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MARSCI ONLINE JOURNAL FOR UNDERGRADUATE RESEARCH IN MARINE AND AQUATIC SCIENCE

SPRING 2010

MARSCI ONLINE JOURNAL FOR UNDERGRADUATE RESEARCH IN MARINE AND AQUATIC SCIENCE Issue 9 Spring 2010

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NICHOLAS P. BURNETT

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TABLE OF CONTENTS Renchen, Gabrielle F., Jeffrey D. Renchen, and Erin J. Burge Input of dissolved nutrients by submarine groundwater discharge to the lagoon at Discovery Bay, Jamaica pg

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Tatalovic, Mico Species selectivity of clients by the neon goby cleaner fish Gobiosoma Oceanops

INPUT OF DISSOLVED NUTRIENTS BY SUBMARINE GROUNDWATER DISCHARGE TO THE LAGOON AT DISCOVERY BAY, JAMAICA GABRIELLE F. RENCHEN†, JEFFREY D. RENCHEN† AND ERIN J. BURGE* Department of Marine Science, Coastal Carolina University, PO Box 261954, Conway, SC 29527

Abstract Submarine groundwater discharge (SGD) has become recognized as an important source of low salinity, nutrient rich waters to coastal ecosystems. Coral reefs typically represent low nutrient, high salinity environments that are sensitive to changes in these parameters. The intent of this study was to determine the relationship between nutrient concentrations of NO3-, NO2- and PO43-, and salinities present in water originating from and near groundwater springs in Discovery Bay, Jamaica, and to examine the relationship between these nutrients inputs and relative percent macroalgal cover. Nutrient concentrations varied both spatially between SGD locations and temporally on short time scales (days), suggesting that there are important local effects of SGD within Discovery Bay. Levels of nitrate up to 37.8 µM were detected emanating from groundwater discharge points, and these represent a significantly higher local source of nitrate compared to the surrounding oceanic waters (NO3- 0.50 µM). There was a strong (p < 0.01) positive correlation between increasing salinity and increasing dissolved oxygen concentrations associated with decreasing influence of the SGD. Keywords: Eutrophication, SGD, Nitrate, Nitrite, Phosphate, Macroalgae, Phase Shift

Introduction Within coastal aquifers, seawater and groundwater mixing has been characterized as a process involving both saltwater intrusion and submarine groundwater discharge (Kaleris 2006; Niencheski et al. 2007). Recently, the presence of submarine groundwater discharge (SGD) has been recognized as a significant source of low salinity, nutrient rich waters that are transported from land to shallow coastal waters (Valiela et al. 1990; Bokuniewicz et al. 2003; Taniguchi et al. 2003; Young et al. 2008). SGD tends to be highly variable, depending on season, hydrology and if the †Current address: University of the Virgin Islands, Office

of Student Activities Box 384, #2 John Brewers Bay, St. Thomas, USVI 00802 *Corresponding author and advisor: Tel.: +011-­‐843-­‐349-­‐ 6491; fax: +011-­‐843-­‐349-­‐2545; e-­‐mail: eburge@coastal.edu

location is urbanized or agriculturally influenced (Valiela et al. 1990). Because SGD is both spatially and temporally variable, measurements of nutrients and salinities taken on a short term basis may not accurately depict the behavior of such properties over a longer period (Umezawa et al. 2002), but these data are nonetheless useful for providing baseline information on understudied SGD systems.

Although highly biologically productive, coral reefs are typically low in nutrients, making them susceptible to potential ecological consequences of SGD (D'Elia et al. 1981; Street et al. 2008). For example, elevated nutrients can shift the delicate balance between scleractinian communities in favor of one dominated by macroalgae, especially when herbivore densities are low (Szmant 2002).

The coral reef ecosystems surrounding Jamaica are some of the most intensively studied in the world. Discovery Bay, which is located on the north-central coast of Jamaica, is home to the

SGD IN DISCOVERY BAY, JAMAICA

Discovery Bay Marine Lab (DBML) as well as three Caribbean Coastal Marine Productivity (CARICOMP) monitoring sites that are maintained by the United States National Oceanic and Atmospheric Administration (NOAA). The lagoon and surrounding reefs at Discovery Bay are currently dominated by macroalgal communities rather than corals, in contrast to surveys conducted prior to 1980 (Liddell and Ohlhorst 1986; Goreau 1992; Lapointe 1997). This phase shift from coral to macroalgal domination occurred due to a combination of the mass mortality of the grazer Diadema antillarum, overfishing, storm damage (Goreau 1992; Hughes 1994) and nutrient-rich groundwater input (D'Elia et al. 1981).

The Discovery Bay drainage basin is comprised mostly of limestone, with areas of submerged fractures allowing for significant groundwater seepage (D'Elia et al. 1981; Bonem 1988). Allen (1976) claimed that limestone in an area that is solution riddled can provide channels for the rapid flow of groundwater further offshore than usual.

Inside Discovery Bay, D’Elia et al. (1981) found nitrate concentrations to be as high as 33.5 µM near groundwater springs in salinities of 20 ppt or less, while phosphate concentrations were much lower, only reaching 0.25 µM. Accompanying nutrient enrichment from SGD is the potential reduction of salinities. Species of macroalgae have been found to distribute according to their osmotic optima in addition to light and nutrient availability (Montague and Ley 1993).

Diversity of marine algal species has been found to decrease as salinity decreases (< 10 ppt) due to slowed sporophyte production and development, thus causing species to distribute according to salinity in order to obtain maximum growth and reproductive potential (Norton and South 1969; Nygren 1975).

There is much controversy in determining the catalyst in coral reef phase shifts from coral to macroalgal domination. The intent of this study was not to determine the cause, but to determine the relationship between nutrient concentrations of NO3-, NO2- and PO43-, and salinities present in water originating from and near groundwater springs in Discovery Bay, Jamaica. Macroalgal species diversity as well as total and relative percent cover were also examined to test the hypothesis that these communities distribute according to salinity levels.

Methods This study was conducted at Discovery Bay, Jamaica, during May of 2008. Springs at three sites were sampled on multiple days over approximately three weeks. Springs were studied adjacent to the University of the West Indies, Discovery Bay Marine Laboratory (DBML) facilities in the mangroves, an area locally known as the Blue Maze (Gayle and Woodley 1998) (18°28'8.20"N, 77°24'56.36"W), directly north of the DBML dock at the White Pole channel marker (18°28'9.40"N, 77°24'53.98"W), and to the east within Discovery Bay proper, just off the shore of the DBML dormitories (18°28'3.91"N, 77°24'49.67"W), at depths of approximately 20 m. At each spring, 45 m line transects were used to collect water samples analyzed for nutrient concentrations of NO3-, NO2and PO43- as well as dissolved oxygen concentrations, salinity and temperature, and benthic community data.

