-Space for ’hanging out’, clubs, student govt meetings Satisfaction-Academic Advising (from faculty and Assistant Deans) Satisfaction-Computer Labs

41.238 3.414 (+) 3.688 (+) 3.351 (+) 3.247 (+)

Discussion Value-added information was obtained regarding student satisfaction in two groups of students. This information was provided to administration. Utilizing this information, actionable plans were formulated in conjunction with Dr. David Mahan, Assistant Provost and Executive Director for Institutional Effectiveness at Manhattan College. In the School of Engineering, focus groups for seniors could be formed to specifically identify what made their experience at Manhattan College special. Additionally, pairing upperclassmen Female Engineers with freshmen Engineers, both Male and Female, in a mentorship program was also proposed. For the Male Commuters, the administration could work in conjunction with Student Life to open the new Common Interest Communities to Commuters. These Common Interest Communities are “. . . a series of themed residences where students can enhance their experiences at the College by living with other students who share their interests — regardless of what their academic courses or majors might be” [4]. Lastly, because satisfaction with Campus Ministry and Social Action was significant in positively affecting overall satisfaction for Resident Males, administration could work with Campus Ministry and Social Action to get Commuters involved with community service.

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Future Work This study is a starting point in examining student satisfaction at Manhattan College. Future research could examine trends in student satisfaction over a number of years. In addition, the impact of new campus infrastructure, namely, the Raymond W. Kelly ’63 Student Commons, on student satisfaction can be studied. Lastly, the results and effectiveness of those actionable plans implemented to impact student satisfaction must be closely monitored.

Acknowledgements The author wishes to thank Dr. Rani Roy and the Manhattan College Summer Grants Committee for funding this project. In addition, thanks are extended to Nicolas Lara and the Manhattan College ITS Staff for their technological assistance. Finally, this project would not have been possible without the support and guidance of Dr. Ira Gerhardt, Department of Mathematics, and of Dr. David Mahan.

References [1] Volkwein, J. Fredericks, “Gaining Ground: The Role of Institutional Research in Assessing Student Outcomes and Demonstrating Institutional Effectiveness,” September 2011, http://www.learningoutcomeassessment.org/documents/Volkwein.pdf [2] http://nsse.indiana.edu/html/about.cfm [3] National Science Foundation, “Engineering degrees awarded, by degree level and sex of recipient: 1966–2008,” http://www.nsf.gov/statistics/nsf11316/pdf/tab46.pdf [4] https://manhattan.edu/student life/residence-life/common-interest-communities

Study of Higgs Boson production in different channels at the Large Hadron Collider Dylan Grayâ&#x2C6;&#x2014; Department of Physics, Manhattan College Abstract. I review the Higgs Boson production mode of Vector Boson Fusion with regards to current studies of Higgs phenomenology. I review the Effective Field Theory approach being applied to the Higgs Boson production vertex in order to study Beyond Standard Model contributions. I discuss the motivation behind using a morphing technique to model the Beyond Standard Model contributions. I review the morphing technique principles and discuss the development of a code to manifest them. I discuss my contribution to the code by completing an equation for the production vertex cross section by using the Monte Carlo generator, MadGraph5.

Introduction In physics, there is a model that tries to explain the fundamental forces and particle interactions that make up everything in the universe called the Standard Model (SM), but it is not entirely complete. While it has been verified through various experiments and is consistent, there are some things that it does not explain nor does it account for everything. One of the last things that needed to be found to prove that the Standard Model is correct, was the Higgs Boson. The Higgs Boson results from the quantum excitation of the Higgs Field. The Higgs Field is a scalar field that acts as the mechanism in which all other matter acquires a mass. It opaerrates through spontaneous symmetry breaking [1]. Currently, the search for new physics comes from the idea of Beyond Standard Model (BSM) physics, which will help correct the Standard Model.

The search for new physics currently being done involves studying the Higgs Boson. The Large Hadron Collider (LHC) at CERN (European Center for Nuclear Research) uses high energy proton collisions to produce and study fundamental particles, such as the Higgs Boson. Since the discovery of the Higgs Boson in 2012, there has been a lot of work done to study its properties such as its production and decay [1]. Some of the things being looked at is how the Higgs Boson couples to other particles during production and decay. The search for non-SM Higgs Bosons revolves around these couplings, which are a part of BSM physics.

Accompanying the results of Run 1 data analysis, theoretical and computational work have been done to prepare for the upgraded energy, 8 TeV to 13 TeV, Run 2 data at the LHC. The Higgs Boson can be produced through a few different modes, and Run 1 has yielded about 30 possible Higgs events, with a majority of them being produced through the Gluon Fusion mode. Another way the Higgs Boson can be produced is through a process called Vector Boson Fusion (VBF), which had one possible event from Run 1 [1]. VBF is more likely to occur with the upgraded â&#x2C6;&#x2014;

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energy of the LHC and detected with the Insertable B-Layer (IBL) sub detector upgrade to the ATLAS detector.

