Biodiversitas vol. 11, no. 3, July 2010 by Biodiversitas Unsjournals

ISSN: 1412-033X (printed edition) ISSN: 2085-4722 (electronic)

Journal of Biological Diversity V o l u m e

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N u m b e r

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FIRST PUBLISHED: 2000

ISSN: 1412-033X (printed edition) 2085-4722 (electronic)

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BIODIVERSITAS Volume 11, Number 3, July 2010 Pages: 107-111

ISSN: 1412-033X (printed edition) ISSN: 2085-4722 (electronic) DOI: 10.13057/biodiv/d110301

Chloroplast DNA variation of Shorea acuminata Dyer in Eastern Sumatra assessed by microsatellite markers ZULFAHMI1, â&#x2122;Ľ, ISKANDAR ZULKARNAEN SIREGAR2, ULFAH JUNIARTI SIREGAR2 1

Department of Agrotechnology, Faculty of Agricultural and Animal Science, State Islamic University of Sultan Syarif Kasim Riau, UIN SUSKA Campus at Panam, PO Box 1004, Pekanbaru 28293, Riau, Indonesia, Tel. +62-761-562051, Fax +62-761-562052. â&#x2122;Ľe-mail: fahmi2509@gmail.com 2 Department of Silviculture, Faculty of Forestry, Bogor Agricultural University (IPB), IPB Campus at Darmaga, PO Box 168, Bogor 16680, West Java, Indonesia Manuscript received: 2 January 2010. Revision accepted: 21 May 2010

ABSTRACT Zulfahmi, Siregar IZ, Siregar UJ (2010) Chloroplast DNA variation of Shorea acuminata Dyer in Sumatra assessed by microsatellite markers. Biodiversitas 11: 107-111. Shorea acuminata Dyer is member of the Dipterocarpaceae family. It is ecologically and commercially important in the Indonesian region. In the present study, chloroplast microsatellites (cpSSRs) were used to study the distribution of chloroplast DNA haplotypes and to assess the variation within and among populations of S. acuminata from Riau and Jambi provinces eastern part of Sumatra. Based on chloroplast microsatellite analysis, six haplotypes were observed for S. acuminata, namely haplotype P, Q, R, S, T, and U, respectively. The high haplotype variation was detected in Bukit Barisan National Park (TNBT) population (five haplotypes); it may be due to TNBT population status as national parks (conservation area) under government protection. The value of genetic differentiation measured for S. acuminata was Gst = 0.150. The Gst values in this study is lower than the mean Gst value estimated in angiosperms plant for maternally inherited. Information on the status of genetic variation of the species in this study could be used as scientific consideration in formulating appropriate strategies for conservation and sustainable utilization of genetic resources. Key words: Dipterocarpaceae, Shorea acuminata, chloroplast microsatellites, genetic variation.

Indonesian tropical rain forest is rich in genetic resources. Rapid destruction of forests due to illegal logging, forest fires, and over exploitation has been threatening the existence of genetic resources in forest ecosystem. We must consider how to conserve the genetic diversity of the tropical rain forest. For this purpose, we started a study of genetic variation in forest trees (Shorea acuminata) which is one of high quality timbers in Indonesia. Shorea acuminata Dyer is a member of the genus Shorea (section Mutica) in the Dipterocarpaceae family. This tree is distributed in a mixed dipterocarp forest in Malaysia, Sumatra and Lingga (Ashton 1982). In Indonesia, it is known locally as meranti bunga, and belongs to the light red meranti timber group (Newman et al. 1996). Meranti bunga is an important timber because of its economic value. The hard wood of meranti bunga is suitable for heavy construction, to make poles, flooring, furniture, window panels, and doors. Meranti bunga is one of the fast growing species among other dipterocaps for planting as quality timber in Indonesia (Soekotjo and Wardhana 2005). Genetic variation is the fundamental requirement for the maintenance and long term stability of forest ecosystem since the amount and pattern of genetic variation would determine the ability of forest tree species to adapt on

variable environment condition. Information on the genetics of species would be useful in designing appropriate tree breeding program and conservation of genetic resources. One of the genetic resources conservation objectives is to prevent the species extinction. Genetic information as life history (evolution) and population structure knowledge of plants are important for development of sound genetic conservation strategies. Therefore, there are needs to know status of variability of chloroplast DNA, mitochondria and nuclear genome of plants. Studies on genetic variation of S. acuminata have been conducted based on various markers targeted at nuclear DNA such as RAPDs, (Harada et al. 1994), microsatellites (Takeuchi et al. 2004; Tani et al. 2009), AFLPs (Cao et al. 2006, 2009), DNA sequencing (Ishiyama et al. 2003; Kamiya et al. 2005; Inomata et al. 2008). In this study, we analyzed the chloroplast genome using the microsatellite markers. We choose the chloroplast genome due to its uniparental inheritance, the absence of recombination, and slow mutation rates (Provan et al. 2001). The objectives of this research were to determine distribution of chloroplast DNA haplotypes and to estimate the genetic diversity of chloroplast DNA within and among populations of S. acuminata.

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MATERIALS AND METHODS Sample collection Leaf tissues from seedlings or poles or trees of the Shorea acuminata were harvested from natural populations in Sumatra. The number of individuals collected per population is showed in Table 1. Field distance among individuals was kept at around 150 m. The samples collected in the fields were stored in plastic packages containing silica gel with ratio leaf to silica (1:5 g), subsequently stored in a freezer at temperature -60oC until DNA extraction was performed. DNA extraction and PCR-cpSSR Total DNA was extracted from dry leaf tissue (2 cm2) using the Dneasy 96 Plant DNA isolation Kit (Qiagen, Hilden). The extraction was done following the manufacturer’s instructions. The quality of DNA isolation results was visualized in 0.8% (w/v) agarose gels. Electrophoresis was performed using 1X Tris-acetate (TAE) buffer for about 30-80 minutes at 100-150 V. The quality of DNA was examined in comparison to a Molecular Weight Standard (Lambda DNA Marker, Roche Mannheim). Ten universal primers, namely consensus chloroplast microsatellite primers (ccmp) ccmp1 to ccmp10 (Weising and Gardener 1999) were tested in order to analyze the chloroplast microsatellite genome. The amplification of cpSSRs was performed using fluorescence dyed forward primers (Metabion) for genotyping purpose, namely 6-FAM/Blue (ccmp2, ccmp4, ccmp6 and ccmp9), HEX/Green (ccmp1, ccmp3, ccmp7 and ccmp10) and NED/yellow (ccmp5 and ccmp8). The PCR procedure was according to Indrioko (2005) using the following reaction conditions: initial denaturation for 15 minutes at 95oC, followed 35 cycles of denaturation for 1 minute at 94oC, annealing for 1 minute at 50oC, extension for 1 minute at 72oC and final extension for 10 minutes at 72oC. Reaction mix (15 µl) of PCR reagents was prepared as follows: 2.0 μl template DNA (5-10 ng), 1.8 μl forward primers (5 pmol/μl) and reverse primers (5 pmol/μl), 1.9 μl Distillated water, and 7.5 μl HotStarTaq Master Mix Kit (Qiagen, Hilden). PCR products were separated on 2.0% (w/v) agarose gels and quality of DNA was examined in comparison to a Molecular Weight Standard XIV (100 bps ladder) DNA Marker (Roche Mannheim). The gel was stained in ethidium bromide solution for about 20 minutes at room temperature; the banding patterns of gel were observed under UV light apparatus in the dark room and documented using a digital camera.

11 (3): 107-111, July 2010

Genotyping of PCR products The reagents for genotyping (96 probes) were composed of: 1152 μl HiDi Formamide (Applied Biosystem) and 1.5 μl GS 500 ROX TM (Applied Biosystems). The reagents mix was distributed equally into 96 samples tubes (12 μl each sample), and then 2 μl of the amplification product of each sample was added to the tubes. The samples were denaturated for 2 minutes at 90oC, subsequently stored on ice for about 5 minutes before capillary electrophoresis. The separation was done by capillary electrophoresis on an automated sequencer ABI PRISM 3100 Genetic Analyzer (Applied Biosystems) with polymer 3100 POP4TM (Applied Biosystems). The length of electrophoresis products expressed in base pairs was measured with the help of the internal size standard GS500 ROX TM (Applied Biosystems). Individual alleles were analyzed using GeneScan Version 3.7 (Applied Biosystems) and Genotyper Version 3.7 NT (Applied Biosystems). Data analysis Haplotypes were inferred as combination from individual alleles sizes found at each locus. In analyzing fragment patterns of cpSSR, the fragments are coded with 1 and 0 indicating the presence or absence of fragments. Haplotype frequencies and population structure was calculated using the POPGEN Software Version 32 (Yeh et al. 1999). UPGMA dendogram analysis based on Nei’s genetic distance (1972) was calculated with NTSYSpc Software Version 2.0 (Rohlf 1998). RESULTS AND DISCUSSION cpSSR haplotypes The ten chloroplast microsatellite (cpSSR) primers ccmp1-ccmp10 (Weising and Gardener 1999) were tested initially in two samples per population. Out of ten chloroplast microsatellites primers used, five primers (ccmp4, ccmp5, ccmp7, ccmp8 and ccmp9) showed no amplification products, whereas five primers (ccmp1, ccmp2, ccmp3, ccmp6 and ccmp10) were successful to be amplified in all DNA samples. Out of these five primers, three primers (ccmp1, ccmp2 and ccmp10) showed monomorphic patterns with fragment sizes of 113 bp, 150 bp and 101 bp, respectively. At ccmp3 and ccmp6 primers showed polymorphic patterns. Amplification products of ccmp3 revealed presences of four length variants (100 bp, 101 bp, 102 bp and 104 bp), while the products of ccmp6 showed only two length variants (97 bp and 98 bp). In total, there were observed six haplotypes (Table 2).

Table 1. The number of individuals (N), approximate latitude and longitude, and haplotype frequency of S. acuminata per population. Province District Jambi Riau Riau

Tebo Pelalawan Indragiri Hulu

Population name

Longitude o

Pasir Mayang Nanjak Makmur Bukit Tigapuluh National Park (TNBT)

6 101 48’57”-101 49’17”E 7 101o30’37”- 103o21’36”E 7 102o13’-102o45’E

Total

Latitude o

00 52’32”-01o54’17”S 00o46’24”-00o24’34”S 00o40’-01o30’S

ZULFAHMI et al. â&#x20AC;&#x201C; Chloroplast microsatellite variation in Shorea acuminata Table 2. Definition of haplotypes and fragment sizes of cpSSRs Haplotypes P Q R S T U

Fragment amplification sizes of cpSSR (bp) ccmp3 ccmp6 101 97 101 98 98 100 102 97 104 97 100 97

cpSSR haplotypes variation Based on Genescan results, there were six haplotypes observed for S. acuminata, namely P, Q, R, S, T and U, respectively. Details of haplotype frequencies in S. acuminata are shown in Table 3. Hapotype P, Q and T are only observed in TNBT population, haplotype R in TNBT and Nanjak Makmur populations, Haplotype S in Pasir Mayang, TNBT and Nanjak Makmur populations, whereas haplotype U is only found in Pasir Mayang population. The high haplotype variation was detected in TNBT population (five haplotypes); it may be due to TNBT population status as national parks (conservation area) under government protection. In general, the number of haplotype variation is low in this study. The low chloroplast DNA haplotypes is closely related to slow mutation rates (Provan et al. 2001). A low number of haplotypes was also observed in Populus tremula (six haplotypes, Salvini et al. 2001), wild Grapevine (five haplotypes, Grassi et al. 2006), Fraxinus excelsior (six haplotypes, Hebel et al. 2006), Fraxinus ornus (four haplotypes, Heuertz et al. 2006), and Hagenia abyssinica (six haplotypes, Ayele et al. 2009). One the other hand, high chloprolast DNA haplotype variation was observed in Oak (Deguilloux et al. 2004b), Fraxinus excelsior L. (12 haplotypes, Heuertz et al. 2004), Fagus sylvatica (14 haplotypes, Vettori et al. 2004), Ulex (47 haplotypes, Cubas et al. 2005), Fraxinus angustifolia (13 haplotypes, Heuertz et al. 2006), S. boivinii (14 haplotypes, Pardo et al. 2008), and S. genistoides (30 haplotypes, Pardo et al. 2008). Genetic variation within and among populations Values of genetic differentiation measured for S. acuminata was Gst = 0,150 (Hs = 0,203; Ht = 0,239). This value indicated that moderate gene flow among populations of S. acuminata, which is explained by restricted seed dispersal due to relatively heavy seeds and dispersed by wind or gravity. Although seed of S. acuminata dispersal

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distances can be up to 500 m or even further, more than half of the mature seeds land within 50 m of the parent tree under forest conditions (Takeuchi et al. 2004). The Gst values in this study is lower than the mean Gst value estimated in angiosperm plants for maternally inherited DNA (Gst = 0.637, Petit et al. 2005) and another study for some species such as Arabis holboellii (Gst 0.20, Dobes et al. 2004); Fagus sylvatica (Gst = 0.855, Vettori et al. 2004); wild Grapevine (Gst = 0.631, Grassi et al. 2006); Fraxinus ornus (Gst = 0.983, Heuertz et al. 2006); Fraxinus angustifolia (Gst = 0.964, Heuertz et al. 2006); and Hagenia abyssinica (Gst = 0.899, Ayele et al. 2009). The low of Gst estimated based on chloroplast microsatellite markers were also obtained in Populus tremula. L (Gst = 0.07, Salvini et al. 2001); Cunninghamia lanceolata (Gst = 0.017, Hwang et al. 2003); Cunninghamia konishii (Gst = 0.073, Hwang et al. 2003); and Magnolia stellata (Gst = 0.137, Setsuko et al. 2007). The geographic distribution of haplotypes for S. acuminata does not correspond with geographical separation among populations (Figure 1). In S. acuminata, six haplotypes (P, Q, R, S, T, and U) were found. Five out of the six haplotypes were found in TNBT population, two haplotypes in Pasir Mayang and Nanjak Makmur populations. This result also showed that haplotype P, Q, and T was specifically in TNBT population and haplotype U was specifically in Pasir Mayang population. The specific haplotype may be useful for the detection of species geographical origin. This study was first method to explore the possibility of using molecular marker as tool to prove the geographical origin of the individual trees. The DNA method to detect the geographic origin of species has been developed in Oak species (Deguilloux et al. 2002; 2003; 2004a) and Dipterocarps species (Finkeldey et al. 2007; Indrioko 2007; Lee and Tnah 2007; Nuroniah 2009; Finkeldey et al. 2010). Genetic distance indicates the genetic relationship among populations. Genetic distances among populations, namely TNBT and Pasir Mayang, Nanjak Makmur and Pasir Mayang, and Nanjak Makmur and TNBT was 0.0942, 0.0129, and 0.0791, respectively. UPGMA dendograms (Figure 2) based on Neiâ&#x20AC;&#x2122;s genetic distance (1972) showed that S. acuminata was divided into two clusters with Pasir Mayang and Nanjak Makmur populations forming first a cluster, and TNBT population forming a second cluster. TNBT population was separated from another population due to high haplotype diversity within population.

Table 3. The number of individuals (N), approximate latitude and longitude, and haplotype frequency of S. acuminata per population. Province

District

Population name

Jambi Riau Riau

Tebo Pelalawan Indragiri Hulu

Pasir Mayang 6 Nanjak Makmur 7 Bukit Tigapuluh National Park (TNBT) 7 Total 20

P 0.000 0.000 0.143

Q 0.000 0.000 0.143

Haplotypes R S 0.000 0.833 0.143 0.857 0.143 0.286

T 0.000 0.000 0.286

U 0.167 0.000 0.000

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Implications on conservation of genetic resources of Shorea acuminata in Sumatra One of the goals of the conservation of genetic resources is to prevent species extinction. Genetic conservation of S. acuminata can be made either in situ or ex situ. In situ conservation requires a large population size, whereas ex situ conservation requires collection from represented individuals so that genetic diversity within population is maintained. Based on differentiation values of S. acuminata (Gst = 0.150) showed that moderate level of genetic diversity partitioned between populations. The most important conservation objective is preservation of maximum number alleles of target species. Therefore, if insitu conservation and sampling for ex-situ conservation of S. acuminata will be established, we recommend that S. acuminata conservation could be implemented in TNBT population for Sumatra island due to high haplotype diversity and habitat status of this population which is found in a national park.

2 3 1

SUMATRA

Haplotypes: P

U CONCLUSION

Figure 1. Geographical distribution of haplotypes chloroplast microsatellite in S. acuminata. Note: 1. Pasir Mayang, 2. Nanjak Makmur, 3. Bukit Tigapuluh National Park (TNBT). Pasir PasirMayang Mayang

Nanjak Makmur

TNBT TNBT

Figure 2. Dendogram of UPGMA cluster analysis on S. acuminata based on Neiâ&#x20AC;&#x2122;s genetic distance (1972).

The six haplotypes were observed for S. acuminata populations in Sumatra, namely P, Q, R, S, T and U, respectively in which TNBT population possessed high haplotype diversity. The genetic differentiation in the three studied populations was moderate (Gst = 0.150). It was suggested to use the available information as scientific consideration in formulating genetic conservation strategies of the species.

ZULFAHMI et al. – Chloroplast microsatellite variation in Shorea acuminata

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BIODIVERSITAS Volume 11, Number 3, July 2010 Pages: 112-117

ISSN: 1412-033X (printed edition) ISSN: 2085-4722 (electronic) DOI: 10.13057/biodiv/d110302

Genetic diversity of sago palm in Indonesia based on chloroplast DNA (cpDNA) markers

BARAHIMA ABBAS1,â&#x2122;Ľ, YANUARIUS RENWARIN1, MUHAMMAD HASIM BINTORO2, SUDARSONO2, MEMEN SURAHMAN2, HIROSHI EHARA3 Faculty of Agriculture and Technology (FAPERTEK), The State University of Papua (UNIPA), Manokwari 98314, West Papua, Indonesia. Tel. 0986211095, Fax. 0986-211095, â&#x2122;Ľe-mail: barahimabas@yahoo.com 2 Faculty of Agriculture, Bogor Agricultural University (IPB), IPB Campus at Darmaga, Bogor 16680, West Java, Indonesia 3 Faculty of Bioresources, Mie University, 1577 Kurimamachiya,Tsu-city, Mie-Pref. 514-8507, Japan Manuscript received: 16 November 2009. Revision accepted: 16 June 2010.

ABSTRACT Abbas B, Renwarin Y, Bintoro MH, Sudarsono, Surahman M, Ehara H (2010) Genetic diversity of sago palm in Indonesia based on chloroplast DNA (cpDNA) markers. Biodiversitas 11: 112-117. Sago palm (Metroxylon sagu Rottb.) was believed capable to accumulate high carbohydrate content in its trunk. The capability of sago palm producing high carbohydrate should be an appropriate criterion for defining alternative crops in anticipating food crisis. The objective of this research was to study genetic diversity of sago palm in Indonesia based on cpDNA markers. Total genome extraction was done following the Qiagen DNA isolation protocols 2003. Single Nucleotide Fragments (SNF) analyses were performed by using ABI Prism GeneScanR 3.7. SNF analyses detected polymorphism revealing eleven alleles and ten haplotypes from total 97 individual samples of sago palm. Specific haplotypes were found in the population from Papua, Sulawesi, and Kalimantan. Therefore, the three islands will be considered as origin of sago palm diversities in Indonesia. The highest haplotype numbers and the highest specific haplotypes were found in the population from Papua suggesting this islands as the centre and the origin of sago palm diversities in Indonesia. The research had however no sufficient data yet to conclude the Papua origin of sago palm. Genetic hierarchies and differentiations of sago palm samples were observed significantly different within populations (P=0.04574), among populations (P=0.04772), and among populations within the island (P=0.03366), but among islands no significant differentiations were observed (P= 0.63069). Key words: genetic diversity, sago palm, chloroplast DNA, haplotype, Indonesia.

INTRODUCTION Sago palm (Metroxylon sagu Rottb.) is capable to accumulate high carbohydrate content in its trunk. The potential of sago palm accumulating high carbohydrate content will be good choice crops for anticipating carbohydrate crisis in the world. Increasing utilities of sago palm need genetic diversity information within the species. The genetic diversity of this plant is important to comprehend for germplasm conservation and breeding program in the future. Up to present information on genetic diversity of sago palm is very limited. Previous studies examined the levels diversity of sago palm by using RAPD markers (Ehara et al. 2003; Barahima et al. 2005) and AFLP (Celiz et al. 2004). One of the most important markers for assessing genetic diversity of plant is cpDNA. The chloroplast genome of eucaryotes evolved from endosymbiotic an ancestral cyanobacterium (Douglas 1998). Most chloroplast genes of higher plants are organized in clusters and co-transcribed as polycistronic pre-RNAs, which are generally processes into shorter overlapping RNA species (Sugita and Sugiura 1996). The circular double-stranded DNA contains a pair of inverted repeats of 25,156 bp which are separated by a small and a

large single copy region of 18,271 bp and 81,936 bp, respectively (Kato et al. 2002). A total of 84 predicted protein-coding genes including 7 genes duplicated in the inverted repeat regions, 4 ribosomal RNA genes and 37 tRNA genes (30 gene species) representing 20 amino acids species were assigned on the genome based on similarity to genes previously identified in other chloroplasts (Kato et al. 2002). Chloroplast DNA (cpDNA) diversity was exhibited in several species. Intraspecific variation of cpDNA sequences was detected in Fagopyrum cymosum (Yamane et al. 2003). Estimated interspecific sequence divergence of Astragalus was reached 3.92% (Liston 1992). Amplification specific chloroplast genes of Conifers by polymerase chain reaction (PCR) were detected at 23, 26, 38, 48, 67, and 25 site changes in frxC, rbcL, psbA, psbD, trnK, and 16S, respectively among species of Conifer (Tsumura et al. 1995). A molecular phylogeny of dipterocarpaceae was constructed which was revealed by 141 site changes in different specific chloroplast genes: rbcL, psbA, psbD, rpoB, rpoC, petB, atpH, 16S, psaA, petA, and trnK (Tsumura et al. 1996). Chloroplast DNA are suitable marker for assessing genetic relationship among individuals of plant or plant species such as Prunus species (Badenes and Parfitt 1995),

ABBAS et al. â&#x20AC;&#x201C; Diversity of sago palm based on cpDNA markers

Pinus species (Wang et al. 1999), Fagopyrum species (Yamane et al. 2003), among cultivars of Swichgrass, Panicum virgatum L. (Hultquist et al. 1996), and among accessions of Syringa (Kim and Jansen 1998). The chloroplast genome have been demonstrated that is maternal inheritance in apples (Savolainen et al. 1995; Ishikawa et al. 1992), and largely conserved sequences such as chloroplast gene rbcL encoding the large subunit of the RuBisCo of Cucumber, Pumpkin, and Rose (MacKenzie et al. 2002). The chloroplastic atpB and rbcL coding sequences were found only five divergence sequence in 904 base pairs chloroplast DNA of 40 apples cultivars (Savolainen et al. 1995). The molecular markers which are very conservative markers and preferable for revealing genetic diversities should be chloroplast DNA (cpDNA) markers. In the previous study, the cpDNAs were already applied for revealing genetic diversities of barley (Russel et al. 2003), potato (Bryan et al. 1999), alfalfa (Mengoni et al. 2000),

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and several species of plant (Raamsdonk et al. 2003; Kormuak et al. 2003; Viard et al. 2001; Besnard et al. 2002; Parducci et al. 2001). The objectives of research were to reveal the diversities and the differentiations of sago palm in Indonesia based on cpDNA markers. MATERIALS AND METHODS Total genome extraction Leaf tissue samples were preserved by using silica gel granules (Chase and Hill 1991). DNA extraction was following Qiagen DNA isolation protocols 2003. A total 97 samples of sago palm were collected from six islands and nine populations of sago palm centre in several islands in Indonesia. The location and the vernacular name of samples that were used in this experiment were presented in Table 1 and Figure 1.

Table 1. The populations and the vernacular name of sample used Island

Population

Vernacular name of sample

Papua

Jayapura

Bharahabow, Bharahabow-1, Bharawalisa, Bharawalisa-1, Bharawalisa-2, Folo, Folo-1, Folo-2, Hobolo, Osukhulu, Osukhulu-1, Osukhulu-2, Phane, Phane-1, Phane-2, Rondo, Rondo-1, Ruruna, Ruruna-1, Ruruna-2, Wani, Wani-1, Yakhalobhe, Yebha, Yerirang, Yerirang-1, and Yerirang-2 Aming, Aming-1, Animpeun, Awa, Awa-1, Awa-2, Huworu, Huworu-1, Huworu-2, Kurai, Kurai-1, Kurai-2, Sunare, Sunare-1, Sunare-2, Weun, Owawu mambai, Owawu Ureifasei, Owawu-1, Umar, Umar-1, Umbeni, Woru), and Woru-1 Antah, Anandong, MKW, MKW-1, MKW-D1, and MKW-D2 Bosairo, Bosairo-1, Bosairo-2, Igo, Kororo, Kororo-1, Raimamare, Raimamare-1, and Raimamare-2 Hihul, Tuni, and Makanalu Tawaro-1, Tawaro-2, Tawaro-3 and Tawaroduri Sagu-1, sagu-2, sagu-3, sagu-4, sagu-5, sagu-6, sagu-7, sagu-8, sagu-9, sagu-10, sagu-11, sagu-12, sagu-13, sagu-14, sagu-15, sagu-16, sagu-17, and sagu18. Kirai-1 and Kirai-2 Molat, Riau-1, Riau-2, Riau-D1, Riau-D2, Rotan, and Tuni-R

Serui

Maluku Sulawesi Kalimantan

Manokwari Sorong Maluku Palopo Pontianak

Java Sumatra

Bogor Selat Panjang

1 3

7 6

8 9

5 4 2 0

500

1000 km

Figure 1. The map of sampling sites of sago palm used. The cycles represent the population sampling: 1. Selat Panjang, 2. Bogor, 3. Pontianak, 4. Palopo, 5. Ambon, 6. Sorong, 7. Manokwari, 8. Serui, 9. Jayapura

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Chloroplast DNA Amplification The cpDNA of sago palm was amplified by using three pairs of primer (rpl1671, NTCP21 and NTCP22) and performed by using polymerase chain reaction (PCR). The PCR reaction mix consisted of 2.5μl of 10x buffer containing 15 mM MgCl2, 0.5μl of 2.mM dNTP (GeneAmpR mix, Warrington, UK), 10μg of BSA, 0.25μl each of NTCP21 primer pairs (forward primer 44.8 nmol and reverse primer 54.8 nmol) and NTCP22 primer pairs (forward primer 40.8 nmol and reverse primer 49.4 nmol), 0.42 U Ampli Taq GoldTM (Applied Biosystems) and 10ng genomic DNA. The PCR cycle conditions were as follows: initial denaturation step of 4 min at 94oC, followed by 35 cycles of 30 second denaturation at 94oC, 1 min annealing (9 level touchdown) at 59oC for the first cycle, decreasing by 1oC per cycle until the annealing temperature reached 51oC, then continuing 26 cycles at 51oC, 1 min extension at 72oC, and an additional 5 min extension at 72oC at the end of 35 cycles.

number of individual analyzed in a population and pi is the frequency of the i-th haplotype in the the populations, Nei 1987). The Genetic Hierarchies and differentiations were estimated by the Analysis of Molecular Variance (AMOVA, Excoffier et al. 1992) by using Arlequin software (ver. 2.000, Schneider et al. 2000, University of Geneva, Switzerland). This test can estimate sources of variance (SV) such as among individuals, within populations, among populations within groups, and among groups. Significant values were calculated by a permutation test from 16000 permutated matrices. The AMOVA was based on distances between cpDNA haplotypes calculated from the sum of the squared number of repeat differences between two haplotypes with formula: dxy = ∑(axy -ayi)2, axy and ayi are the number of repeats for the ith locus in haplotype x and y.

Single nucleotide fragment (SNF) analysis The analysis was performed by using ABI Prism GeneScanR 3.7. The three primer sets used (rpl1671, NTCP21, and NTCP22) were labeled with FAM, HEX, and NED respectively which synthesized by Qiagen and the PCR reaction was perform as describe above. The total volume cocktail needs for Gene Scan reaction were 11μl as follows: mixed Hi-DiTM Formamide and GeneScaneTM – 500 RoxTM size standard (20: 1) and 1μl DNA PCR which have been amplified by fluorescent primer then denatured at 95 μl for 2 min before the plate well insert into Gene Scan tools.

Polymorphism of cpDNA Primers rpl1671, NTCP21 and NTCP22 generated PCR products of 100 samples, but no-polymorphism were detected on 3% agarose gels. SNF analysis by using fluorescence primers observed polymorphic on 97 of 100 samples whereas other three samples failed to detect amplification fragments. The characteristic of the fluorescence primer sets were showed in Table 2. The performance of SNF analyses can be seen in Figure 2. The nucleotide detections clearly appeared in each individual sample. Primer pairs of rpl1671-FAM produced 4 alleles in the ranges of the sizes 147 to 406 base pairs (bp), primer pairs of NTCP21-HEX produced 5 alleles in the ranges of the sizes 76 to 406 bp, and primer pairs of NTCP22-NED produced 2 alleles in the ranges of 75 to 160 bp (Table 2). In the previous study, Primer pairs of NTCP21 and NTCP22 also detected alleles polymorphism in potato (Bryan et al. 1999).