The mangrove spring was located in a slightly southeast direction upon entering the grotto, and was protected from open access to the lagoon by a shallow limestone sill (< 1 m water depth). The largest spring head and outflow was located at the base of limestone rocks along the shore. A transect was laid from the base of the rocks in the southwest corner of the mangroves towards the reef crest for approximately 29 m in a northeasterly direction, and then towards the east for approximately 16 m into the lagoon. Transect compass orientation was set such that distance from the spring head was always toward the seaward channel entrance at the mouth of Discovery Bay. During the first sampling at this location, a portable YSI 85 multiparameter instrument (YSI Incorporated, Yellow Springs, Ohio) was used to measure the salinity, dissolved oxygen (percent saturation and concentration), and temperature every 1 m. During subsequent samplings measurements were taken every 2 m with the YSI meter. Along the same transect, 250 mL LPDE Nalgene bottles (Thermo Fisher Scientific Inc., Waltham, Massachusetts) were used to collect water samples at less than 1 m depth every 4 m. A total of 10 bottle samples were collected per transect and sampling date. Also along the same transect, 1 m2 quadrats were laid and pictures were taken of the benthic community every 2 m in order to identify macroalgae species and estimate percent 2

SGD IN DISCOVERY BAY, JAMAICA

macroalgal cover. Two observers’ approximations of percent macroalgal cover were averaged for each quadrat location and macroalgae were identified to genus using the identification guides of Littler and Littler (2000) and Humann and DeLoach (2001).

The spring located north of the DBML dock was near the furthest channel marker away from the shore. This location was referred to as the “White Pole” spring. A 45 m transect was laid along the spring which in this case was a large crack in the seafloor. Transect compass orientation was set such that distance from the spring head was always toward the seaward channel entrance at the mouth of Discovery Bay. Water samples were collected every 4 m using the same materials and methods noted for the Blue Maze, and immediately returned to the lab to be analyzed. Quadrats were laid every 4 m to determine the species composition and percent cover of macroalgae present. All of the data for this location as well as the Blue Maze were collected by snorkeling.

Three springs located in the western portion of Discovery Bay (~20 m deep) were sampled differently than the lagoon springs. Water samples were collected every 4 m, but only for approximately 20 m, through the use of SCUBA. Transect compass orientation was set such that distance from the spring head was always toward the seaward channel entrance at the mouth of Discovery Bay. Temperatures for the deeper springs were not collected due to a lack of equipment that could obtain accurate in situ measurements. At each spring location additional notes on community structure were collected in addition to the macroalgae species composition.

Water samples were also collected at Dairy Bull Reef (18°28'4.56"N, 77°23'18.76"W), located ~2 km east of Discovery Bay because this site exhibited minimal apparent groundwater input or runoff compared to Discovery Bay. The benthic community at Dairy Bull Reef is mostly dominated by scleractinian corals, and has shown an increase in coral cover in recent years (Idjadi et al. 2006; Quinn and Kojis 2008). Water samples were collected along two parallel, 66 m transects at approximately 8 m depth. Along one transect, samples were collected at 0 and 33 m, and on the second transect, water samples were collected at 0, 33 and 66 m. Surface water samples were also collected at these positions along the transects.

Once collected, the samples were immediately returned to the lab for analysis. This site served as a reference location to which the nutrient and dissolved oxygen concentrations and salinities from Discovery Bay were compared.

Once the water samples were collected, they were immediately returned to the lab for nutrient analysis using a HACH DR 890 series colorimeter (Hach Company, Loveland, Colorado) and associated methods. All appropriate blanks and internal controls were utilized. Briefly, nitrate (NO3-) concentrations were measured using HACH method 8039; a cadmium reduction using NitraVer 5 Reagent Powder Pillows. This method was used to assay a high range of nitrate concentrations ranging from 0 - 30.0 mg/L after a 5 minute reaction period. Nitrite (NO2-) concentrations were obtained using HACH method 8507. A low range assay of concentrations (0 - 0.350 mg/L) was measured by a diazotization method with NitriVer 3 Reagent Powder Pillows after a 15 minute reaction period. Phosphate (PO43-) concentrations were obtained using HACH method 8048. This method employed an orthophosphate ascorbic acid method, which used PhosVer 3 Powder Pillows to detect reactive phosphate concentrations (0 - 2.50 mg/L) after a 2 minute reaction period.

Statistical analyses used to assess the nutrient data were conducted either in SigmaStat 3.11 (Systat Software, Inc., Chicago, Illinois) or Microsoft Excel 2003 (Redmond, Washington) with α = 0.05, and the results were graphically displayed using SigmaPlot 9.1 (Systat Software, Inc., Chicago, Illinois). When the assumptions of equal variance or normal distribution were violated Kruskal-Wallis One Way Analysis of Variance on Ranks was used to test for significant differences.

Linear regression was conducted in SigmaStat 3.11.

Results Nitrate concentrations were highly variable within the Blue Maze. Nitrate concentrations ranged from 4.84 - 30.64 µM with an average concentration of 16.24 ± 7.271 µM (Figure 1a).

There was not a significant difference in concentrations detected between the four sampledays (p = 0.64), despite sampling at highs and lows of the tidal cycle, although a significant difference in salinity between days was detected (Kruskal3

SGD IN DISCOVERY BAY, JAMAICA

Wallis One Way Analysis of Variance on Ranks, p < 0.01) (Figure 2a). No significant correlation existed between the salinity gradient and nitrate concentrations (p = 0.16, R2 = 0.051). Nitrite concentrations were extremely low (0 - 0.11 µM) with an average concentration of 0.0429 ± 0.0322 µM, while phosphate ranged from 0 - 4 µM and had an average concentration of 1.223 ± 0.8535 µM. Salinities were variable as well (25.4 - 34.3 ppt).

The average salinity was 29.8 ± 2.82 ppt. The concentrations of dissolved oxygen were lowest at this site (Figure 3) with an average concentration of 4.68 ± 1.01 mg/L and a range of 2.93 - 6.58 mg/L (Table 1). The mangroves spring site within the Blue Maze consisted of a community of Red (Rhizophora mangle), White (Laguncularia racemosa) and a few Black (Avicennia germinans) mangroves that were supported by a mostly limestone substrate. The prop roots and limestone substrate provided shelter for both adult and juvenile Stegastes adustus and other juvenile fishes.