To fully understand this process however, requires a deeper analysis of the production vertex.

This is done through utilization of an effective field theory (EFT) to understand the BSM physics contributions. We are trying to easily model each BSM contribution independently from the EFT. This will give us insight on how each affects the production vertex which will allow scientists at CERN to identify the production mode and couplings involved, as well as identifying the properties of the Higgs Boson in question to see if it is BSM or SM. This can be done through a method call morphing, which morphs base samples of set couplings together in order to easily produce a specific sample of certain couplings. To do morphing properly, you need a minimum number of base samples generated, and a high enough number of events. These can be found from the cross section (which refers to that of the production vertex) of the process in conjunction with the sample weights [2].

The goal of this project was to aid in the creation of a code that acts as a morphing function generator, which will give the number of base samples needed to perform morphing for any combination of values of the BSM coupling constants in a VBF process. Assuming a cut-off scale for new physics is applied, we can put constraints on the values of BSM contributions at play. From the EFT, an equation can be found that gives the cross section in terms of coupling constants and coefficients. This equation is to be added to the code when all of the coefficients are found, which can be done using the Monte Carlo Generator, MadGraph5. With the obtained coefficients of the cross section equation, we can find the cross section of the process with any couplings and in turn, the number of base sample events needed for morphing.

Vector Boson Fusion The context in which the code is being developed for and tested in, is the production of the Higgs Boson through Vector Boson Fusion. VBF is a process in which the Higgs Boson is produced through the collision (fusion) of a W ± or a Z ± boson. These two vector bosons come from quarks that undergo a weak decay. Vector bosons are the force carriers of the weak interaction, which is why they come from the quark decay. At the LHC, proton (p) beams are accelerated to high enough energies that allow for pp collisions to occur, which yield parton showers. From these jets come the quarks that experience the weak decay that VBF uses. The pairing of the vector bosons that results in a Higgs Boson should be W ∓ W ± * or ZZ ∗ , where the plus/minus is the spin and the star is a virtual particle [3, 4]. Fig. 1 is the Feynman diagram that represents a VBF production process.

The probability of this process happening is described by a parameter called the branching ratio, which is as follows, BR =

Γi . Σi Γi

(1)

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Figure 1. The Feynman diagram for VBF. q and q 0 are quarks and scattered quark showers respectively. W and Z are the vector bosons, and H is the Higgs Boson [3]. The vertex at which the W, Z, and H meet, is where the EFT is being applied, since physically, it is more than a point, i.e. a loop(s).

In Eq. (1), Γi is the number of events of the process being considered and the Σi Γi is the total number of events, where events are the produced Higgs Bosons. Run 1 of the LHC which used 8 TeV as the center of mass energy (4 TeV for each proton beam), yielded only one candidate of produced Higgs Bosons that was produced through VBF, and only about 30 total Higgs events.

The branching ratio of VBF shows that this process is less likely to occur at current accelerator energies [3, 4]. From this, the need for higher energy beams becomes apparent. The greater energy will result in an increase of Higgs events in various production modes. This will be achieved with the LHC Run 2 energy upgrade to 13 TeV, along with the upgraded luminosity, i.e. the ratio of the number of events in a certain time to the cross section (which by definition includes the production and decay vertices) of the process.

The need for a higher energy to produce Higgs Bosons through VBF tells us that the production vertex of the process occurs with a large amount of energy. This high energy scale can be predicted to exceed that of the Standard Model. If the vertex has a higher energy scale than the SM-scale, then there is Beyond Standard Model physics occurring. The production vertex is studied to look at properties of the Higgs Boson such as its couplings, and in this case, the couplings are considered to be BSM contributions. The BSM contributions can be described by an effective field theory (EFT), which describes them in general [5].

Effective Field Theory An Effective Field Theory is used to describe something complicated in a simplified way to get relevant answers without having to fully understand the details. EFTs are useful when the details in question cannot investigated directly. In our case an EFT is being used to describe the Higgs production vertex. The production vertex in Fig. 1 is represented as a point, which is most likely not physically accurate. What is meant by this is that, within the production vertex there is physics

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Figure 2. The EFT representation of the VBF production vertex.

occuring as single and/or as a combination of loops occurring simultaneously. Fig. 2 shows how the EFT can be represented to describe the production vertex.

The reason that the production vertex is acting in this way can be attributed to the high energy that it entails. If this is the case, then the interactions are non-SM physics. This means that the EFT framework that needs to be established will describe this new scale. This can be achieved by creating an effective Lagrangian that describes higher order contributions expanded on the SM Lagrangian [6]. This can be done in the following way: Lef f = LSM + LD=6 .