Data analysis The genetic diversities were calculated by using Infinite Allele Model (IAM, Kimura and Crow 1964). The effective number of haplotypes (ne = 1/∑Pi2 ) and the haplotypic diversity (HE = [n/(n-1)][1- ∑pi2 ], n is indicated the

RESULTS AND DISCUSSIONS

Table 2. Characteristic of three cpDNA loci were observed on sago palm Primers name rpl1671-FAM NTCP21-HEX NTCP22-NED

Primer Sequences (5’-3’) F: gct atg ctt agt gtg tga ctc; R: tca tat agt gac tgt ttc tt F: aaa aag atc cca caa aga aaa; R: ctt atc gat tcc tgt caa aaa g F: tat cag aaa aag aaa aag aag g; R: gtc aaa gca aag aac gat t

Location in Tobacco No information ORF74A exon ORF74A/trnS intergenic region

Figure 2. Sample of single nucleotide fragment analyses by using ABI PRISM GeneScanR3.7

Numbers of alleles 4 5 2

Base pairs (bp) sizes 147- 406 76 - 406 75 - 160

ABBAS et al. â&#x20AC;&#x201C; Diversity of sago palm based on cpDNA markers

Haplotypes identification and composition In the three cpDNA loci (rpl1671, NTCP21 and NTCP22) of sago palm were observed ten haplotypes and eleven alleles in the populations of sago palm (Table 3). Haplotypes H01 and H02 were located in two cpDNA loci and haplotypes H03 to H10 were located in three cpDNA loci. Composition of haplotypes frequencies in the populations was showed in Table 4. Haplotypes H01, H02, H07, and H09 were found spread into two or more than two populations. Only small individual of sago palm were moved from certain population to others because only four of ten haplotypes were shared into two or more than two populations, which indicated that four haplotypes only of sago palm were estimated to migrate by many ways. In the related studies by using cpDNA markers were also reported that there were refugee population in the species of P. sylvestris L. and A. alba Mill. (Provan et al. 1998; Vendramin et al. 1999). Haplotype H05 was found only in the population of Palopo with 0.25 frequencies and haplotype H10 was found only in the population of Pontianak with 0.06 frequencies. Haplotypes H04, H06, and H08 were only found in the population of Jayapura with 0.04, 0.04, 0.12 frequencies respectively. Haplotype H03 was found only in the population of Serui with 0.04 frequencies, so that we found four specific haplotypes in the Papua islands. In these observations we found six specific haplotypes which were distributed in Papua, Sulawesi, and Kalimantan islands. Specific haplotypes phenomenon was also found in the species of Pinus sylvestris L. (Provan et al. 1998), Alyssum spp. (Mengoni et al. 2003), and Cunninghamia spp. (Hwang et al. 2003). Specific haplotypes in the populations indicated that population should be origin of diversities, but the research can not mention the populations of sago palm were diverse because the populations also have a haplotype which shared overall population (H07 in Table 4). Populations from Papua island (Jayapura and Serui), Sulawesi island (Palopo), and Kalimantan island (Pontianak) which belongings specific haplotypes should be origin of sago palm diversities. The degree of haplotypes numbers can be used as one of many indicators to show the centre of diversities. Vendramin et al. (1999) and Mengoni et al. (2003) reported that high number of haplotypes indicated high level of variation. The presence of the widespread common haplotype was indicated a major ancient population (Provan et al. 2001). Papua islands should be origin and centre of sago palm diversities because it has the highest specific haplotypes and the highest numbers of haplotypes, as well as existence of wild types. Haplotypes were described in this study should be existed in a long time in the past because cpDNA markers highly conservative sequences (Provan et al. 2001), very low mutation rates which range from 3.2 x 10-5 to 7.9 x 10-5 (Provan et al. 1999), no recombinant DNA (Ishikawa et al. 1992; Provan et al. 2001) and uniparentally inherited (Savolainen et al. 1995; Viard et al. 2001). The highest numbers of haplotypes indicated the highest variation in the population such as occurred in the population of Abies alba Mill. (Vendramin et al. 1999). Mengoni et al. (2003) documented that the differentiation of chloroplast

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haplotypes in the population reflected genetic entity. The other report was similar with our observation as follows: Flach (1983) and Flach (1997) were documented that Papua islands are the highest of sago palm diversities based on morphological characters and the widest wild stands. Based on the diversities and vast wild stands the Papua islands should be considered as the centre of diversity (Flach 1997). In Papua also were recognized the highest sago palm varieties based on morphological characters and environmental adaptability (Yamamoto et al. 2005). Table 3. Haplotypes identification of 97 samples of sago palm by using cpDNA markers No. of Haplotypes H01 H02 H03 H04 H05 H06 H07 H08 H09 H10

rpl1671-FAM allels (bp) 147 158 159 406 76 0 0 1 0 0 0 0 1 0 0 0 1 0 0 0 1 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 1 0 0 1 0 0

NTCP22NED allel (bp) 99 160 161 406 75 160 0 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 1 0 0 0 1 0 1 0 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 0 1 0 1 0 0 0 0 1 0 1 0 0 0 0 1

NTCP21-HEX allels (bp)

Table 4. Composition of haplotype frequencies based on 11 polymorphic alleles from 3 cpDNA loci Haplo1 2 3 4 5 6 7 8 9 type H01 - 0.04 0.08 H02 0.14 0.50 0.31 - 0.33 - 0.12 H03 - 0.04 H04 - 0.04 H05 - 0.25 H06 - 0.04 H07 0.86 0.50 0.63 0.75 0.67 1.00 1.00 0.77 0.58 H08 - 0.12 H09 - 0.04 0.15 H10 - 0.06 Note: Population from Selat Panjang (1), Bogor (2), Pontianak (3), Palopo (4), Ambon (5), Sorong (5), Manokwari (7), Serui (8), dan Jayapura (9), and Number of haplotypes (H01 to H10).

Genetic diversity The genetic diversities within the island showed that Papua island has the highest values of haplotype numbers, polymorphic sites numbers, and percentages of polymorphic haplotype than any other islands. Java island has the highest mean pairwise differences (Table 5). Haplotype diversity values (HE) among individual were relatively high than overall populations. HE value of one indicated that no haplotype sharing in the sample (single haplotype) or samples different from the others such as occurred in the island of Java. These features occurred probably by the sizes of samples were very limited and criteria of sampling in the population it based on phenotypic differences. In the related cases were also

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recorded in individual tree (Pinus sylvestris L.) within the Woodland (Provan et al. 1998). In the previous study of sago palm using RAPD markers high variance in individual level of sago palm was observed (Ehara at al. 2003) and was also observed using AFLP (Celiz et al. 2004). Table 5. Genetic diversity based on 10 haplotypes and 11 polymorphic alleles Genetic variabilities No. of ∑H S π HE P R populations IP Papua 4 16 8 9 0.9216 0.4544 81.8182 Maluku 1 3 2 1 0.6667 0.6667 9.0909 Sulawesi 1 4 2 1 0.5000 0.5000 18.1818 Kalimantan 1 17 3 2 0.6029 0.5221 27.2727 Java 1 2 2 1 1.0000 1.0000 9.0909 Sumatra 1 7 2 1 0.2857 0.2857 9.0909 Note: average individual number per population (RIP), haplotype number (∑H), polymorphic site number (S), haplotype diversity (HE) mean pairwise differences (π), percentage of haplotype polymorphism (P) Island

Genetic hierarchy and differentiation AMOVA values of sources of variance (SV) indicated that among islands (-3.88% and FCT= -0.03884) were no significantly different, but SVs values of within populations (95.39% and FST=0.04610), among populations irrespective of islands (5.91% and FCT=0.05054), and among populations within the island (8.49% and FSC=0.0817) were significantly different. The highest level of variation percentages was observed within the population (95.39% and FST=0.04610) (Table 6). The largest part of genetic variation in the sample populations was attributed to variation within the population then following by among populations within the island and among populations irrespective of the islands (among populations). Among populations in the Papua island contributed the largest part variation to the total variant. The probabilities of over all SV were significantly different, except among islands were no significantly different. In the previous study on the Pinus sylvestris L. low percentages of variant among populations (3.24%) was observed, but probability value was significantly different (Provan et al. 1998). The negative values were observed for among the islands (Table 6). It means that the islands did not contribute to the total variance. These features similar to the tetraploid alfalfa populations were observed by

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Mengoni et al. (2000). The biological meanings of negative values of coefficient correlation (FCT) were samples among the islands more related than samples within the islands (Schneider et al. 2000). No significant differences among the island can be estimated that the geographical differences were not contributed to population variation. The small percentage of variant among populations were observed (5.91%) in sago palm. This was similar to Parducci et al. (2001) observed in Abies sp. Parducci et al. (2001) reported that variation among populations was low (6.10%), but variation within population or among individuals was high (74.66 %). Another low genetic variation was found in Pinaceae sp. (Viard et al. 2001) and tree species (Austerlitz et al. 2000). These observations showed that the site of within and among populations of sago palm should be the main focus for conservation and sustainable used rather than the site of islands. CONCLUSIONS cpDNA markers were used for accessing genetic diversities of sago palm in Indonesia it showed polymorphism. Ten haplotypes and eleven alleles were found into on 97 samples of sago palm. Specific haplotypes were detected in the population from Papua, Sulawesi, and Kalimantan islands. Sulawesi and Kalimantan islands will be source of sago palm diversities and Papua islands will be origin and centre of sago palm diversities in Indonesia based on cpDNA data. The haplotype numbers were ranged from 2 to 8, the polymorphic sites were ranged from 1 to 9, the mean numbers of pairwise differences were ranged from 0.2857 to 1.0000, the haplotype diversities were ranged from 0.2857 to 1.0000, and the percentages of polymorphic haplotype were ranged from 9.0909 % to 81.8182 %. Genetic hierarchies and differentiations of sago palm samples were estimated by AMOVA which showed significantly differences among individuals and among population. Population from Jayapura was significantly different with population from Palopo and Pontianak. Genetic differentiations of sago palm samples were observed significantly different within the population, among populations, and among populations within the island, but no significantly different was observed among islands.

Table 6. Analysis of molecular variance (AMOVA) based on eleven alleles and ten haplotypes Source of variation (SV) Among island Among populations within an island Within populations Total Among populations irrespective of island

d.f. 5 3 88 96 8

Sum of Variance Percentage of squares components variation 2.382 -0.01573 -3.88 2.634 0.03440 8.49 33.995 0.38630 95.39 39.010 0.40497 5.016 0.02428 5.91

Fixation Index

FCT=-0.03884 FSC =0.08177 FST =0.04610

0.63069ns 0.03366* 0.04574*

FST=0.05914

0.04772*

Note: AMOVA calculation performed by 10,000 permutations. Degree of freedom (d.f), Probability (P) Fixation Index of samples among island levels (FCT), Fixation Index of samples among population within an island levels (FSC), Fixation Index of samples among individual levels or within population levels (FST ), not significantly different (ns), and significantly different (*)

ABBAS et al. â&#x20AC;&#x201C; Diversity of sago palm based on cpDNA markers

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MacKenzie TDB, Campbell DA, Cockshutt AM (2002) Primer design. http://aci.mta.ca/courses/biotechemistry/bc3531/lbs/primer.htm1 Mengoni A, Gori A, Bazzcalupo M (2000) Use of RAPD and micro satellite (SSR) variation to assess genetic relationships among populations of tetraploid alfalfa, Medicago sativa. Plant Breeding 119: 311-317. Mengoni A, Gonelli C, Brocchini C, Galardi F, Pucci S, Gabrielli R, Bazzicalupo M (2003) Chloroplast genetic diversity and biogeography in the serpentine endemic Ni-hyperacculator Alyssum bertolonii. New Phytol 157: 349-356. Nei M (1987) Molecular evolutionary genetics. Colombia University Press, New York. Parducci L, Szmidt AE, Madaghiele A, Anzidei M, Vendramin GG (2001) Genetic variation at chloroplast microsatellites (cpSSRs) in Abies nebrodensis (lojac.) Mattei and three neighboring Abies sp. Theor Appl Genet 102: 733-740. Provan J, Powel W, Hollingsworth M (2001) Chloroplast microsatellites: new tools for studies in plant ecology and evolution. Trend Ecol Evol 16(3): 142-147. Provan J, Soranzo N, Wilson NJ, Goldstein DB, Powel W (1999) A low mutation rate for chloroplast microsatellites. Genetics 153: 943-947. Provan J, Soranzo N, Wilson NJ, McNicol JW, Forrest GI, Cottrell J, Powel W (1998) Gene-pool variation in Caledonian and European scots pine (Pinus sylvestris L.) revealed by chloroplast simplesequence repeats. Proc R Soc B Biol Sci 265: 1697-1705. Raamsdonk LWDV, Ensink W, Heusden AWV, Ginkel MVV, Kik C (2003) Biodiversity assessment based on cpDNA and crossability analysis in selected species of Allium subgenus Rhizirideum. Theor Appl Genet 107: 1048-1058. Russel JR, Booth A, Fuller JD, Baum M, Ceccarelli S, Grando S, Powel W (2003) Patterns of polymorphism detected in the chloroplast and nuclear genomes of barley landrases sampled from Syria Jordan. Theor Appl Genet 107: 413-421. Savolainen V, Corbaz R, Moncousin C, Spchiger R, Manen JF (1995) Chloroplast DNA variation and parentage analysis in 55 apples. Theor Appl Genet 90: 1138-1141. Schneider S, Roessli D, Excoffier L (2000) Arlequin: a software for population genetics data analysis. Ver 2.000. Genetics and Biometry Lab, Department of Anthropology, University of Geneva. Sugita M, Sugiura M (1996) Regulation of gene expression in chloroplasts of higher plant. Plant Mol Biol 32: 315-326. Tsumura Y, Kawahara T, Wickneswari R, Yoshimura K (1996) Molecular phylogeny of Dipterocarpaceae in South Asia using RFLP of PCRamplified chloroplast genes. Theor Appl Genet 93: 22-29. Tsumura Y, Yoshimura K, Tomaru N, Ohba K (1995) Molecular phylogeny of conifer using RFLP analysis of PCR-amplified specific chloroplast genes. Theor Appl Genet 91: 1222-1236. Vendramin GG, Degen B, Petit RJ, Anzidei M, Madaghiele A, Ziegenhagens B (1999) High level of variation at Abies alba chloroplast microsatellite loci Europe. Mol Ecol 8: 1117-1126. Viard F, El-Kassaby YA, Ritland A (2001) Diversity and genetic structure in populations of Pseudotsuga menziesii (Pinaceae) at chloroplast micro-satellite loci. Genome 44: 336-344. Wang XR, Tsumura Y, Yoshimaru H, Nagasaka K, Szmidt AE (1999) Phylogenetic relationships of Eurasian pines (Pinus, Pinaceae) based on chloroplast rbcL, MATK, RPL20-RPS18 spacer, and TRNV intron sequ-ences. Am J Bot 86: 1742-1753. Yamamoto Y, Yoshida T, Miyazaki A, Jong FS, Pasolon YB, and Matanubun H (2005) Biodiversity and productivity of several sago palm varieties in Indonesia. In: Karafir YP, Jong FS, Fere VE (eds). Sago palm development and utilization. Proceeding of the Eight International Sago Symposium in Jayapura, Indonesia. Jayapura, 4-6 Agustus 2005. Yamane K, Yasui Y, Ohmishi O (2003) Intraspecific cpDNA variations of diploid and tetraploid perennial buckwheat, Fagopyrum cymosum (Polygonaceae). Am J Bot 90: 339-346.

B I O D I V E R S IT A S Volume 11, Number 3, July 2010 Pages: 118-123

ISSN: 1412-033X (printed edition) ISSN: 2085-4722 (electronic) DOI: 10.13057/biodiv/d110303

Genetic variability among 18 cultivars of cooking bananas and plantains by RAPD and ISSR markers YUYU SURYASARI POERBAâ&#x2122;Ľ, FAJARUDIN AHMAD Botany Division, Research Centre for Biology, The Indonesia Institute for Sciences (LIPI), Jl. Raya Jakarta-Bogor Km. 46, Cibinong-Bogor 16911, West Java, Indonesia, Tel.: +62-21-8765066/7, Fax.: +62-21-8765063, ď&#x201A;Še-mail: yyspoerba@yahoo.com Manuscript received: 5 February 2010. Revision accepted: 31 May 2010.

ABSTRACT Poerba YS, Ahmad F (2010) Genetic variability among 18 cultivars of cooking bananas and plantains by RAPD and ISSR markers. Biodiversitas 11: 118-123. This study was done to assess the molecular diversity of 36 accessions (18 cultivars) of the plantain and cooking bananas (Musa acuminata x M. balbisiana, AAB, ABB subgroups) based on Random amplified polymorphic DNA (RAPD) and and Inter Simple Sequence Repeats (ISSR) markers and to determine genetic relationships in the bananas. RAPD and ISSR fingerprinting of these banana varieties was carried out by five primers of RAPDs and two primers of ISSRs. RAPD primers produced 63 amplified fragments varying from 250 to 2500 bp in size. 96.82% of the amplification bands were polymorphic. ISSR primers produced 26 amplified fragments varying from 350 bp to 2000 bp in size. The results showed that 92.86% of the amplification bands were polymorphic. The range of genetic distance of 18 cultivars was from 0.06-0.67. Key words: RAPD analysis, Musa acuminata, Musa balbisiana, plantain, cooking bananas.

INTRODUCTION Plantain and cooking bananas (Musa acuminata x M. balbisiana, AAB, ABB subgroups) are important components of food security in the tropics and they also provide income to the farming community through local trade (Crouch et al. 1998). The fruits are usually boiled, steamed, roasted or fried before consumption. The bananas are natural triploid (2n=3x=33) hybrids of two diploid species, M. acuminata Colla and M. balbisiana Colla, which contributed the A and B genomes, respectively (Swennen et al. 1995). The bananas originated in South-east Asia (Ude et al. 2003; Simmonds and Shepherd 1955). The bananas are regarded as the most diverse of Musa subgroups among triploid Musa. These triploid genotypes are virtually or completely sterile and develop their fruit by vegetative parthenocarpy. The accumulation of recurrent somatic mutations followed by human selection for their tasty fruit led to great phenotypic diversity amongst plantain and cooking bananas in the region (De Langhe 1969). Germplasm characterization and classification provide useful information for the genetic improvement of crops (Ortiz 1997). Morphological description has proven very useful for the identification of the large diversity of plantain and cooking banana cultivars that exist in the tropics (Jarret and Gawel 1995). However, close genetic relationships among cultivars as well as frequent somatic mutations and morphological changes due to environment which have resulted in large number of cultivars, are major obstacles that limit the use of this technique. Consequently,

the use of only morphological parameters could result in over- or underestimations of the degree of relatedness among plantain cultivars (Kaemmer et al. 1992). In addition to the use of morphological description in identification of specific banana cultivars, various DNAbased marker techniques are also been employed. These techniques can supply additional information which are not available from the examination of morphological characteristics alone (Jarret and Gawel 1995). The random amplified polymorphic DNA (RAPD) and Inter Simple Sequence Repeats (ISSR) are DNA-based marker techniques that has been successfully used to determine genetic diversity and relationships Musa germplasm (Kaemmer et al. 1992; Howell et al. 1994; Bhat and Jarret 1995; Crouch et al. 2000; Jain et al. 2007; Racharak and Eidathong 2007; Ruangsuttapha et al. 2007; Agoreyo et al. 2008; Brown et al. 2009) and for genome identification (Howell et al. 1994; Pillay et al. 2000), analysis of Musa breeding populations (Crouch et al. 1999), detection of somaclonal variants (Grajal-Martin et al. 1998), and genetic stability (Harirah and Khalid 2006; Ray et al. 2006; Lakshmanan et al. 2007; Venkatachalam et al. 2007). Using these techniques an unlimited number of polymorphic bands can be produced with relative ease from minute amounts of genomic DNA (Welsh and McClelland 1990; Godwin et al. 1997; Reddy et al. 2002) allowing simultaneous screening of a large number of accessions. The present study reports the use of RAPD and ISSR analyses for the assessment of genetic variability among 36 accessions (18 cultivars) of plantains and cooking bananas collection of Cibinong Science Center (CSC).

POERBA & AHMAD – Genetic variability of cooking bananas and plantains

MATERIALS AND METHODS Materials DNA materials consist of 36 accessions (18 cultivars) of Musa acuminata x M. balbisiana, AAB, ABB subgroup collected from different sources and grown at Cibinong Science Center, West Java. The materials were leaf samples dried with silica gel collected from those areas using method for DNA sampling (Widjaya and Poerba 2004). Methods DNA extraction Total genomic DNA was isolated from dried silica leaves according to Delaporta et al. (1983) with the addition of RNase treatment (100 mg mL-1). Isolated DNA was visualized for its quantity and quality by running them in 1% Agarose gel electrophoresis. DNA amplification DNA amplification was performed in Takara Thermocycler according to Williams et al. (1990) with total volume of PCR reaction of 15 µl consisting of 0.2 nM dNTPs; 1X reaction buffer; 2mM MgCl2; 10 ng of DNA sample ; 0.5 pmole of single primer; and 1 unit of Taq DNA polymerase (Promega). Five arbitrary RAPD primers: OPA-18, OPA-13, OPD-08 OPN-06 dan OPN-12 (Operon Technology Ltd.) and two ISSR primers: UBC 834 dan UBC 828 (University of British Columbia, Canada) were used in the analyses. PCR reaction was conducted twice to ensure the reproducibility of RAPD. PCR products were visualized in 2% agarose gel electrophoresis for 60 min at 50 Volt. This was followed by EtBr staining (0.15 µl mL-1) before photographed in gel documentation system (Atto Bioinstruments) and 100 bp ladder (Promega) was used as DNA marker. Data scoring Each band in the RAPD and ISSR fingerprint pattern will be considered as a separate putative locus. Only distinct, reproducible, well-resolved fragments were selected and scored for presence (1) and absence (0) of a band. The binary matrices of RAPD phenotypes will then be assembled for analyses. A similarity matrix was constructed and subjected to cluster analysis following the un-weighted pair group method with arithmetical averages (UPGMA) of the computer program NTSYS-pc version 1.8 (Rohlf 1993). Measurement of genetic distance for pair-wise accessions was based on Nei's unbiased genetic distances (Nei 1978) using POPGENE software (Yeh et al. 1999)

RESULTS AND DISCUSSION RAPD profiles Results of DNA amplification showed that the 36 accession of bananas produced a wide array of strong and weak bands. However, only distinct, reproducible, wellresolved fragments were scored as present or absent band for each of the RAPD primers with 36 accessions. Figure 1 and 2 illustrated the typical level of polymorphisms

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observed among the 36 banana accessions for primer OPA18. For genetic identification purposes, primer used is important to be able to differentiate varieties or cultivars of the species. The DNA amplification produced 63 bands. The amplification products showed that 4.16% were monomorphic and 96.82% were polymorphic bands. Among the selected primers OPD-08 and OPN-06 produced maximum number of polymorphic 15 bands, while OPA-18 produced the minimum number of polymorphic 7 bands. Size of DNA bands varied from 250 bp to 2.5Kbp, OPA-13 being the highest range of DNA size (250bp-2.5 Kb) and OPA 18 is the lowest (250 bp-2.0 Kb) (Table 1). Table 1. List of primers, their sequences, number of amplified fragments and number of polymorphic bands generated by PCR using five RAPD primers.

Primer code OPA-13 OPA-18 OPD-08 OPN-06 OPN-12

Primer PolyTotal nucleotide morphic % Size (bp) sequence bands bands (5’-3’) CAGCACCCAC 13 12 92.31250-2000 AGGTGACCGT 7 7 100 300-1200 GTGTGCCCCA 15 15 100 350-2000 GAACGGACTC 15 15 100 300-1800 CACAGACACC 13 12 92.31300-1700 Total 63 61 96.82

9 10 11 12 13 14

Figure 1. Random amplified polymorphic DNA profiles of 14 Musa accessions using primer OPA-18. Lanes 1–2 = Kepok kuning Jogya (ABB), 3-4 = Kepok Jember (ABB), 5-6 = Kepok OP (ABB), 7-8 = Siam (ABB), 9-10 = Raja sewu (AAB), 11-12 = Raja dengklek (AAB), 13-14 = Raja bulu (AAB), M = 100 bp DNA marker (Promega).

The RAPD profiles indicated that each primer could generate a polymorphism. Number of DNA amplification bands depended on how primer attached to its homolog at DNA template (Tingey et al. 1994). RAPD polymorphism are the result of either a nucleotide base change that alters the primer binding site, or an insertion or deletion within the amplified region (Williams et al. 1990), polymorphism usually noted by the presence or absence of an amplification product from a single locus (Tingey et al. 1994). The differences in polymorphism may be due to the

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3 4

8 9

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10 11 12 13 14 M 15 16 17 18 19 20 21 22

Figure 2. Random amplified polymorphic DNA profiles of 22 Musa accessions using primer OPA-18 Lanes 1-2 = Raja nangka (AAB), 3-4 = Tanduk Bawen (AAB), 5-6 = Pisang puju (ABB), 7-8 = Pisang awak (ABB), 9-10 =Tanduk byar (AAB), 11-12 = Budless Sulawesi (ABB), 13-14 = Raja Kristen (AAB), 15-16= Kepok Amorang (ABB), 17-18 = Raja Sere (AAB), 19-20 = Kepok SP (ABB), 21-22 = Raja Sewu (AAB), M = 100 bp DNA marker (Promega)

11 12 13 14 15 16 M

Figure 3. Inter Simple Sequence Repeats profiles for 16 Musa accessions using primer UBC-834. Lanes 1-2 = Raja Nangka, 3-4 = Raja Kristen, 5-6 = Tanduk Byar, 7-8 = Tanduk Bawen, 9-10 = Raja Sere, 11-12 = Raja Sewu, 13-14 = Taja Dengklek, 15-16 = Raja Bulu, M= 100 bp DNA marker (Promega)

10 11 12 13 14 15 16 17

18 19

Figure 4. Inter Simple Sequence Repeats profiles for 20 Musa accessions using primer UBC-834. anes 1-2 = Pisang Puju, 3-4 = Pisang Awak, 5-6 = Kepok Alpha, 7-8 = Budless Sulawesi, 9-10 = Kepok SP, 11-12 = Kepok Amorang, 13-14 = Kepol Kuning Yogya, 15-16 = Kepok Jember, 17-18 = Kepok OP, 19-20 = Siam, M= 100 bp DNA marker (Promega)

differences in amount of genetic variation that exist among the different accessions. ISSR Profiles Results of DNA amplification showed that the 36 accession of bananas produced a wide array of strong and weak bands. However, only distinct, reproducible, well-resolved fragments were scored as present or absent band for each of the RAPD primers with 36 accessions. Figure 3 and 4 illustrated the typical level of polymorphisms observed among the 36 accessions for primer UBC-834. The DNA amplification produced 28 bands, of which 8.14% were monomorphic, common to all the genotypes, and 92.86% were polymorphic bands. Among the selected primers UBC-826 produced the highest number of polymorphic 15 bands, while UBC-834 produced the lowest number of polymorphic 13 bands. Size of DNA bands varied from 350 bp to 2.0Kbp, UBC-834 being the highest range of DNA size (350bp-2.0 Kb) and UBC-826 is the lowest (Table 2). The ISSR profiles indicated that each primer could generate polymorphisms among the accessions. The polymorphism may be due to mutation at priming sites and/or insertion/deletion event within the SSR region; and the extent of polymorphism also varies with the nature and the sequence repeat (motif) of the primer used (Reddy et al. 2002).

POERBA & AHMAD – Genetic variability of cooking bananas and plantains Table 2. List of primers, their sequences, number of amplified fragments and number of polymorphic bands generated by PCR using two ISSR primers. Primer Primer nucleotide Total code sequence (5’- bands 3’) UBC-826 (AC)8C 15 UBC-834 (AG)8YT 13 Total 28

Polymorphic bands 15 11 26

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accessions which were further divided into two subclusters. Among them, the first subcluster was consist of 8 accessions (4 cultivars of AAB genome) i.e, : Tanduk Byar (25-26), Raja Dengklek (33-34), Raja Bulu (35-36), and Raja Sere (29-30). Second subcluster was composed of 8 accessions (4 cultivars of AAN genome) i.e: Raja Nangka (21-22), Raja Kristen (23-24), Raja Sewu (31-32), dan Tanduk Byar (27-28) (Figure 3). The conventional classification of banana genotypes into distinct genome combinations by Simmonds and Shepherd (1955) is based on their morphological similarity to M. acuminata Colla and M. balbisiana Colla. The cultivars examined in this study clustered accordingly to their hypothetical genetic homologies. These result agreed with Brown et al. (2009), for example cultivars designated having ABB genomic constituent (Pisang Puju, Pisang Awak, Kepok Alpha, Budless Sulawesi, Kepok SP, Kepok Amorang, Kepok Kuning Yogya, Kepok Jember, Kepok OP, and Pisang Siam) are clustered together (Fig 5). The genetic distance values for the 36 accessions (18 cultivars of banana) ranged from 0.06 to 0.67 (Tabel 3). The lowest genetic distance (0.06) was observed between Pisang Puju (1) and Pisang Kepok Alpha (3), while the highest genetic distance (0.67) was detected between Kepok Amorang (6) and Pisang Raja Bulu (18) (Table 3).

Size (bp)

100 400-2000 84.61 350-2000 92.86

Combined analyses of RAPD and ISSR Cluster analysis performed from combining data of both RAPD and ISSR markers generated a dendrogram that separated the genotypes into two distinct clusters. First cluster is composed of all cultivars within ABB genome and second cluster is consist of all cultivars within AAB genome. Twenty accessions (10 cultivars of cooking banana) of M. acuminata x M. balbisiana (ABB) i.e Pisang Puju (1-2), Kepok Alpha (5-6), Pisang Awak (3-4), Budless Sulawesi (7-8), Kepok Siharangan Purba (9-10), Kepok Amorang (11-12), Kepok Kuning Yogya (13-14), Kepok Jember (15-16), Kepok OP (17-18), Siam (19-20) are clustered in the fist group. Second group was contained 16 Table 3. Genetic distance among 18 cultivars of triploid banana 1

0.14

0.06

0.21

0.24

0.22

0.32

0.29

0.25

0.37

0.20

0.26

0.37

0.28

0.37

0.47

0.30

0.33

0.35

0.28

0.41

0.37

0.32

0.37

0.36

0.43

0.40

0.10

0.29

0.33

0.28

0.37

0.33

0.13

0.16

0.29

0.19

0.36

0.26

0.33

0.37

0.15

0.11

0.46

0.39

0.48

0.36

0.34

0.48

0.34

0.26

0.40

0.31

0.58

0.40

0.60

0.47

0.36

0.59

0.53

0.46

0.50

0.41

0.22

0.52

0.55

0.51

0.46

0.47

0.61

0.53

0.58

0.52

0.40

0.35

0.29

0.40

0.32

0.20

0.44

0.34

0.30

0.39

0.28

0.18

0.24

0.45

0.50

0.42

0.43

0.46

0.45

0.48

0.47

0.40

0.42

0.34

0.31

0.40

0.46

0.39

0.48

0.36

0.34

0.48

0.34

0.26

0.40

0.31

0.02

0.22

0.52

0.18

0.42

0.54

0.60

0.41

0.59

0.53

0.49

0.54

0.39

0.49

0.43

0.41

0.37

0.57

0.35

0.46

18 0.60 0.60 0.66 0.42 0.53 0.67 0.62 0.66 0.51 0.63 0.50 0.48 0.40 0.58 0.40 0.54 0.10 Note: Lanes/columns 1 = Pisang Puju, 2 = Pisang Awak, 3 = Kepok Alpha, 4 = Budless Sulawesi, 5 = Kepok SP, 6 = Kepok Amorang , 7 = Kepok Kuning Yogya, 8 = Kepok Jember, 9 = Kepok OP, 10 = Pisang Siam, 11 = Raja Nangka, 12 = Raja Kristen, 13 = Tanduk Byar, 14 = Tanduk Bawen, 15 = Raja Sere, 16 = Raja Sewu, 17 = Raja Dengklek, 18 = Raja Bulu.

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Figure 5. Dendrogram of 36 triploid banana accessions. Accessions 1-2 = Pisang Puju, 3-4 = Pisang Awak, 5-6 = Kepok Alpha, 7-8 = Budless Sulawesi, 9-10 = Kepok SP, 11-12 = Kepok Amorang , 13-14 = Kepok Kuning Yogya, 15-16 = Kepok Jember, 17-18 = Kepok OP, 19-20 = Pisang Siam, 21-22 = Raja Nangka, 23-24 = Raja Kristen, 25-26 = Tanduk Byar, 27-28 Tanduk Bawen, 29-30 = Raja Sere, 31-32 = Raja Sewu, 33-34 = Raja Dengklek, 35-36 = Raja Bulu

CONCLUSION

ACKNOWLEDGMENTS

The five RAPD and two ISSR primers could be used to detect DNA polymorphism in 36 accessions of banana. RAPD primers produced 63 amplified fragments varying from 250 to 2500 bp in size. 96.82% of the amplification bands were polymorphic. OPD-08 and OPN generated the highest amplified bands (15). ISSR primers produced 26 amplified fragments varying from 350 bp to 2000 bp in size. 92.86% of the amplification bands were polymorphic. UBC-826 produced the highest number of polymorphic 15 bands. Cluster analysis performed from combining data of both RAPD and ISSR markers generated a dendrogram that separated the genotypes into two distinct clusters, according to genome constitution. The genetic distance values for the 36 accessions (18 cultivars of triploid bananas) ranged from 0.06 to 0.67. The lowest genetic distance (0.06) was observed between Pisang Puju (1) and Pisang Kepok Alpha (3), while the highest genetic distance (0.67) was detected between Kepok Amorang (6) and Pisang Raja Bulu (18). In conclusion, this research demonstrated RAPD and ISSR markers to be useful tool to detect DNA polymorphisms to examine genetic relationship in CSC banana germplasm.

This study was funded by DIPA Project 2008-2009 entitled â&#x20AC;&#x153;Genetic Assessment of Indonesian Fruitsâ&#x20AC;? by The Indonesia Institute of Science. We are grateful to Herlina for her help during the experiments.