Other large, benthic invertebrates found included Lytechinus variegatus, Diadema antillarum, and Condylactis gigantea. The presence of macroalgae was greatest at this site from 0-24 meters along the transect, an area characterized by large cracks in the substrate where groundwater emerged near the 5 m and 10 m marks. The dominant species of macroalgae present along the transect included Jania (Rhodophyta), Ventricaria (Chlorophyta), Halimeda (Chlorophyta), Galaxuara (Rhodophyta), Agardhiella, and turf algae. All were positively identified except for Agardhiella. The average percent cover was 79.94 ± 24.62 % with a range of 7.5 - 98.5 %.

The concentrations of nitrate near the White Pole Channel marker were highly variable. Nitrate concentrations ranged from 3.22 - 29.02 µM and had an average concentration of 14.107 ± 6.227 µM (Figure 1b). Concentrations did not differ between sample-days (p = 0.15), and no significant correlation existed between the salinity gradient and nitrate concentrations (p = 0.85, R2 = 0.001), although salinities differed significantly between sample days (Kruskal-Wallis One Way Analysis of

Figure 1. The relationship between concentrations of NO3- and salinity for the lagoonal springs in the Blue Maze (a) and near the White Pole (b). No significant differences were present between days at each site (p = 0.64 and p = 0.15, respectively) or between the sites (p = 0.299).

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Variance on Ranks, p < 0.001).

Nitrite concentrations were extremely low (0 - 0.11 µM) and averaged 0.0468 ± 0.0417 µM. Phosphate concentrations were slightly higher than the NO2concentrations but were still low ranging from 0 4.74 µM, with an average concentration of 0.8588 ± 0.7782 µM. Temperatures ranged from 27.3 28.5°C and had an average of 28.015 ± 0.2424ºC while dissolved oxygen (Figure 3) had an average concentration of 5.22 ± 0.74 mg/L and a range of 3.6 - 6.6 mg/L (Table 1). This location, like the mangroves site, had a mostly limestone substrate with a few patches of sand, but in contrast to the Blue Maze site, bottom topography was more uniform. The average percent cover at this location was 66.11 ± 1.067% with a range of 9 - 97.5%. The dominant species of algae present included Jania (Rhodophyta), Sargassum (Phaeophyta), Halimeda (Chlorophyta), Dictyota (Phaeophyta) and possibly Agardhiella. All were positively identified with the exception of Agardhiella. Both Diadema and

Lytechinus were present within cracks and crevices of the limestone, and Diodon hystrix, Scarus taeniopterus, and Haemulon flavolineatum were all observed utilizing the cover of the spring head.

Located at 4 m on the transect was a large, welldefined spring head with a strong outflow. The outflow was strong enough that it could be observed disturbing the surface waters. Another large spring was located at 12 m. In addition, there was a 21 m long crevice in the substrate that coincided with the transect. This crevice contained numerous sporadically placed points or springs where groundwater was observed at the surface as well.

After the 20 m mark, the signal of SGD ceased and the substrate was sandy.

In contrast to the lagoonal springs, springs within Discovery Bay were sampled at depths of approximately 20 m. Similar to the other springs studied, nitrite concentrations were minimal and variable. Concentrations ranged from 0-0.11 µM with an average of 0.0442 ± 0.0434 µM. The nitrate

Figure 2. Salinity trends with increasing distance from the main spring opening for the lagoonal springs within the Blue Maze (a) and near the White Pole channel marker (b). Distances are compass oriented toward the main shipping channel entrance to Discovery Bay. (a) Blue Maze salinity data were collected during slack high tide on 15, 17, and 19 May, and during slack low tide on 21 and 22 May (p < 0.01). (b) White pole salinity data were collected during slack high tide on 18, 19, and 20 May, and during slack low tide on 23 and 24 May (p = 0.007). Note the difference in scale for the abscissa between (a) and (b).

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transect were located at 0, 4, and 8 m, but were observed exhibiting variable flow strength depending on the occurrence of rain events.

Dissolved oxygen had a range of 4.65 - 6.25 mg/L and an average of 5.59 ± 0.51 mg/L. There was not a clear relationship between dissolved oxygen and salinity at this location. The deeper springs were found to have little to no algal coverage and were mostly dominated by sponge communities. For all of the data, including the mangroves and white pole springs, it should be noted that rain events occurred on May 15 and 22, 2008.

Samples taken from surface and bottom waters at Dairy Bull Reef were significantly lower for nitrate (p < 0.01), nitrite (p < 0.01) and phosphate (p < 0.01), when compared to locations within Discovery Bay (Table 1). Other abiotic parameters were also less variable, and were representative of the adjacent oligotrophic ocean. Waters collected from public taps at DBML were found to contain low levels of nitrate (1.6 µM) and phosphate (0.09 µM) when sampled.

Figure 3. Dissolved oxygen concentrations at the lagoonal springs compared to salinity concentrations. Concentrations at the two sites were significantly different (p = 0.004). There was a strong positive correlation between increasing salinity and increasing dissolved oxygen concentration at both sites (Blue Maze, p < 0.01, R2 = 0.616, y = 0.282x – 3.71; White Pole, p = 0.017, R2 = 0.113, y = 0.152x + 0.0168).

concentrations ranged from 11.29 - 38.7 µM with an average concentration of 19.276 ± 7.334 µM. There was no significant difference in nitrate concentrations between sample-days (p = 0.73), although there was a significant relationship between salinity and nitrate concentrations at the springs (p = 0.012; R2 = 0.254; y = -0.5883x + 37.861). Phosphate concentrations had a range of 0 - 6.63 µM and an average of 1.637 ± 1.693 µM. The lowest salinities were found at the spring heads where outflow was easily observed, and increased with increasing distance from the springs. Salinities ranged from 18.1 - 35.3 ppt and had an average of 30.5 ± 6.77 ppt. The large spring heads along the

Discussion In this study, concentrations of major dissolved nutrients (NO3-, NO2-, PO43-), temperature, salinity, dissolved oxygen, and dominant benthic community type were determined for areas of submarine groundwater discharge (SGD) in Discovery Bay, Jamaica. All measured parameters varied both spatially and temporally on short time scales (days), suggesting that there are important local effects of SGD within Discovery Bay. The nitrate concentrations in this study closely approximated those documented by D’Elia et al.

(1981), Lapointe (1997), and Greenaway et al.

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(2006) with concentrations of 4.96-27.86 µM, 33.5 µM and 20-32 µM respectively. It is important to note that although D’Elia et al. (1981) documented NO3-concentrations as high as 80 µM near Discovery Bay, Jamaica, this was in undiluted spring water whereas the highest concentrations found in seawater only reached 33.5 µM. Although variable, the nitrate concentrations did typically decrease as salinity increased suggesting that the nutrients become diluted and dispersed as they move away from the springs (D'Elia et al. 1981; Giblin and Gaines 1990; Lapointe 1997).