(2)

A Lagrangian is an equation that describes a system of particles and fields that is restricted by its degrees of freedom. The SM-Lagrangian describes the fundamental forces and particles which are included in the Standard Model. Eq. (2) describes the way in which the SM-Lagrangian can be modified by adding higher-dimension terms than that of the SM to get the Lagrangian for the EFT. The higher-dimension terms are dimension-6 operators, which augment the Higgs couplings [7]. The EFT framework that is utilized results in the following effective Lagrangian for the Higgs interaction with two vector bosons under the Higgs Characterization Model with the 14 BSM couplings

(3) This effective Lagrangian comes from the Higgs Characterization Model. It is the Lagrangian for the interaction of the spin-0 Higgs Boson with two vector gauge bosons. It describes the non-

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SM couplings of the Higgs Boson as 14 EFT operators. These couplings are the BSM contributions that are being studied within the VBF production vertex, particularly, the way in which the higher dimension BSM operators affect it [8]. While useful as a first step to the deeper analysis of Higgs phenomenology; it would be preferable to understand the details i.e. the effect of each operator.

Morphing Experiment The goal of the experiment is to be able to model the contributions of the different BSM operators on the VBF production vertex independently through morphing using independent Monte Carlo samples. The final x-dimensional analysis histograms (or the final data sample) can be produced by morphing the histograms from individual Monte Carlo samples according to a simple analytical relation, presented in the following equation S (g1 , g2 , . . . ) =

N X

0

0

Wi (g1 , g2 , . . . )Si (g1i , g2i , . . . ).

(4)

i=1

This is the analytical relation for morphing where S is the sample of interest, (g1 , g2 , . . . ) are the coupling constants of interest, Wi are the sample weights, and Si is the set of N base samples 0 0 produced at fixed couplings (g1i , g2i , . . . ). This allows us to model easily the BSM contribution of interest (i.e. specific choice of couplings) by mixing a finite set of base samples. Essentially, morphing can be used to produce any sample needed by combining the proper set of base samples.

The benefit of this method is that morphing can be done with any set of base samples [2, 5]. This method also saves a lot of computation time because it allows for easier modeling by eliminating the need to generate every sample (i.e. every possible combination of couplings within the cross section in the different process possibilities) individually.

To properly perform the morphing, the correct number of samples is needed, which depends on the number of couplings being considered and their values. Just as important, enough events are needed. The morphing will only happen correctly if there is a high enough number of generated events; which also gives better statistics for data. To get the number of events, one needs to know the weight (Wi ) coefficients, which are obtained from a morphing function, and the cross section of the base samples [2]. From the Lagrangian presented in Eq. (3), an equation can be derived for the cross section of the production vertex in terms of coefficients and couplings. To find the coefficients we can use the Monte Carlo Generator, MadGraph5. By finding the coefficients, we can use the equation to find the cross section of the process with any couplings and in turn, the number of base sample events needed for morphing.

Monte Carlo Simulation Using MadGraph5, Monte Carlo generator, I was able to generate multiple cross sections of base samples with set couplings. Using the data from these samples and the maximum cross section of 1.25Ă&#x2014;(SM-cross section) for a VBF production process, I was able to solve for all 55 coefficients by reducing the equation, i.e. setting non-relevant couplings to 0 to cancel out terms.

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The equation for the cross section σ (‘sig’) that has been implemented into the morphing code is presented below in a type-set format for the code along with the table of the values found for the coefficients.

(5) The coefficients (C . . .) were found by generating Monte Carlo samples using MadGraph5 with varying coupling constants (k . . .) and solving the reduced equation using 1.25 as ‘sig.’ The cross Table 1. The found values of the coefficients in Eq. (5) with three parameter values

section, 1.25×(SM-cross section), was used to put constraints on the couplings. This cross section is found from Run 1 data to be the maximum possibility, so we assume that any cross section with BSMl terms is less than this. Within MadGraph5, the process generated was VBF under the Higgs Characterization Model. After editing the run card.dat file to use the proper parameters (such as 13 TeV) as well as changing the param card.dat file to the appropriate coupling values and proper parameters (such as SM term, cos α, cut-off scale), the cross section (in pb) is generated for the process pp → Hj using leading order (LO) computations [9].

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Conclusion The cross section result has been implemented into the code, tested, and validated for 13 TeV LO production cases (in the CERN software library) [9]. Since real Higgs processes cross sections have production and decay vertices with different couplings and combinations, a different cross section and morphing code is needed to produce more general results on a broader spectrum. The correction between NLO (one extra parton) and LO computations is small, but NLO cases are to be studied for more precise results. Ref. 9 is the full report on the entire morphing project and offers a more detailed discussion. The 13 TeV energy upgrade to the LHC and higher luminosity will produce more Higgs bosons in different production channels and the IBL upgrade will increase the detection rate of different decay modes. This will produce exciting new data from real events for the computational and theoretical work to be compared to. This morphing technique will be a convenient way to predict what the new data will look like.