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POERBA & AHMAD – Genetic variability of cooking bananas and plantains plantain landraces (Musa spp., AAB group). Theor Appl Genet 101: 1056–1065. De Langhe F (1969) Bananas (Musa spp.). In: Ferwerda FP, Wit F (Eds.). Outlines of perennial crop breeding in the trapocs. Miscellaneous papers 4. Agricultural University of Wageningen, Wageningen. Delaporta SL, Wood J, Hicks JB (1983) A plant DNA minipreparation. Version II. Plant Mol Biol Rep 4: 19-21. Godwin ID, Aitken EAB, Smith LW (1997) Application of inter simple sequence repeat (ISSR) markers to plant genetics. Electrophoresis 18: 1524-1528. Grajal-Martin M, Siverio-Grillo G, Marrero-Dominguez A (1998) The use of randomly amplified polymorphic DNA (RAPD) for the study of genetic diversity and somaclonal variation in Musa. Acta Horticulturae 490: 445-454. Harirah AA, Khalid N (2006) Direct regeneration and RAPD assessment of male inflorescence derived plants of Musa acuminata cv. Berangan. Asia Pacific J Mol Biol Biotech 1: 11-17. Howell EC, Newbury HJ, Swennen RL, Withers LA, Ford–Lloyd BV (1994) The use of RAPD for identifying and classifying Musa germplasm. Genome 37: 328-332. Jain PK, Saini ML, Pathak H, Gupta PK (2007) Analysis of genetic variation in different banana (Musa species) variety using random amplified polymorphic DNAs (RAPDs). African J Biotech 6: 19871989. Jarret RL, Gawel N (1995) Molecular markers, genetic diversity and systematics in Musa. In: Gowen S (ed.). Bananas and plantains. Chapman and Hall, London. Kaemmer D, Afza R, Weising K, Kahl G, Novak FJ (1992) Oligonucleotide and amplification fingerprinting of wild species and cultivars of banana (Musa spp.). Biotechnology 10: 1030-1035. Lakshmanan V, Venkataramareddy SR, Neelwarne B (2007) Molecular analysis of genetic stability in long-term micropropagated shoots of banana using RAPD and ISSR markers. Electronic J Biotech 10 (1) http://www.ejbiotechnology.info/content/vol10/issue1/full/12. Nei M (1978) Estimation of average heterozygosity and genetic distance from a small numbers of individuals. Genetics 89: 583-590. Ortiz R (1997) Morphological variation in Musa germplasm. Gen Res Crop Evol 44: 393-404. Pillay M, Nwakanma DC, Tenkouano A (2000). Identification of RAPD markers linked to A and B genome sequences in Musa. Genome 43: 763-767. Racharak P, Eiadthong W (2007) Genetic relationship among subspecies of Musa acuminata Colla and A-genome consisting edible cultivated

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bananas assayed with ISSR markers. Songklanakarin J Sci Tech 29: 1479-1489. Ray T, Indrajit I, Saha P, Sampa DAS, Roy SC (2006) Genetic stability of three economically important micropropagated banana (Musa spp.) cultivars of lower Indo-Gangetic plains, as assessed by RAPD and ISSR markers. Plant Cell Tissue Organ Cult 85: 11-21. Reddy MP, Sarla N, Siddiq EA (2002) Inter simple sequence repeats (ISSR) polymorphism and its application in plant breeding. Euphytica 128: 9-17. Rohlf FJ (1993) NTSYS-PC. Numerical taxonomy and multivariate analysis. Version 2.0. Exeter Software, New York. Ruangsuttapha S, Eimert K, Schöder MB, Silayoi B, Denduangboripant J, Kanchanapoom K (2007). Molecular phylogeny of banana cultivars from Thailand based on HAT-RAPD markers. Gen Res Crop Evol 54: 1565-1572. Simmonds NW, Shepherd K (1955) The taxonomy and origins of the cultivated bananas. Bot J Linnaean Soc 55: 302-312. Swennen R, Vuylsteke D, Ortiz R (1995). Phenotypic diversity and patterns of variation in West and Central African plantains (Musa spp., AAB Group, Musaceae). Econ Bot 49: 320-327. Tingey SV, Rafalski JA, Hanafey MK (1994). Genetic analysis with RAPD markers. In: Coruzzi C, Puidormenech P (eds.). Plant molecular biology. Springer, Berlin. Ude G, Pillay M, Ogundiwin E, Tenkouano A (2003) Genetic diversity in an African plantain core collection using AFLP and RAPD markers. Theor Appl Genet 107: 248-255. Venkatachalam L, Sreedhar V, Bhagyalakshmi (2007) Genetic analyses of micropropagated and regenerated of banana as assessed by RAPD and ISSR markers. In Vitro Cellular Dev Biol Plant 43: 267-274. Welsh J, McClelland M (1990) Fingerprinting genomes using PCR with arbitrary primers. Nucleic Acids Res 18:7213-7218. Widjaya EA, Poerba YS (2004) Data collection of germplasm and genetics. In: Rugayah, Widjaya EA dan Praptiwi (eds.). Manual on data collection of flora diversity. Pusat Penelitian Biologi–LIPI, Bogor. [Indonesia] Williams JG, Kubelik AR, Livak KJ, Rafalsky JA, Tingev SV (1990) DNA plolymorphism amplified by arbitrary primers are useful as genetic markers. Nucleic Acids Res 18: 6531-6535. Yeh FC, Yang RC, Boyle T (1999) Popgene Version 1.31. Microsoft Windows-based freeware for population genetic analysis. http://www.ualberta.ca/~fyeh/download.htm.

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ISSN: 1412-033X (printed edition) ISSN: 2085-4722 (electronic) DOI: 10.13057/biodiv/d110304

Flower and fruit development of Syzygium pycnanthum Merr. & L.M. Perry DEDEN MUDIANA♥, ESTI ENDAH ARIYANTI♥♥ Purwodadi Botanical Garden, Indonesian Institute of Sciences (LIPI), Jl. Raya Surabaya-Malang, Km 65, Purwodadi, Pasuruan 67163, East Java, Indonesia. Tel./Fax.: +62- 341-426046. email: dmudiana@yahoo.com, estimudiana@yahoo.com Manuscript received: 3 June 2010. Revision accepted: 22 July 2010.

ABSTRACT Mudiana D, Ariyanti EE (2010) Flower and fruit development of Syzygium pycnanthum Merr. & L.M. Perry. Biodiversitas 12: 124128. Flower formation is a process of flowering plant in order to produce the next generation. Flower plays a major role in pollination and fertilization as early stage of fruit and seed formation. Syzygium pycnanthum is a member of family Myrtaceae or known as ‘Jambujambuan’ family. The research aim was to observe the development process of flowering and fruiting phase of S. pycnanthum at Purwodadi Botanical Garden. It has been noted that this species has ten (10) stages of flowering and fruit development, namely flower bud initiation, flower bud fully emerge, unfolding calyx, visible corolla, bud starts blooming, early blooming, perfectly blooming, perianths and anthers fall, early fruit structure and ripe fruit. All these stages require 80-89 days. Key words: Syzygium pycnanthum, flower and fruit development.

INTRODUCTION Flower is a vital organ of flowering plants. This organ is not only important as an identification instrument, but also plays a major role on reproduction. Every plant has specific floral character, both morphological and physiological characters. The differences in shape and color of flowers are the effect of adaptation process of certain species to survive. This is also related to the pollinators that help the pollination of the flowers (Boulter et al. 2006). Plant responses to their environment are correlated to the periods of their development. The science dealt with this issue is phenology. Basically, flower and fruit development are divided into 6 phases, i.e. (1) flower induction, (2) flower initiation, (3) pre-anthesis, (4) anthesis, (5) pollination and fertilization and (6) fruit formation, fruit ripening and seed formation (Ratnaningrum 2004). However, these phases are different among the species, which depend on the interaction between internal and external factors. The external factors include temperature, light intensity, humidity and minerals; while the internal factors contain phytohormone and genetic characters. The interaction between the internal and external factors give an impact to whole flowering process, such as flowering periods, juvenility, dormancy, irregular bearing or irregular fruiting time at the same period (Ashari 2002). Michalski and Durka (2007) clarified that environmental indications such as temperature, humidity or irradiance are known to have an effect on different aspects of flowering phenology. For an instance, Rahayu et al. (2007) reported that the initiation flowering process of Hoya lacunosa was influenced by external factors, i.e. the average and the variation of daily temperature, light intensity and humidity.

One of flowering plant collections at Purwodadi Botanical Garden is Syzygium pycnanthum Merr. & L.M. Perry. It has potential as an ornamental plant based on its floral and fruit characters. Moreover, this species had flowering time throughout the year as stated by Backer and Bakhuizen van den Brink (1963); this was also the case in Purwodadi BG. This research aim was to observe the phase of flower and fruit development of S. pycnanthum. The information obtained was expected to be a basic reference for further research related to this species. MATERIALS AND METHODS The research was done at Purwodadi Botanical Garden (Purwodadi BG) on February-May 2009 at bed (location number) XXII. It was rainy season. The climatic pattern of Purwodadi during the latest three years was shown in Figure 1. Purwodadi BG is located in Purwodadi Village, Purwodadi Sub District, Pasuruan District, East Java Province. It is sited on west direction of Gunung Baung at 300 m asl., about 65 km from Surabaya and 20 km from Malang. It has type C climate (based on Schmidt and Ferguson’s) with annual rainfall 2,366 mm at average. (Arisoesilaningsih and Soejono 2001). This research was conducted by observation using instruments such as writing tools, ruler, label paper and digital camera to help the observation and to compile data. The observation of plant collection was carried out at bed XXII.F.4. This collection origin was Mt. Pandan forest, Madiun District, East Java. It was planted on 31 January 1985 therefore it was about 25 year-old at the time of observation. The height was 6.5 m with diameter at breast height 22 cm and the crown width 3-4 m.

MUDIANA & ARIYANTI – Flowering phases of Syzygium pycnanthum

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First observation was done to know the phases of flower and fruit development generally, then the picture of flower development at each phase was taken. Furthermore, the sketch was drawn based on this picture. The next step was to determine which flower to be observed in more details. Five flowers on the same plant were chosen. Labels were tied on the observed objects. The observation dates were recorded on the labels. The observation was carried out daily from the buds emerged until the fruits produced and ripe.

RESULT AND DISCUSSION Taxonomy of S. pycnanthum Syzygium Gaertn. is a member of Myrtaceae with a large number of species; it can be found from Africa eastwards to the Hawaiian Islands and from India and southern China southwards to southeastern Australia and New Zealand. The most recent study on Syzygium’s infrageneric classification was done by Craven and Biffin (2010). They distinguished genus Syzygium into six (6) subgenera; one of them was subgenus Syzygium where S. pycnanthum belonged, other five subgenera were Acmena, Sequestratum, Perikion, Anetholea and Wesa. The subgenus Syzygium was characterized by usually open inflorescence, rarely congested and head-like; ovules c. (3)8-60(-90) per locule, arranged irregularly or rarely in two longitudinal rows (Craven and Biffin, 2010). Morphological characters of Syzygium pycnanthum The S. pycnanthum’s habit is small tree with diameter c.a. 20 cm and height 15-20 m. In nature, it can be found at 50-1600 m above sea level in primary or secondary forest (Backer and Bakhuizen van den Brink 1963). Flowers were arranged in terminal or auxiliary inflorescences. The

inflorescence was set on a dense panicle. The flower has short pedicel (3-4 mm), white to reddish white corolla and white to purplish calyx. There were at least three (3) color variations of S. pycnanthum’s calyx at Purwodadi BG, i.e. white, purplish green and purple. Like other Syzygium species as also ensured by Belsham and Orlovich (2002), Parnell (2003) and Viswanathan and Manikandan (2008), the stamens of S. pycnanthum were numerous and densely organized. The filaments were white on the tip and purplish on the base. The fruit type was berry, globular, diameter 2.5-3.5 cm. The young fruit was green and later becomes purplish green to light purple when ripe. S. pycnanthum has hermaphrodite flower since it has male and female organ on the same flower. The flower has complete parts that are corolla, calyx, stamen and pistil; therefore it is called a ‘perfect’ flower (Ashari 2002; Tjitrosoepomo 1999). Flower and fruit development The first phase of flower development is flower induction, which is microscopic and takes place inside the cells; whereas the next five phases are macroscopic so that these phases can be viewed easily. The first phase involves chemical reactions inside the cells that cause meristematicvegetative cells transform to meristematic-reproductive cells. Rai et al. (2006), in their research on mangosteen’s flower development, confirmed that the flower induction phase had correlation with the changes of gibberellin and sugar contents. This research was observing the last five phases of flower development. The details of observation results were showed in the next table (Table 1). Based on recorded data, it was shown that the total period needed to complete the whole process of fruit formation was 80-89 days. As comparisons, Schmidt-Adam et al. (1999) recognized six stages of flower development on Metrosideros excelsa (Myrtaceae), it needed approximately

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Table 1. Phases of flower and fruit development of S. pycnanthum Phases and Period (days) Phase I. Flower induction (microscopic); not observed

Stage 6: Early blooming 1 day

Phase II. Flower initiation Stage 1: Flower bud initiation 4-5 days

Phase IV. Anthesis Stage 7: Perfectly blooming 1-2 days

Stage 2: Flower bud fully emerge 6-7 days

Phase V. Pollination and fertilization

Stage 3: Calyx begin to unfold 6-7 days

Stage 8: Perianths and anthers fall 29-30 days

Phase VI. Fruit formation, fruit ripening and seed formation Stage 4: Corolla become more visible 6 days

Phase III. Pre-anthesis Stage 5: Bud starts to bloom 2-3 days

Stage 9: Pistil become dry, swollen receptacle, early fruit structure 16-18 days

Stage 10: Ripe fruit 9-10 days

Total period: (80-89 days) Notes: line bars in picture represent 5 mm

MUDIANA & ARIYANTI â&#x20AC;&#x201C; Flowering phases of Syzygium pycnanthum

20 days from closed bud to fruit formation. Research of Jamsari et al. (2007) proved that the flower development of Uncaria gambir consisted of 5 phases, i.e. flower initiation, early bud, bud, flower blooming and fruit formation. The average time for the whole process needed is 112 days. Whereas study done by Rahayu et al. (2007) provided evidence that Hoya lacunosa needed 8-11 weeks or 56-77 days. Another closer related species (Myrtaceae family), namely Melaleuca cajuputi, needs 277 days to pass the whole process of ripening fruit, starting from the flower initiation (Baskorowati et al. 2008). Alas, the study on the flower and fruit development of other Syzygium species by other workers has not been found yet. S. pycnanthum needs 26-31 days to pass the initiation phase and the anthesis phase; to be specific; the anthesis takes place for 1-2 days. Generally, the initiation and anthesis processes of tropical and subtropical plants take place in a very short time; however, the needed periods were varied among different species (Ashari 2002). For instance, Metrosideros excelsa (Myrtaceae) needs less time, i.e. 6 days to go through the anthesis phase (SchmidtAdam et al. 1999). Greatly more times (roughly 8 months) were needed by avocado (Persea americana Mill.) to go past anthesis as observed by Salazar-GarcĂa and Lovatt (2002). Some species of Syzygium at Purwodadi BG were also observed, they were S. jambos and S. creaghii. S. jambos needed 54-73 days, whereas S. creaghii needed 82112 days to pass the flowering and fruiting formation phases. The observation of other Syzygium collections have still being carried out continuously. The phase of flower blooming determines the pollination process. At this time, the flower usually produces fragrant odor that attract insects or other pollinators to help the pollination process. Beside the scented smell, some flowers also produce nectar to attract the pollinators (Uji 1997). The percentage during flower initiation to fruit ripening was presented in Figure 2.

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Figure 2 describes the percentage of periods needed for each phase of flower initiation and fruit development of S. pycnanthum. It showed that among the periods needed for flower to transform into fruit, the most time spent was for pollination and fertilization (36%). This phase was characterized by: the fall of corolla and stamen, the stigma dried out and the swollen receptacle. This phase is very important for producing fruit and seed successfully. Among the flowers on the same inflorescence, only few of them can develop and go through this phase. Some of them fall off and did not develop to form fruits. This could be assumed that the pollination and fertilization process was not working properly. Gomes da Silva and Pinheiro (2009) stated that not all flowers produced fruit during reproductive process because of limiting factors occurred during at each stage of the process. However S. pycnanthum has ideal position of anther and stigma. The position of stigma is in the middle of the whorl (of stamens), cause the pollination process easily happen. Moreover, the same height of the anthers and the stigma caused the pollen easily fall off on the stigma. In addition, S. pycnanthum had numerous dense stamens; this made higher changes of pollination possibly occurred especially when pollinators perch on the flowers. The moves of the pollinators assist to stick the pollen on to the stigma. Pollination is a process of falling pollen on the stigma, and fertilization is a process of the assembly of male gamete (from pollen) and female gamete (inside the ovary). The later process is influenced by internal and external factors. The internal factors consist of the flower numbers, the stigma and stamen position, the pollen maturity and the stigma fertility. Pollen and stigma of S. pycnanthum mature at the same time. The external factors include pollination vectors, weather and climates. Rahman (1997) suggested that beside those two factors, there was another factor namely the compatibility of pollen and stigma. This factor related to the genetic structure and composition of pollen and stigma. Pollination and fertilization will only occur to the similar species or to plants if they have compatible genetic structures and compositions. Cross pollination is also possible when some flowers mature at the same time. Flow Aer initiation When S. pycnanthum blooming, flower releases Fruit form ation, fruit E 28%28% ripening and seed fragrant odor to the air so that the people around the plant 31% form ation can smell the fragrant. According to Ashari (2002) the 31% aroma, the color and the flower shape were the attractive parts of flower to draw the insects attention to visit the flower. Some insects were recorded visiting the flowers of Pre-anthesis B S. pycnanthum at the time of observations; they were 4% 4% honeybees, butterflies, bumble bees, black ants and others. This research was only observing the visitors of S. D C pycnanthum, while the real pollinator needed further 36% Anthesis 1%1% research and observation so that it can not be clearly stated yet which one was the real pollinator or which one was merely visitor. Pollination and The last phase of flower development of S. pycnanthum fertilization was characterized by the formation of young fruit; it 36% Figure 2. Percentage of the period of flower and fruit emerged from the developed receptacle. The increase of developmentâ&#x20AC;&#x2122; phases of S. pycnanthum. A. Flower initiation fruit size and the change of fruit color (from green to (28%), B. Pre-anthesis (4%), C. Anthesis (1%), D. Pollination and purplish green, and finally became purple) were visible fertilization (36%), E. Fruit formation, fruit ripening, and seed phenomenon. The other observable fact was the decrease of formation (31%).

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calyx size (that still remained on the fruit apex). This is common in the Syzygium species, i.e. the calyx trace still can be seen on the fruit apex. The ripe fruit was globular, purple, 2.5-3.5 cm in diameter and one to two seeded.

CONCLUSION It has been noted that there were ten (10) stages of flower and fruit development of Syzygium pycnanthum. These stages were part of six (6) main phases of common development of flower and fruit, apart from the first one (was not observed), namely (1) flower induction, (2) flower initiation, (3) pre-anthesis, (4) anthesis, (5) pollination and fertilization and (6) fruit formation, fruit ripening and seed formation. Syzygium pycnanthum required 80-89 days to go through these latest five phases.

REFERENCES Arisoesilaningsih E, Soejono (2001) Purwodadi Botanical Garden has dry climate? In: Arisoesilaningsih E, Yanuwiadi B, Indriyani S, Yulistyarini T, Ariyanti EE, Yulia ND, Soejono (eds) Conservation and use of biodiversity of dry lowland plants; proceeding of national seminar on conservation and use of biodiversity of dry lowland plants. Purwodadi Botanical Garden, Pasuruan, 30 January 2001. [Indonesia] Ashari S (2002) The Introduction of reproduction biology of plants. PT Rineka Cipta, Jakarta [Indonesia]. Backer CA, Bakhuizen van den Brink RC (1963) Flora of Java Vol. I. NVP Noordhoff, Groningen. Baskorowati L, Umiyati R, Kartikawati N, Rimbawanto A, Susanto M (2008). Flowering and Fruiting Study of Melaleuca cajuputi subsp. cajuputi Powell at Paliyan Seedling Seed Orchard, Gunungkidul, Yogyakarta [Indonesia]. J Pemuliaan Tanaman Hutan 2 (2): 1-13. Belsham SR, Orlovich DA (2002) Development of the hypanthium and androecium in New Zealand Myrtoideae (Myrtaceae). N Z J Bot 40: 687-695.

Boulter SL, Kitching RL, Zalucki JM, Goodall KL (2006) Reproductive biology and pollination in rainforest trees: techniques for a community-level approach. Cooperative Research Centre for Tropical Rainforest Ecology and Management. Rainforest CRC, Cairns, Australia Craven LA, Biffin E (2010) An infrageneric classification of Syzygium (Myrtaceae). Blumea 55: 94-99 Gomes da Silva AL, Pinheiro MCB (2009) Reproductive success of four species of Eugenia L. (Myrtaceae). Acta Bot Bras 23(2): 526-534. Jamsari, Yaswendri, Kasim M (2007) Phenology of flower and fruit development of Uncaria gambir. Biodiversitas 8 (2): 141-146. [Indonesia] Michalski SG, Durka W (2007) Synchronous pulsed flowering: analysis of the flowering phenology in Juncus (Juncaceae). Ann Bot 100: 1271-1285 Parnell J (2003) Pollen of Syzygium (Myrtaceae) from SE Asia, especially Thailand. Blumea 48: 303-317 Rahayu S, Trisnawati DE, Qoyium I (2007) Biology of Hoya lacunosa Bl. in Bogor Botanical Garden. Biodiversitas 8 (1): 07-11. [Indonesia] Rahman E (1997) Fruit development. In: Sutarno H, Sudibyo (eds) Introduction of forest plant empowering. PROSEA Bogor. [Indonesia]. Rai IN, Poerwanto R, Darusman LK, Purwoko BS (2006) Changes of gibberellin and total sugar content in flower developmental stages of mangosteen. Hayati 13 (3):101-106. [Indonesia]. Ratnaningrum Y (2004) Flowering. In: Summary of e-Learning lectures: Techniques of forest plants’ seedling. http://elisa.ugm.ac.id/files/yeni_wn_ratna/kRYOOS-m3/II-kualitas%20dan%20prod-bunga3.doc [Indonesia]. Salazar-García S, Lovatt CJ (2002) Flowering of avocado (Persea americana Mill.) I. Inflorescence and flower development. Revista Chapingo Serie Horticultura 8 (1): 71-75 Schmidt-Adam G, Gould KS, Murray BG (1999) Floral biology and breeding system of pohutukawa (Metrosideros excelsa, Myrtaceae). N Z J Bot 37: 687-702 Tjitrosoepomo G (1999) Plant morphology. Gadjah Mada University Press, Yogyakarta. [Indonesia]. Uji T (1997) Flowering, pollination, fertilization and phenology of forest trees. In: Sutarno H, Sudibyo (eds). Introduction of forest plant empowering [Indonesia]. PROSEA Bogor. [Indonesia]. Viswanathan MB, Manikandan U (2008) A new species of Syzygium (Myrtaceae) from the Kalakkad-Mundanthurai Tiger Reserve in Peninsular India. Adansonia, sér. 3, 30 (1): 113-118.

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ISSN: 1412-033X (printed edition) ISSN: 2085-4722 (electronic) DOI: 10.13057/biodiv/d110305

Screening of antimicrobial producing strains isolated from the soil of grassland rhizosphere in Pocut Meurah Intan Forest Park, Seulawah, Aceh Besar LENNI FITRI♥, BETTY MAULIYA BUSTAM♥♥ Biology Department, Faculty of Mathematics and Natural Sciences, Syiah Kuala University, Banda Aceh (UNSYIAH), Indonesia, Indonesia. Tel. 06517552291, Fax. 0651-7552291, e-mail: l.fitri_bio@yahoo.co.id, liya1304@yahoo.com. Manuscript received: 7 April 2010. Revision accepted: 22 May 2010.

ABSTRACT Fitri L, Bustam BM (2010) Screening of antimicrobial producing strains isolated from the soil of grassland rhizosphere in Pocut Meurah Intan Forest Park, Seulawah, Aceh Besar. Biodiversitas 11: 129-132. This research was a part of some works that was conducted to find antibiotics from soil microbes. The aim of this research was to screen isolates of antibiotics-producing microbes. Soil samples were collected from grassland rhizosphere in Pocut Meurah Intan Natural Reserved Forest Seulawah, Aceh Besar. This research was conducted at the microbiology laboratory Department of Biology , Faculty of Mathematics and Natural Sciences, Syiah Kuala University. This research covers six steps i.e. collecting soil samples, isolation of microbes, making colony library, purifying colony library, antagonism test and disk method test. Eleven isolates of microbes were selected, and purified for colony, library. However, only six isolates were assumed to have an ability to produce antibiotics, as confirmed by antagonism test. Those isolates have greater ability to inhibit the growth of Staphylococcus aureus than that of Escherichia coli. 13.25 mm was The average of clear zones formed for Staphylococcus aureus and Escherichia coli were 13.25 and 11.33 mm, respectively. Key words: grassland rhizosphere, antibiotic, microbes.

INTRODUCTION Indonesia, like some others tropical countries, is the site of easily spreading diseases caused by microbes. This is because of tropical areas provide good environment for growth of pathogens or useful ones. At present, in Indonesia, some diseases caused by microbial infection are still at the top list. Using antibiotics for curing the diseases is always the option. As a result, Indonesia has been spending quite large amount of money to provide antibiotics (Akmal et al. 1993). Improper uses of antibiotics, however, are leading to microbial resistance. Microbes are able to produce enzymes that can destroy antibiotics (Sudarmono 1994). Soeripto (2002) added that resistance of bacteria can be transferable to other bacteria that make those bacteria also resistant. Antibiotics are compounds produced by microorganisms that are able to inhibit the growth of other microorganisms (Lay 1994). Antibiotics are spread in the world, as key role in organizing soils, water, and compos microbes’ population (Chatim and Suharto 1994). Antibiotics also have enormous economic values in health because these can be used to cure many infection diseases. Generally, antibiotics are used to cure the infections caused by bacteria, virus, fungi and parasites. Typically, antibiotics have selective toxicity. It means those antibiotics are dangerous for parasites only but not for the host (Jawetz et al. 1989). There have been some studies conducted in order to find useful microorganism, particularly microorganisms

that are able to produce antibiotics. Although microbes can be found everywhere, soil is the popular site in conducting that kind of research (Reinhold et al. 1986; Grayston et al. 1998; Handelsman et al. 1998; Burgess et al. 1999; Miya and Firestone 2000; Fang et al. 2001; Hamilton and Frank 2001; Jensen et al. 2001; Marschner et al. 2001; Porazinska et al. 2003; Reynolds et al. 2003; Schlüener et al. 2003; Krutz et al. 2005; Voget et al. 2005; Pesaro and Widmer, 2006; Chung et al. 2008). Moreover, rhizosphere soil has a more diverse and active microbial communities compared to non vegetated soils (Krutz et al. 2005). One kind of rhizosphere soil is soil from grasslands. Even though grassland rhizosphere is a promising place to get soil microbial-rich samples, merely few studies have been performed in Aceh to address this issue particularly in Pocut Meurah Intan Natural Reserved Forest Seulawah, Aceh Besar. Pocut Meurah Intan Natural Reserved Forest Seulawah, Aceh Besar is a forest conservation which is approximately 6.622 km2 large area, about 21% is grassland area (Department of Forestry 2003). To address the issue that grassland is important microbial resources then the study has been conducted at Microbiology Laboratory, Faculty of Mathematics and Natural Sciences, Syiah Kuala University. Soil samples were taken from Pocut Meurah Intan Natural Reserved Forest Seulawah, Aceh Besar. The objectives of this study were: (i) finding antibiotics-producing microbes, (ii) measuring the ability of isolates to inhibit the growth of Staphylococcus aureus and Escherichia coli.

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MATERIALS AND METHODS Making media Nutrient Agar (NA) disc and Aslant Agar. Nutrient agar (NA) was used as growing and purifying medium. Nutrient agar media was made by weighing out 23 grams of nutrient agar powder then dissolving it into 1 liter of pure water (aquadest) until fully dissolved. Bring it to boil. Afterwards, the media was sterilized in an autoclave for 15 minutes at 1210C. To make a disc agar, approximately 20 ml of the sterile media was poured in a petridisc aseptically. Let it dry. To make an aslant agar, approximately 5 ml of the sterile media was put in a test tube. Then, put it sideways. Nutrient Broth (NB). To make nutrient broth media, 8 grams of nutrient broth powder was weighed. Then, the media powder was dissolved in 1 liter of aquadest. Bring it into boil. Afterwards, 5 ml of NB media was put in a test tube. The media was placed in an autoclave for 15 minutes at 1210C. Microbes isolation Soil samples were taken from 10 randomly grassland rhizosphere areas in Pocut Meurah Intan Natural Reserved Forest Seulawah, Aceh Besar. One gram of soil sample was diluted in 9 ml of sterilized aquadest. Next, the sample was vortexed to homogenize the solution. Afterwards, one mL of the soil was diluted into 9 ml of sterilized aquadest to make 10-1 soil dilution. The processes were repeated until we have 10-5 soil dilution. 0.1 ml of soil dilution was spreaded into the nutrient agar disc media. Then, it was incubated upside down at room temperature for 3x24 hours. Microbesâ&#x20AC;&#x2122; isolations were done in every 24 hours. Making colony library Maximal 3 colonies that are morphologically similar were inoculated from every soil dilution. Afterwards, the inoculations were put in a library. The library then was incubated for 24 hours at room temperature. Purifying isolates of colony library Purifying isolates were done from colony libraries. Purification process was conducted through quadrant scratching in purification media. The media was incubated upside down. Purification processes were done at least twice to get colonies which are similar in size and morphology. Antagonism test Antagonism test was conducted to select the isolates that are potentially as antimicrobials. Scratching method was used to distinguish the potential antimicrobials isolates. S. aureus (representative of Gram positive bacteria) and E. coli (representative of gram negative bacteria) were used as test organisms. S. aureus and E. coli were grown in separate petridisc. Then, the bacteria in petridiscs were incubated for 24 hour at the temperature of 300 C. After that, the purified isolates were scratched to the petri discs that consist of S. aureus and E. coli. Positive potential antimicrobials isolates can be distinguished if the isolates are able to inhibit the growth of S. aureus and E.

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coli. As confirmation test, disc paper method was used. Only the positive potential antimicrobials isolates will be used in the test. Disc paper method Positive potential antimicrobials isolates were grown in nutrient broth media for 4 days. After 4 days, to homogenize isolates and media, the isolates were vortexed for about three minutes. Twenty ÎźL of homogenized isolates, were then placed in a 5 mm paper disc. The isolates filled paper discs were put in petridiscs that have previously filled with S. aureus and E. coli. Positive isolates were distinguished from the ability to inhibit the growth of either S. aureus or E. coli or both of them with the appearance of clear zone (inhibited zone) surrounding the paper discs.

RESULTS AND DISCUSSION There were 11 isolates retrieved from the soil samples (Figure 1), namely A1, A2, A3, A4, A5, A6, A7, A8, A9, A10 and A 11. All isolates are white. In order to separate other organism from isolates, all isolates were sampled as colony library before purification. This research used twice purification to make sure having pure isolates (Figure 2). Having pure isolate is an important thing in doing microbiological research. This is supported by Sofa (2008) that in an attempt to get better result, microbiological processes require purification of organism. There were six isolates (A1-A6), however, that are assumed contain antibiotics because they are able to cut lines of S. aureus or E. coli (Figure 2). Five other isolates (A7-A11) are assumed having no antibiotics because there have no cutting lines of bacteria test in the media. It means that those isolates have no ability to inhibit the growth of bacteria test. This is supported by Lay (1994) that stated about antagonism test. According to him, antagonism test is a test that involve two kind of organism (bacteria), first organism (bacteria) is produced something that has ability in inhibiting the second organism (bacteria). Moreover, Hidayat et al. (2006) stated that producing antibiotics are the way of microorganisms to protect them from endangered habitat. This mechanism is happened because of metabolism processes. Results of metabolism can be grouped as acid or any other compounds that are able to kill other microorganisms. Morphological characters of the six colony isolates that are assumed to produce antibiotics can be seen in Table 1. Table 1. Isolates code and they morphological characters Isolate code A1 A2 A3 A4 A5 A6

Colony tipe Round Un-arrangement Dots Coil Round Round

Colony surface Dome-shaped Curve Flat emerge Curve Flat Flat

Colony edge Wavy Wavy Unimpaired Serrated Serrated Unimpaired

FITRI & BUSTAM â&#x20AC;&#x201C; Antimicrobial isolations from Seulawah

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A B

Figure 1. Isolates of microbes, the arrow Figure 2. Purification of colony library, the Figure 3. Antagonism test. A = Bacteria shows the colony of bacteria arrow shows the colony of bacteria test (E. coli), B = Isolate that is assumed to contain antibiotics

As the way to confirm the antagonism test, the disc paper method test was conducted. The disc paper method was used to measure the ability of microbes isolates in inhibiting the growth of S. aureus and E. coli. This method was supported by Hatmanti et al. (2009). She and her colleagues stated that the disc paper test can be used to measure the inhibiting ability of microbes on the growth of pathogenic bacteria. Table 2 shows the clear zone average that was formed from the disc paper method.