Nitrate concentrations were documented as highly variable at both the Blue Maze mangroves and White Pole springs; however there was not a significant difference in the concentrations between sampling days or locations (p = 0.30). The highest concentrations of NO3- were found in the water samples collected nearest to the springs or over cracks in the substrate where the lowest salinities occurred. Of all the sampling locations, the West Bay springs had the most discrete outflows, the highest nitrate concentrations, and the lowest salinities. It is likely that this was the case due to reduced vertical mixing of the water column from the lack of wind disturbances at depth and tidal inundation. It would be predicted that if nitrate mixes conservatively with the surrounding nutrientpoor seawater then concentrations would correlate well with observed salinities. This was only the case for the deep springs (~16 m) observed within Discovery Bay. The results suggest that saltwater intrusion occurs within the aquifers inland of the coast before the groundwater is discharged at the springs. In another study, salinities measured in pools within the Green Grotto Caverns (18°27'36.36"N 77°22'25.57"W), located inland and approximately 3 km east of Discovery Bay, ranged from 2 ppt at the surface to 17.5 ppt at 5 m with a strong halocline near 3 m depth (Maddocks and Iliffe 1993). The White Pole spring was subject to winds, currents and tidal mixing all of which could affect the nutrient and salinity levels and flushing time of the spring on a daily basis (Johannes and Hearn 1985). It also had one main spring head or vent in which SGD could be seen rising to the lagoon surface early in the morning before the trade winds increased around 1100 each day. The Blue Maze spring exhibited less variation in both nitrate

concentrations and salinity over the sampling period. This is most likely due to the isolated location, in which the spring was protected by the grotto and mangroves from wind and current mixing. It was within the Blue Maze that the effects of SGD were the most evident. It should be noted however that this location had multiple seeps, as opposed to one main spring head, allowing the lower salinity groundwaters to mix with subsurface seawater within the limestone substrate more freely.

The Blue Maze is also where the largest volume of freshwater discharge occurs within Discovery Bay and thus supplies a large volume of low salinity, nutrient rich waters (Gayle and Woodley 1998).

Nitrite was essentially absent in all samples from all locations suggesting that biogeochemical processes within the aquifers are controlling the attenuation of nitrate. Denitrification is just one biogeochemical process that greatly affects nitrate attenuation and its rate is typically related to dissolved oxygen concentrations. Exceedingly high concentrations of nitrate accompanied by intermediate concentrations of dissolved oxygen have the potential to arrest denitrification which could explain the high nitrate, low nitrite concentrations documented in sampling (Rivett et al. 2008). Dissolved oxygen concentrations exhibited a positive trend with salinity at the Blue Maze (Figure 3). This trend was opposite what normally occurs in seawater where dissolved oxygen decreases as salinity increases and is most likely explained by depletion within the aquifer via heterotrophic metabolism (Rivett et al. 2008).

Phosphate concentrations in this study were also low, likely due to sorption with iron oxides and calcium carbonate deposits. These minerals are prevalent in the coastal geology of the north coast of Jamaica, and within the sediments of Discovery Bay due to bauxite mining operations and the carbonate dominated sediments associated with coral reefs (Perry and Taylor 2004; Rivett et al.

2008).

The effect of SGD on the benthic community structure and macroalgal distributions was not as clear as the chemical and physical measurements suggested. Based on observations of percent cover and species distribution, the macroalgae identified at the Blue Maze and White Pole springs did not exhibit a clear distributional relationship with salinity and or nutrients. A similar study conducted 7

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on macroalgal distributions in Biscayne Bay, Florida (Biber and Irlandi 2006), demonstrated that drift algal species such as Jania and Sargassum were most abundant in waters that received pulses of low salinity waters, while rhizophytic algae such as Halimeda and Caulerpa were most abundant in higher salinity waters. Although Caulerpa was not documented along any of the transects in this study, it was prevalent in other locations within Discovery Bay (personal obs.). The percent cover and distribution of macroalgae at the White Pole spring however did not display any apparent trends associated with the groundwater likely due to the rapid dilution associated with mixing from winds and currents. The species of macroalgae were slightly different than those in the Blue Maze in that Sargassum was most dominant near the spring head instead of turf algae or Jania, and Dictyota as well as Halimeda were found further away from the springs.

The nutrient concentrations and salinity levels documented in this study may not be representative of how the SGD behaves over the course of a year due to lack of sampling over the seasons. Jamaicaâ&#x20AC;&#x2122;s seasons tend to deviate from year to year but it typically has a primary wet season that occurs from April through December and a dry season from December through April. Within these described seasons however there is a short wet period in May and June and a short dry period in July (Nkemdirim 1979; Stephenson et al. 2008). Groundwater seepage flux can vary, but tends to be higher during the wet season (Lewis 1987). Over the course of this study, two sampling dates occurred after rain events. At the West Bay springs, SGD did appear to be stronger at different spring heads after these rain events, but this was likely due to rain that had occurred at an earlier time. Greenaway et al. (2006) documented that variations in salinity represented short and long terms rainfall patterns on the order of 1-5 days or months prior to sampling respectively.

In addition, they also documented slight increases in nitrate with the decreased salinities in Discovery Bay. In Great South Bay, NY changes in rainfall were noticeable in the water table after approximately 6 months and it was indicated that water table height could determine the groundwater outflow rates (Capone and Slater 1990).

The results of this study provide more information on the properties of SGD and its

potential biological and ecological affects within Discovery Bay, Jamaica. Although the population of Discovery Bay was approximately 2500 in 2001 and has nearly doubled since 1981, land use practices have changed little (Greenaway and Gordon-Smith 2006) making it unlikely that the nutrients in the SGD are anthropogenically derived.

To accurately determine the effects of submarine groundwater discharge on Discovery Bay, seepage rates and water quality need to be monitored over the course of the seasons. In addition, macroalgal coverage, growth and tissue nutrient concentrations should be monitored as well to determine if the nutrient rich groundwater is accelerating the abundance of macroalgae as would be the case in a eutrophic, bottom-up regulated system.

Acknowledgements The authors wish to thank the staff of the Discovery Bay Marine Laboratory, University of the West Indies, for facilities support. Steven Luff, Scientific Dive Safety Officer, Coastal Carolina University, supervised the SCUBA diving portions of this project and contributed to the completion of this study. Dr. Susan Libes, Coastal Carolina University, contributed technical expertise in nutrient analyses, and materials and supplies.

Literature Cited Allen, A. D. 1976. Outline of the hydrogeology of the superficial formations of the Swan Coastal Plan. Western Australia Geological Survey. Annual Report 1975: 31-42.