Acknowledgments I would like to thank the Manhattan College Department of Physics and Dr. Constantine Theodosiou, for their support and encouragement. I would like to especially thank Dr. Rostislav Konoplich, for inviting me to go to CERN under his National Science Foundation grant No. 1402964 and for being my mentor. I would to thank Dr. Rani Roy, for all of her guidance and support. I would like to thank the New York University Department of Physics, for being the home institution for my trip to CERN and hosting me. I would like to especially thank Drs. Peter Nemethy and Allen Mincer, for adding me to the NYU ATLAS team. I would like to thank all of the people at CERN and ATLAS that I worked with, who gave me a very insightful and humbling experience.

Especially K. Prokofiev, for teaching me about the project and including me on various talks, and A. Sakharov, for connecting me with people in ATLAS to work with.

References [1] G. Aad, et al. [ATLAS Collaboration], “Observation of a new particle in the search for the Standard Model Higgs boson with the ATLAS detector at the LHC,” Phys. Lett. B 716, 1 (2012) [arXiv:1207.7214 [hep-ex]].

[2] N. Belyaev et al. “EFT Morphing Studies Progress.” 2015. Presentation. CERN. [3] C. D. Burgard, “Study of Higgs boson production via Vector Boson Fusion in 0 H → W ∓ W ±(∗) → l− ν˜ l + ν 0 the decay mode with the ATLAS Detector,” Master’s thesis, Albert-Ludwigs-Universit¨at Freiburg, 2013.

[4] M. Carena et al. [Particle Data Group], “Status of Higgs Boson Physics,” July 29th , 2014, http://pdg.lbl.gov/2013/reviews/rpp2013-rev-higgs-boson.pdf [5] N. Belyaev et al. “Monte Carlo For The Tensor Structure Analysis In The Higgs Sector.” 2015.

Presentation. CERN.

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[6] A. Falkowski, “Effective Lagrangian approach to physics beyond the standard model,” LPT Orsay, 22 September 2014, Presentation.

[7] A. Falkowski, “Effective Field Theory Approach to LHC Higgs Data,” [arXiv:1505.00046v2 [hep-ph]] [8] F. Maltoni, K. Mawatari, and M. Zaro, “Higgs characterisation via vector-boson fusion and associated production: NLO and parton-shower effects,” Eur. Phys. J. C74 (2014), no. 1 2710, [arXiv:1311.1829].

[9] A. Kaluza, D. Gray, et al. The ATLAS Collaboration. “A morphing technique for signal modelling in a multidimensional space of coupling parameters,” ATLAS Internal Note, ATLPHYS-PUB-2015-047 (10th November 2015)

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APPENDIX. My trip to CERN and work with ATLAS While at CERN I was able to work with ATLAS first hand in a few different capacities. Being able to work so directly with ATLAS was incredible because I was able to see and do things that most people don’t get to, even if they are on the ATLAS Collaboration! For three weeks I shadowed a few people and their groups in different parts of ATLAS where they showed and let me help with their work.

The first week I was introduced to a young engineer named Joel. He was in charge of installing various things to the data acquisition racks. I accompanied him into “the caverns,” which is an area that is a hundred meters below ground but also a hundred meters above the ATLAS Detector.

There, I worked on helping him install cooling racks and pipes to the DAQ racks. I also helped install different monitoring sensors to the racks. Joel explained to me how some of the circuits are made up by connecting the sensors on each rack to each other. At one point, I almost removed something but asked first. Joel informed that had I removed, what looked like a broken wire, it would have shut done ATLAS because the circuit would no longer have been mirrored.

The second week I worked with a man named Phillip who was the run coordinator at the Muon Desk in the ATLAS Control Room. He showed me how ATLAS works from the control room. I was able to experience what it was like to have shifts, where people monitor different parts of ATLAS. He explained a lot about the control room, like the status screens that showed the detector and sub detectors status and the status of the beam from CERN Central Control. Working with Phillip was great because he informed so much about the general operation of the LHC and ATLAS. The third week I was with people in the ATLAS Satellite Control Room. The people over there were mainly involved with the software side of things. They were also involved with the Pixel sub detector and the new Inner-B Layer detector. I worked with a man named Geoffrey who worked in the Pixel and IBL labs. He was doing some circuit mapping for DAQ rack testing. He also showed me another lab that he was using for senor durability testing. For this he was using a pressure and humidity chamber. I also worked with a man named Marcello, who was in charge of the DAQ boards for IBL. He showed me some of the software behind it as well as the computer boards they used. I went to an electronics lab with him where he was having his colleagues work on testing some of the boards. I also went down to the caverns with him where he hooked up boards to actual DAQ racks for testing. I also got to help with them while they were doing signal testing on the test DAQ racks. I felt particularly useful because they were using oscilloscopes, which was really the only piece of equipment I was familiar with over there. Being able to work for and explore ATLAS was an amazing and truly unique experience.