Table 3. Classification of clear zones response

Table 2. Clear zones from disc paper method

As stated above that the average clear zones were produced in both bacteria test, were 11.33 mm and 13.25 mm for E. coli and S. Aureus, respectively. Those ranges of clear zones are classified as having strong inhibiting response. However, the average of clear zones of S. aureus as representative of gram positive are wider than the average of clear zones of E. coli as representative of gram negative. It shows that isolates have more ability to inhibit the growth of S. aureus than to inhibit the growth of E. coli. This is because gram negative bacteria usually have better protection to other antimicrobial compound rather than positive bacteria because both kinds of bacteria have different cell wall components. Cell wall of gram positive bacteria contains peptidoglican while cell wall of gram negative bacteria contains peptidoglican and lipopolysaccharide. The statement was supported by Zuhud et al. (2001) and Ajizah et al. (2007) stated that cell walls of gram positive bacteria contain very thick peptidoglican to protect the bacteria. Campbell et al. (1996) added that cell walls of gram negative bacteria, besides peptidoglican, they also contain lipopolysaccharide to protect the bacteria from antibiotics. Jawetz et al. (1989) added that the death of bacteria caused by antibacterial compounds happened because the antibacterial produce chemical components that are able to inhibit the synthesis of cell wall, inhibit function of cell membrane, inhibit the protein synthesis and or inhibit the nucleate acid synthesis.

Isolate Code A1 A2 A3 A4 A5 A6 Average

Clear zones to E. coli (mm) 11.0 12.5 13.0 10.5 10.5 10.5 11.33

Cear zones to S. aureus (mm) 12.0 13.0 16.0 13.5 14.0 11.0 13.25

According to Table 2, the wider clear zones were produced by the A3 isolate. The A3 isolate was able to inhibit the growth of E. coli and S. aureus as wide as 13 mm and 16 mm in diameter, respectively. Other isolates are able to produce clear zones in the range of 10.5-14 mm. The differences in the ability to produce the clear zone were presumably dependent on the secondary metabolites that were produced by test isolates. This assumption was supported by Dharmawan et al. (2009) that stated the variation of clear zone diameter happen because every isolate produces different types of secondary metabolites. Different types of secondary metabolites have different chemical structure, compounds and also different in chemical concentration. To measure the inhibiting response of clear zones can be classified as follow in Table 3.

Diameter of clear zones

Inhibiting respon

20 mm > â&#x20AC;Śâ&#x20AC;Ś. 10-20 mm 5-10 mm >5 mm Source: Davis and Stout (1971)

Very strong Strong Medium No response

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There are eleven isolates found from grassland rhizosphere area in Pocut Meurah Intan Natural Reserved Forest Seulawah, Aceh Besar. Six isolates are assumed to be able to produce antibiotics. Average of clear zone to inhibit the growth of S. aureus is 13.25 mm whereas 11.33 mm is the average of clear zone to inhibit the growth of E. coli. The ability of isolates in inhibiting the growth of S. aureus is higher than they ability to inhibit the growth of E. coli.

ACKNOWLEDGMENTS We would like to thank Syiah Kuala University Research Center as funding provider and Maisarah, former Biology Department student, to her help in this research.

REFERENCES Ajizah A, Thihana, Mirhanuddin (2007) Potential of Eusideroxylon zwageri T. et B. bark extract to inhibit the growth of Staphylococcus aureus in in vitro. Bioscientiae 4(1): 37-42. [Indonesia] Akmal, Arifin H, Hendri (1993) Preliminary research of screening antibiotics microorganism from soil samples of Bung Hatta Forest Park, Padang. Majalah Farmasi Indonesia 4 (3): 107-112. [Indonesia] Burgess JG, Jordan EM, Bregu M, Sprangg AM, Boyd KG (1999) Microbial antagonism: a neglected avenue of natural products research. J Biotech 70 (1-3): 27-32. Chatim A, Suharto (1994) Sterilization and disinfection in medical microbiology. Binarupa Aksara, Jakarta. [Indonesia] Chung EJ, Kim HK, Kim JC, Choi GJ, Peak EJ, Lee MH, Chung VR, Lee SW (2008) Forest soil metagenome gene cluster involved in antifungal activity expression in Escherichia coli. Appl Environ Microbiol 74 (1): 37-43. Davis WW, Stout TR (1971) Disc plate method of microbiological antibiotic assay, I: factors influencing variability and error. Appl Microbiol 22 (4): 659-665 Department of Forestry (2003) Proposal of Pocut Murah Intan Forest Park expansion, Seulawah, Aceh Besar. BKSDA, Department of Forestry, Banda Aceh. [Indonesia] Dharmawan IWE, Retno K, Made SP (2009) Isolation of Streptomyces spp. in Bali Barat National Park and inhibition test to five diarrheagenic Escherichia coli strain. J Biologi 13 (1): 1-6. [Indonesia] Fang C, Rodosevich M, Fuhrmann JJ (2001) Characteristics of rhizosphere microbial community structure in five similar grass species using fame and biological analyses. Soil Biol Biochem 33 (45): 679-682.

11 (3): 129-132, July 2010 Grayston SJ, Wang S, Campbell CD, Edwards AC (1998) Selective influence of plant species on microbial diversity in the rhizosphere. Soil Biol Biochem 30 (3): 369-378. Hamilton EW, Frank DA (2001) Can plant stimulate soil microbes and their own nutrient supply? Evidence from a grazing tolerant grass. J Ecol 82 (9): 2397-2402. Handelsman J, Rondon MR, Brady SF, Chardy J, Goodman RM (1998) Molecular biological access to the chemistry of unknown soil microbes: a new frontier for natural products. J Chem Biol 5: 245249. Hatmanti A, Nuchsin R, Dewi J (2009) Screening of inhibitor bacteria to inhibit the growth of diseases causing bacteria grouper fish nursery in Banten and Lampung. Makara Sains 13 (1): 81-86. [Indonesia] Hidayat N, Masdiana CP, Sri S (2006) Industrial microbiology. Andi Offset, Yogyakarta. [Indonesia] Jawetz E, Melnick JL, Adelberg EA (1989) Medical microbiology. Appleton & Lange, East Norwalk, CT. Jensen LB, Baloda S, Boye M, Aerestrup FM (2001) Antimicrobial resistance among Pseudomonas spp. and the Bacillus cereus group isolated from Danish agricultural soil. Environ Int 26 (7-8): 581-587. Krutz LJ, Beyrouty CA, Gatry TJ, Wolf DC, Reynolds CM (2005) Rhizosphere pyrene degrader population in rhizosphere soil and non vegetated soil. Biol Fert Soils 41 (5): 359-364. Lay WB (1994) Microbes analysis in laboratory. Raja Grafindo Persada, Jakarta. [Indonesia] Marschner P, Yang CH, Lieberei R, Crowley DE (2001) Soil and plant specific effects on bacterial community composition in the rhizosphere. Soil Biol Biochem 33 (11): 1437-1445. Miya RK, Firestone MK (2000) Penathrene-degrader community dynamics in rhizosphere soil from a common annual grass. J Environ Qual 29: 584-592. Pesaro M, Widmer F (2006) Identification and specific detection of a novel Pseudomonadaceae cluster associated with soil from winter wheat plots of a long term agricultural. Appl Environ Microbiol 72 (1): 37-43. Porazinska DL, Bardgett RD, Blaaw MB, Hunt HW, Parsons AN (2003) Relationships at the above ground-bellow ground interface plants, soil biota and soil processes. Ecol Monograph 73 (3): 377-395. Reinhold B, Hurek T, Niemann EG, Fendrik I (1986) Close association of Azospirillum and Diazotrophic rods with different root zones of kallar grass. Appl Environ Microbiol 52 (3): 520-530 Reynolds HL, Packer A, Bever JD, Clay K (2003) Grassroots ecology: plant-microbe-soil interactions as drivers of plant community structure and dynamics. J Ecol 84 (9): 2281-2291. Schlusener MP, Spiteller M, Bester K (2003) Determination of antibiotics from soil by pressurized liquid extraction and liquid chromatographytandem mass spectrometry. J Chromatograph 1003 (1-2): 21-28 Soeripto (2002) Animal health care concept through vaccination. J Litbang Pertanian 21 (2): 48-55. [Indonesia] Sudarmono (1994) Genetic and resistance in medical microbiology. Binarupa Aksara, Jakarta. [Indonesia] Voget S, Leggewie C, Vesbeck A, Raasch C, Jaeger KE, Streit WR (2005) Prospecting for novel biocatalysts in a soil metagenome. Appl Environ Microbiol 69 (10): 6235-6242. Zuhud EAM, Rahayu WP, Wijaya CH, Sari PP (2001) Antimicrobial activity of kedawung extract (Parkia roxburghii G. Don) on food borne pathogens. J Teknologi dan Industri Pangan 12 (1): 6-12. [Indonesia]

B I O D I V E R S IT A S Volume 11, Number 3, July 2010 Pages: 133-138

ISSN: 1412-033X (printed edition) ISSN: 2085-4722 (electronic) DOI: 10.13057/biodiv/d110306

Community structure of macrozoobenthic feeding guilds in responses to eutrophication in Jakarta Bay AM AZBAS TAURUSMAN1,2,â&#x2122;Ľ 1

Department of Utilization of Fisheries Resources, Faculty of Fisheries and Marine Science, Bogor Agricultural University (PSP-FPIK-IPB), IPB Campus at Dramaga, Bogor 16680, West Java, Indonesia. Tel. 62-251-8622935, Fax. 62-251-8421732, ď&#x201A;Še-mail: azbastm@yahoo.com 2 Center for Coastal and Marine Resources Studies, Bogor Agricultural University (CCMRS - IPB/PKSPL - IPB), IPB Campus at Baranangsiang, Jl. Raya Pajajaran, Bogor 16144, West Java, Indonesia. Tel: 62-251-8374820, Fax: 62-251-8374726 Manuscript received: 2 January 2010. Revision accepted: 21 Mei 2010.

ABSTRACT Taurusman AA (2010) Community structure of macrozoobenthic feeding guilds in responses to eutrophication in Jakarta Bay. Biodiversitas 11: 133-138. The group of benthic fauna which feed on the same food sources are classified as a feeding guild. The objective of the present study was to evaluate the distribution and composition of macrozoobenthic feeding guilds along gradient of organic enrichment (trophic states) in Jakarta Bay. The result of the present study was shown that at the hypertrophic stations of the bay dominated by species of surface deposit feeding polychaetes such as, Dodecaceria sp., Cirratulus sp., Capitella sp., and Spionidae. The eutrophic zone of the bay was dominated by suspension feeding bivalves Mactra sp., Chione sp. The offshore area (mesotrophic zone) showed a high diversity of species and feeding guilds compared to other areas. The patterns of feeding guilds in the mesotrophic zone indicated a higher stability of macrozoobenthos community, indicated by the presence of deep-deposit feeder (e.g. Acetes sp.), surface deposit feeders (e.g. Prionospio sp.), suspension feeders (e.g. Chione sp.), and carnivores (e.g. Nephthys sp.) in comparable proportions. The structure of macrozoobenthic feeding guilds in an eutrophic coastal water is positively related to the quantity and quality of organic matters (eutrophic states), and the capability of benthic species in adaptation to such environmental condition. Key words: macrozoobenthos, feeding guild, eutrophication, coastal water, Jakarta Bay.

INTRODUCTION Coastal and marine pollution is one of the most notorious problems in terms of sustainable development in Indonesia, for example in the bay of Jakarta. In the last two decades the phenomena of eutrophication and heavy metal pollution have occurred in Jakarta Bay. The study of Damar (2003) and Taurusman (2007) have indicated the high input of organic matters into the bay and severe pollution occur. Base on the criteria of trophic index for marine waters (TRIX) that formulated by Vollenweider et al. (1998), Damar (2003) has characterized the Jakarta Bay into three trophic zones: hypertrophic zone (located in all river mouth and inner part of the bay), eutrophic zone (in middle part), and mesotrophic zone (in the outer part). A fundamental question in the marine ecology study is how responses the marine animals (consumers) to the availability of food sources and hydrodynamic processes (environmental variations), and what is the role of the animals within the complexity of the marine food web. Moreover, for benthic ecology how assemblages of marine soft sediment are structured. The information of the functional aspects (e.g. feeding guilds) needs to be considered (Gray and Elliott 2009). Furthermore, the functional aspects of ecosystem are mainly feeding guilds and predator-prey relationships, inter-and intraspecific competition, production, and association. The concept of functional ecosystem is basically derived from trophic

dynamics introduced by Lindeman in 1942 (Gray and Elliot 2009). There are five reasons why the study of feeding guilds of benthic macrofauna in a marine ecosystem important to be carried out. Firstly, one of the most common approaches to understand the community structure of macrozoobenthos is by the analysis of feeding guilds (Putman and Wratten 1984). Secondly, the information of feeding guilds is needed for our understanding of benthic processes and to construct the food webs. The role of benthic macrofauna in a food web is crucial to support sustainable ability of fish and marine mammal (e.g. Grebmeier and Dunton 2000). Thirdly, the information of feeding guilds is fundamental for studying the predator-prey relationship and therefore determining the carrying capacity of an ecosystem. Fourthly, this information is fundamental in the analysis of ecological network, i.e. a linear function describes the flow into and out of an ecological compartment (Gray and Elliot 2009). Finally, for water management purposes, the concept of the macrozoobenthic feeding guilds has been adopted to be included in measuring and indexing the environmental quality, for example the ecological status quality of the European Water Framework Directive criteria (e.g. Borja et al. 2000). Originally, a guild is defined by Root (1967) as assemblages of species that exploit the same environmental resources. Thus the group of benthic fauna which feed on the same food sources is classified as a feeding guild.

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However, Rosenberg (2001) and Diaz and Schaffner (1990) suggested to use the term ‘functional groups’ instead of feeding guilds. They argued that animals in the same feeding guild commonly compete for the same food sources, whereas such interaction does not necessarily occur within a functional group (Rosenberg 2001). There are generally two main feeding guilds of macrozoobenthos: suspension feeders and deposit feeders. Faucald and Jumars (1979) suggested a classification of annelids (polychaetes) into 22 different feeding modes (feeding guilds) that were purposed based on feeding habits, type of food, and motility. The feeding habits are classified as: jawed, ciliary mechanisms, tentaculate, pumping, and others; three degrees of motility (motile, discretely motile, and sessile); types of foods: macrophagous modes (herbivores and carnivores) and microphagous modes (filter feeders, surface deposit feeders, and burrowers (Rosenberg 2001; Pagliosa 2005). Additionally, Rosenberg (2001) and Arruda et al. (2003) suggested that some species can successfully switch between surface deposit feeding and suspension feeding, e.g. related to the food supply like the Echinoderm Amphiura filiformis (brittle star) and from deposit feeders to suspension feeders such as Macoma sp., which is influenced by water velocity and sediment transport. If water velocity is higher, then less sediment (organic matter) accumulated in the sediment, thus by switching to suspension feeding they could easier collect food from the water.

The distribution of the dominant functional groups of macrozoobenthos is related to the total organic carbon in sediment (Denisenko 2003), food availability (Dauwe et al. 1998; Rosenberg 2001), depth and salinity (Rosenberg 2001), and physical characteristics of the substrates (Arruda et al. 2003). Sanders (1958) postulated that the distribution of certain functional groups, such as suspension feeders and deposit feeders is controlled by hydrodynamic processes that determine sediment characteristics. Low current flows allow deposition of fine particles, including organic matter. Under these conditions suspension feeders become less abundant and they are replaced by the deposit feeders. There were limited studies about effects of organic enrichment (eutrophication) on macrozoobenthic feeding guilds in Indonesian coastal water. The study of changing structure of macrozoobenthic feeding guilds as responses to gradient organic enrichment (eutrophication states) in tropical water is important to overcome eutrophication problem. Most of the previous studies have been conducted in temperate waters (e.g. Fauchald and Jumars 1979, Diaz and Schaffner 1990, Borja et al. 2000). Therefore, the present study was conducted to evaluate the distribution and composition of macrozoobenthic feeding guilds along gradient of organic matter (trophic states) in the coastal water of Jakarta Bay. Thus, the research question of the present study is whether there are relationship between community structure of macrozoobenthic feeding guilds and eutrophication states of coastal water.

107.16 E

107.00 E

106.66 E

20 km

JAKARTA BAY 06.00 S

1 10

12 11 5

13 9

710 5

6 5

Tanjung Priok Harbour

Fishing PortMarina

Marunda river

Priok river

Angke river

06.16 S

JAKARTA CITY Sampling station

Border between trophic zones

Depth contours Figure 1. Sampling stations in Jakarta Bay and geographical position.

St. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14.

Longitude

Latitude

106o 45’ 29.1”

06o 02’ 07.9”

106o 47’ 49.4”

06o 00’ 56.6”

106o 50’ 14.5”

06o 00’ 13.0”

106o 55’ 43.3”

06o 03’ 07.1”

106o 57’ 28.6”

06o 06’ 31.0”

106o 57’ 22.4”

06o 05’ 26.3”

106o 55’ 29.1”

06o 05’ 26.0”

106o 49’ 46.7”

06o 06’ 48.0”

106o 52’ 44.9”

06o 04’ 49.6”

106o 44’ 21.4”

06o 05’ 15.6”

106o 46’ 50.3”

06o 06’ 00.4”

106o 46’ 47.2”

06o 03’ 29.2”

106o 49’ 44.1”

06o 04’ 07.9”

106o 55’ 01.9”

05o 58’ 44.6”

TAURUSMAN – Microzoobenthos of Jakarta Bay

MATERIALS AND METHODS Sampling methods Benthic macrofauna samples were taken randomly by means of a 0.023 m2 “Petite” Ponar grab with ten hauls at each sampling station in Jakarta Bay. The samples were taken during rainy season: February 2005 in Jakarta Bay. By considering previous study of Damar (2003), the sampling location has been divided into 14 sampling stations representing the three trophic zones (Fig.1): river mouth and inner part of the bay stations to represent the hypertrophic zone (stations 5, 6, 7, 8, 9, 10, and 11); Sampling stations at the centre part of the bay (stations 1, 4, 12, and 13) to represent the eutrophic zone; and stations 2, 3, and 14 at the outer part of the bay (as mesotrophic zone). Nine of the samples were immediately sieved on board through a 0.5 mm screen and the residue collected separately in a plastic bag, preserved in 4 % formalin and stained with rose Bengal. The 10th grab of sediment was stored wet in a plastic bag, labelled and kept in ice box for organic matter and sediment grain size analysis. Laboratory samples analysis In the laboratory the macrozoobenthos samples were washed to remove formalin, sorted, identified to family or species level if possible, and counted (Holme and McIntyre 1984). The major taxonomic books that were used for identification of the samples were: Gosner (1971) to general analyses of all taxonomic samples; Roberts et al. (1982), Dharma (1988, 1992), Abbot (1954), especially for mollusks; Fauchald (1977), Fauvel (1923) for polychaete worms; and Yamaguchi (1993) for some of crustaceans. In order to classify each macrozoobenthos species in Jakarta Bay, references of benthic feeding studies were used, e.g. Fauchald and Jumars (1979), Abbott (1954), Arruda et al. (2003) and Koulouri et al. (2006) for mollusks; Pagliosa (2005) and Sarkar et al. (2005) for polychaetes; Borja et al. (2000); Llansό (2002); Grall et al. (2006); French et al. (2004); Gray (1981) and Luczkovich et al. (2002). Furthermore, for this study the major five feeding categories of Fauchald and Jumars (1979) were used that are comparable to those used by most authors, namely: suspension feeders, surface (sub-surface) deposit feeders, deep- deposit feeders (burrowers), herbivores, and carnivores. This is a simplified classification, and overlapping may occurs, because some species show an overlap in food sources (Rosenberg 2001; Grall et al. 2006; Arruda et al. 2003). The variations in classification of feeding guilds of macrozoobenthos species are observed between authors, e.g. Llansό (2002) has classified the Polychaete family Capitellidae as deep-deposit feeders, while other authors (e.g. Grall et al. 2006; Sarkar et al. 2005) have classified this group as sub-surface deposit feeders. Data analyses To assess the effects of organic matter and nutrients (eutrophication) on the macrozoobenthic feeding guilds, a multivariate statistics were used because it is useful and

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highly sensitive to detect changes in species composition which are signs of eutrophication (Gray et al. 2002). In practice, a multivariate statistical analysis of the macrozoobenthic data were applied using various routines of the PRIMER version 5.2 (Plymouth Routines in Multivariate Ecological Research) software package (Clarke and Gorley 2001). The PRIMER package is able to integrate the physio-chemical measurements to provide a correlative explanation for possible causes of changes observed in the fauna (Gray et al. 2002). Statistic analysis of similarities (ANOSIM) was employed to test significance of the influence of grouping factors (stations and trophic states) by means of PRIMER Software (Clarke and Gorley, 2001). ANOSIM is a nonparametric procedure analogous to analysis of variance (ANOVA), which is based on the ranks of the value in the similarity matrix. Quinn and Keough (2002) have recommended using ANOSIM to test hypotheses about group differences in a multivariate context. The similarities relationship was calculated by change in Clarke’s R value according to the following equation:

R

aver .rb  aver .rw M 2

M 

n ( n  1) 2

aver. rb = average of rank similarities between the groups, aver. rw = average of rank similarities within the groups (stations or trophic states), n = number of involved data in the analysis.

The Clarke’s R value gives an absolute measure of how separated groups are, on a scale of 0 (indistinguishable) to 1 (all similarities within groups are less than any similarity between groups).

RESULTS AND DISCUSSION Generally, polychaetes represent the dominant benthic group in both hypertrophic and mesotrophic zones, and codominate in the eutrophic zone in Jakarta Bay. The hypertrophic stations of Jakarta Bay was dominated by surface deposit feeding polychaetes such as, Dodecaceria sp., Cirratulus sp., Capitella sp., except for station 7 which was dominated by suspension feeding Mactra sp. (Bivalve), see Tabel 1 and Figure 2. The surface deposit feeding group was mostly abundant in estuarine stations in Jakarta Bay. These stations were characterized by shallow areas, and high water velocity, by fine sand fraction and relative lower organic content in sediment. The river station (Marunda, station 5) showed a similar pattern; this particular area was actually dominated by subsurface deposit feeders such as Notomastus sp. and Capitella sp. (Figure 2).

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Table 1. Spatial distribution and composition of dominant spesies (ind/m2) of macrozoobenthic feeding guilds related to eutrophication in Jakarta Bay. Trophic states and stasiun Feeding guilds Hypertrophic Eutrophic Mesotrophic S5 S6 S7 S8 S9 S10 S11 S1 S4 S12 S13 S2 S3 S14 (referen.) Mactra sp. (Bivalvia) 0 13 13 83 13 226 26 43 74 122 0 4 SF9,10 Chione sp. (Bivalvia) 4 0 0 4 0 70 26 0 35 139 30 661 SF11 Gafrarium sp. (Bivalvia) 0 0 0 0 0 4 0 0 4 13 13 70 SF5 Prionospio sp. (Polychaeta) 0 39 0 148 - 1252 52 61 13 4 152 52 83 SDF7 Cirratulus sp. (Polychaeta) 0 413 4 470 217 4 4 0 0 17 87 26 SDF5 Dodecaceria sp. (Polychaeta) 0 30 0 - 3552 - 5657 4 30 0 0 17 13 0 SDF5 Notomastus sp. (Polychaeta) 61 4 0 17 74 13 0 0 0 61 57 9 sSDF2,4,5 Heteromastus sp. (Polychaeta) 43 0 0 0 0 0 0 0 0 22 0 0 sSDF2,4,5 Capitella sp. (Polychaeta) 22 39 0 0 13 0 0 0 0 4 0 0 sSDF4,5,8 Tellina sp. (Bivalvia) 0 0 0 43 13 4 4 0 4 83 9 113 DDF2,3 Lucifer sp. (Crustacea) 0 0 0 0 0 13 17 9 39 70 70 35 DDF12 Acetes sp. (Crustacea) 0 0 0 4 0 30 0 0 9 26 61 17 DDF12 Sigambra sp. (Polychaeta) 0 65 0 287 139 43 4 0 0 35 35 26 C5,6 Microdeutopus sp. (Crustacea) 0 0 0 278 4 0 0 0 0 4 9 0 C5 Nephtys sp. (Polychaeta) 0 13 0 35 30 4 0 0 0 30 100 35 C6 Nereis sp. (Polychaeta) 4 26 0 39 209 13 9 9 9 17 17 22 C5 Calanus sp. (Crustacea) 0 0 0 0 0 17 0 0 4 0 91 39 nc Note: SF = Suspension feeder; SDF = Surface-deposit feeder; sSDF = Sub-surface deposit feeder; DDF = Deep-deposit feeder (burrower); C = Carnivores; nc = no classification;- : unavailable data. References: 1) = Koulouri et al. (2006); 2) = Grall et al. (2006); 3) = French et al. (2004); 4) = Sarkar et al. (2005); 5) = Borja et al. (2000); 6) = LlansĎ&#x152; (2002); 7) Pagliosa (2005); 8) Gray (1981); 9) Abbot (1954); 10) Wong et al.(2003); 11) Arruda et al. (2003); 12) Luczkovich et al. (2002) Taxa

characterized by a simple system that is primarily composed of surface deposit feeders and in addition carnivores become established (Pearson and Rosenberg 1978). The eutrophic zone in Jakarta Bay was dominated by suspension feeding bivalves Mactra sp., Chione sp., except station 4 which was dominated by the surface deposit feeding polychaete Prionospio sp.. The abundance of the deep-deposit feeding crustacean Lucifer sp. increased according to an increasing the silt-clay fraction in the sediment, except at station 4 (Figure 2). The explanation for this might be that station 4 is located at middle-eastern part of the bay close to the mouth of Marunda River (station 6) where 100 similar environmental conditions may 90 influence the community structure of the 80 macrozoobenthos in this particular area. 70 These are characterized by a lower silt-clay fraction and a high content of organic matter 60 in the bottom water. 50 The high abundance of suspension 40 feeders in the eutrophic zone (and station 7) 30 may be the result of high quality of food that 20 consists predominantly of living phytoplankton, as well as a high organic 10 content of the material suspended in the 0 water column and settling at the sediment5 6 7 9 11 12 1 4 13 2 14 3 water interface (Heip 1995). The latter was Stations demonstrated by the extreme high organic D-deposit-F S-deposit-F Suspension-F Carnivores Herbivores N.C. content of material collected in sediment traps in this particular area (see also Figure 2. Spatial distribution and composition of macrozoobenthos feeding guilds Taurusman 2009). The high growth rate of in Jakarta Bay. Stations are ordered from inshore to offshore areas and grouped cultivated green mussels in Jakarta Bay according to trophic zones: 5-11 (hypertrophic zone), 12-13 (eutrophic zone), and (Setyobudiandi 2004) might be also an 2-3 (mesotrophic zone), N.C. (no classification) Abundance (%)

Similarly, Pagliosa (2005) showed that surface (subsurface) deposit feeding and filter feeding polychaetes were frequently observed in fine sandy sediment (inshore area) in Santa Catarina Island Bay (Brazil). Therefore, the variation in the macrozoobenthos community in the hypertrophic zone may be influenced not only by organic matter input, but also by water velocity which leads to sediment stability (Sanders 1958). In contrast to the eutrophic and mesotrophic zones, the hypertrophic zone, where organic matter input is very high, feeding guilds are

TAURUSMAN – Microzoobenthos of Jakarta Bay

Table 2. Result of one-way analysis of similarity (ANOSIM) between abundance of macrozoobenthic feeding guilds and stations and trophic zones Parameters Statistic R Differences between station 0.488 Differences between trophic zone 0.281  hypertrophic vs eutrophic 0.342  hypertrophic vs mesotrophic 0.306  eutrophic vs mesotrophic 0.228 Note: ** = very significantly differences

p-value 0.001** 0.001** 0.001** 0.001** 0.001**

indication of the high quality of suspended material. Arruda et al. (2003) suggested that suspension feeders are adapted to exploit the particulate matter and microorganisms in suspension, and are able to benefit from sulphur-oxidizing bacteria in such intermediate to high organic matter conditions. The offshore area (mesotrophic zone) showed a high diversity of species and feeding guilds compared to other areas. The patterns of feeding guilds indicated a higher stability of macrozoobenthos community, indicated by the presence of deep-deposit feeder (e.g. Acetes sp.), surface deposit feeders (e.g. Prionospio sp.), suspension feeders (e.g. Chione sp.), and carnivores (e.g. Nepthys sp.) in comparable proportions. According to the classical concept of diversity and stability of Elton, a more diverse community could indicate higher stability (Gray 1981). Statistically, there was a significant difference in distribution and composition of macrozoobenthic feeding guilds in Jakarta Bay between stations with a global ANOSIM R = 0.488, p < 0.001 (Table 2). The ANOSIM analysis also revealed strong differences of macrozoobenthic feeding guilds between trophic zone (Global R = 0.281, p < 0.001). Its pairwise tests showed also there were significant differences all trophic zone in Jakarta Bay: between hypertrophic and eutrophic (R = 0.342, p < 0.001), hypertrophic and mesotrophic (R = 0.306, p < 0.001), and eutrophic versus mesotrophic (R = 0.228, p < 0.001), see Table 2. The result of the present study shown an indication of stronger effects of organic enrichment on macrozoobenthos community in Jakarta Bay, deep deposit feeders e.g. are a group that more sensitive to effects of organic enrichment than suspension feeders (Borja et al. 2000). Again, effects of higher organic enrichment on macrozoobenthos community were indicated by a higher share of deposit feeders in total abundance in eutrophic and mesotrophic zone compared to hypertrophic zone. Additionally, surface (subsurface) deposit feeders that are classified as tolerant or even opportunistic species (Borja et al. 2000) were found to be most abundant in the hypertrophic zone in Jakarta Bay, supporting the hypothesis that they thrive at organic enrichment. Carnivores were found in all locations, but in variable percentage. This result coincides with Rosenberg (2001). He suggested that related to food availability and water depth (current), highest diversity of functional groups (feeding guilds) could be observed in off-shore sandy mud. Herbivores and suspension feeders attain highest abundance in shallow waters, whereas deposit feeders prefer areas with low water movement where the bottom is

Tests Global test Global test Pairwise test Pairwise test Pairwise test

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accumulating organic material and carnivores were found in all habitats, irrespective of organic enrichment or sediment characteristics.

CONCLUSION

The result of the present study can be concluded that the gradient of organic matter enrichment, indicated by different trophic zones, in Jakarta Bay lead to patterns in the distribution of macrozoobenthos species and composition of the functional groups of feeding. Surface deposit feeders were the dominant macrozoobenthic feeding guilds at the hypertrophic zone, while the eutrophic zone was dominated by suspension feeders. The mesotrophic zone showed a high diversity and all of the feeding guilds present, indicating the higher stability of the ecosystem. This result supports the hypothesis that the distribution and composition of macrozoobenthic feeding guilds in Jakarta Bay was positively related to spatial gradient of organic enrichment (trophic states) of the bay.