Biber, P. D., and E. A. Irlandi. 2006. Temporal and spatial dynamics of macroalgal communities along on anthropogenic salinity gradient in Biscayne Bay (Florida, USA). Aquat. Bot. 85(1): 65-77.

Bokuniewicz, H., Buddemeier, R., Maxwell, B., and C. Smith. 2003. The typological approach to submarine groundwater discharge (SGD). Biogeochemistry. 66(1/2): 145158.

Bonem, R. M. 1988. Effects of submarine karst development on reef succession. Proc. 6th Int. Coral Reef Symp. 3: 419423.

Capone, D. G., and J. M. Slater. 1990. Interannual patterns of water table height and groundwater derived nitrate in nearshore sediments. Biogeochemistry. 10(3): 277-288.

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D'Elia, F. F., Webb, K. L., and J. W. Porter. 1981. Nitraterich ground water inputs to Discovery Bay, Jamaica: A significant source of N to local coral reefs. Bull. Mar. Sci. 31(4): 903-910.

Montague, C. L., and J. A. Ley. 1993. A possible effect of salinity fluctuation on abundance of benthic vegetation and associated fauna in northeastern Florida Bay. Estuaries. 16(4): 703-717.

Gayle, P. M. H., and J. D. Woodley. 1998. Discovery Bay, Jamaica. In CARICOMP - Caribbean coral reef, seagrass and mangrove sites. ed. B. Kjerfve, 17-33 Paris: UNESCO.

Niencheski, L. F. H., Windom, H. L., Moore, W. S., and R. A. Jahnke. 2007. Submarine groundwater discharge of nutrients to the ocean along a coastal lagoon barrier, Southern Brazil. Mar. Chem. 106(3-4): 546-561.

Giblin, A. E., and A. G. Gaines. 1990. Nitrogen inputs to a marine embayment: The importance of groundwater.

Biogeochemistry. 10(3): 309-328.

Nkemdirim, L. C. 1979. Spatial and seasonal distribution of rainfall and runoff in Jamaica. Geogr. Rev. 69(3): 288-301.

Goreau, T. J. 1992. Bleaching and reef community change in Jamaica: 1951-1991. Am. Zool. 32(6): 683-695.

Norton, T. A., and G. R. South. 1969. Influence of reduced salinity on the distribution of two laminarian algae. Oikos.

20(2): 320-326.

Greenaway, A. M., and D. A. Gordon-Smith. 2006. The effects of rainfall on the distribution of inorganic nitrogen and phosphorus in Discovery Bay, Jamaica. Limnol. Oceanogr.

51(5): 2206-2230.

Nygren, S. 1975. Influence of salinity on the growth and distribution of some Phaeophyceae on the Swedish West Coast. Bot. Mar. 18: 143-147.

Hughes, T. P. 1994. Catastrophes, phase shifts, and largescale degradation of a Caribbean coral reef. Science.

265(5178): 1547-1551.

Perry, C. T., and K. G. Taylor. 2004. Impacts of bauxite sediment inputs on a carbonate-dominated embayment, Discovery Bay, Jamaica. J. Coast. Res. 20: 1070-1079.

Humann, P., and N. DeLoach. 2001. Reef coral identification: Florida, Caribbean, Bahamas. New World Publications, Jacksonville, Florida.

Quinn, N. J., and B. L. Kojis. 2008. The recent collapse of a rapid phase-shift reversal on a Jamaican north coast coral reef after the 2005 bleaching event. Rev. Biol. Trop. 56(Suppl. 1): 149-159.

Idjadi, J. A., Lee, S. C., Bruno, J. F., Precht, W. F., AllenRequa, L., and P. J. Edmunds. 2006. Rapid phase-shift reversal on a Jamaican coral reef. Coral Reefs. 25(2): 209-211.

Rivett, M. O., Buss, S. R., Morgan, P., Smith, J. W. N., and C. D. Bemment. 2008. Nitrate attenuation in groundwater: A review of biogeochemical controlling processes. Water Res. 42(16): 4215-4232.

Johannes, R. E., and C. J. Hearn. 1985. The effects of submarine groundwater discharge on nutrient and salinity regimes in a coastal lagoon off Perth, Western Australia.

Estuar. Coast. Mar. Sci. 21(6): 789-800

Stephenson, T. S., Chen, A. A., and M. A. Taylor. 2008.

Toward the development of prediction models for the primary Caribbean dry season. Theor. Appl. Clim. 92(1): 87-101.

Kaleris, V. 2006. Submarine groundwater discharge: Effects of hydrogeology and of near shore surface water bodies. J. Hydrol. 325(1-4): 96-117.

Street, J. H., Knee, K. L., Grossman, E. E., and A. Paytan.

2008. Submarine groundwater discharge and nutrient addition to the coastal zone and coral reefs of leeward Hawai'i. Mar. Chem. 109(3-4): 355-376.

Lapointe, B. E. 1997. Nutrient thresholds for bottom-up control of macroalgal blooms on coral reefs in Jamaica and southeast Florida. Limnol. Oceanogr. 42(5): 1119-1131.

Szmant, A. M. 2002. Nutrient enrichment on coral reefs: Is it a major cause of coral reef decline? Estuaries. 25(4): 743-766.

Lewis, J. B. 1987. Measurements of groundwater seepage flux onto a coral reef: Spatial and temporal variations. Limnol.

Oceanogr. 32(5): 1165-1169.

Taniguchi, M., Burnett, W. C., Smith, C. F., Paulsen, R. J., Oâ&#x20AC;&#x2122;Rourke, D., Krupa, S. L., and J. L. Christoff. 2003.

Spatial and temporal distributions of submarine groundwater discharge rates obtained from various types of seepage meters at a site in the Northeastern Gulf of Mexico. Biogeochemistry.

66(1-2): 35-53.

Liddell, W., and S. Ohlhorst. 1986. Changes in community composition following the mass mortality of Diadema at Jamaica. J. Exp. Mar. Biol. Ecol. 95(3): 271-278.

Littler, D. S., and M. M. Littler. 2000. Caribbean Reef Plants. OffShore Graphics, Inc, Washington, D. C.

Umezawa, Y., T. Miyajima, M. Yamamuro, H. Kayanne and I. Koike. 2002. Fine-scale mapping of land-derived nitrogen in coral reefs by δ15N in macroalgae. Limnol.

Oceanogr. 47(5): 1405-1416.

Valiela, I., Costa, J., Foreman, K., Teal, J. M., Howes, B., and D. Aubrey. 1990. Transport of groundwater-borne

Maddocks, R. F., and T. M. Iliffe. 1993. Thalassocypridine ostracoda from anchialine habitats of Jamaica. J. Crustac.