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Figure 3. The author working for ATLAS. The top left picture, working in the IBL and Pixel Lab. The top right picture, working in the caverns on DAQ racks. The bottom picture, working in the ATLAS Control Room.

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Fractal analysis of diffraction and interference patterns Christina Hibnerâ&#x2C6;&#x2014; Department of Physics, Manhattan College Abstract. Fractal analysis was conducted on the interference patterns of sound waves traveling through Chladni plates (Fig. 1). It was found that as the images progress diagonally, the fractal dimension increased and the lacunarity remained relatively constant. This suggests the Chladni plate patterns are self-similar to some extent.

Background A fractal is a simple infinitely repeating pattern that can result in shapes of infinite complexity.

Fractals are commonly found in nature. As an example, consider a tree branch, which splits from one unit into two, then into four, then eight, then sixteen, and so on. These patterns have a unique geometrical property in that they are self-similar. Self-similarity is when a small section of a shape strongly resembles the whole shape [1] (Fig. 2).

Figure 1. Chladni plate

Figure 2. Self-similarity

To analyze these patterns, we must find their fractal dimension, which is the ratio that shows the index of complexity of a fractal pattern by comparing how the shape of the pattern changes with the scale at which it is measured. These measurements are performed with box counting, which involves superimposing a grid of boxes of increasingly small sizes over the pattern and counting the number of boxes that overlap the pattern (Fig. 3). A comparison to a pixel display can be drawn, in which a denser array of pixels yields greater detail. As the box size approaches zero, smaller self-similar units can be measured [2]. Using this method, we can determine how much space the pattern takes up when examined at small scales.

Another way to examine a fractal is to look at its lacunarity, which describes the texture of a fractal. If it has large gaps or holes in its structure, it will have a high lacunarity. Similarly, when â&#x2C6;&#x2014;

Research mentored by Bruce Liby, Ph.D.

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Figure 3. Box counting demonstration

Figure 4. Increasing lacunarity from left to right

it is a complete, whole fractal with all of its branches, it has a low lacunarity. Fig. 4 demonstrates increasing lacunarity from left to right.

A Chladni plate is a metal plate of any shape with a pin in the center whose edges are allowed to move freely (Fig. 1). When silica sand is poured on top of a vibrating plate, a distinct pattern emerges [3]. There are a few methods for vibrating the plates. I connected the fixed metal pin to a mechanical oscillator that is capable of inducing vibration at constant, measurable frequencies.

Another method is to anchor the pin to a fixed surface and expose the plate to intense sound of similarly regular frequencies, e.g. using powerful speakers. Using a violin bow to vibrate the plate (Fig. 1) is mainly used for demonstration; this method is not very good for computational analysis because the frequencies are unknown.

I used a square 24 cm Ă&#x2014; 24 cm plate of an unknown metal. When two waves interact, they create an interference pattern. When two waves that are equal are traveling in opposite directions through a medium cross each other, their energies momentarily add resulting in a wave amplitude twice as big as that of the individual waves. This is called constructive interference. After interfering, the two waves continue on their way unchanged. Similarly, when two waves of equal but opposite amplitudes cross each other, the resultant wave has no amplitude and is therefore flat.

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Figure 5. Constructive and destructive interference

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Figure 6. Standing wave in 1 dimension

This is called destructive interference (Fig. 5). When these waves come one after the other at the right frequency, they interact to form a standing wave. Standing waves are like jump ropes or guitar strings; they have at least one fixed point called the boundary condition from which a wave reflects to cause interference along the medium (Fig. 6).

Chladni plates have a boundary condition which is as follows [4]:

A Chladni plateâ&#x20AC;&#x2122;s interference pattern is made of standing waves in 2-dimensions. Think of Fig. 6 as a side-on image of a Chladni plate. The sand bounces away from the parts of the plate that are vibrating the most, called the antinodes, and falls into the places where the plate is not vibrating at all, called the nodes. However, when waves interact in 2-dimensions, instead of forming point-like nodes, they form nodal lines (Fig. 7).

Figure 7. Interference in 2 dimensions

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The patterns these interactions form are dictated by the equation

where m is the number of nodal lines parallel to the y-axis and n is the number of nodal lines parallel to the x-axis [4]. Fig. 8 shows all possible Chladni plate interference patterns.

Figure 8. Chladni plate interference patterns [5]

Methods ImageJ FracLac [2] is an open source program which uses box counting to analyze fractals.