ACKNOWLEDGEMENTS I would like to thanks to F. Colijn (Forschungs-und Technologiezentrum Westküste, FTZ-Kiel University, Germany) and H. Asmus (Alfred-Wegner Institut, AWI, Germany) for their valuable inputs for this study. Thanks also for the two reviewers for their remarks to improve the manuscript. This study was supported by funds from German Academic Exchange Services (DAAD) and Indonesian Government (Dikti).

REFERENCES Abbot RT (1954) American Seashells. D. Van Nostrand Company, Inc. Princeton, New Jersey. Arruda EP, Domaneschi O, Amaral ACZ (2003) Mollusc feeding guilds on sandy beaches in São Paulo State, Brazil. Mar Biol 143: 691-701. Borja A, Franco J, Pérez V (2000) A Marine biotic index to establish the ecological quality of soft-bottom benthos within European estuarine and coastal environments. Mar Poll Bull 40 (12): 1100-1114. Clarke KR and Gorley RN (2001) Plymouth Routines In Multivariate Ecological Research (PRIMER) V 5.2: User manual/Tutorial. PrimerE Ltd. Damar A (2003) Effects of enrichment on nutrient dynamics, phytoplankton dynamics and productivity in Indonesian tropical waters: a comparison between Jakarta Bay, Lampung Bay and Semangka Bay. [Dissertation]. Kiel University, Kiel. [Germany]. Dauwe B, Herman PMJ, Heip CHR (1998) Community structure and bioturbation potential of macrofauna at four North Sea stations with contrasting food supply. Mar Ecol Prog Ser 173: 67-83. Denisenko SG, Denisenko NV, Lehtonen KK, Andersin AB, Laine AO (2003) Macrozoobenthos of the Pechora Sea (SE Barents Sea): community structure and spatial distribution in relation to environmental conditions. Mar Ecol Prog Ser 258: 109-123. Dharma B (1988) Siput dan kerang Indonesia (Indonesian shells) I. PT. Sarana Graha, Jakarta. Dharma B (1992) Indonesian shells II. Verlag Christa Hemmen. Wiesbaden, Germany.

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Diaz RJ, Schaffner LC (1990) The functional role of estuarine benthos. In: Heirem M, Krome EC (eds) Perspectives on the Chesapeake Bay, 1990. Advances in estuarine sciences, pp. 25-56. Chesapeake Research Consortium, Glucester. Fauchald K (1977) The polychaete worms; definitions and key to the orders, families and genera. Natural history museum of Los Angeles County co. with the Allan Hancock Foundation University of California. Fauchald K, Jumars P (1979) The diet of worms: a study of polychaete feeding guilds. Oceanogr. Mar Biol Ann Rev 17 : 193-284. French K, Robertsona S, O’Donnellb MA (2004) Differences in invertebrate infaunal assemblages of constructed and natural tidal flats in New South Wales, Australia. Estuar Coast Shelf Sci 61: 173183. Gosner KL (1971) Guide to identification of marine and estuarine invertebrate. John Wiley and Sons, Inc., New York. Grall J, Le Loc’h F, Guyonnet B, Riera P (2006) Community structure and food web based on stable isotopes (δ15N and δ13C) analyses of a North Eastern Atlantic maerl bed. J Exp Mar Biol Ecol 338:1-15 Gray JS (1981) The ecology of marine sediments: an introduction to the structure and function of benthic communities. Cambridge University Press. London. Gray JS, Wu RS, Or YY (2002) Effects of hypoxia and organic enrichment on the coastal marine environment: Rev Mar Ecol Prog Ser 238: 249-279. Gray JS, Elliot M (2009) Ecology of marine sediments: from science and management. 2nd ed. Oxford University Press, New York. Grebmeier JM, Dunton KH (2000) Benthic processes in the northern Bering/Chukchi Seas: status and global change. In: Impact of changes in sea ice and other environmental parameters in the Arctic. Report of the Marine Mammal Commission Workshop, 15-17 February 2000, Girdwood, Alaska. Heip C (1995) Eutropication and zoobenthos dynamics. OPHELIA 41: 113-136. Holme NA, McIntyre AD (eds) (1984) Methods for the study of marine benthos. 2nd ed. IBP Hand Book 16. Blackwell Scientific Publications. Oxford. Koulouri P, Dounas C, Arvanitidis C, Koutsoubas D, Eleftheriou A (2006) Molluscan diversity along a Mediterranean soft bottom sublittoral ecotone. J Scientia Marina 70 (4): 573-583. Llansό RJ (2002) Methods for calculating the Chesapeake Bay benthic index of biotic integrity. Versar Inc. www.baybenthos.versar.com. Luczkovich JJ, Ward GJ, Johnson JC, Christian RR, Baird D, Neckles H, Rizzo WM (2002) Determining the trophic guilds of fishes and

11 (3): 133-138, July 2010 macroinvertebrates in a seagrass food web. Estuaries 25 (6): 11431164. Pagliosa PR (2005) Another diet of worms: the applicability of polychaete feeding guilds as a useful conceptual framework and biological variable. Mar Ecol 26: 246-254. Pearson TH, Rosenberg R (1978) Macrobenthic succession in relation to organic enrichment and pollution of the marine environment. Oceanogr Mar Bio Ann Rev 16: 229- 311. Putman RJ, Wratten SD (1984) Principles of ecology. Chapman and Hall, London. Quinn GP, Keough MJ (2002) Experimental design and data analysis for biologists. Cambridge University Press, London. Roberts D, Soemodihardjo S, Kastoro W (1982) Shallow water marine molluscs of North-West Java. Lembaga Oseanologi Nasional, Lembaga Ilmu Pengetahuan Indonesia (National Institute of Oceanology, Indonesian Institute of Sciences (LON-LIPI), Jakarta. Rosenberg R (2001) Marine benthic faunal successional stages and related sedimentary activity. J Scientia Marina 65:107-119. Root RB (1967) The niche exploitation pattern of the blue-gray gnatcatcher. Ecol. Monogr. 37: 317-350. Sanders HL (1958) Benthic studies in Buzzards Bay. Animal-sediment relationships. Limnol Oceanogr 3: 245-258. Sarkar SK, Bhattacharya A, Giri S, Bhattacharya B, Sarkar D, Nayak DC, Chattopadhaya AK (2005) Spatio-temporal variation in benthic polychaetes (Annelida) and relationships with environmental variables in a tropical estuary. Wetlands Ecol Manag 13: 55-67. Setyobudiandi I (2004) Some aspects of reproductive biology of the green mussel, Perna viridis Linnaeus, 1758 under different water conditions. [Dissertation]. Bogor Agricultural University, Bogor. [Indonesia] Taurusman AA (2007) Community structure, clearance rate, and carrying capacity of macrozoobenthos in relation to organic matter in Jakarta Bay and Lampung Bay, Indonesia. [Dissertation]. Kiel University, Kiel. [Germany]. Taurusman AA (2009) Sedimentation rate and organic matter flux on different trophic states of Jakarta Bay. Indon Nat J Mar Sci 2: 52-58. Vollenweider RA, Giovanardi F, Montanari G, Rinaldi A (1998) Characterization of the trophic conditions of marine coastal waters, with special reference to the NW Adriatic Sea: proposal for a trophic scale, turbidity and generalized water quality index. Environmetrics 9: 329-357. Wong HW, Levinton JS, Twining BS, Fisher NS, Kelaher BP, Alt AK (2003) Assimilation of carbon from a rotifer by the mussels Mytilus edulis and Perna viridis: a potential food-web link. Mar Ecol Prog Ser 253:175-182.

B I O D I V E R S IT A S Volume 11, Number 3, July 2010 Pages: 139-144

ISSN: 1412-033X (printed edition) ISSN: 2085-4722 (electronic) DOI: 10.13057/biodiv/d110307

Litter decomposition of Rhizophora stylosa in Sabang-Weh Island, Aceh, Indonesia; evidence from mass loss and nutrients IRMA DEWIYANTIâ&#x2122;Ľ Department of Marine Science, Coordinatorate of Marine and Fisheries, Syiah Kuala University (UNSYIAH), Darussalam, Banda Aceh 23111, Indonesia. Tel.Fax. +62-651-51321, 555622, 51977, Ps. 4187 ď&#x201A;Še-mail: irma_alfian@yahoo.com Manuscript received: 20 April 2010. Revision accepted: 9 June 2010.

ABSTRACT Dewiyanti I (2010) Litter decomposition of Rhizophora stylosa in Sabang-Weh Island, Aceh, Indonesia; evidence from mass loss and nutrients. Biodiversitas 11: 139-144. Mangrove is an essential coastal ecosystem that provides nutrients to estuarine and its surrounding environments through its litter decomposition. This vegetation can be considered as an important ecosystem in food web along the coast. The research was conducted in mangrove forest in Sabang-Weh Island, Aceh. Rhizophora stylosa was dominant species of mangrove in the study area that still remains after tsunami catastrophe in 2004. This study was conducted from February to April 2008, and the purposes were to obtain the decomposition rate of senescent leaves and to measure mass loss, and nutrient contents of decomposing leaves under different inundation regime. Three plots were established in each site. Decomposition of R. stylosa leaves were studied by using litter bag technique. They were made of synthetic nylon which had size 20x30 cm and mesh size was 1x1.25 mm2. Senescent leaves were used because they present major leaves on the forest floor and started to decay. Remaining leaves decreased during experiment period because decomposition process had been taking place in the study area. Time required for decomposing a half of the initial material (t50) was 67 days and 63 days for site next to the land and site next to the sea, respectively. The decay rate can be expressed by the decay coefficient (K) and the results of K were 0.010 and 0.011 (d-1). The value of carbon (C), nitrogen (N), C: N ratio and phosphorous (P) during decomposition periods were no significant difference in sites but significant difference in time. The C: N ratio of decomposing leaves decreased in both sites. Low C: N ratio in the last of observation indicated that R. stylosa leaves were decomposed easier at the end of observation than that in the beginning of observation. Key words: Rhizophora stylosa, leaves litter, mass loss, nutrients, Aceh.

INTRODUCTION Mangrove defined as primary natural features which have characteristic littoral plant formation and they grow in tropical and subtropical regions (Hutchings and Saenger, 1987; Aksornkoae, 1993). Mangrove forest is a unique and productive ecosystem along coastal zone that spread from Western part of Sabang to Eastern part of Merauke, Indonesia. It has significant role in ecological, environmental and socioeconomical sector (Lacerda 2002). As primary sources, this ecosystem providing organic matter that supports not only the mangrove ecosystem itself but also other related ecosystems (Aksornkoae 1993; Jonathan 1999). Mangrove leaves are the biggest part of the primary litter production and they become available to consumers and had a significant contribution towards the coastal food chain by following senescent and death leaves (Ananda et al. 2007; Berg and McClaugherty 2008). Breakdown of leaf is defined as weight loss due to some physical-chemical properties caused by environmental conditions such as temperature, moisture, and nutrient availability (GraĂ§a et al. 2005), animal feeding, microbial activity and leaching (Steward and Davies 1989). Berg and McClaugherty (2008) mentioned that chemical composition of decaying litter changes during decay process; it can be

characterized by the rate of mass loss and the nutrient immobilization. If nutrients are leached from leaves into the water, so they are available to organisms that live in mangrove ecosystem (Kao et al. 2002). Decomposers play an important role in the cycling of material and the flow of energy through an ecosystem (Holmer and Olsen 2002; Kuers and Simmons 2006). Besides fungi and bacteria as decomposer, protozoan, diatoms, nematodes, and polychaetes presence in the surface of senescent and decomposing leaves (Fell et al. 1984) and also on the soil surface and in the soil (Kuers and Simmons 2006). Crabs are also responsible for decomposition broken down litter into small pieces in order to be more easily decomposed by fungi and bacteria. Tidal flush and tidal current also give assistance in breaking down the litter to small pieces (Aksornkoae 1993). The amount of litter production and decomposition rate is very important to the nutrient cycle, main production, structure, and function of the ecosystem. Nitrogen (N) and Phosphorus (P) are important nutrients determining the quality of plant litter and their decomposition rates (Flindt and Lillebo 2005). The nutrient cycling and energy flow in mangrove ecosystem are quite complex, when mangrove plants receive sunlight for photosynthesis then they produce organic substances (Saenger and Snedaker 1993). Comparison between the value of carbon content and nitrogen content is called C: N

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ratio, this ratio estimate degradability ofthe organic material. Lower C: N ratio in one material indicates that the material is easier to be decomposed (Patrianingsih 2000). Rhizophora stylosa is dominant species of mangrove vegetation in Sabang- Weh Island, Aceh and it is growing naturally. Some of communities in this island entrust their life as fishermen and they commonly use mangrove area for fishpond land in order to increase their income besides tourism sector. Significantly, the most important indirect role is the fertilization of the estuary and coastal area. Nowadays, the area of mangrove forest in study area is starting to decrease with increasing the population and finally this condition will result in low mangrove production in this area. Deterioration of coastal ecosystem and mangrove vegetation will led to decrease of organic material productivity and decline of biological productivity in coastal area, owing to litter fall of mangrove is food, energy and material resources of and coastal ecosystem.. Therefore, the present study aims (1) to measure mass loss, the changing of carbon and nutrient content during decomposition period, (2) to obtain the decomposition rate of senescent leaves of mangrove (R. stylosa), and (3) to determine the correlation between decomposition rate and physical-chemical characteristics of water.

11 (3): 139-144, July 2010

the loss of leaf weight (Kuers and Simmons 2006). The litter bags were made of synthetic material and had size 20 x 30 cm (Mackey et al. 1995) with mesh size 1 x 1.25 mm2. Leaves as primary component were collected from senescent leaves. Collecting of senescent leaves was done manually by handpicked from the tree. Furthermore, collected leaves were oven dried at 60oC for 24 hours in order to make no surface water remained in leaves (Strojan et al. 1987; Hegazy 1998). 20 g of leaves after oven dried was placed in each litter bag and every bag was tied up in the prop root. Collecting of litter bags was done at 1st, 3rd, and 5th days, then weekly for three weeks and biweekly for six weeks. 18 litter bags were needed in each observation. Totally for 9 observations in 10 weeks, dry leaves needed were 3240 gram and litter bag was 162 bags. 0 day was also measured for sample control before decomposition was started. After collecting sample, the bags were returned to laboratory where they were rinsed in a sieve to remove sediment, and then continue with oven dried to have a constant mass. The samples were oven dried at 60oC for 2 days and weighed until constant and then final dry mass was recorded then continue with graining process to be a fine powder with mortar and pestle, finally leaves sample were taken ±5 gram to analyzed carbon, nitrogen, and phosphorous contents. Those analyses were done in Stable Isotope Laboratory, Goettingen University, Germany.

MATERIALS AND METHODS Study area The research had been conducted in Sabang-Weh Island, Aceh, Indonesia since February-April 2008. It is located in 05o46’28”-05o54’28” N and in 95o13’02”-95o22’36” E. The climate is dominated by rainy and dry season. The location was conducted in two sub-village of Iboih-Sabang affected by tsunami. Mangrove in research location is dominated by Rhizophora stylosa. Totally, 6 plots were selected of two sites which has different inundation regime. The 1st site consists of plot 1, 3 and 5 located next to the land (low inundation), and then the 2nd site consists of plot 2, 4 and 6 situated next to the sea (high inundation). Sampling of environmental parameters and sediment Environmental parameters were carried out in order to support analyses of decomposition process such as water temperature, salinity, and pH. Measuring of these parameters was done in situ. Sampling of sediment was taken by using shovel as depth as 10 cm from soil surface. Sample of sediment was transported to the laboratory in order to analyze textures, C, N and P of mangrove sediment. Analyses of sediment were done in Soil Laboratory, University of Syiah Kuala, Banda Aceh. Leaf decomposition experiments Leaf litter decomposition is commonly measured by using the litter bag technique (Ashton et al.1999). This technique is simple and effective to assess decomposition rate of leaf litter (Fell et al. 1984). Decomposition rate is usually investigated by enclosing an exact amount of mangrove leaves in litter’s bags, and regularly measuring

Statistical analysis Litter (leaf) which was already decomposed and percentage of leaves decomposed were calculated by using formula: D (%) 

B1  B 2 x 100 % B1

D is litter decomposed, B1 is dry weight before decomposition; B2 is dry weight after decomposition. The percentage of initial dry mass remaining in the litter bags were determined by using two sample t-Tests in STATISTICA 6.0 software. It was carried out to investigate the effect of site and time. The t-test method was based on the assumption that the variances in two groups are the same and this method was used to evaluate the differences mean between groups (Anonymous 2000). The relationship between percentage dry mass remaining in litter bags and sampling time at all sites best fitted in a negative single exponential model (Ashton et al. 1999). The formula is Xt  Xoe  Kt .Where Xt is percentage of the initial material, Xo is remaining after time t (days) and K is a decay coefficient (d-1). The times required for decomposition of half the initial material (t50) were determined by using the formula: t 50  ln 2 / K

RESULTS AND DISCUSSION Stand characteristics The composition of Rhizophora stylosa in the site next to the land had 76 stems/0.04 ha and in the site next to the

DEWIYANTI – Litter decomposition of Rhizophora stylosa

sea had 78 stems/0.04 ha. However, the differences between number of stems/ha found in both sites were not statistically significant (t-test, P=0.835). In average, diameter of R. stylosa was 11.15 cm and height was 7.56 m. For site next to the land, R. stylosa had 8.16 cm in diameter and 6.36 m in height. Furthermore, t-test showed that the differences between diameter and height found in both sites were not statistically significant (P diameter= 0.13, P height=0.14). R. stylosa had big value of basal area was found in the site next to the sea. It was covered about 121.51 cm2 of the area given of land that is occupied by the cross-section of tree trunks and stems at their base. Site next to the land had basal area of this species about 74.74 cm2. Besides R. stylosa, another species of mangrove found was Avicennia marina. A. marina found out in plot 1 was 4 stems/0.04 ha and it had big diameter. The basal area of this species achieved 1097.06 cm2. Mangrove vegetation in the study area was categorized low biodiversity because the presence of species detected was less than five species. R. stylosa is growing well in the study area which was dominated by sandy loam soil containing nutrient. Environmental parameter and sediment Average of temperature, salinity and pH were 28.72 0C, 36 ‰, and 8, respectively. Temperature was influenced by light penetration and forest cover. Salinity was high in both sites because directly influenced by the sea, and high salinity value was affected by evaporation and tide. Range of pH was the same in all plots, and close to sea water pH. They were not significantly difference between site (P>0.05), and did not show big fluctuation. The observation was done in the same season (dry season), so the characteristics of all plot were assumed uniform. In average, chemical and physical of surrounding water at mangrove vegetation was similar in site next to the land and next to the sea. It was presumed because the distance between two sites was not quite far due to the limitation of width (vertical) of study area; the distance was approximately 40 m. Texture of soil was analyzed according to percentage of sand, silt and clay fraction. Soil was dominated by sand fraction in both sites, due to the study area directly receives water from the sea and sand fraction was brought from the sea. Sand which is heavier than silt will settle on the soil surface. In the study area, sand was mainly deposited indicating that there was no strong current, tidal water and waves. For site next to the land, fraction of sand, silt, and clay were 59%, 19% and 21%, and site next to the sea were 62%, 25% and 13%, respectively (Table 1). These percentage was not statistically different between sites (P>0.05). Soil texture in study area was sandy loam and R. stylosa was growing well in the study area because it grows in appropriate sediment. The surface layers of 10 cm depth of mangrove forest were high in C content, ranging from 6.81% to 10.54%. The range of N was 0.23%-0.27% and C: N ratios ranged from 29.61 to 42.42. High organic matter in mangrove floor was presumed mostly come from fallen litter of mangrove leaves which was contributing significantly to the higher organic matter in sediment.

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Table. 1. General characteristics of sediment in study area

Site Next to the land

Plot

1 3 5 Average 2 Next to 4 the sea 6 Average

Sand (%) 68 53 57 59 61 62 62 62

Fraction Silt (%) 13 20 25 19 26 19 30 25

Clay (%) 19 27 18 21 13 19 8 13

Textures Sandy loam Sandy clay loam Sandy loam Sandy loam Sandy loam Sandy loam

Mass loss Mass loss was observed in the 1st, 3rd, 5th, 12th, 19th, th 26 , 40th, 54th and 68th day; in order to gain information about changing of mass loss not only in daily but also in weekly and biweekly. During the experiment period, the mass loss of mangrove leaves was changed significantly in both sites. The comparison between both sites at the end of observation showed that the percentage of decomposed litter was 56.68% ± 0.67 in site next to the land and it was 59.30% ± 1.81 in site next to the sea. In the first day of observation the percentage (%) of remaining litter was 92.38 ± 0.94 and 91.46 ± 1.62 in site next to the land and site next to the sea, respectively and then decreased until 43.32 ± 0.67 in site next to land and 40.71 ± 1.81 in site next to the sea at the end of observation (68th days) (Figure 1). The result explained that mass loss in site next to the sea was slightly higher than site next to the land where leaves remaining less in this site and both sites had similarity of the response to decomposition time; a longer time of decomposition results in a less remaining litter per period. This condition was caused because site next to the sea received bigger influence of physical tide process from sea water directly impacted fragmentation of leaves. Robertson (1988) and Ashton et al. (1999) explained that increasing decomposition rates because of water soaking caused leaching of labile material and high inundation caused more litter will be decomposed. Another reason the mass loss result from the abundant invertebrate such as juvenile of shrimps and crabs in the litter bag during experiment period, they entered as juveniles and then unable to escape after feeding. Decomposition rate is influenced by environmental factors such as temperature, nutrient content, sediment deposition rate, and densities of leaf-shredding invertebrates and soil moisture (Meyer and Johnson 1983). Mesh size of litter bag was enough to allow small invertebrates and microorganism as decomposer and feeder access to the leaves. Lambertini et al. (2000) mentioned that the abundance of bacteria, microorganisms and invertebrates enormously accelerates the decomposition process of the organic material produced by mangrove forest. Leaves decomposition rate were high in the beginning and at the end of degradation process and they were fluctuated during experiment period. Fell et al. (1984) stated that decomposition initially rapid than slow. This mode was suspected due to quality and quantity of the litter, element content acting as food for the soil microbe. It was also suspected that some materials of litter were easily

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dissolve or leaching in the beginning. After two weeks, leaves had lost 27.72% in site next to the land and 32.11% of site next to the sea; Davis et al. (2003) found that total leaf mass may be lost because of leaching up to 33% during an initial phase of a few days to weeks. Mass loss obtained by Ananda et al. (2007) after one week showed a rapid initial mass loss indicated by dried leaves had lost 38.3% owing to leaching in a mangrove of Southwest India.

Figure 1. Percentage of litter remaining in site next to the land and in site next to the sea during experiment period

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Carbon (C), nitrogen (N), C: N ratio and phosphorous (P) content The changing of C, N, C: N ratio and P during decomposition is showed in the Figure2. R. stylosa leaves contained high C and N content compared to P as nutrient during the decomposition period. Between sites, R. stylosa had similar values of C contained in decomposing leaves during observation. C content in site next to the land ranged from 42.33% ± 1.00 to 46.91% ± 1.88 and in site next to the sea it ranged from 42.41% ± 1.07 to 46.41% ± 1.10. The lowest C content was found in the first day of observation. Figure below also shows that site next to the land had the highest C content at the last observation (the 68th day) and at the 54th day for site next to the sea. Based on this figure, C contained in decomposed leaves increased during observation but sometimes it was fluctuated during observation in both sites. Increasing C was presumed because the rising concentrations of structural carbohydrates as a result of the loss of sugars and starches in detritus and decreasing carbon content was indicated by dry weight loss caused rapid release of total nonstructural carbohydrates which is easily used by microbes. Mfilinge et al. (2002) found that C an initial decreased and then increased during decomposition a subtropical mangrove forest at Oura Bay, Okinawa, Japan. Fell and Master (1980) mentioned that in dry weight of senescent Rhizophora mangle leaves, carbon represents 45% and about half of this carbon is leached and then half becomes particulates detritus. Nitrogen (N) increased slowly with increasing duration of decomposition periods in both sites. It was presumed because of microbial N immobilization as a result of accumulation of microbial biomass and products of microbial activity. Comparison of both sites showed that increasing N content was slightly higher in site next to the land than site next to the sea which ranged from 0.53% ± 0.01 to 1.03% ± 0.07. In site next to the sea, N ranged from 0.53% ± 0.01 to 0.99% ± 0.05. The lowest N was gained in the first observation and this value was the same in both sites of observation. Fell and Newell (1981) and also Holguin et al. (2001) found that total N in decomposing leaves increased from time because of N immobilization and decomposer activity (Rice 1982). Fell and Master (1980) found that N was initially 0.2-0.4% of the dry weight and then increasing to 0.5 % because of microbial N immobilization.

K (d-1) is decay coefficient that can determine the rate of decomposition. Average of K in site next to the land was 0.010 d-1 ± 0.000577 and in site next to the sea was 0.011 d1 ± 0.001. There was not significantly different between K next to the land and next to the sea (at P> 0.05) by using 95% confidence interval (α=0.05). T-test result informed that the mean of K was equal in both sites; implying that there was not significantly different decomposition rate of R. stylosa leaves in both sites. Ananda et al. (2007) stated that mass loss as function of time by using exponential decay model can be categorized into tree categorizes those are fast (K>0.01), medium (K= 0.005-0.01), and slow (K<0.005). Decay coefficient in both sites indicating that rate of decomposition in this study area was medium. A t50 is time required for the decomposition of half the initial material, average of t50 were 67 days and 63 days for site next to the land and site next to the sea, respectively (Table. 2). The value showed that time to decompose a half the initial material in site next to the sea decompose slightly fewer than at the site next to the land. This value was correlated with mass loss where at the end of observation site next to the sea had less percentage of litter remaining (40.70%) than site next to the land Table 2. Value of decay coefficient (K) from litter remaining (%) and t50 (43.32%). Ashton et al. (1999) found that t50 in Rhizophora Site Plot Equation K (d-1) R2 apiculata was 76 day (in cleared site) and 43 day (in Virgin Jungle Next to the land 1 y = 0.8742e-0.01x 0.01 R² = 0.9321 Forest Reserve) of mangrove forest 3 y = 0.8758e-0.011x 0.011 R² = 0.919 5 y = 0.8892e-0.01x 0.01 R² = 0.9294 in Peninsular Malaysia. Some Average 0.010 ± 0.00056 0.927 factors presumed influence high Next to the sea 2 y = 0.8861e-0.012x 0.012 R² = 0.9439 leaves decomposed in this site were -0.01x 4 y = 0.867e 0.01 R² = 0.9168 inundation factor, environmental 6 y = 0.8762e-0.011x 0.011 R² = 0.938 factors, and decomposer. Average

0.011 ± 0.001

0.933

t50 (days) 69 63 69 67 57 69 63 63

DEWIYANTI – Litter decomposition of Rhizophora stylosa

143

Figure 2. Changes in C, N, C: N ratio, and P Content from both sites during decomposition.

Furthermore, increasing N was related to the decreasing T-test result explained that, there was no significant C: N ratio. The initial of C: N ratio was 81.81 and it difference in the loss of dry weight, C, N, C: N ratio, and P decreased during the decomposition period in both site. of decomposed R. stylosa leaves in the two sites of the field The study found that C: N ratio ranged from 79.61 ± 2.76 research at the P> 0.05. It means the mean value of those in the beginning of observation to 45.52 ± 1.54 at the end parameters during observation were equal in the both sites. of observation in site next to the land and from 79.76 ± On the other hand, there was significant difference in the 3.27 to 45.58 ± 1.76 in site next to the sea. Leaves of R. loss of dry weight, C, N, C: N ratio, and P content based on stylosa decompose faster at the end of observation than in time (at the beginning and at the end of observation) in all the beginning of observation which was indicated by low plots of study area at the P< 0.05. It means the mean values of C: N ratio at the end of observation. Mfilinge et al. of those parameters during observation were not equal to (2002) mentioned that high N concentration or low C: N the all plot observation and those variables were changed ratio enhanced rapid microbial colonization and low C: N from time to time. ratio will have relatively low recalcitrant and will decompose fast. Fell et al. (1984) found that C: N ratio decreased Correlation between physical and chemical during the decomposition from 120 in senescent leaves to characteristics of water and remaining litter 43 in partially decomposed leaves observed from nutritive The correlation between physical and chemical enrichment of Rhizophora mangle in South Florida because characteristics of water and remaining litter gained in six loss in carbon content and increase in final nitrogen. plots during experiment period is shown in Table 3. They Phosphorous content ranged from 0.06% ± 0.03 to were analyzed in order to know the linear relationship 0.19% ± 0.08 in both site. The highest content of P was in between two variables. Correlation coefficient ranged from the 54th day in site next to the land and the 40th day in site -1.00 to +1.00. There was significant correlation between next to the sea. In average, the P content in both sites had temperature and remaining litter (P<0.05), the r value of similar value. In Figure above is also showed that in the correlation between temperature and remaining litter was early step of decomposition process P did not show 0.80, this value represents a significant correlation between significantly. Content of P increased during the observation temperature and proportion of remaining litter (P<0.05). although occasionally in some period P declined, it increased because of P Table 3. Value of coefficient determination (r2), correlation coefficient (r), P immobilization (Tam et al. 1990). The content value and regression equation of P in study area can be categorized height (0.05%-0.19%) if compared with result of the Parameters r2 r P value Equation research done by D’Croz et al. (1989). They Temperature 0.6400 -0.8000 0.0000* y = 587.524785-18.3255229*x found that P increased from 0.04% to 0.13% of Salinity 0.0133 -0.1153 0.4066 y = 174.045371 -2.9428318*x red mangrove (Rhizophora mangle L.) leaves pH 0.0458 -0.2141 0.1200 y = 324.8625-32.2706897*x in the bay Panama.

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This means that the higher the temperature the less the remaining litter will be gained but there was no significant correlation between salinity, pH and remaining litter (P>0.05) because salinity and pH did not change during observation. Graca et al. (2005) mentioned that breakdown of the leave is defined as weight loss due to some physicalchemical properties caused by environmental conditions such as high temperature and also Kuers and Simmons (2006) found that the decomposition process increases in accordance with temperature.

CONCLUSION Mangrove vegetation in Iboih village, Weh Island, Aceh, Indonesia is dominated by Rhizophora stylosa and this species is growing well in study area. Remaining leaves decreased during experiment period owing to decomposition was happened in the study area, which also implies that the percentage of decomposed mangrove litter increased by increasing the decomposition period. Rate of decomposition was not statistically different between site next to the land which had lower inundation than site next to the sea and remaining litter was significant different between time where dry weight of decomposed leaves was changed during the observation period. Time required for the decomposition of half the initial material (t50) was 67 days in site next to the land and 63 days in site next to the sea. Remaining litter of Rhizophora stylosa was influenced by water temperature where higher the temperature would result in less remaining litter during experiment period, but pH and salinity did not have correlation with remaining litter. Carbon and nutrients contained in Rhizophora stylosa leaves changed during decomposition process but there was no significant difference in carbon, and nutrients between sites where the mean value of those was similar but significant difference was found in time. Leaves of Rhizophora stylosa decomposed faster at the end of observation than in the beginning of observation which was indicated by low of C: N ratio at the end of observation.