Biol. 13(1): 142-164.

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nutrients from watersheds and their effects on coastal waters.

Biogeochemistry. 10(3): 177-197.

Characterizing sources of groundwater to a tropical coastal lagoon in a karstic area using radium isotopes and water chemistry. Mar. Chem. 109(3-4): 377-394.

Young, M. B., Eagle Gonneea, M., Fong, D. A., Moore, W. S., Herrera-Silveira, J., and A. Payatan. 2008.

10

SPECIES SELECTIVITY OF CLIENTS BY THE NEON GOBY CLEANER FISH GOBIOSOMA OCEANOPS MICO TATALOVIC1 1

Keble College, University of Oxford, Parks Road, OX1 3PG

Abstract Neon goby (Gobiosoma oceanops) is an obligate marine cleaner fish that lives in the Caribbean. I investigated several color patterns found on client fish to examine preferences of G. oceanops for visual qualities of client fish. G. oceanops were presented with a choice of wooden models painted with varied color patterns and times spent with each model type were recorded. I observed G. oceanops in situ on a coral reef patch in Honduras. I also recorded the identity of client species that visited the cleaning stations, posed, and were inspected by neon gobies, as well as the amount of time each fish spent posing and being inspected. I observed the cleaning stations at two different times of day, morning and afternoon, to assess daily variation in composition of the client fish. My experiments indicated that G. oceanops had no preference for any of the color patterns tested. If neon gobies use visual cues to select clients they may be using them in combination with other cues, such as olfactory. Fewer species posed and were inspected in the morning than the afternoon. This finding contradicts the expectation from the distribution of gnathiid parasites in the Caribbean; gnathiid parasites are present at higher levels on client fish in the morning. A reason behind the observed variation in posing behavior may be that the parasite infection levels of the client fish are not the proximate cause of visits to cleaning stations in some species.

Introduction Cleaning symbioses Cleaning symbioses occur in a wide range of animal taxa. Examples include birds cleaning various reptiles (Geospiza finch species) and mammals such as deer (Aphelocoma jay species) and ungulates (Buphagus oxpecker species), crabs cleaning turtles (Planes crab species), banded mongoose, Mungos mungo, cleaning warthogs, shrimps cleaning fish (Periclimenes species), as well as fish cleaning fish and turtles (Thalassoma species) (Poulin and Grutter 1996). Most cleaning symbioses described so far occur in marine and freshwater aquatic environments. In marine environments, cleaning symbioses are found in

1

Corresponding author: mico.tatalovic@keble.oxon.org Advisor: Dr. Thereesa Burt de Perera, Keble College, University of Oxford, Parks Road, OX1 3PG, UK

temperate and tropical seas, but contemporary research has mainly focused on coral reef species.

Cleaning stations are usually positioned in prominent places of coral reefs (e.g. coral heads).

These places are occupied by multiple cleaners of one or more species and are relatively permanent features: several generations of cleaners may choose the same cleaning station as their habitat. Cleaners may be obligate or facultative, depending on species. The neon goby, Gobiosoma oceanops, is an obligate cleaner throughout its life, feeding mainly on ectoparasites and mucus of client fish whereas facultative cleaners tend to be juveniles of species such as french angelfish, Pomacanthus paru, or spanish hogfish, Bodianus rufus, which feed on other items as well and cease to be cleaners as adults (Deloach and Humann 2003). Cleaners advertise their availability to clients by positioning themselves in a visible place at the station. Clients visit the stations and often pose to initiate inspection

CLEANER FISH SPECIES SELECTIVITY

by the cleaner. Sessions of inspection are usually several seconds long and the cleaner may remove ectoparasites, mainly gnathiid isopods (Darcy et al.

1974; Deloach and Humann 2003). During this process the client remains calm although it may occasionally jolt (Bshary 2001). Jolts may indicate instances of cleaners biting clients’ tissues rather than removing the ectoparasites (Bshary 2001).

Alternatively, jolts may be the client’s signal that it is leaving the cleaning station (Trivers 1971). The clients’ poses are specific to their species but often involve the client fish hovering vertically with their head pointing up or down (Losey 1971). Cleaners exhibit dancing movements prior to and during the inspection, which may also involve tactile stimulation of the client. The tactile stimulation may act as cleaners’ risk management strategy towards piscivorous clients (Grutter 2004). There are some fish that do not pose, and yet cleaners still attempt to swim towards and inspect them (personal observation) and there are also fish that do pose but are not cleaned (Arnal 2000). The motivation responsible for these behaviors is still unknown, but it appears that cleaners are using signals other than posing to choose some clients. The cleaners’ posing frequency may depend on how attractive a client is to a cleaner based on these other signals (Sheridan 2002).

Cleaning symbioses have been viewed as mutualistic selfless cooperations (Poulin and Grutter 1996) as an example of reciprocal altruism (Trivers 1971) and more recently as behavioral parasitism (Poulin and Grutter 1996). Removal of the ectoparasites is central to the first two views whereas the third view concentrates on client mucus ingestion by cleaners. The most recent theoretical background to understanding cleaning symbioses has been the biological market theory where goods are seen as being exchanged between the cleaner and the client (Bshary 2001; Bshary and Schäffer 2002; Grutter 2004). In the light of this theory, cleaning interactions provide opportunity for both cleaners and clients to cheat. Cleaners can cheat by ingesting mucus and taking bites out of clients whereas piscivorous clients can cheat by eating the cleaner. Clients can also punish cleaners for not cooperating by chasing them (Bshary and Grutter 2002a), which could be energetically costly for both parties. Cleaners, on the other hand, may apply pre-

conflict management strategies to avoid being eaten (Grutter 2004). Although piscivorous clients may eat their cleaners, they generally do not do so. This fact has been exploited by some other fish species that are mimics of cleaner fish (e.g. wrasse blenny, Hemiemblemaria simulus, mimic juvenile blue head wrasse, Thalassoma bifasciatum) to avoid being eaten by piscivores and exploit them as a food source (mucus) (Deloach and Humann 2003).