FracLac measures how much space a pattern takes up by using increasingly small side lengths and counting the number of boxes that overlap at the pattern for each box size. This allows us to measure the degree of how a 1-dimensional becomes a 2-dimensional pattern. As the pattern becomes more and more complex, what was once a line begins to fill a 2-dimensional space. The fractal dimension should always be between 1 and 2 for this reason. FracLac calculates the fractal dimension as well as the lacunarity for the fractal image. Because direct images of the Chladni plates of sufficient quality could not be obtained from Fig. 8, each pattern was replicated using Microsoft Paint tools â&#x20AC;&#x201C; the pre-programmed shapes and curves.

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Results The images I duplicated from the chart of Chladni sketches (Fig. 8) were run though FracLac [2]. Fig. 9 is a graph of fractal dimension and lacunarity when m and n are equal.

Figure 9. Fractal Dimension and lacunarity when m is equal to n

On the scale of fractal dimension, the numbers from 0 to 1 were removed because fractal dimension can only be between 1 and 2. There is a clear upward trend of fractal dimension, as one moves down the main diagonal of the chart, which means that fractal dimension rises as m = n = 1, 2, 3, . . . . On the contrary, lacunarity remains relatively constant.

Discussion Analysis of these patterns show that the fractal dimension increases, which means the index of complexity increases from the top left corner to the bottom right corner of Fig. 8; the detail of the pattern became more and more complex as the scale used to measure it got smaller. Boxcounting revealed that 1-dimension progresses into 2-dimensions going from the top left corner to the bottom right corner of the chart. In other words, as the complexity of the pattern increased, the fractal dimension increased, which was expected. However as the complexity of the pattern increased, the lacunarity did not change much. Even though the complexity is increasing, the measurement of the gaps and holes stays relatively constant. This suggests a â&#x20AC;&#x153;zooming outâ&#x20AC;? along the diagonal, which supports the assertion that these patterns are self-similar.

Determining the boundary condition for the Chladni plate has proven elusive. Because the Chladni plate is connected to the mechanical oscillator at the center of the plate, there is an antinode at the center. It is unknown whether Waller [5] introduced the vibrations using the method used here, by introducing vibrations via a violin bow, or via speakers directed at the plate (in which case a node would be at the center of the plate), or another method.

Conclusion The interference patterns of sound waves traveling through Chladni plates were examined using an open source program designed to analyze fractals using box counting. That the lacunarity

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stayed relatively constant suggests that the patterns from the top left corner of Fig. 8 to the bottom right corner are successively â&#x20AC;&#x153;zooming outâ&#x20AC;? from the same pattern, which means they are selfsimilar.

Because light is also a wave, it interacts much like sound waves, constructively and destructively, creating an interference pattern when isolated using two small slits or a fine mesh screen.

Laser light interference pattern research is currently ongoing because it is very difficult to analyze.

The quality of the picture is very important to analysis through FracLac. Minute variants of light are harshly highlighted when the image is converted to binary for analysis. Further research will be conducted.

Acknowledgement The author thanks the School of Science Research Scholars Program for financial support.

References [1] Falconer, Kenneth. Fractals; A Very Short Introduction. New York: Oxford University Press.

2013.

[2] ImageJ FracLac user guide. http://imagej.nih.gov/ij/plugins/fraclac/FLHelp/Introdu-ction.htm [3] Bourke, Paul. Chladni Plate Mathematics, 2D. March 2003. http://paulbourke.net/geometry /chladni/ [4] Xiao, Wence. Chladni Pattern. Basic Studies in the Natural Sciences, RUC. May 31 2010. http://rudar.ruc.dk/bitstream/1800/5190/1/Chladni%20Pattern.pdf [5] Waller, Mary D. Vibrations of Free Square Plates: Part I. Normal Vibrating Modes. Lecturer in Physics, London (R.F.H.) School of Medicine for Women, 1939. http://iopscience. iop.org/0959-5309/52/4/304/pdf/prv52i4p452.pdf

Limits on Higgs Boson Couplings in Effective Field Theories Thomas Reid∗ Department of Physics, Manhattan College Abstract. I review the Effective Field Theory (EFT) to make projections on physics beyond the Standard Model in the Higgs sector. I provide relations between the non-Standard Model couplings of the Strongly-Interacting Light Higgs (SILH) effective Lagrangian implemented in the eHDecay package and the corresponding terms of the spin-0 Higgs Characterisation model’s effective Lagrangian used with the aMC@NLO Monte Carlo generator. Constraints on BSM couplings are determined on the basis of existing experimental limits on Higgs boson width and branching ratios.