ACKNOWLEDGEMENTS My great honorable is to German Academic Exchange Service (DAAD) for financing during my study. My deepest thanks and appreciation to Dr. Luitgard Schwendenmann and Prof Dr. Dirk Hölscher from the Institute of Tropical Silviculture, University of Göttingen for their kindness to supervise with valuable knowledge and encourage me continuously. My special gratitude I address to Tropenzentrum staff and the committee of Triangle Partnerships GAUG-IPB-UNSYIAH. REFERENCES Aksornkoae S (1993) Ecology and management of mangroves. IUCN, Bangkok, Thailand. Ananda K, Sridhar KR, Raviraja NS, Baerlocher F (2007) Breakdown of fresh and dried Rhizophora mucronata leaves in a mangrove of Southwest India. Original Paper: Wetlands Ecol Manage. 112: 73-81

11 (3): 139-144, July 2010 Anonymous (2000) Experiment planning and data analysis. Institut fuer Forstliche Biometrie und Informatik. Lecturer material. Georg August University, Goettingen, Germany. Ashton EC, Hogarth PJ, Ormond R (1999) Breakdown of mangrove leaf litter in a managed mangrove forest in Peninsular Malaysia. Hydrobiologia 413: 77-88. Berg B, McClaugherty C (2008) Plant Litter; decomposition, humus formation, carbon sequestration. Springer, Berlin. Davis SE, Corronado-Molina C, Childers DL, Day JW Jr (2003) Temporally dependent C, N, and P dynamics associated with the decay of Rhizophora mangle L. Leaf litter in oligotrophic mangrove wetlands of the Southern Everglades. Aquatic Bot 75: 199-215. D’Croz L, Del Rosario J, Holness R (1989) Degradation of red mangrove (Rhizophora mangle L.) leaves in the Bay of Panama. Rev Biol Trop 37: 101-104. Fell JW, Master IM (1980) The association and potential role of fungi in mangrove detrital systems. Bot Mar 23: 257-263. Fell JW, Master IM, Wiegert RG (1984) Litter decomposition and nutrient enrichment. Monogr Oceanogr Meth 8: 239-251. Fell JW, Newell SY (1981) Role of fungi in carbon flow and nitrogen immobilization in coastal marine plant litter systems. In: Wicklow DT, Carroll GC (eds.). The fungal community. Marcel Dekker, New York. Flindt MR, Lillebo AI (2005) Determination of total nitrogen and phosphorous in leaf litter. Springer, Netherlands. Graça MAS, Baerlocher F, Gessner MO (2005) A practical guide; methods to study litter decomposition. Springer, Netherlands. Hegazy AK (1998) Perspectives on survival, phenology, litter fall and decomposition and caloric content of Avicennia marina in the Arabian Gulf Region. Arid Environ 40: 417-429. Holguin G, Vazquez P, Bashan Y (2001) The role of sediment microorganisms in the productivity, conservation, and rehabilitation of mangrove ecosystems. Biol Fertil Soils 33: 265-278. Holmer M, Olsen AB (2002) Role of decomposition of mangrove and sea grass detritus in sediment carbon and nitrogen cycling in a tropical mangrove forest. Mar Ecol Prog Ser 230: 87-101. Hutchings P, Saenger P (1987) Ecology of mangroves. University of Queensland Press, Australia. Jonathan MD (1999) Spatial variation in litter production by the mangrove Avicennia marina var. australasica in Rangaunu Harbour, Northland, New Zealand. Aust J Mar Freshwat Res 33: 163-172. Kao WY, Hung CT, Chen NS, Tyng TT, Linda LH (2002) Nutrient contents, d13C and d14N during leaf senescence in the mangrove, Kandelia candel (L.). Druce. Bot Bull Acad Sin 43: 277-282. Kuers K, Simmons J (2006) Leaf litter decomposition. CAWS Litter decomposition study. Springer, Netherlands. Lacerda LD (2002) Mangrove ecosystem; function and management. Springer, Netherlands. Lambertini M, Venerella J, Capua K (2000) A naturalist’s guide to the Tropics. University of Chicago Press, Chicago, United States. Mackay AP, Smail G (1995) The decomposition of mangrove litter in a sub tropical mangrove forest. Hydrobiologia 332: 93-98. Meyer JL, Johnson C (1983) The influence of elevated nitrate concentration on rate of leaf decomposition in a stream. Freshwater Biol 13: 177-183. Mfilinge PL, Atta N, Tsuchiya M (2002) Nutrient dynamics and leaf litter decomposition in a subtropical mangrove forest at Oura Bay, Okinawa, Japan. Trees 16: 172-180. Patrianingsih AE (2000) The effect of concentration bacteri isolate mangrove sediment with leaves litter mangrove decomposition (Rhizophora sp). (Thesis). FMIPA, Universitas Hasanuddin, Makassar. [Indonesia]. Rice DL (1982) The detritus nitrogen problem; new observations and perspectives from organic geochemistry. Mar Ecol Prog Ser 9: 153-162. Robertson AI (1988) Decomposition of mangrove leaf litter in tropical Australia. J Exp Mar Biol Ecol 116: 235-247. Saenger P, Snedaker SC (1993) Pantropical trends in mangrove aboveground biomass and annual litter fall. Oecologia 96: 293-299. Stewart BA, Davies BR (1989) The influence of different litterbag designs on the breakdown of leaf material in a small mountain stream. Hydrobiologia 183: 173-177. Strojan CL, Randall DC, Turner FB (1987) Relationship of leaf litter decomposition rates to rainfall in the Mojave desert. Ecology 68: 741744. Tam NFY, Vrijmoed L, Wong YS (1990) Nutrient dynamics associated with leaf decomposition in a small mangrove community in Hong Kong. Bull Mar Sci 47: 68-78.

B I O D I V E R S IT A S Volume 11, Number 3, July 2010 Pages: 145-150

ISSN: 1412-033X (printed edition) ISSN: 2085-4722 (electronic) DOI: 10.13057/biodiv/d110308

Predicting infectivity of Arbuscular Mycorrhizal fungi from soil variables using Generalized Additive Models and Generalized Linear Models IRNANDA AIKO FIFI DJUUNA1,2,â&#x2122;Ľ,, LYNETTE K. ABBOTT2, KIMBERLY VAN NIEL2 1

Department of Soil Sciences, Faculty of Agriculture and Agriculture Technology, The State University of Papua (UNIPA), Manokwari, Gunung Salju St. Amban Manokwari 98314, West Papua, Indonesia. Tel. +62-0986- 211830, Fax: +62-0986-213513, ď&#x201A;Še-mail: irnanda_d@yahoo.com.au 2 School of Earth and Geographical Science, The University of Western Australia, Crawley 6009, WA Manuscript received: 25 January 2010. Revision accepted: 5 June 2010.

ABSTRACT Djuuna IAF, Abbott LK, Van Niel K (2010) Predicting infectivity of Arbuscular Mycorrhizal fungi from soil variables using Generalized Additive Models and Generalized Linear Models. Biodiversitas 11: 145-150. The objective of this study was to predict the infectivity of arbuscular mycorrhizal fungi (AM fungi), from field soil based on soil properties and land use history using generalized additive models (GAMs) and generalized linear models (GLMs). A total of 291 soil samples from a farm in Western Australia near Wickepin were collected and used in this study. Nine soil properties, including elevation, pH, EC, total C, total N, P, K, microbial biomass carbon, and soil texture, and land use history of the farm were used as independent variables, while the percentage of root length colonized (%RLC) was used as the dependent variable. GAMs parameterized for the percent of root length colonized suggested skewed quadratic responses to soil pH and microbial biomass carbon; cubic responses to elevation and soil K; and linear responses to soil P, EC and total C. The strength of the relationship between percent root length colonized by AM fungi and environmental variables showed that only elevation, total C and microbial biomass carbon had strong relationships. In general, GAMs and GLMs models confirmed the strong relationship between infectivity of AM fungi (assessed in a glasshouse bioassay for soil collected in summer prior to the first rain of the season) and soil properties. Key words: AM Fungi, GAM, GLM, land use.

INTRODUCTION Most agricultural crops are colonized by arbuscular mycorrhizal fungi (AM fungi), which occur in almost all soils, but the variability of species abundance differs across soil types (Abbott and Robson 1991). These fungi are claimed to be a main component of the soil micro biota in most agro-ecosystems. Some studies have been done on the benefit of indigenous AM fungi to the growth of plants in field soils, but it is difficult to assess the contribution of these fungi under the field conditions (Fitter 1985; Jakobsen 1994; Jakobsen et al. 2002). The infectivity of AM fungi in soil has been found to be related to agricultural management practices such as (i) cropping systems (e.g. Thompson 1987; 1991; Bagayoko et al. 2000; Johnson et al. 1991; Hendrix et al. 1995), (ii) fertilizer application (e.g. Abbott and Robson 1984; Thomson et al. 1992; Gryndler et al. 1990; Liu et al. 2000; Joner 2000), (iii) cultivation (e.g. McGonigle and Miller 2000; Kabir et al. 1997; Johnson and Pfleger 1992; Douds et al. 1995), and (iv) land use intensity (Oehl et al. 2003; 2004). Agricultural practices are also known to reduce the abundance and diversity of mycorrhizal fungi (Boerner et al. 1996; Helgason et al. 1998). However, these relationships do not always hold.

Statistical modeling is commonly used to test relationships and to predict species distributions. With statistical techniques and GIS tools, the development of predictive habitat models has rapidly increased especially in ecological studies (Guisan and Zimmermann 2000). Statistical methods are based on correlation and often have as their purpose, the aim of prediction. Soil properties and land use history are the most important variables which are directly related to the infectivity of AM fungi. However, the nature and strength of the relationships between AM fungal infectivity, soil properties and land use history has not been explored. If there is a strong relationship, it would be possible to spatially predict the infectivity of AM fungi in soil based on soil characteristics and land use variables using statistical modeling. A range of data analysis methods can be applied to develop models for spatial prediction using environmental correlation. The most common method includes multiple regression models such as generalized linear modeling (GLM) (McCullagh and Nelder 1989) and generalized additive modeling (GAM) (Hastie and Tibshirani 1986; Yee and Mitchel 1991), which appear to be increasingly used for predicting species and habitat distribution. These models have been extensively reviewed by Franklin (1995), and Guisan and Zimmermann (2000).

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GAMs and GLMs were selected in this study because these statistical models have been used as an exploratory tool in the analysis of species distribution with respect to the environmental factors. GAMs have been used in numerous studies of species-environment relationships (e.g., Bio et al. 1998; Austin 1999; Guisan and Zimmermann 2000). They are considered useful for exploring the shape of the response function because they do not assume any general shape of the response prior to estimation (Austin and Meyer 1996). Bio et al. (1998) concluded that GAMs are a useful and practical technique for improving current regression-based vegetation models by allowing for alternative complex response shapes. GLMs allow those response functions to be parameterized and their significance tested (Franklin 1998). GAMs and GLMs approaches have enabled biologists to model species responses to a wide range of environmental data types under a single theoretical and computational framework (Yee and Mitchell 1991). The objectives of this study were: (i) to test the strength and nature of the relationships (using GAM) and, if possible, predict the infectivity of AM fungi in soil based on soil characteristic variables and land use history on a Wickepin farm, and (ii) to model the relative impacts of land use and soil characteristics at a farm scale.

MATERIALS AND METHODS Data sets Soils and land use history data of Wickepin (Djuuna 2006) were used. The 291 sampling points contains records of 15 data sets determined for each paddock. Each sampling point covers an area of 150 m2. The infectivity records of AM fungi from bioassay data such as the percentage of root length mycorrhiza (%RLC) was used as response variable (dependent variable), and the following nine soil variables as predictors (independent variables): elevation, pH, EC, total C, total N, P, K, soil texture, and microbial biomass carbon. The selection of the predictor variables was based on important major factor influencing AM fungi generally in soil. Correlation coefficient tests were used to determine if there is any correlation among the predictor variables. The selected predictor variables show weak correlation with each other except for total C and total N. Because of this high correlation between total C and total N (r=0.91), one of these predictor variables cannot be used in the modeling. Total N was therefore only examined for shape and strength of the response in GAM modeling, but was not included in the stepwise model development and k-fold cross-validation analysis. Total N was selected for removal rather than total C, because two components of N (N-NH4) and N- NO3) were included. Methods of analysis Generalized Linear Models and Generalized Additive Models GAMs were first parameterized using soil characteristics and land use variables. A smoothing spline term was used to explore the shape of the response curve

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and the strength of the relationship between response variable (dependent variable) such as %RLC and predictors (independent variables) i.e. soil characteristics (pH, EC, P etc). GLMs were parameterized for all variables using the response functions suggested by the GAMs (Franklin 1998). The interactions of variables were evaluated for significance in the GLMs. All variables were tested for significance using forward and backward stepwise selection, with response curves at different levels of complexity for each variable. The stepwise model selection procedure was started with the full model, and then at each step, one independent variable was tested for omitting and re-introducing to the model (Pearce and Ferrier 2000). Variables in the GLMs were tested for significance and deleted if not significance (backward elimination). The backward elimination is one of the procedures to be used in the model which is most powerful for fitting models to designed experimental situations (Nicholls 1989). In addition, the forward stepwise procedure is useful for exploratory model building. The model that had the lowest value for Akaikeâ&#x20AC;&#x2122;s Information Criterion (AIC) was kept. The selection stopped when there was no independent variable addition or omission that would lower the AIC value. Statistical analyses were carried out using the S-Plus version 6.2 for Windows. Goodness of-fit The model fit and significance of the variables were evaluated using the residual deviance (analogous to the residual sum of squares in the linear model). The residual deviance can be compared with analysis of variance using a x2- test. Model evaluation The GAM and GLM models obtained from stepwise selection for infectivity of AM fungi were compared and evaluated in terms of discrimination using the Area Under the receiver operator Curve (AUC). This method provides a threshold-independent evaluation of the predictive performance of models than traditional comparison of relative error (Bradley 1997; Duda et al. 2001). Cross validation Model power and stability was evaluated using a k-fold cross-validation method (Fielding and Bell 1997). This method provides insight to the predictive power of the model, by measuring how well models developed from different data segments predict the omitted data. It gives a reasonable estimation of how well the model would perform on new data and can point to model instability. Data were randomly split into 10 equal-size groups. At each iteration, 9 of the 10 groups were used to build the model, and the other group was used as an independent validation set to evaluate the performance. This method was repeated 10 times. As a measure of how well the model predicts unknown data, the mean prediction error and the variance in the prediction error were also calculated across all iterations. Mean prediction error provides information on how well all models performed, while the variance gives insight to model instability.

DJUUNA et al â&#x20AC;&#x201C; Predicting infectivity of AM fungi using GAMs and GLMs

RESULTS AND DISCUSSION GAMs and GLMs: Variable selection and response curves Regarding the different response shapes between soil variables and the percentage of root length colonized by AM fungi, GAMs parameterized for root length mycorrhiza suggested skewed quadratic responses to soil pH, NH4-N NO3--N and microbial biomass carbon; cubic responses to soil K, soil P and EC; and linear responses to elevation, total carbon, C/N ratio, clay and silt as well as the land use history (pasture). These results show that there is a tendency of a strong relationship between some soil variables and the root length colonized by AM fungi, especially for the linear response shapes. For example, elevation and total carbon showed negative linear relationships with percentage root length colonized by AM fungi. This indicates that the infectivity of AM fungi varies with elevation and total carbon distribution in the soil. However, percent clay and silt showed positive linear relationship to infectivity. Based on the distribution of soil types on the farm, sandy soils were more common at higher elevation, and this corresponded with lower infectivity. The different response shapes between soil variables and the total mycorrhizal root length, GAMs parameterized for total mycorrhizal root length suggested skewed quadratic responses to NH4-N, soil pH, EC, C/N ratio and microbial biomass carbon; cubic response to elevation; and linear responses to NO3-N, total carbon, soil P and soil K. In general, the strength of the relationships between percentage root length colonized by AM fungi and soil properties on this farm showed that some soil properties had little influence on the infectivity of AM fungi. In general, the GAM models demonstrated that total mycorrhizal root length was not influenced by some of the soil properties, including NH4, NO3, P, pH, K and EC. This result contradicts that from greenhouse studies which have found strong explanatory relationships between P and the infectivity of AM fungi (e.g. Abbott and Robson 1982; Bolan 1991; Marschner and Dell 1994: Ryan et al. 2004; Thomson et al. 1992; Vejsadova et al. 1989). However, the past studies have focused on a small range of P at low levels (0-60 mg.kg) compared to those found at the Wickepin farm (11-500 mg/kg). The shape of the response curve within the range of previous studies for P and %RLC is in agreement with these findings, displaying a reasonably tight fit around these levels of P with decreasing AM fungi infectivity with increasing P. In addition, there was a reasonably strong negative relationship between elevation and percentage root length. This relationship may be explained by higher soil moisture levels at lower elevations as well as a deeper soil profile. Percentage and total mycorrhizal root length also increased with increase in total N but decreased with increase in C. The summary of the shape of response functions for each soil variable and land use history for %RLC is presented in Table 1. Among the response variables, elevation, microbial biomass carbon and total C showed significant correlations (p<0.05) with %RLC for the GAM model. This was also similar to %RLC of the GLM model. The significant relationships for %RLC, for example with

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elevation, were generally linear, although some of the weak relationships were skewed quadratic (e.g. pH). Table 1. Summary of the shape of response functions for each soil variables and land use history for %RLC Response Eleva- Land function tion use RLC (n=291) GAMs Linear 1 1 Piecewise linear 0 1 Skewed quadratic 0 0 Bimodal 0 0 No relationship 0 0 GLM Significant 1 1

pH EC

Total C

K MBC

0 0 1 0 0

1 0 0 0 0

0 0 0 0 1

0 0 1 0 1

Note: 1 = Presence, 0 = Absence

The deviance from the GAM and GLM models obtained by stepwise analysis is summarized in Table 2. Both the GAM and GLM models had similar values of residual deviance and the null deviance. However, the residual deviance of GAM models for %RLC were lower than the GLM models, showing that the GAM models had slightly better model fits. The GAM models explained 14% of the variation in %RLC while the GLM models only explained 6.5%. These outcomes show that although others have found strong relationships with soil properties and mycorrhizal colonization, these relationships may not be evident in field data. The final models from the stepwise selection method and the model evaluation are shown in Table 3. The GAM model for %RLC had the best AUC value (0.61) while all models had the same kappa (pk) value (0.50). The explanatory variables selected for the final GAM and GLM models were very similar with only minor differences. The most frequently selected explanatory variables were elevation, land use, total carbon, soil P, soil K, microbial biomass carbon and soil pH. However, the weakness of the relationship with P, as discussed earlier, along with other evident but weak relationships (e.g. elevation) is demonstrated in the weak predictive power of all four models. Results based on the 10-fold cross-validation are presented in Table 4. The mean prediction error for %RLC differed for GAM and GLM. However, mean prediction error of the GLM models was lower than that of the GAM model. This may indicate that although GAMs had a better fit, across all iterations they may be over fitted and unable to generalize to unknown data. However, the AUC values for the GAM model for %RLC indicate that the final GAM model selected was reasonably good at predicting unknown data. In general, the regression models of GAM and GLM developed in this study provide insight to the nature of the relationship between AM fungi and environmental factors in the field. However, they were not good predictors of AM fungi infectivity. These prediction models mainly depend on environmental variables such as soil properties and land

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Table 2. Summary of GAM and GLM final models of the infectivity of AM fungi from soil characteristics and land use history. Infectivity of AM Fungi %RLC

GAM n of Null Residual Residual degree observation deviance deviance of freedom 291 289.16 248.64 255

n of Residual variables deviance 10 270.26

GLM Residual degree of freedom 272

n of variables 10

Table 3. The final models and their model evaluation parameters Infectivity of AM Fungi %RLC

Model GAM GLM

Terms Land use + s (elevation)+s (NO3)+s (TotalC)+s (P)+s (K)+s (MBC) Elevation + Total-C + C/N + P + MBC + I (totalC^2)+I (C/N^2)

AUC

0.61 0.55

0.50 0.50

Table 4. Cross validation results of GAM and GLM models of the infectivity of AM fungi from soil characteristics and land use history (K=10 replicates; SQRT= Square root)

Infectivity n of of AM fungi observation %RLC

291

Mean prediction error 1593.35

GAM SQRT Mean log variance prediction prediction error error 19.03 1.69

use features. As some soil properties had low correlation with the infectivity of AM fungi, the GAM and GLM models were influenced by these relationships. This is supported by some studies which investigated how the variation in response variable would influence the outcome of the model (Pearce and Ferrier 2000; Pearce et al. 2001). In the GAM response curve, there was a linear relationship between the infectivity of AM fungi and environmental and soil properties such as elevation, total carbon, C/N ratio, soil P, EC, soil K and NO3. Among these predictor variables, soil P is only the major nutrient that was expected to directly influence AM fungi status in the soil. It is generally accepted that the beneficial effects of AM fungi decrease as the supply of P increases (Abbott and Robson 1984). Previous studies have found that very high and very low levels of soil P reduced AM fungi colonization (e.g. Koide and Li 1990). However, these studies have investigated a smaller range of P, with much lower values than found at this site. There is some evidence in the GAM response curves that the relationship found by others between %RLC and P may be identified within the known range. Generalized additive modeling is a powerful tool to facilitate choice of a possible response shape without having to assume any particular relationships between the dependent and independent variables (Shipley and Hunt 1996). However, most of the relationships were found to be linear. The linear response curves of some soil properties were not followed with the significant correlation with the infectivity of AM fungi. Elevation, total carbon and soil microbial biomass carbon showed significantly correlations

SQRT log variance prediction error 0.02

Mean prediction error 211.88

GLM SQRT Mean log variance prediction prediction error error 16.40 0.80

SQRT log variance prediction error 0.005

(p<0.05) with %RLC in the GAM and GLM models. These results indicated that these three factors were better predictors of the infectivity of AM fungi in the soil than other soil properties. Elevation was an important factor in this field study because it predicted the infectivity of AM fungi better than other soil properties. This result might be correlated with the soil moisture depth of the soil profile, as at low elevations the infectivity of AM fungi was higher. Different elevation can cause a different moisture content of soils, because soil water has a characteristic of potential gravity. That is mean the water tend to move to the lower part or low elevation. Consequently, the moisture content of the upper elevation is more dry than on the lower elevation. There have been no other agricultural studies which have identified the influence of elevation on the status of AM fungi in the soil. However, in tropical rainforest, Meyer (1973) hypothesized that lower elevation of forest trees are predominantly by AM fungi, while at higher elevations mostly found the ectomycorrhizal. As noted by Read (2002), tropical grasslands are predominantly by AM fungi, while in the deserts areas are dominated by AM fungi plants with occasional ectomycorrhizal trees. In addition, in more temperate regions, at low elevations, grasslands are also dominated by AM fungi with some individual of ectomycorrhizal trees. These broader ecological studies may have little relevance to the local landscape at the farm at Wickepin however, where low agricultural plant diversity occurs. The final GAM model was chosen from the stepwiseselected models based on their performance assessed through cross-validation. More than a half of the soil

DJUUNA et al â&#x20AC;&#x201C; Predicting infectivity of AM fungi using GAMs and GLMs

properties were able to predict the %RLC. However, the ROC analysis, which was used to assess the expected performance of the GAM model, was rather low for %RLC as the AUC value was lower than 0.7%. Similar results were also shown for the GLM model with a low AUC value. The infectivity of AM fungi has previously been found to depend partly on soil characteristics and the environment. This study, however, has shown either a lack of relationship (e.g. with P) or a contradictory relationship (e.g. with C) to those found in glasshouse experiments. There may be various reasons for this for the marked differences between this field study and that of previous glasshouse studies. The outcomes in this study may be due primarily to driving factors which have not been considered or included in these models. Field experiments do not allow for control of a number of factors, including unknown environmental and historical (including climatic and weather) influences. Certain findings (such as the relationship with P) may have been affected by the inclusion of fertilizer in field samples. However, it is also possible that clear relationships in glasshouse studies may not be directly applicable to the field, where competing influences may interact and impact both the strength and nature of relationships. This study suggests that some soil properties and land use variables could be used as predictor variables to predict the infectivity of AM fungi. Further investigation is required to develop models with good predictive power, including the selection of explanatory variables. However, this study has demonstrated that predictive modeling using standard statistical regression procedures can be applied to studies of AM fungi.

CONCLUSION This study found that soil properties (i.e. total carbon, phosphorus, potassium, nitrate, soil pH, and microbial biomass carbon) and land use tended to have weak linear relationships with %RLC on a sheep-cropping farm at Wickepin in Western Australia. The relationship with elevation was again supported in this analysis. Further study is necessary into the potential direct drivers of infectivity in paddocks, for which elevation was a weak surrogate. This study demonstrated that a generalized additive model and a generalized linear model are useful tools to study the nature and strength of the relationships between environmental and land use variables and the infectivity of AM fungi.

ACKNOWLEDGMENT The authors would like to thank Australian Government through provision of an Australian Development Scholarship, ADS-AusAID for the Postgraduate Scholarship, and Dr Berwin Turlach (The University of Western Australia) for the training in use of the GAM and GLM models.

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B I O D I V E R S IT A S Volume 11, Number 3, July 2010 Pages: 151-156

ISSN: 1412-033X (printed edition) ISSN: 2085-4722 (electronic) DOI: 10.13057/biodiv/d110309

Floristic composition at biodiversity protection area in Lubuk Kakap, District of Ketapang, West Kalimantan SUGENG BUDIHARTA♥ Purwodadi Botanic Garden, Indonesian Institute of Sciences (LIPI). Jl. Raya Surabaya-Malang Km. 65, Purwodadi, Pasuruan 67163, East Java , Indonesia. Tel.: +62 341 426046; Fax.: +62 341 426046; e-mail: sugengbudiharta@yahoo.com Manuscript received: 10 March 2010. Revision accepted: 14 June 2010.

ABSTRACT Budiharta S (2010) Floristic composition at biodiversity protection area in Lubuk Kakap, District of Ketapang, West Kalimantan. Biodiversitas 11: 151-156. A study on floristic composition has been conducted at biodiversity protection area (Kawasan Perlindungan Plasma Nutfah, KPPN) of PT. Suka Jaya Makmur in Lubuk Kakap, District of Ketapang, West Kalimantan. Two sampling methods were used: Point-Quarter sampling (Quadrant method) of 50 m was applied to class of tree, and 2x2 m2 plot sampling to class of sapling. Of 20 sampling units, 48 species of tree (belong to 27 genera and 13 families) and 94 species of sapling (belong to 54 genera and 28 families) were recorded. Shannon-Wiener diversity index (H’) were 3.54 and 3.49 for tree and sapling respectively, while Pielou evenness index (J’) were 0.91 and 0.77 for tree and sapling respectively. Forest ecosystem in this area can be classified as lowland ever wet tropical rain forest which dominated by dipterocarps species. Species of sapling with the highest importance value index were Shorea laevis, Hopea dryobalanoides and Shorea sandakanensis, while that of tree included Dipterocarpus caudiferus, Shorea laevis and Dryobalanops sp. The floristic composition at family level showed comparatively similar pattern with that at other sites in Kalimantan although composition at species level was different. Key words: biodiversity protection area, dipterocarpaceae, floristic composition, High Conservation Value Forest (HCVF), production landscape.

INTRODUCTION Indonesia is one of 17 mega-biodiverse countries (Mittermeier et al. 1997), but is facing a rapid loss of biodiversity (Sodhi et al. 2004). In terms of floristic richness, Indonesia ranks fifth in the world and contains more than 38,000 plant species with 20,000 of these identified as endemic species (Bappenas 2003). In just 50 years, Indonesia has lost as much as 50% of forest cover with cover being reduced from 162.29 million hectares in 1950 to 86 million hectares in 2003 (FWI/GFW 2002; Indonesian Ministry of Forestry 2005). The major causes of deforestation in Indonesia are timber extraction, local population migration, and forest conversion to agricultural lands, plantation areas and mining sites (FWI/GFW 2002; Bappenas 2003). Even though the Indonesian government has officially preserved as much as 23.89 million hectares (12.5% of total land) as protected areas (WRI 2003), the pressures on biodiversity are still high since the reserved areas are threatened by forest fires, illegal logging, mining, and oil palm plantation establishment that reduce their effective size by more than 50% (Curran et al. 2004; Fuller et al. 2004; Gaveau et al. 2007). Considering that conventional conservation strategy by preserving primary forest as protected area has not made optimal contribution, there is an opportunity for conservation beyond strictly protecting forest (Wilson et al. 2010). Production forests, which account for more than half

of Indonesia’s forests, can be maximized as potential contributors for biological conservation (FWI/GFW 2002; Meijaard et al. 2005). Well-managed logging practices in production forest which produces certified timber will benefit not only for business but also for conservation (Meijaard and Sheil 2007). One of such practices is setting aside High Conservation Value Forest (HCVF) areas within timber concession areas. Biodiversity protection area (Kawasan Perlindungan Plasma Nutfah/KPPN) can be classified as high conservation value forest due to its importance in protecting wildlife. The Decree of Indonesian Ministry of Forestry stated that the establishment of biodiversity protection area is aimed to preserve plant and animal biodiversity in their natural habitat (in situ) and should be retained in every production forests (Indonesian Ministry of Forestry 1998). This preservation has important value not only for ecological functions and scientific activities but also for local communities to fulfill their ritual and medicinal needs (Meijaard et al. 2005). The aim of this study was to investigate species richness, evenness and dominancy of two classes of plant (i.e. tree and sapling) at biodiversity protection area in a timber concession area. Therefore, the most important species and families for both plant classes are revealed. The floristic composition of trees was also compared to that at other sites in Kalimantan based on previous studies to analyze the general pattern of plant biogeography of the island.

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MATERIALS AND METHODS The study was carried out at biodiversity protection area of PT. Suka Jaya Makmur, a forest concession company (Hak Pengusahaan Hutan/HPH) belongs to Alas Kusuma Group. It is located in Lubuk Kakap, sub-District Hulu Sungai, District of Ketapang, West Kalimantan and positioned at S 01°14.978’ and E 111°07.940 (Figure 1). The study site is a virgin forest, surrounded by logged over forests, with approximately 300 hectares in the extent and covers hilly (up to 60% in elevation) area with an altitude of 178 m above sea level. It has the ’A’ climate type (Schmidt-Fergusson) with annual rainfall of 1500-3000 mm/year (the highest level in December) and tropical wet months between October and March. The soil types of Yellow Red Podsolic, Latosol and Litosol dominate almost all landscape. On its timber management, PT. Suka Jaya Makmur implements Indonesian Selective Cutting and Planting System (Tebang Pilih Tanam Indonesia/TPTI). This system mandates the company only to cut trees with minimum dbh (diameter at breast high) 50 cm and to plant commercial tree species on logged over areas subsequently. Therefore,

11 (3): 151-156, July 2010

from the silvicultural aspects, the existence of KPPN is very important as a source of seeds and seedlings. At glance, a number of emergent trees, with more than 40 m in height, are distinguishable from the lower canopy. These are mostly dominated by dipterocarp species such as bengkirai (Shorea laevis), keruing (Dipterocarpus spp.), and meranti (Shorea spp.) and also small number from other families such as durian (Durio spp.) and kempas (Koompassia malaccensis). The second canopy layer with average height of 20-30 m is occupied by species from various families such as kulim (Scorodocarpus borneensis), medang-medangan (Litsea spp., Cryptocarya spp.) and ubar (Syzygium spp.). Several ground layer species potential as medicine can be found at the study site, for instances gambir (Uncaria gambir), bemban (Donax cannaeformis), sirih (Piper spp.) and bemali darah (Leea amabilis). There are many orchids that occupy the site including species from genus Appendicula, Bulbophyllum, Dendrobium, Eria, and Thrixspermum. In addition to being inhabited by many commercially and ecologically important plants, the area is home to charismatic animals such as Malayan Sun Bear (Helarctos malayanus), orangutan (Pongo pygmaeus), owa (Hylobates moloch), deer (Cervus spp.) and rangkong (Bucerotidae).

Figure 1. Location of study site within forest concession areas of PT. Suka Jaya Makmur, Ketapang, West Kalimantan (blank circle).