A question that remains unanswered is what determines clients’ level of attraction to the cleaner, in relative terms. One possibility is that cleaners recognize clients’ parasite load and choose clients that are more infected (Gorlick 1984), although some results have questioned role of parasite loads as the only proximate cause of cleaning behavior (Côté and Molloy 2003). Another possibility is that clients are chosen on basis of nutritional quality of their mucus (Gorlick 1980; Bshary and Grutter 2002a, 2003) but presumably mucus quality would have to be related to some signal that allows cleaners to recognize clients with high-quality mucus. However, there is no information on potential color cues that cleaners may use in recognition and choice between clients. This is important for several reasons. Firstly, cleaners have been shown to be able to recognize familiar clients (Tebbich et al. 2002). More specifically, they can distinguish clients that have access to only one cleaning station from those that have access to more than one (Bshary and Grutter 2002b; Bshary and Schäffer 2002) – this means they have some kind of client recognition system that might or might not include clients’ color. Secondly, cleaners seem to be able to recognize piscivorous clients as well as their satiation level (Bshary and Würth 2001; Grutter 2004). The ability to accurately recognize these clients may be visually based and color may play a large role in this recognition process. This is supported by studies that show that client fish use color cues to identify cleaners. Clients pose to cleaner models that possess basic coloration pattern of obligate cleaners – most often a lateral black stripe (Stummer et al. 2004; Arnal et al. 2005), but use of ultraviolet (UV) color cues may also be important (Losey 2003). Experiments that expose naïve clients (clients that have never encountered a cleaner before) to cleaners have shown that some clients have an innate posing response to cleaners 12

CLEANER FISH SPECIES SELECTIVITY

whereas others need to learn what the cleaners look like before they pose to them (Losey 1995).

Furthermore, Deloach and Humann (2003) report that client bluestriped grunt, Haemulon sciurus, have an innate response (opening mouth to be cleaned) to the orange and white horizontal stripes and black vertical bars of adult porkfish, Anisotremus virginicus that only clean as juveniles.

This response indicates that the color pattern of cleaners may be recognized by clients and in this case may even represent a response to a supernormal stimulus—an adult fish has larger color surfaces than the juvenile cleaner. So if client fish use colors to recognize and respond to cleaners and if cleaners are able to recognize and respond to individual clients then perhaps they also use color cues to do so. I tested this possibility by investigating client selectivity of cleaner fish G. oceanops in Honduras, Central America.

Department in Oxford. These models were painted using a non-toxic and water-resistant paint.

To test Hypothesis 1, three species of clients were used as models: clown wrasse, Halichoeres maculipinna; blue chromis, Chromis cyanea; and achilles tang, Acanthurus achilles. H. maculipinna has a black lateral stripe running from its nose to its tail. Two models were made for this species: one containing the lateral black stripe and one without the stripe. Both models were 15 cm long. C. cyanea is a blue fish with contrasting black outlines along its back, tail, and rear underside. To test the importance of contrasting outlines, two models were made: one with black outlines and one without black outlines. Both models were 15 cm long. A. achilles has a large yellow blotch at the base of its tail, which contrasts with the deep blue color of the rest of its body. Two models were made: one with the yellow blotch and one without the blotch. Both models were 20 cm long.

To test Hypothesis 2, three C. cyanea models were used: a model with the normal color pattern, a model with an enlarged eye surface (2x original radius) and a model with enlarged black outlines.

All three models were 15 cm long.

Aims To investigate how color patterns influence a cleaner’s (G. oceanops) choice of clients. To investigate cleaners’ behavior in situ and assess the extent of choice the cleaner has at the cleaning stations in the morning and afternoon.

Neon gobies, Gobiosoma oceanops

Hypotheses

G. oceanops were caught from coral reefs within the Cayos Cochinos Marine Reserve Area using a plastic net bought from a local supplier.

Fourteen fish were caught in total. They varied in size from 1 to 4.5 cm. G. oceanops are obligate cleaners throughout their lifespan, so the size differences were not considered to be important for this study. The sex of the fish was not assessed, as both sexes act as obligate cleaners and should show preferences for same clients (Patrick Denning, field supervisor, personal communication). The fish were held in separate holding tanks between experiments.

They were left for twenty-four hours in order to acclimate to their new environment before the experiments started. The fish were not fed during the experiments (six days total) to avoid interfering with their motivation for cleaning. Lenke (1982) found no effect of the cleaner Labroides dimidiatus satiation on propensity to clean dummy clients, but this might not apply to different species such as G. oceanops. Four fish died during the experiments.

1) The cleaner prefers clients with contrasting color features such as black lateral stripe or yellow round blotch.

2) The cleaner prefers clients with enlarged eyes or enlarged color contrasts (supernormal stimuli).

3) The visiting and posing frequencies of different client species differ in the morning and the afternoon, therefore limiting cleaners’ feeding opportunities.

Materials & Methods Wooden models Wooden models of two reported client species for G. oceanops (Colin 1975) and one Indo-Pacific client species were made in the Zoology 13

CLEANER FISH SPECIES SELECTIVITY

All surviving fish were returned to their natural habitat after the experiments.

Aquaria and other laboratory equipment

mechanical damage caused by boats on edges of the reef and some bleaching in the middle of the reef due to its shallow position. Twenty-eight cleaning stations were observed once, and they were situated within a depth range of 1.35-3.90 m.

Six aquaria were utilized: five of which were used as holding tanks and one as an experimental tank. All tanks were 44.4 cm long and 30 cm deep.

They were divided into three sections each of 14.8 cm in length using a black marker across the outside of all three tanks. The same markings were drawn on both holding and experimental tanks. The water was at an ambient temperature (27-29 °C) and the salinity was not measured – water came from the sea and due to lack of measuring equipment salinity was assumed to be constant. Water in the experimental tank was changed every morning before each experiment. Water in the holding tank was refreshed at night with an automatic inflow of seawater and an outflow of excess water.

Two stopwatches were used to measure time.

Plastic nets were used for handling the fish. A transparent plastic tube was used to confine the fish to the middle of the tank. Transparent fishing line and transparent tape were used to attach the models to the sides of the tank.

Aquaria experiments The models were introduced into opposite sides of the tank. Then a single G. oceanops was transferred from a storage tank into the experimental tank. The cleaner’s movement was restricted with a transparent plastic tube placed in the middle of the tank. When the fish resumed a calm swimming or resting position, (typically after two minutes), the tube was removed, and the amount of time spent in the three different parts of the tank was recorded during a five-minute period.

Each fish was tested twice for the same set of models, and the models were placed in the opposite ends of the tank on the second trial. By doing so, a fish was unable to prefer a certain side of the tank and avoided the problem of pseudoreplication (Grafen and Hails 2002). Each model set was tested on all available cleaner fish.

The models were suspended from the top of the tank using a transparent nylon line, which was taped to the backside of the wooden models. Both sides of the models were painted the same color.

Snorkeling equipment A short wetsuit, fins, mask and snorkel were used for snorkeling observations. Times were recorded using a wrist stopwatch, and observations written on a white board with a marker.