Introduction to the Higgs Boson In the latter half of the twentieth century, an effort to establish the relationship between the four fundamental interactions (electromagnetic, strong, weak, and gravitational) and all elementary particles, observed and postulated, was undertaken. By the 1970’s, a working theory had emerged in the literature, and it was quickly dubbed the Standard Model (SM). Since then, the predictions of the SM have been repeatedly vindicated by experiment, and while its success has not been unqualified, no other theory so complete has been able to threaten its preeminence in the worldview of modern physicists.

The SM predicts that all elementary particles are conferred mass in part during their interaction with the Higgs field. Mass being a fundamental characteristic of matter, the Higgs field is as such an integral component of the SM. If experiments were to fail to verify its existence, drastic revisions to the SM and, by extension, many hard-won intuitions about the principles undergirding elementary particle physics, would be required. For that reason, proof of the Higgs field has been placed among the most pressing issues in science. But, obtaining it poses an issue – the Higgs field cannot be detected directly.

Fortunately, a solution exists. From QFT, we know that the Higgs field, if it exists, must instantiate as an elementary particle itself – what we have deemed the Higgs boson. The Higgs boson should be quite massive (relatively speaking), and therefore unstable – liable to decay into smaller particles. And, unlike the Higgs field and even the Higgs boson itself, we have the means of detecting those smaller particles straightforwardly. So, if the Higgs boson exists, confirming its existence could be a matter of ascentaining whether we can observe the decays that we predict are characteristic of it. AAnd, obtaining such confirmation, we would have confirmation of the Higgs boson and, then, the Higgs field.

More fortunate still, this is not conjecture. In 2012, having used essentially this very method, CERN (European Organization for Nuclear Research) research teams ATLAS and CMS jointly announced that they had collected cross-sections compelling enough to constitute a discovery of ∗

Research mentored by Rostislav Konoplich, Ph.D.

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the Higgs boson. Their achievement has affirmed the validity of the core of the SM, and, now, we can move with confidence toward a new set of scientific opportunities.

Effective Field Theory For now, it would be wise to set aside the more exotic possibilities, as we may still encounter new physics a little closer to home. In spite ATLAS’s and CMS’s triumph, a quandary remains: We may have found a Higgs boson, but is it the one we predicted? This question requires a subtle distinction. Of course, the discovery of the Higgs was announced as such because the discovered particle bears a sufficiently close resemblance to the theoretical one, but that is the issue – there is room for disparities between the characteristics of the discovered particle and those of the SM Higgs in which it is still safe to describe the discovered particle as “the Higgs boson”. But, that does not necessarily make such disparities unimportant, and finding any may require a reevaluation of accepted theories and, thus, new physics.

To the great credit of the SM, no significant differences between the discovered Higgs and the theoretical Higgs have yet been found. However, there are certain questions about our universe’s Higgs boson which, for now, lay just beyond our ability to answer. To be more specific, they are questions about the relationship between the couplings of the two particles, which are the terms in the Lagrangians that dictate how the Higgses interacts with other elementary particles. We wish to determine whether the couplings of the discovered particle deviate to any degree from the SM ones, but the only way to satisfy our interest is with decay cross-sections derived from more energetic particle collisions. This is to say that we need data from the newly upgraded Large Hadron Collider, and, unfortunately, the LHC has yet to complete its latest run. However, in the meantime, work can still be done. To prepare for the possibility that the new data will reveal coupling deviations that the current data does not, we can create computational models that correspond to a potential non-SM Higgs.

Used in conjunction with Monte Carlo simulators like MadGraph 5, such models can be used to forecast the behavior of theories for which data not yet been produced, which is helpful for determining practical properties like branching ratios and widths.

Practicality is key. Without the data, the whys of the non-SM Higgs’s behavior are not important. For now, our main concern is providing experimentalists with the projections they need to refine their analysis once the data becomes available. For that reason, the models I will be evaluating concern only “measurables” – those properties like branching ratio and width that are only relevant for, in our case, extracting the Higgs boson from statistical noise. Such models are called effective field theories [1].

For this research, I looked at two effective field theories. The effective Higgs Lagrangian constructed by Artoisenet, et al. [2] follows. It has recently become quite popular, and it would be wise to understand it better. Broadly, this formula depicts the researchers’ conception of a non-SM Higgs boson. Each term corresponds to a particular coupling [2].

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(1)

eHDecay The second effective field theory we considered is the one implemented into HDecay by Contino, et al. [3]. Formally speaking, the implementation modified HDecay such that it now includes “the full list of leading bosonic operators of the Higgs effective Lagrangian with a linear or nonlinear realization of the electroweak symmetry and . . . two benchmark composite Higgs models” [3]. For me, it is of greatest importance that (1) eHDecay (the name of the implementation) is a computational suite, which allows me to calculate branching ratios and widths in all decay channels for arbitrary coupling coefficients and (2) that each term in the Lagrangian can be converted into its counterpart in Artoisenet et al.’s Lagrangian.