BUDIHARTA – Floristic composition at biodiversity protection area

153

Ten most important species for belta

In this study we used two sampling methods for two classes of plant. PointQuarter sampling (Quadrant method) of 50 m in distance was applied to trees with dbh more than 10 cm, while 2x2 m plot was applied to saplings with dbh between 2 and 10 cm. As many as 20 sampling units were taken. All species were then recorded in spreadsheets in order to calculate its relative density (RD) and relative frequency (RF). Only to trees, we also measured diameter and height in order to calculate their relative coverage/dominance (RC). According to Cottam and Curtis (1956), we calculated those three parameters as:

RD RF

Value

RD = Number of individual s of a taxon  100 Total number of individual s

Litsea sp.

Shorea lamellata

Gluta renghas

Shorea scaberrima

Shorea johorensis

Shorea sandakenensis

Hopea dryobalanoides

Shorea laevis

Shorea acuminatissima

Shorea compressa

Species Nam e

Figure 2. Ten most important species for sapling. Importance Value (IV) is sum of Relative Density (RD) and Relative Frequency (RF) of each species.

RF = Ten most important families for belta

Number of plots containing a taxon  100 Total frequencies of all taxa

100

RC = Basal area of a taxon  100

Important Value

Total basal area of taxa

By adding those three parameters, we determined Important Value index (IV) for each species. Shannon-Wiener diversity index (H’) and Pielou evenness index (J’) were calculated to analyze species richness and its distribution pattern (Ludwig and Reynolds 1988). H’ was computed as:

60 40 20

Sapindaceae

Euphorbiaceae

Dilleniaceae

Arecacaeae

Annonaceae

Clusiaceae

Lauraceae

Anacardiacaeae

H’=- pi ln pi; pi= ni/N,

Myrtaceae

Dipterocarpaceae

Fam ily

while J’ was computed as: J’ = H’/ln S

Figure 3. Ten most important families for sapling. Family Importance Value is sum of Importance Value of all species contained in a single family. Ten most important species for tree

ni = number of individual from speciesRC

N = total number of individual S = number of species

RF IV

Syzigium sp

Hopea dryobalanoides

Diospyros sp.

Shorea fallax

Shorea acuminatissima

Sindora sp

Lauraceae

Dryobalanops sp

0 Shorea laevis

Floristic composition of saplings Of 20 sampling units, 48 species of tree (belong to 27 genera and 13 families) and 94 species of sapling (belong to 54 genera and 28 families) were recorded. For sapling, Shorea laevis was the most important species, in term of its abundance and frequency (Figure 2). As many as 92 saplings of S. laevis were recorded, resulting in approximately 11500 plants per hectare. Even though Hopea dryobalanoides ranked

Dipterocarpus caudiferus

RESULTS AND DISCUSSION

Value

Species Nam e

Figure 4. Ten most important species for tree. Importance Value (IV) is sum of Relative Density (RD), Relative Frequency (RF) and Relative Coverage (RC) of each species. ‘Lauraceae’ refers to a morphospecies that we were not able to identify.

addition, Lauraceae were represented by six species (i.e. from genus Eusideroxylon, Litsea and Cryptocarya), Myrtaceae had five species (i.e. from genus Syzygium, Tristania and Tristaniopsis), and Fabaceae had four species (i.e. from genus Sindora, Koompassia and Dialium). Ten most important families for trees 200 160 120 80 40

Cornaceae

Annonaceae

Olacaceae

Anacardiaceae

Clusiaceae

Ebenaceae

Myrtaceae

Fabaceae

Lauraceae

fourth in the number of plants (5875 plants per ha) compared to Shorea sandakanensis and S. acuminatissima (6625 and 7125 plants per ha respectively), it was the second most important species due to the higher frequency of plots (nine plots compared to six and four plots respectively). Genus of Shorea dominated the study site with seven species from this genus were listed in the top ten most important species. Dipterocarpaceae was the most important family for sapling followed by Myrtaceae and Lauraceae (Figure 3). The gaps of Important Value between Dipterocarpaceae and other families were very wide showing the dominancy of this family. At the study site, Dipterocarpaceae also had the highest number of species contained in a single family with 17 species (i.e. from genus of Shorea, Dipterocarpus, Hopea and Vatica) followed by Myrtaceae with eight species (i.e. from genus of Syzygium, Memecylon and Tristania), Clusiaceae with seven species (i.e. from genus of Calophyllum and Garcinia), Annonaceae with six species (i.e. from genus of Polyalthia, Desmos and Uvaria) and Lauraceae with six species (i.e. from genus of Litsea, Dehaasia and Cryptocarya).

11 (3): 151-156, July 2010

Dipterocarpaceae

B I O D I V E R S IT A S

Family Important Value

154

Fam ily

Floristic composition of trees Different from that of sapling, the floristic composition of tree at biodiversity protection area of PT. Suka Jaya Makmur was dominated by Dipterocarpus caudiferus (keruing) while Shorea laevis (bangkirai) ranked second (Figure 4). Dryobalanops sp. (kapur) appeared as the third most important tree species followed by a ‘morphospecies’ from Lauraceae family and Sindora sp. In mixed dipterocarp forest, species richness and density are not necessarily correlated with the successful growth and development of seedlings (Ashton 1998). The difference of floristic composition between sapling and tree is probably caused by the difference in mast flowering and fruiting frequencies which influence the survival of seedling. For instance, dipterocarp species that fruit frequently, such as Shorea, tend to have shorter-lived seedlings than species which fruit occasionally, such as Hopea (Fox 1973). Shorea laevis (bangkirai) was distinguishable from other trees as primary emergent tree which can reach 60 m tall and up to 240 cm in diameter. Although it ranked second after Dipterocarpus caudiferus, in some areas nearby, S. laevis was very dominant in which local people name the place as ‘Bukit Bangkirai’. In addition, D. caudiferus also acted as emergent trees which can reach 50 m in height and 160 cm in diameter. Despite their dominancy in basal area and number of individual, spatial configuration of both S. laevis and D. caudiferus tended to be clumped than dispersed. This fact is in accordance with Soerianegara and Lemmens (1994) view that both species are usually found in group on clay soils in mixed dipterocarp forest on undulating land and hillsides below 800 m asl. In term of the most important families for tree, Dipterocarpaceae ranked first followed by Lauraceae and Fabaceae (Figure 5). The number of tree species belonging to Dipterocarpaceae family was 20 species (i.e. from genera of Shorea, Dipterocarpus, Dryobalanops and Hopea). In

Figure 5. Ten most important families for tree. Family Importance Value is sum of Importance Value of all species contained in a single family.

In addition to the dominant S. laevis and D. caudiferus, other dipterocarps species recorded at the study site (e.g. Shorea acuminatissima, S. fallax, S. leprosula, S. stenoptera, S. hopeifolia, S. compressa, S. ovalis, S. pinanga, S. smithiana, and S. scaberrima) were those that commonly found in lowland ever wet tropical rain forest. These species will be at the most abundant and richest condition if situated at thick layer and well-drained soils (Soerianegara and Lemmens 1994). In contrast, other species from dipterocarpaceae family common in other ecosystem types were not found at study site, such as S. materialis, S. coriacea and S. venulosa (dipterocarp species in heath forest); S. falcifera, S. geniculata, S. curtisii, S. flemmichii and S. rugosa (dipterocarp species in sandy soil); and S. albida, S. balangeran, S. macrantha, S. platycarpa, and S. teysmanniana (dipterocarp species in peat swamp forest). Diversity and evenness index Shannon-Wiener diversity index (H’) for both plant classes was categorized as high with H’ of 3.54 for tree and 3.49 for sapling. Nonetheless, the diversity index of tree at the study site was much lower than that at sample plot on primary forest in Barito Ulu, Central Kalimantan with H’ was 4.17 (Brearley et al. 2004). Comparative study on floristic composition across Borneo showed that the diversity in western part of Borneo is the lowest among all areas of the island (Slik et al. 2003). This low index is presumably caused by mid-domain effect of the island and the lately reforested landscape in western Borneo (approximately 10000 years ago) (Slik et al. 2003). Mid-

BUDIHARTA – Floristic composition at biodiversity protection area

domain effect can be defined that in the absence of environmental constraints, species diversity is at the highest in the centre of geographical areas, in which most taxa distribution will overlap (Laurie and Solander 2002). In Borneo, this means that the highest taxa diversity can be found in central part of the island, while diversity will be at the least along its edges, including at this study site. In contrast, Pielou evenness index (J’) at the study area were categorized as very low (0.91 and 0.77 for tree and sapling respectively) referring that species were not evenly dispersed and tended to be clumped. The J’ value of trees at the study site was even lower than that in sub-montane forest in Gunung Gede-Pangrango National Parks (1.95) which categorized as low (Arrijani et al. 2006). This clumping was probably due to the poor ability of dipterocarp species, particularly the dominant ones, to sprout their seeds extensively (Ashton 1998; Condit et al. 2000). The clumpiness can also be caused by ‘limited parent fecundity’ which means the number of seedlings is not enough to cover all the space, even if seed dispersal is not limited (Webb and Peart 2001). This limitation in fecundity is related to previous explanation that particular dipterocarp species have lower survival rates which make the regenerated plants tend to concentrate nearby the parent trees due to a larger number of seeds pooled than other location with further distance.

Ketapang showed a different list of dominant dipterocarp species (e.g. Dipterocarpus sublamellatus, Shorea crassa and S. quadrinervis) while it is located in relatively close distance to our study site and has similar habitat type (welldrained and undulated lowland). This difference is probably caused by the limited capacity of seed to migrate across landscapes which leads to the independent evolution of each community, resulting in high levels of gamma diversity (Cannon and Leighton 2004).

CONCLUSION Plant diversity at biodiversity protection area of PT. Suka Jaya Makmur, Ketapang was categorized as high with Shannon-Wiener diversity index (H’) of 3.54 and 3.49 for tree and sapling respectively. In addition, species distribution tended to be clumped as indicated by the very low Pielou evenness index (J’) either for tree (0.91) or sapling (0.77). Dipterocarpaceae was the most important family for both plant classes with Shorea laevis and Dipterocarpus caudiferus as the most important species for sapling and tree respectively. Comparison to other sites in Kalimantan showed that floristic composition at family level was relatively similar although composition at species level was clearly different. Despite being inhabited by

Across Borneo7

Barito Ulu6

Sangai 5

ITCI 4

Apo Kayan4

Lempake3

Wanariset2

Families

Sungai Wain1

Table 1. Comparative rank of the most important families at various sites in Kalimantan based on Importance Value, except for Barito Ulu, Lempake, Sangai, Sungai Wain and Wanariset, which are based on number of species. BPA SJM

Comparison to other sites in Kalimantan In general, the floristic composition at the biodiversity protection area of PT. Suka Jaya Makmur, Ketapang had relatively similar pattern with that in other areas in Kalimantan (Table 1). Across the island, Dipterocarpaceae dominated the plant community except at three sites located in eastern Kalimantan (i.e. Sungai Wain, Wanariset and Lempake) which were dominated by Euphorbiaceae. At this study site, the little difference was that Euphorbiaceae was excluded as dominant families (rank 13), while in the other areas it ranked first or second. The low rank of Euphorbiaceae at this study site is probably due to the small number of sampling units that have been made, which can lead to false negative interpretation. Another rationale was that the study site, which is in close proximity to Gunung Palung National Park (GPNP), has been isolated from other Bornean tree population for potentially millions of year (Cannon and Manos 2003). This isolation has made the plant community at this study site evolve differently from that at other areas in Borneo. Even though Dipterocarpaceae is consistently dominant in many areas in Borneo, the floristic composition in species level varies across different locations. For instances, a study by Cannon and Leighton (2004) in Gunung Palung National Park,

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Dipterocarpaceae 1 5 2 6 1 1 1 1 1 Lauraceae 2 2 2 3 5 4 9 5 Fabaceae 3 7 10 Myrtaceae 4 4 4 3 3 3 Ebenaceae 5 7 9 Clusiaceae 6 Anacardiaceae 7 10 7 3 8 Olacaceae 8 9 Annonaceae 9 8 8 2 10 9 8 10 Cornaceae 10 Bombacaceae 11 6 Moraceae 12 9 Euphorbiaceae 13 1 1 1 2 2 2 2 2 Myristicaceae 3 5 7 5 4 6 Fagaceae 5 3 8 Burseraceae 8 6 8 5 5 10 5 7 Meliaceae 4 5 7 Sapotaceae 5 9 7 4 9 4 Rubiaceae 8 4 Polygalaceae 8 Verbenaceae 6 Flacourtiaceae 7 Thymelaceae 5 Note: 1 = Sidiyasa; 2 = Kartawinata et al. (1981); 3 = Riswan (1987); 4 = van Valkenburg (1997); 5 = Wilkie et al. (2004); 6 = Brearley et al. (2004); 7 = Slik et al. (2003).

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various dipterocarps species, other important tree species such as Durio spp., and Koompassia spp. can be found. Results of this study strengthen the importance of KPPN as High Conservation Value Forest (HCVF) and should be retained in production forest landscapes since it possesses highly ecological and economical values.

ACKNOWLEDMENTS I acknowledge the contribution of M. Solkhan, Sri Wuryanti, Pitrus Narun and Cakus Kibi for assistance during fieldwork and species identification.

REFERENCES Arrijani, Setiadi D, Guhardja E, Qayim I (2006) Vegetation analysis of the upstream Cianjur watersheds in Mount Gede-Pangrango National Parks. Biodiversitas 7: 147-153. [Indonesia] Ashton MS (1998) Seedling ecology of mixed-dipterocarp forest. In: Appanah S, Turnbull JM (eds) A review of dipterocarps. Center for International Forestry Research (CIFOR), Bogor. Bappenas (2003) Indonesian biodiversity strategy and action plan. The National Development Planning Agency, Jakarta. Brearley FQ, Prajadinata S, Kidd PS, Proctor J, Suriantata (2004) Structure and floristics of an old secondary rain forest in Central Kalimantan, Indonesia, and a comparison with adjacent primary forest. Forest Ecol Manag 195: 385-397. Cannon CH, Leighton M (2004) Tree species distribution across five habitats in a Bornean rain forest. Jour. of Veg. Sci. 15: 257-266. Cannon CH, Manos PS (2003) Phylogeography of the Southeast Asian stone oaks (Lithocarpus). J Biogeography 30: 211-226. Condit R, Ashton PS, Baker P, Bunyavejchewin S, Gunatilleke S, Gunatilleke N, Hubbell SP, Foster RB, Itoh A, LaFrankie JV, Lee HS, Losos E, Manokaran N, Sukumar R, Yamakura T (2000) Spatial patterns in the distribution of tropical tree species. Science 288: 14141418. Cottam G, Curtis JT (1956) The use of distance measurements in phytosociological sampling. Ecology 37: 451-460. Curran LM, Trigg SN, McDonald AK, Astiani D, Hardiono YM, Siregar P, Caniago I, Kasischke E (2004) Lowland forest loss in protected areas in Borneo. Science 303: 1000-1003. Fox JED (1973) Dipterocarp seedling behaviour in Sabah. Malay Forest 36: 205-214.

11 (3): 151-156, July 2010 Fuller DO, Jessup TC, Salim A (2004) Loss of forest cover in Kalimantan, Indonesia, since the 1997-1998 El NiĂąo. Cons. Biol. 18 (1): 249-254. FWI/GFW (2002) The state of the forest: Indonesia. Country Report. Forest Watch Indonesia, Bogor and Global Forest Watch, Washington DC. Gaveau, DL, Handono W, Setiabudi F (2007) Three decades of deforestation in southwest Sumatra: Have protected areas halted forest loss and logging, and promoted re-growth? Biol Cons 137: 495504. Indonesian Ministry of Forestry (1998) The decree of Indonesian Ministry of Forestry number 375 year 1998. http://www.dephut.go.id/ INFORMASI/skep/skmenhut/375_98.htm. [Indonesia] Indonesian Ministry of Forestry (2005) Indonesian forestry outlook 2020. Centre of Planning and Statistics, Indonesian Ministry of Forestry, Jakarta. [Indonesia] Laurie H, Solander JA (2002) Geometric constraints and spatial pattern of species richness: critique of range-based null models. Divers Distr 8: 351-364. Ludwig JA, Reynolds JF (1988) Statistical ecology, a primer on methods and computing. John Wiley & Sons, New York. Meijaard E, Sheil D (2007) A logged forest in Borneo is better than none at all. Nature 446: 974. Meijaard E, Sheil D, Nasi R, Augeri D, Rosenbaum B, Iskandar D, Setyawati T, Lammertink M, Rachmatika I, Wong A, Soehartono T, Stanley S, Oâ&#x20AC;&#x2122;Brien T (2005) Life after logging: reconciling wildlife conservation and production forestry in Indonesian Borneo. CIFOR, Bogor. Mittermeier RA, Gil PR, Mittermeier CG (1997) Megadiversity: earth's biologically wealthiest nations. CEMEX, Mexico City. Slik JWF, Poulsen AD, Ashton PS, Cannon CH, Eichhorn KAO, Kartawinata K, Lanniari I, Nagamasu H, Nakagawa M, van Nieuwstadt MGL, Payne J, Purwaningsih, Saridan A, Sidiyasa K, Verburg RW, Webb CO, Wilkie P (2003) A floristic analysis of the lowland dipterocarp forests of Borneo. J Biogeography 130: 1517-1531. Sodhi NS, Koh LP, Brook BW, Ng PKL (2004) Southeast Asian biodiversity: an impending disaster. Trend Ecol Evol 19 (12): 645-650. Soerianegara I, Lemmens RHMJ (1994) Plant resources of South East Asia 5. Timber trees: major commercial timber. PROSEA, Bogor. Webb CO, Peart DR (2001) High seed dispersal rates in faunally intact tropical rain forest: theoretical and conservation implication. Ecol Lett 4: 491-499. Wilson KA, Meijaard E, Drummond S, Grantham HS, Boitani L, Catullo G, Christie L, Dennis R, Dutton I, Falcucci A, Maiorano L, Possingham HP, Rondonini C, Turner W, Venter O, Watts M (2010) Conserving biodiversity in production landscapes. Ecol App (doi: 10.1890/09-1051). http://www.esajournals.org/doi/abs/10.1890/09-1051 WRI (2003) Biodiversity and protected areas. Country profile: Indonesia. World Resources Institute. http://earthtrends.wri.org/pdf_library/ country_profiles/bio_cou_360.pdf.

B I O D I V E R S IT A S Volume 11, Number 3, July 2010 Pages: 157-166

ISSN: 1412-033X (printed edition) ISSN: 2085-4722 (electronic) DOI: 10.13057/biodiv/d110310

Review: Biotechnological strategies for conservation of rare and endangered medicinal plants MAHENDRA KUMAR RAI♥ Department of Biotechnology, SGB Amravati University, Amravati 444602, Maharashtra, India. Tel: +91-721-2662207/8, Extension-267. Fax: +91 721 2660949, 2662135. ♥email: pmkrai@hotmail.com Manuscript received: 6 June 2010. Revision accepted: 22 July 2010.

ABSTRACT Rai MK (2010) Review: Biotechnological strategies for conservation of rare and endangered medicinal plants. Biodiversitas 11: 157166. The use of medicinal plants is as old as human civilization. The biotechnological tools play a crucial role in conservation of rare and endangered medicinal plants. The rapid depletion of plant genetic diversity has made essential to develop new in situ and ex situ conservation methods. Advances in biotechnology offer new methods for conservation of rare and endangered medicinal plants. The present review is focused on biotechnological tools like in vitro culture, micropropagation, mycorrhization, genetic transformation and development of DNA banks. These are imperative and important alternatives for the conservation of rare and endangered medicinal plants. Key words: biotechnological strategies, DNA banks, medicinal plants, transformation, micropropagation, mycorrhization.

INTRODUCTION Since the beginning of the civilization medicinal plants have been important resource without which the survival of mankind has not been possible. According to World Health Organization (WHO) up to 80% of people still rely mainly on traditional knowledge-based remedies. As a matter of fact, plants are the main source of modern medicines. It is estimated that 25% medicines are still obtained from the plants (Tripathi and Tripathi 2003). The famous Indian herbal therapy ‘Ayurveda’ is based mainly on herbal system. India is home to a great variety of medicinal plants, and is ranked sixth among 12 hotspots of mega diversity countries of the world. The Himalayas is designated as one of the global biodiversity hotspots. Unfortunately due to over exploitation, habitat loss and non-judicious use, many species of medicinal plants have become rare, threatened or endangered. In addition to this, the medicinal plants are highly affected by climate change, such as: increase in carbon dioxide concentration which favors C3 plants over C4 plant, increase in diseases and pest, high rain fall and high salt content in soil etc. In article 8 of The Convention on Biological Diversity (CBD) emphasized on the fundamental requisite of in situ conservation of ecosystems and natural habitats. All over the world, the protected areas are the most widely accepted and practically approachable to biodiversity conservation. There are two methods of conservation of medicinal plants: (i) ex situ conservation, and (ii) in situ conservation, but these techniques are natural and time-consuming. Tripathi and Tripathi (2003) stated that biotechnological tools are important for multiplication and conservation of the critical genotypes of medicinal plants. Therefore, biotechnological techniques can be applied for the conservation of rare and

endangered medicinal plants. Biotechnological approaches are imperative for rapid multiplication and genetic improvement of medicinal plants. These include: (i) Micropropagation (ii) Mycorrhization (iii) Genetic transformation, and (iv) Development of the DNA banks. O'Gara (1996) stated that the in the process of development of sustainable plant production the use of microbial inoculants as substitution for chemical fertilizers and pesticides is getting attention. It is believed that delivery of microbial inoculants via micropropagation is one of the solutions to this problem. In micropropagation practices, the growth substrate lacks microbe and, as a result of this nutrient-rich growth substrate, delicate plants having no interaction with other microorganisms are produced (Dolcet-Sanjuan et al. 1996). Micropropagation is an important technique for the production of elite plants, but due to transient transplantation shock plants require biohardening before transplantation. For this reason, mycorrhizal technology can be applied. Inoculation of arbuscular mycorrhizal fungi (AMF) into the roots of micropropagated plantlets plays a advantageous role (Blal et al. 1990; Schubert et al. 1990; Azcon-Aguilar et al. 1994; Declerck et al. 1994; Varma and Schuepp 1994a,b; Gribaudo et al. 1996; Martins et al. 1996; Vestberg and Uosukaninen 1996; Budi et al. 1998; Naqvi and Mukerji 1998; Gange and Ayres 1999; Vosatka et al. 1999; Sylvia et al. 2003; Voets et al. 2005; Chandra et al. 2010). There are excellent reviews on micropropagation and mycorrhization by Conner and Thomas (1981), Vestberg and Estaun (1994), Varma and Schuepp (1995) and Lovato et al. (1996) and Rai (2001). This article is focused at biotechnological strategies for conservation of rare and endangered medicinal plants particularly on micropropagation and mycorrhization.

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MICROPROPAGATION (IN VITRO REGENERATION) Micropropagation is the technique of in vitro multiplication of large number of plants from its part, whether it is leaves, seeds, nodes and tubers etc. In vitro propagation is used for the production and multiplication of novel plants, which are genetically similar and virus free. Micropropagation has been proved as an important technique for the multiplication of plants in a large scale. Usually, micropropagation is carried out in two ways: direct and indirect. Callus production from explant followed by shoots and roots is one method, while direct shooting on the auxiliary explant followed by rooting is another method. The concept behind the in vitro regeneration is that from the single explant the development of whole plantlet under controlled conditions can be obtained, and thereafter its acclimatization followed by transfer in the field can be achieved. Gottlieb Heberlandt (1854-1945) cultivated plant tissues in culture in vitro. He is regarded as father of plant tissue culture (Chawla 2002). Later on, Murashige and Skoog (1962) developed basal medium in which major and minor elements, vitamins, amino and iron sources were considered for the growth of the plant besides the temperature and humidity. Micropropagation, the application of tissue culture for efficient clonal plant production has been used commercially since the 1960s and is possibly the oldest example of commercial Biotechnology. In the United States, the micropropagation industry has been developed primarily to provide service the temperate and tropical ornamental plant industry. Production of elite stock plants for small fruit and vegetable crops is a secondary area of activity. It should also be applied for the conservation of rare and endangered medicinal plants. The technique of micropropagation is applied with the objective of enhancing the rate of multiplication. Through tissue culture over a million plants can be grown from small piece of plant tissue within 12 months. Such a prolific rate of multiplication cannot be expected by any of the in vivo methods of clonal propagation. Another advantage in propagation through tissue culture is that shoot multiplication cannot be expected by any of the in vivo methods of clonal propagation. Moreover, the shoot multiplication usually has a short cycle, results in logarithmic increase in the number of shoots. Tissue culture provides propagules such as minitubers or minicorms for plant multiplication throughout the year irrespective of the season. Using this method stock of germplasm can be maintained for many years. Clonal propagation in vitro appears to have permanent advantages in case in which serious problem occur. This is because of the fact that through in vitro methods more pathogen free plants can be raised and maintained economically. Three examples of in vitro propagation are Gloriosa superba L, Rauwolfia serpentina L. Benth. Ex. Kurz. and Buchanania lanzan Spreng. Gloriosa superba L. Gloriosa superba (Colchicaceae) also known as Malabar glory lily or ‘Kembang telang’ (Java, Indonesia) is a

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perennial tuberous climbing herb, widely scattered in the tropical and sub-tropical parts of the India, including the foothills of Himalayas. It is also called as ‘Mauve beauty’, ‘Purple prince’, ‘Modest’, ‘Orange gem’, ‘Salman glow’ and ‘Orange glow’. It is adapted to different soil texture and climatic conditions. The plant grows in sandy-loam soil in the mixed deciduous forest in sunny weather. It occurs in thickets, forest edges and boundaries of cultivated areas in warm countries upto height of 2530 m. (Neuwinger 1994). G. superba is a inhabitant of tropical Africa and now found growing naturally in many countries of tropical Asia including Bangladesh, India, Sri Lanka, Indonesia, Malaysia and Myanmar. In India, it occurs commonly in tropical forests of Bengal and Karnataka (Sivakumar and Krishnamurthy 2002). The plants thrive from the arid Bundelkhand to humid Assam valley. It is known by different names in India such as ‘Kalihari’, ‘Agnishikha’, ‘Languliata and ‘Nangulika’. Different species of Gloriosa includes G. superba, G. abyssinica, G. carsonii, G. simplex, G. grandiflora, G. minor, G. magnifica, G. lutea, G. plantii, G. latifolia, G. longifolia, G. rothschildiana, G. virescens, G. sudanica, G. lutea and G. baudii. Gloriosa superba is also known as the national flower of Zimbabwe. Except diverse pharmaceutical products and other therapeutic preparations, it is also a popular plant for providing color in greenhouse and conservatories even immature flowers are gorgeous to behold (Kranse 1986; Ghani 2000). G. superba is a semi-woody herbaceous branched climber, reaching just about five meters in height. One to four stems arise from a single V-shaped fleshy cylindrical tuber. G. superba is an essential medicinal plant because all parts are used in the medicine, which contains two important alkaloid, colchicine and colchicoside; leaves are used to treat cancer related diseases, also in ulcer, piles, scrofula (Evans et al. 1981). Usually G. superba is multiplied by corm and seeds but due to low germination capability it restricts for the regeneration. Consequently, in order to safeguard and conserve this important plant, biotechnological approaches would be very useful (Sivakumar and Krishnamurthy 2002). The conventional method of propagation has many drawbacks as 50% of the yield has to be set aside for raising the next crop, transmittance of soil-borne diseases from one crop to the next, and from one location to another and during the 2-3 month storage period between harvest and the raising of next crop (Mrudul et al. 2001). Hassan and Roy (2005) reported 92% of the cultures of apical and axillary buds of young sprout from naturally grown G. superba plants regenerate four shoots per culture in MS basal medium fortified with 1.5 mg/L BA + 0.5 mg/L NAA. Custers and Bergervoet (1994) reported tissue culture of G. superba by shoot cuttings and explants from node, internodes, leaves, flowers, pedicels and tubers. G. rothschildiana and G. superba were cultured on MS basal medium with 3% w/v sucrose, 0-10 mg/L Benzyl Adenine (BA) and 0.1 mg Indole Acetic Acid (IAA) and maintained for 24 days under 16 hours photoperiod. Addition of low level of Benzyl Adenine (BA) (1 mg/L) improved plant growth, whereas the high level of BA (10

RAI – Biotechnology for conservation of medicinal plants

mg/L) caused proliferation of multiple shoots, from rhizome meristem, by applying alternatively high and low BA level, a method of continued propagation was achieved which resulted in a 4-7 fold multiplication of qualitatively good plantlets every 18 weeks. The resulting shoots were incubated on MS medium, with 3% sucrose and 0-1 mg/L IAA or NAA. Transplantation into soil was only possible after the plants had formed. In 1993, Samarajeewa and group studied clonal propagation of G. superba from apical bud and node segment of shoot tip, cultured on solidified agar (0.8% w/v) Gamborg’s B5 medium containing BA, IAA, Kinetin, NAA, IBA or 2,4-D. The cultures were maintained under fluorescent light at 25-27ºC. Primary cultures were initiated on solid B5 medium containing 0.5 to 1 mg/L BA and 0.010.5 mg/L IAA, IBA, NAA when shoot tip of primary cultures were transferred to shoot multiplication media, shoot proliferation occurred via adventitious bud formation within 4-8 weeks. In vitro propagation and corm formation in G. superba was reported by Somani et al. (1989). The fresh sprouts were excised from corms of G. superba and dissected propagules with shoot and root primordia were placed on MS basal medium containing 3% sucrose and 0.6% agar. Explant germinated on the MS medium producing shoot and root, which formed new corm within one month. For shoot and cormlet regeneration, 1-4 mg/L kinetin was added to the medium. Cultures were maintained at 25ºC in white fluorescent light (2500 lux) with an 8-h/day photoperiod. Sivakumar and Krishnamurthy (2002) reported in vitro organogenetic responses of G. superba. They used MS medium supplemented with Adenine sulfate) ADS and BA, 98%. The callus induction occurred in non-dormant corm bud explants. The maximum number of multiple shoot (57%) was observed in corm-derived calluses. Sivakumar and Krishnamurthy (2002, 2004) studied induction of embryoids from leaf tissue of G. superba. The nodular calli were observed on Schenk and Hildebrandt (SH) basal medium supplemented with 2, 4-D and 1 isopentyldene. Jha et al. (2005) reported production of forskolin, with anolides, colchicine and tylophorine from plant source by using biotechnological approach. G. superba is a commercially important medicinal plant which has diverse medicinal applications and eventually due to over-exploitation this plant is facing local extinction in India. It has been affirmed as endangered plant by IUCN and hence there is a pressing need to conserve the plant by in situ and ex situ multiplication in general and micropropagation and mycorrhization in particular so as to meet the ever-increasing demand from the industries. Much research has not been carried out on Gloriosa due to some problems. Basically the plant is monocot having very low germination capacity (0.001%), and life span is also very short just 2-3 months, conventional propagation is very limited and also slow since one tuber produce only one plant at a time, besides this the plant is the richest source of colchicine, the high priced alkaloid (USD 3600/100 g) along with gloriosin and colchicoside, which has very high demand in pharmacological companies from all over the world. The whole plant is used for the medicinal purposes. Due to overexploitation by the local

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people his plant is endangered, that is why it is the pressing need to conserve this important medicinal plant. There are many contributions on micropropagation and secondary metabolites production of G. superba (Sivakumar and Krishnamurthy 2004; Jha et al. 2005; Ade and Rai 2009). The research on micropropagation of G. superba is in progress in Department. of Biotechnology of SGB Amravati University, Amravati, Maharashtra State, India. We have developed effective protocol and standardized the optimum culture conditions. Moreover, biohardening was done by delivery of mycorrhizal propagues into the roots of the plantlets of G. superba. Encouragingly, 90% survival of the plantlets was observed. Rauwolfia serpentina (L.) Benth. ex Kurz. Rauwolfia serpentina belongs to Family Apocynaceae and commonly known as ‘Sarpagandha’ or ‘Pulai pandak’ (Indonesia). It is a woody perennial shrub and also known as ‘Chota chand’ and ‘Chandrika’. In traditional and ayurvedic medicine, the plant is used for mental disorders, epilepsy and also for sleeplessness. The plant is grown by means of vegetative propagation using cuttings. The germination of the seeds is poor due to presence of cinnamic acid and its derivatives (Sahu 1979). R. serpentina has been overexploited by local people, pharmaceuticals and government agencies of India, and thus it is endangered medicinal plant. Therefore, micropropagation of this plant has been need of the hour. Bhatt et al. (2008) developed protocol for micropropagation of R. serpentina. They used shoots and leaves as explant and grew on MS medium supplemented with 2,4Dicholorophenoxyacetic acid (2,4-D) plus 2-benzyl amino purine (BAP) and Indole-3 butyric acid. They found induction of callus from leaf and stem tissues. The authors reported that combination of IBA (0.125 mg/ml) plus BAP (1.0 mg/L) demonstrated better results. Boke (2004) biohardened the micropropagated plantlets by using arbuscular mycorrhizal fungi. Two mixtures i.e. sand: soil: cow-dung 1: 1: 1 and sand: soil: vermicompost 1: 1: 1 was taken because it gave best survival rate and then they were combined with Glomus macrocarpum and mixture of Glomus species. The survival was 98% after 30 days, 93% after 60 days and 85% after 90 days on the mixture of sand: soil: vermicompost in combination with mixture of Glomus species containing G. mosseae, G. fasciculatum and G. geosporum and second combination that resulted best was sand: soil: cow-dung in combination with mixture of Glomus species containing G. mosseae, G. fasciculatum and G. geosporum where 84% survival was observed after 30 days, 60% after 60 days and 55% after 90 days. Consequently, it can be said that sand: soil: vermicompost + mixture of Glomus species was the best for biohardening of in vitro grown plantlets of R. serpentina. Buchanania lanzan Spreng. Buchanania lanzan Spreng (Chironji) (Anacardiaceae family) is a commercially useful tree species all over the greater part of India. It is a vulnerable medicinal plant. The seeds are used as expectorant and energizer. The oil extracted from kernels is applied on skin diseases and also

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to remove spots and blemishes from the face. The root is used as expectorant, in biliousness and also for curing blood diseases. The juice of the leaves is digestive, expectorant, aphrodisiac and purgative. The gum after mixing with goat milk is used for treating pains. The tribal people collect the fruits of this tree to earn their livelihood, through its sale and are consequently overexploited. During the recent past, due to excessive felling of trees and overgrazing, considerable reduction in the population of the B. lanzan in the forest and non-forest areas has been observed (Singh et al. 2002). There is a problem in the regeneration of B. lanzan due to association of fungi with seeds. These fungi include Alternaria alternata (Pr.) Keissler, Aspergillus flavus Link, A. ochraceus Withelm, A. niger Van Tiegh, A. aculeatus Lizuka, A. funiculosus Smith, Cladosporium Link ex Fr, Chaetomium globosum Kunze and Schum., Curvularia lunata (Wakker) Boedijn, Fusarium moniliforme var. subglutinans Wr. and Rg, F. semitectum Berk and Rav, Macrophomina phaseolina Ashby, Mucor varians Povah, Penicillium citrinum Thom, Trichothecium roseum Link, Rhizopus arrhizus and Verticillium species (Sharma et al. 1998). The presence of hard seed coat is another inherent problem which leads to low germinating capability. We have developed technique for the rapid clonal multiplication and establishment of a gene bank in vitro (Shende and Rai 2005). The decoated seeds of B. lanzan were cultured in MS medium enriched with different auxins and cytokinins alone or in combination. MS medium supplemented with BAP 22.2 µM and NAA 5.37 µM promoted formation of the maximum number of shoots as compared to BAP and IBA. BAP and NAA were found to be superior as compared to BAP and IBA combinations. MS medium with kinetin 23.3 µM induced profuse rooting of the initiated multiple shootlets.