(2)

Conversion Formulas As stated, it is important that I be able to convert the couplings of the eHDecay Lagrangian into the terms of those of Artoisenet, et al.’s Lagrangian. Parity between these two effective field theories permits me to make projections about Artoisenet, et al.’s Lagrangian for branching ratios and width by simply utilizing the computational package already present in eHDecay. Such projections were previously impossible to make.

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Depicted here are the conversions I made – Artoisenet, et al.’s coupling coefficients in terms of eHDecay’s.

Branching Ratio and Width Before I go on, I will define the terms “branching ratio” (B) and “width” (W ). The width is ~ over the particle lifetime τ, W =

~ τ

(1)

and is used for measuring the energy a particle possessed during its lifetime or, given an finite lifetime, the range of energy over which the particle could have existed.

The branching ratio is the ratio of “signal” events to total events (the identity of the signal being a matter of the researcher’s discretion), B=

Γi . Σi Γi

(2)

In this formula, gamma represents events, and i the category of events in question. For us, events are Higgs decays.

Limits from Branching Ratio and Width With the conversions in hand, I could set about our simulations. At this stage, I had two goals: (1) Determine the highest value for each coupling coefficient that could be achieved in any decay channel before a negative B (a physical impossibility) was yielded and (2) do the same for width, except with 22.0 MeV as the ceiling rather than a negative output.

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Figure 1. Branching Ratio (WW) vs. Coupling (CWW)

Table 1. eHDecay coupling coefficients vs. every Higgs decay channel

CWW CZZ CWdW CZdZ

BB

ττ

µµ

SS

CC

TT

GG

γγ

Zγ

WW

ZZ

5.9 68.5 3.9 35.4

5.9 68.5 3.9 35.4

5.9 68.5 3.9 35.4

5.9 68.5 3.9 35.4

5.9 68.5 3.9 35.4

5.9 68.5 3.9 35.4

5.9 68.5 3.9 35.4

5.9 68.5 3.9 35.4

5.9 68.5 3.9 35.4

1.4 68.5 0.9 35.4

5.9 2.0 3.9 1.1

Table 2. Coupling coefficient value at which a width of 22.0 MeV was obtained

CZγ Cgg Cγγ

Coupling (+)

Coupling (-)

12.687 1.6593 5.827

-12.673 -1.6715 -5.82

Table 1 is of CWW, CZZ, CWdW, and CZdZ eHDecay coupling coefficients vs. every Higgs decay channel. Table 2 is of the Zγ, gg, and γγ coupling coefficients vs. positive and negative coupling values. In Table 1, each cell corresponds to a coupling coefficient value at which a negative branching ratio was obtained. Highlighted are the lowest values that yielded a negative B for each coupling coefficient or, in other words, the upper bound for that coupling. The remaining three couplings are not pictured because they proved to be limitless. In Table 2, each cell corresponds to a coupling coefficient value at which a width of 22.0 MeV was obtained. This width is important because it represents the current experimental limit of the LHC. Similarly, the remaining four coupling coefficients are not pictured because they proved to be limitless here.

Fig. 1 is one of many plots I obtained during my research of the Branching Ratios for the WW

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Figure 2. Width (MeV) vs. Coupling (Cγγ)

decay channel vs. CWW coupling values. Such a plot could serve as an indicator of the likelihood that Artoisenet et al.’s [2] Higgs boson will decay by the WW decay channel given any CWW coupling value. It is especially useful because it is constrained to the CWW limit shown before.

As a result, it can be guaranteed that this data is physical. The final point sitting below the x-axis is the limit – the couplings can be raised no higher.

Fig. 2 is a similar plot, but for width. This plot, width vs. Cγγ coupling values, demonstrates the energy the Higgs decay for each given coupling value until 22.0 MeV, the current LHC limit.

Both plots can help experimentalists interpret data potentially corresponding to a non-SM Higgs.

Conclusion This research accomplished two things – the derivation of a relationship between the corresponding terms of Artoisenet, et al.’s [2] and eHDecay’s [3] effective Lagrangian and, taking advantage of that newly established relationship, the determination of the experimental constraints of a non-SM Higgs corresponding to Artoisenet, et al.’s Lagrangian.

Acknowledgement The author would like to thank Dr. Rostislav Konoplich for his support and guidance during this research; work supported in part by NSF Grant No. 1402964. He would also like to thank Drs. Constantine Theodosiou and Rani Roy for their support.

References [1] A. Alloul, B. Fuks, and V. Sanz, JHEP 1404 (2014) 110, [arXiv:1310.5150].

[2] P. Artoisenet, et al., JHEP 1311 (2013) 043 [arXiv:1306.6464 [hep-ph]].

[3] R. Contino et al. Comput. Phys. Commun. 185, 3412 (2014), [arXiv:1403.3381 [hep-ph]].

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