MYCORRHIZATION Inoculation of mycorrhizal fungi into the roots of plants is referred as mycorrhization. Mycorrhizal fungi are of two kinds: Arbuscular Mycorrhizal Fungi (AMF) and Ectomycorrhizal Fungi. Usually, AMF are used for inoculation in medicinal plants. These are symbiotic fungi and occur in 90% of the plants (Williams et al. 1994). The AMF helps the plant partner by increasing uptake of nutrients in general, and phosphorus in particular (Vestberg and Estaun 1994). The diverse role played by AMF has been extensively studied (Gianinazzi et al. 1990; Ponton et al. 1990; Cargeeg 1992; Arias and Cargeeg 1992; Varma and Schuepp 1995; Lovato et al. 1996; Hindav et al. 1998; Sylvia et al. 2003; Voets et al. 2005; Chandra et al. 2010). AMF reduces the stress and promotes the plant growth for better survival. Associated with nutrition, water/aeration, soil structure, pH, salt, toxic metals, and pathogens (Sylvia and Williams 1992). Vestberg and Estaun (1994) published an admirable review on factors affecting the result of mycorrhizal inoculation. The potential for biocontrol of plant diseases by AM and ectomycorrhizal fungi was reviewed by Linderman (1994) and Duchesne (1994),

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respectively. The need for mycorrhization and the different role played by AMF was discussed at length by Varma and Schuepp (1995). Lovato et al. (1996) reported different roles played by AMF as bioregulators, bioprotectors, biofertilizers, and stressed on mycorrhizal inoculation of tissue-culture-raised plantlets. Delivery of mycorrhizal propagules Colonization of AMF in seedlings grown on agar medium is well experimented (Hayman 1983). AMF establishes symbiosis with root organ culture (Becard and Fortin 1988; Gemma and Koske 1988; Becard and Piche 1989; Chabot et al. 1992a,b; Elmeskaoui et al. 1995; Declerck et al. 1996a, 1998; Pawlowska et al. 1999; Sylvia et al. 2003; Voets et al. 2005; Chandra et al, 2010). In 1994, Vestberg and Estaun emphasized on development of inoculation protocol for each plant species. In 1986, Trouvelot and his colleagues reported that the inoculation techniques differ depending on the substratum or the nature of the inoculum used. Selection of quantity (Morandi et al. 1979; Daniels et al. 1981; Ravolanirina et al. 1989; Guillemin et al. 1992; Morte et al. 1996) and quality of inoculum is an important point both for in vitro and in vivo inoculation (Vestberg and Uosukainen 1996). The inoculums should not only be pure, but also be able to exhibit the desired effect on the host-partner. It is noteworthy that hyphae, spores, chlamydospores and mycorrhizal roots have been used as inocula in various in vitro and in vivo studies. The sterilization of AMF inoculum is an important part of successful inoculation programs. Healthy spores can be easily separated from the old and deteriorated spores by centrifugation (Furlan et al. 1980). Only the healthy inoculum should be selected for surface sterilization. There are many procedures used for surface sterilization of inocula for establishing in vitro symbiosis on agar culture (Tommerup and Kidby 1980; Macdonald 1981; Strullu and Romand 1986; Becard and Piche 1992). Becard and Piche (1992) suggested a method, which is widely used. The mixture of antibacterial agents, such as streptomycin (200 mg) and gentamicin (100 mg), is used for sterilization of spores followed by four rinses (Becard and Piche 1992). The pregerminated spores or pieces of mycorrhizal roots showing hyphal growth are used to inoculate the sterile root system by placing them close to emerging lateral roots. Since, the MS (Murashige and Skoog 1962) rooting medium contains these elements at high concentrations, a change of medium is essential before the tripartite culture stage (Elmeskaoui et al. 1995). Axenically infected mycorrhizal roots can also be used as inoculum to overcome the problem of contamination (Elmeskaoui et al. 1995; Declerck et al. 1996a,b, 1998, 2000; Plenchette et al. 1996). A reliable technique to establish arbuscular mycorrhizal symbiosis in micropropagated plantlets has been developed (Declerck et al. 1998). The tripartite culture system seems to be a potent tool for the commercial production of arbuscular mycorrhizal spores and to get a high percentage of in vitro mycorrhized plantlets (Elmeskaoui et al. 1995).

RAI â&#x20AC;&#x201C; Biotechnology for conservation of medicinal plants

If arbuscular mycorrhizal fungi are inoculated to in vitro-grown plantlets, they may augment the competence of transplant shock tolerance and growth during the acclimatization phase. Fortuna et al. (1992) evaluated transplant shock tolerance by inoculation of Glomus mosseae and G. coronatum into micropropagated Prunus cerasifera. After four weeks growth, 100% survival of plants was recorded. Further, they reported that both fungi improved tolerance of plantlets after removal from in vitro and in vivo systems. Karagiannidis and HadjisavvaZinoviadi (1998) found that G. mosseae improved plant growth up to 11.6 times and increased grain yield up to 5.4 times as compared to non-inoculated plants. In 1998, Nowak claimed that the induced resistance response caused by inoculants is due to `biotization'. In vitro co-culture of plant tissue explants with beneficial microbes induces developmental and metabolic changes, which enhance their tolerance to abiotic and biotic stresses. Further, he reviewed benefits of in vitro biotization of plant tissue cultures with microbial inoculants. Search for potential mycorrhizal partners A vast body of literature provides evidence that mycorrhiza researchers used mostly species of Glomus, including G. mosseae, G. fasciculatum. G. etunicatum, G. tenue, and Gigaspora margarita for inoculation to the in vitro raised plantlets as these occur frequently. The endophytes show host-specificity and therefore vary in their effectiveness in plant growth promotion. (Guillemin et al. 1992; Vestberg and Estaun 1994; Sylvia 1998; Rajan et al. 1999). Many researchers are of the opinion to screen AM fungal inoculants for their efficacy, and the species with high potential for nutrient uptake should be selected for inoculation programs (Abbott et al. 1992; AzconAguilar et al. 1997; Puthur et al. 1998). Sieverding (1989) remarked that it would be more interesting to find one isolate that is effective with a wide range of plant species, since interactions can occur between different isolates in mixtures. Schubert et al. (1990) screened AMF and found G. constrictum to be less effective in enhancement of growth of Actinidia deliciosa than G. caledonium, G. occultum and G. versiforme. Efficacy of Glomus deserticola and G. mosseae on the growth and development of tissue-culture-raised plantlets of avocado (Persea americana Mill.) was assessed by Azcon-Aguilar et al. (1992). He further reported that the former increased shoot height, leaf number and vigor of the plantlets more than the latter. Arines and Ballester (1992) used G. aggregatum and G. deserticola for inoculation of micropropagated plantlets of Prunus avium with 100% survival of plantlets. The influence of inoculation of Glomus fasciculatum (LPA 7), Bouhired et al. (1992) reported positive effect of G. intraradices and Glomus on the growth of Phoenix dactylifera (date palm). Williams et al. (1992) screened more than 80 Finnish inoculants and selected only Finn 98 (G. intraradices) and 128 (Glomus sp.), for inoculation of micropropagated plantlets of strawberry. Glomus geosporum from the Kent collection was chosen as a broad range AMF to include within the trial. G. intraradices and G. mosseae were selected by

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Vestberg (1992) for inoculation of strawberry. They reported that the latter was found to be the most efficient fungus, as it increased shoot growth several-fold. Lemoine et al. (1992) screened seven ericoid mycorrhizal fungi against microplants of nine cultivars of Rhododendron hybrida and found that use of defined disinfected substrata, combined with specific mycorrhizal fungal strains, is essential for guaranteeing an optimal production of outplanted Rhododendron microplants at nursery level. Guillemin et al. (1992) made a noteworthy contribution by screening many AMF for establishment of symbiosis in micropropagated pineapple plantlets, and reported that Queen and smooth cayenne pineapple plants associated with Glomus species (LPA 21) presented better growth than those infected with the other AMF, and the best growth was obtained for the Spanish variety by inoculating plants with Glomus sp. (LPA 25). In 1992, Fortuna and colleagues reported the infectivity and effectiveness of G. mosseae, G. caledonium, G. coronatum and Glomus strain A6, in micropropagated plantlets of plum rootstock (Prunus cerasifera Ehrh, clone Mr S 2/5). The authors also evaluated the most and the least infective fungi, G. mosseae and G. coronatum, respectively, for enhancement of growth of micropropagated P. cerasifera. Verma and Jamaluddin (1995) reported a low percentage of infection in seedlings of teak (Tectona grandis) inoculated with G. fasciculatum. The authors reported that the mixed inoculum of AMF was more efficient for augmentation of growth and biomass of teak. In vitro propagation of Feronia limonia was carried out by Vyas et al. (2008). The authors inoculated Piriformospora indica during in vitro rooting and ex vitro transfer as a result, the survival percentage increased to 90%. In 2009, Ranjan and his coworkers standardized biohardening protocol for in vitro regenerated plantlets of Chilli using G. mosseae, Gigaspora margarita and mixed arbuscular mycorrhizal fungi (AMF) strains. In vitro raised plantlets were treated with AMF, which demonstrated high percentage (97.08%) of plant survival with mixed strain of G. mosseae and G. margarita. The efficacy of ectomycorrhizal fungi was not realized by the researchers for inoculation of tissue culture raised plantlets until 1990. Gay et al. (1992) used ectomycorrhizal fungi as a tool to enhance rooting of tissue culture-raised cuttings of Pinus halepensis and suggested that an Indole3-Acetic Acid (IAA) over producer mutant of ectomycorrhizal fungi, such as Hebeloma hiemale and H. cylindrosporum, could improve the rooting of cuttings of Cerasus avium and Prunus cerasus up to 95%, which are generally non-ectomycorrhizal. Martins et al. (1996) also reported Amanita muscaria, Laccaria laccata, Piloderma croceum and Pisolithus tinctorius to be useful on acclimatization of tissue culture-derived plantlets of Castanea sativa Mill. They found a positive effect on growth of mycorrhized plants of C. sativa. P. tinctorius was most effective in colonizing roots of both micropropagated plants and seedlings, whereas A. muscaria and L. laccata only colonized a few feeder roots of some plants and Piloderma croceum did not form mycorrhizae. The effect of Hebeloma cylindrosporum on in vitro rooting of tissue culture raised plantlets of Prunus avium and P.

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cerasus was reported by Grange et al. (1997). The survival percentage was increased from 30 to 100%. Reddy and Satyanarayana (1998) screened Cenococcum geophilum, L. laccata, Paxillus involutus and two isolates of P. tinctorius, to inoculate micropropagated plantlets of Populus deltoides (G 48), and found that P. involutus formed mycorrhizae with plantlets of P. deltoides while others failed, though they colonized the substrate extensively. The plantlets colonized with P. involutus showed appreciably improved growth and dry weights. Ectomycorrhizal fungi can be utilized efficiently for improvement of growth of the micropropagated plantlets as they are easily available facultative biotrophs. The basic advantage of these fungi is that they can be cultured axenically on artificial medium. Although, the technique of mycorrhization is of greatest importance for the growth and development of the micropropagated plantlets, there are some problems in establishment of mycorrhizal host symbiosis in vitro: (i) contamination of inoculum, (ii) behavior of the host in vitro, and (iii) obligate nature of the endophyte. Lovato et al. (1996) opined that a perspective for the near future should be the development of integrated technologies. Not only the mycorrhizal fungi, but also other organisms capable of promoting plant growth or protection, such as, symbiotic or associative bacteria, plant growth promoting rhizobacteria (PGPR), pathogen antagonists, or hypovirulent strains of pathogens would be incorporated into the substrate for micropropagated plant production, they further added. An additional advantage of these fungi is that they are root-colonizers and can be cultivated easily on artificial culture medium. Recently, Ari and Trappe (1998) discussed the ecological role of different DSEs. Sieber et al. (1998), working on DSE in general and DSH (dark septate hyphomycetes) in particular for the past two decades, suggested that fungal endophytes are ubiquitous in trees, and therefore they should be screened for obtaining more and more DSH. Eventually, the most efficient strains of these fungi should be selected for enhancing plant growth. A new hope in 1998, Verma and his group discovered Piriformospora indica (named after India), a new fungal endophyte, which belongs to hyphomycetes (Basidiomycota) from sandy desert soil of Rajasthan in north-west India. It is worth mentioning that the fungus can be easily cultured on various media (Verma et al. 1998; Varma et al. 1999). The molecular phylogeny of the fungus revealed that it is closely related to the Rhizoctonia group. The characteristic pear-shaped chlamydospores were found to be efficient in successfully colonizing plants like maize, tobacco and tomato in pot cultures. The hyphae generally colonize the surface of the roots and later (about two weeks), the cortex of the plant. The fungus seems to be promising due to its rapid root-colonizing capacity and cultivable nature (Varma et al. 1999). It also promotes growth of medicinal plants (Prasad et al. 2008). These include Withania somnifera, Spilanthes calva (Rai et al. 2001) and Adhatoda vasica (Rai and Varma 2005) and Feronia limonia (Vyas et al. 2008).

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GENETIC TRANSFORMATION Medicinal plants are one the most important source of drugs, as plants contain many secondary metabolites which are mainly responsible for their medicinal properties. Genetic transformation improves yield and quality of medicinal plants, which involve the alteration or introduction of genes which improve the secondary metabolite synthesis in plant. Genetic transformation technology has become a versatile platform not only for trait improvement but also for studying gene function in plants. Genome manipulation is the general aim of the genetic transformation with medicinal plants by developing techniques for desired gene transfer into the plant genome in order to improve the biosynthetic rate of the compounds of interest. An essential strategy in this regard is the choice of the correct marker genes for genetic transformation, as it assists to analyze the transformed cell. Many researchers are mainly focusing on the mechanism of transfer and integration of the marker and reporter genes. Agrobacterium tumefaciens and A. rhizogenes are virulent for plants. They contain a large megaplasmid (more than 200 kb), which plays a key role in tumor induction. During infection the T-DNA, a mobile segment of Ti or Ri plasmid, is transferred to the plant cell nucleus and integrated into the plant chromosome and transcribed. Genetic transformation helps to improve secondary metabolite biosynthesis. The main aim is to identify the enzyme in metabolic pathway and then manipulate this enzyme to provide better control of the pathway. Genetic transformation is a powerful tool for enhancing the productivity of novel secondary metabolites of limited yield. Hairy roots, transformed with A. rhizogenes, have been found to be suitable for the production of secondary metabolites because of their stable and high productivity in hormone-free culture conditions. Genetic transformation facilitates the growth of medicinal plants with multiple durable resistances to pests and diseases. Likewise, transgenes or marker-assisted selection may assist in the development insect, pest, drought, salinity resistant plants, which will be needed to fulfill the worlds need and save land for the conservation of plant biodiversity in natural habitats. There are more than 120 species belonging to 35 families in which transformation has been carried out successfully by using Agrobacterium and other transformations techniques (Birch 1997). Yun et al. (1992) and Cucu et al. (2002) reported genetic transformation in Atropa belladonna by using A. rhizogenes. Agrobacterium tumefaciens mediated high frequency and simple procedure for genetic transformation of the medicinal plant Salvia miltiorrhiza was developed (Yan and Wang 2007). They used Leaf discs and pre-cultured it on MS medium supplemented with 6.6 Îźmol/L BAP and 0.5 Îźmol/L NAA for one day and later co-cultured with A. tumefaciens strain EHA105 having plasmid pCAMBIA 2301 on the same medium for three days. The regenerated buds on selection medium (60 mg/L kanamycin and 200 mg/L cefotaxime) were transferred to fresh MS medium with 60 mg/L kanamycin for rooting. After 15 days, the rooted plantlets were successfully transplanted to

RAI – Biotechnology for conservation of medicinal plants

soil. The transgenicity of the regenerated plants was analyzed by PCR, Southern hybridization and GUS histochemical assay. Transformation study of the figwort, Scrophularia buergeriana (figwort) was done by Park et al (2003). S. buergeriana contains bioactive natural products which are used for the treatment of fever, constipation, neuritis, and laryngitis. In transformation study, S. buergeriana plants were regenerated from leaf explants and co-cultivated with A. tumefaciens strain GV3101. Shoot regeneration was observed on medium supplemented with 2 mg/L 6-BAP and 70 mg/L putrescine. Detection of the NPT gene, and GUS enzyme activity, confirmed the genetic transformation of S. buergeriana. Their work demonstrates the potential of using A. tumefaciens to transfer foreign genes into important medicinal plant. Ruta graveolens L. is important source of active biomolecules such as furocoumarins, furoquinolines and acridone alkaloids. The efficient genetic transformation protocol for R. graveolens was developed by using A. tumefaciens (Karine et al. 2005). The regeneration and transformation was obtained by co-cultivation of hypocotyls of 2-3 weeks old plants and A. tumefaciens strain C58C1RifR containing a plasmid NPT and β-glucuronidase genes. Echinacea purpurea is an important herb which can used to treat cold and act as an imunostimulant and antiinflammatory remedy. The plant regeneration and method for transformation pCHS (pBI121-based vector having GUS, reporter gene) into E. purpurea was firstly reported by Wang and To (2004). Zeef et al. (2000) reported plant transformation system for Hyoscyamus muticus, an important medicinal plant of the Solanaceae family. The system used by them consists of plasmid carrying the nptII and gusA genes. Particle bombardment method was used by them to deliver this gene in to leaf explant. Mentha spp. belonging to the family Lamiaceae, distributed mostly in the temperate and sub-temperate regions of the world. It is an important crop being the source of essential oils enriched in certain monoterpenes, widely used in food, flavor, cosmetic and pharmaceutical industries. The monogenic basis for conversion of menthone to menthol showed that gene R, either homozygous (RR) or heterozygous (Rr), is responsible for the reduction of menthone to menthol or carvone to carveol. Plant transformation technology has not only played an important role in introducing insecticidal genes into relevant crops but also has become a versatile platform for cultivar improvement as well as for studying gene function in plants. Most important extensively studied medicinal plant, the Atropa belladonna, which is member of the Solanaceae family. This plant is a major source of tropane alkaloids, which is used as antimicrobial compounds in pharmaceutical drugs.

DEVELOPMENT OF THE DNA BANKS Genetic diversity has significant contribution in conservation of plant genetic resources (PGR). There are approaches which are widely applied with their strength

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and weaknesses. These include ex situ and in situ conservation. The maintenance of plant populations in their habitats, where they can naturally occur, grow and reproduce is in situ conservation. When they grow outside their natural habitat or production areas is referred to as ex situ conservation of germplasm. Depending on the biological nature of the species to be conserved, different types of ex situ conservation methods are available (Vicente et al. 2006). The establishment of DNA banks is one of the ex situ conservation method which is planned activity. The extraction of genetic material, and storage should be made readily available for molecular applications. DNA resources can be maintained at ‑20ºC for short- and midterm storage (i.e. up to 2 years), and at ‑70ºC or in liquid nitrogen for longer periods. These experiments normally aim to obtain knowledge to improve the efficiency of some conservation activities or to scientifically inform decisions related to the conservation of germplasm. Other objectives of the creation of DNA banks may be related to training or distribution to scientists with an interest in different areas of biology. DNA banks assembled as a means to replace traditional methods of conserving genetic resources. This is important to note as conservation of genome fragments or individual genes are quite a different situation from the conservation of entire genotypes, as living organisms, for their future use. DNA may be a cost effective form for conservation of germplasm depending on the objective of the conservation and the type of use to which it would be applied. For many species that are difficult to conserve by conventional means (either as seeds or vegetatively) or that are highly threatened in the wild, DNA storage may provide the ultimate way to conserve the genetic diversity of these species and their populations in the short term, until effective methods can be developed (Dulloo et al. 2006). Cryopreservation is an important technique for longterm storage of tissues/plants. This requires liquid nitrogen (-196οC). The technique has been proved to be very useful for A. belladonna, Digitalis lanata, Hyoscyamus sp., and R. serpentina. Sharma and Sharma (2003) studied cryopreservation of shoot tips of Picrorhiza kurroa Royle ex Benth (IC 266698), which is also an endangered medicinal plant of India. The authors found that shoot-tips obtained from four weeks old cultures were dehydrated and directly immersed in liquid nitrogen. By vitrification, the shoot tips were cryopreserved and shoot regeneration of cryopreserved shoot tips to 70% and 35%, respectively. Recently, Mandal et al. (2009) cryopreserved embryogenic cultures of Dioscorea bulbifera using an encapsulation-dehydration procedure. They reported 53.3% recovery of growth of embryogenic culture after cryopreservation. On subculturing of these cultures, plantlets were obtained through embryo conversion. The authors reported 80% success of regeneration of cryopreserved embryogenic cultures DNA banks are kind of “Gene Library” in which DNA samples are stored. These provide vital information to the conservation scientists. DNA samples may be of three kinds: (i) total genomic DNA, (ii) DNA libraries, (iii) individual cloned DNA fragments including RFLP probes,

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mini- and microsatellites, etc. Some important DNA banks are as below: (i) The Royal Botanic Garden, Kew, UK, which contains PGR DNA specimens, and presently the world’s largest and the most comprehensive PGR DNA bank, consisting of over 20,000 DNA specimens representative of all plant families. (ii) The US Missouri Botanical Garden has collection of more than 20,000 plant tissue samples, and provide raw material for the extraction of DNA for its subsequent use in conservation research. (iii) The Australian Plant DNA Bank of Southern Cross University, which was established in June 2002. It contains representative genetic information from the entire Australian flora. (iv) DNA bank of Leslie Hill Molecular Systematics Laboratory of the National Botanical Institute (NBI) in Kirstenbosch, South Africa, in collaboration with the Royal Botanic Garden, Kew, which preserves genetic material of the South African flora (Rice et al. 2006).

CONCLUSSION Conservation of rare and endangered medicinal plants needs urgent attention. Although efforts have been made to conserve endangered medicinal plants by in situ and ex situ methods, the biotechnological strategies would open up new vistas in the field of conservation. Micropropagation of endangered plants like Aquilaria malaccensis, Dioscorea deltoidea, Guaicum officinale, Hydrastis canadensis, Nardostachys grandiflora, Panax quinquefolius, Picrorhiza kurroa, Podophyllum hexandrum, Prunus africana, Pterocarpus santalinus, Rauwolfia serpentina, Saussurea costus, Gloriosa superba and Taxus wallichiana will be beneficial because these plants will reach critically endangered, or possibly endangered stage. There is a pressing need to deliver mycorrhizal propagules into the roots of the tissue-culture-raised plantlets of endangered medicinal plants during the acclimatization process because the plantlets are devoid of microbes in sterile medium. Consequently, the plants suffer from ‘transient transplantation shock’. In order to avoid this bottleneck and for better survival and sustainable plant production, mycorrhization of the micropropagated plantlets is necessary. Agrobacterium tumefaciens and A. rhizogenes are the potent biological tools for transformation of endangered medicinal plants for development of varieties resistant to stress conditions and also for over production of secondary metabolites so that exploitation of these plants will be minimized. Cryopreservation is another technique to preserve the endangered medicinal plants. Moreover, DNA banks would be useful for long-term preservation and sustainable plant productions. ACKNOWLEDGEMENT The author would like to thank to the committee and The Society for Indonesian Biodiversity for invitation and hospitality at Solo, Central Java.

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Saharjo BH, Nurhayati AD (2006) Domination and composition structure change at hemic peat natural regeneration following burning; a case study in Pelalawan, Riau Province. Biodiversitas 7: 154-158. Book: Rai MK, Carpinella C (2006) Naturally occurring bioactive compounds. Elsevier, Amsterdam. Chapter in book: Webb CO, Cannon CH, Davies SJ (2008) Ecological organization, biogeography, and the phylogenetic structure of rainforest tree communities. In: Carson W, Schnitzer S (eds) Tropical forest community ecology. Wiley-Blackwell, New York. Abstract: Assaeed AM (2007) Seed production and dispersal of Rhazya stricta. 50th annual symposium of the International Association for Vegetation Science, Swansea, UK, 23-27 July 2007. Proceeding: Alikodra HS (2000) Biodiversity for development of local autonomous government. In: Setyawan AD, Sutarno (eds) Toward mount Lawu national park; proceeding of national seminary and workshop on biodiversity conservation to protect and save germplasm in Java island. Sebelas Maret University, Surakarta, 17-20 July 2000. [Indonesian] Thesis, Dissertation: Sugiyarto (2004) Soil macro-invertebrates diversity and inter-cropping plants productivity in agroforestry system based on sengon. [Dissertation]. Brawijaya University, Malang. [Indonesian] Information from internet: Balagadde FK, Song H, Ozaki J, Collins CH, Barnet M, Arnold FH, Quake SR, You L (2008) A synthetic Escherichia coli predator-prey ecosystem. Mol Syst Biol 4: 187. www.molecularsystemsbiology.com Publication manuscript “in press” can be cited and mentioned in reference (bibliography); “personal communications” can be cited, but cannot be mentioned in reference. Research which not be published or “submitted” cannot be cited. Some annotation. Manuscript typed without sign link (-) (except repeated word in Indonesian). Usage of letter “l” (el) to “1” (one) or “O” (oh) to “0” (null) should be avoided. Symbols of α, β, χ, etc. included through facility of insert, non altering letter type. No space between words and punctuation mark. Progress of manuscript. Notification of manuscript whether it is accepted or refused will be notified in about three months since the manuscript received. Manuscript is refused if the content does not in line with the journal mission, low quality, inappropriate format, complicated language style, dishonesty of research authenticity, or no answer of correspondence in a certain period. Author or first authors at a group manuscript will get one original copy of journal containing manuscript submitted not more than a month after publication. Offprint or reprint is only available with special request. NOTE: Author(s) agree to transfer copy right of published paper to BIODIVERSITAS, Journal of Biological Diversity. Authors shall no longer be allowed to publish manuscript completely without publisher permission. Authors or others allowed multiplying article in this journal as long as not for commercial purposes. For the new invention, authors suggested to manage its patent before publishing in this journal.

NOTIFICATION: All communications are strongly recommended to be undertaken through email.

ISSN: 1412-033X (printed edition) ISSN: 2085-4722 (electronic)

GENETIC DIVERSTY

DNA chloroplast variation in Shorea acuminata Dyer assessed by microsatellite markers ZULFAHMI, ISKANDAR ZULKARNAEN SIREGAR, ULFAH JUNIARTI SIREGAR Genetic diversity of sago palm in Indonesia based on chloroplast DNA (cpDNA) markers BARAHIMA ABBAS, YANUARIUS RENWARIN, MUHAMMAD HASIM BINTORO, SUDARSONO, MEMEN SURAHMAN, HIROSHI EHARA Genetic variability among 18 cultivars of cooking bananas and plantains by RAPD and ISSR markers YUYU SURYASARI POERBA, FAJARUDIN AHMAD

107-111 112-117

118-123

SPECIES DIVERSTY

Flower and fruit development of Syzygium pycnanthum Merr. & L.M. Perry DEDEN MUDIANA, ESTI ENDAH ARIYANTI

124-128

ECOSYSTEM DIVERSTY

Screening of antimicrobial isolations from the soil of grassland rhizosphere area in Pocut Meurah Intan Forest Park, Seulawah, Aceh Besar LENNI FITRI, BETTY MAULIYA BUSTAM Community structure of macrozoobenthic feeding guilds in responses to eutrophication in Jakarta Bay AM AZBAS TAURUSMAN Litter decomposition of Rhizophora stylosa in Sabang-Weh Island, Aceh, Indonesia; evidence from mass loss and nutrients IRMA DEWIYANTI Predicting infectivity of Arbuscular Mycorrhizal fungi from soil variables using Generalized Additive Models and Generalized Linear Models IRNANDA AIKO FIFI DJUUNA, LYNETTE K. ABBOTT, KIMBERLY VAN NIEL Floristic composition at biodiversity protection area in Lubuk Kakap, District of Ketapang, West Kalimantan SUGENG BUDIHARTA

129-132

133-138

139-144

145-150

151-156

REVIEW

Review: Biotechnological strategies for conservation of rare and endangered medicinal plants MAHENDRA KUMAR RAI

157-166

Front cover: Syzygium pycnanthum Merr. & L.M. Perry (PHOTO: DEDEN MUDIANA)

Published four times in one year

PRINTED IN INDONESIA ISSN: 1412-033X (printed)

ISSN: 2085-4722 (electronic)