Snorkeling observations Twenty-eight cleaning stations were chosen randomly across the coral reef site. Water depth, visibility, coral species, and number of G. oceanops were recorded. When two G. oceanops were present on the station, the behavior of both was noted.

Observations were carried out during two different time periods: morning (7:20 -10:15) and afternoon (15:00 -17:15). Each station was observed for one 35-minute session. The total observation time was 14 hours: seven hours in the morning and seven hours in the afternoon. Observations were made following the method of Côté and Molloy (2003): I floated 2 - 2.5 m from the station, faced the incoming current to minimize net movement, and started observations after a five minute delay to allow the fish to become accustomed to my presence. All fish swimming within 1 m of the

Field site The research was carried out in Cayos Cochinos Marine Reserve Area in Honduras between the July 14th and August 24th, 2005. Research was divided into two phases: 1) experiments in the aquaria using wooden models of the clients 2) snorkeling observations on the coral reef.

The aquaria experiments were based in the wet lab at the Operation Wallacea field station on the Cayo Menor island. The snorkeling observations were made on the small coral reef just off the south coast of Cayo Menor island. The reef was 40 m away from the shore and was pristine except for 14

CLEANER FISH SPECIES SELECTIVITY

cleaning station were recorded as well as whether the client species posed or not, duration of pose, number and duration of inspections by the cleaner, and unusual behaviors by any of the fish present.

One 35-minute observation of a juvenile French angelfish, Pomacanthus paru, was also carried out following the same method.

single fish may have contributed to several data points.

Results Aquaria experiments Preliminary tests indicated that the side and model were not confounded due to experimental design error, so the average values from the two trials were used to test for model and side preference. Average times spent with a model compared to expected times (no preference observed) spent with a model are presented for each pair of models tested. The results for average time spent in the left side of the tank are given when there was a significant preference for a side.

Analysis of data There was an error in performing the tank experiments: all the fish were presented with the models in the same order (model A left in trial 1 and right in trial 2) in trials 1 and 2, rather than the order being randomized among fish. This would be problematic if the fish were less willing to examine a model in the second trial the model and side would be confounded. Paired t-tests were used to test whether the fish were equally likely to examine the models in both trials. If there were significant differences for both time spent in a side and with a model in the two trials, I could not average the results from the two trials due to the confounding effect of the side and the model. On the other hand, if either one of the t-tests for time spent with a model and in a side in the two trials gave a nonsignificant result, I carried on with the analyses as if the experiment was a priori randomized. The time spent with one model of the pair was used as a measure of preference. The time spent with one model of the pair was averaged across the two trials and compared to the expected time using paired ttests. The expected time spent with model A was calculated by averaging time spent with the models A and B in the two trials. This expected average time spent with model A was compared to the mean observed time spent with the model A by paired ttests or its non-parametric equivalent Wilcoxon Signed Rank test when the assumptions of the parametric test did not hold (Dytham 2003). The same procedure was repeated to test for preference for side of the tank (left or right).

The observational results were tabulated and presented in a graphical form. It was not possible to adhere to the assumptions of statistical tests so statistical analyses were not used for this part of the results. For example, I was unable to track individual fish throughout the observations, so a

Testing Hypothesis 1: Models tested: lateral stripe versus no lateral stripe Halichoeres maculipinna The time G. oceanops spent with the lateral stripe (normal) model was not significantly different from the time expected under the assumption of no preference between models (Paired t-test, t = 0.33, N = 14, P = 0.746, Figure 1). This indicates that there was no preference for the model with the stripe.

Figure 1. Mean time G. oceanops spent with the model with no horizontal stripe and expected (no preference) mean time with the same model (Paired t-test, t = 0.33, N = 14, P = 0.746). Bars are one standard error from the mean.

Models tested: yellow blotch versus no yellow blotch Acanthurus achilles 15

CLEANER FISH SPECIES SELECTIVITY

Models tested: normal black markings versus no black markings Chromis cyanea

The time G. oceanops spent with the yellow blotch (normal) model was not significantly different from the time expected under the assumption of no preference between models (Paired t-test, t = 0.32, N = 10, P = 0.753, Figure 2).

The time spent in the left part of the tank was significantly longer than the time expected under the assumption of no preference for side (Paired ttest, t = 2.42, N = 10, P = 0.039; data square root transformed, Figure 3). This indicates that there was no preference for the model with the yellow blotch but that there was preference for the left side.

The time G. oceanops spent with the black markings (normal) model was not significantly different from the time expected under the assumption of no preference between models (Paired t-test, t = -0.32, N = 13, P = 0.757; data log transformed, Figure 4). The time spent in the left part of the tank was significantly longer than under the assumption of no preference for side (Wilcoxon signed-ranks test, T = 75.0, N = 13, P = 0.043, Figure 5). This indicates that there was no preference for the normal black markings model but that there was preference for the left side.

Figure 2. Mean time G. oceanops spent with the yellow blotch model and expected mean time spent with the same model if there was no preference (Paired t-test, t = 0.32, N = 10, P = 0.753). Bars are one standard error from the mean.

Figure 4. Mean time G. oceanops spent with the normal black markings model and expected mean time with the same model if there was no preference (Paired t-test, t = -0.32, N = 13, P = 0.757). Bars are one standard error from the mean.

Figure 3. Mean time the G. oceanops spent in the left compartment of the tank and expected mean time spent in the left compartment if there was no preference (Paired t-test, t = 2.42, N = 10, P = 0.039). Bars are one standard error from the mean.

Figure 5. Mean time G. oceanops spent in the left compartment and the expected mean time in the left compartment (Wilcoxon signed-ranks test, t = 75.0, N = 13, P = 0.043). Bars are one standard error from the mean.

16

CLEANER FISH SPECIES SELECTIVITY

preference between models (Paired t-test: t = -0.76, N = 10, P = 0.467, Figure 7).

Models tested: wide (enhanced) black edges versus normal black edges Chromis cyanea

All of the fish species that posed in the afternoon (18 species) were inspected, whereas 2 of 14 species that posed in the morning were not inspected (Figure 8). Although a similar number of species passed by the cleaning station in both time periods (Table 1), more species posed in the afternoon. For individual fish, 78% of those that posed in the morning were inspected, whereas 77% of all fish that posed in the afternoon got inspected (Figure 9). Nearly the same percentage of individual fish that posed was inspected at the two time periods.

The time G. oceanops spent with the enhanced black edges model was not significantly different from the time expected under the assumption of no preference between models (Paired t-test, t = 0.16, N = 12, P = 0.876, Figure 6).

Figure 6. Mean time G. oceanops spent with the wide (enhanced) edges model and the expected mean time with the same model if there was no preference (Paired t-test, t = 0.16, N = 12, P = 0.876). Bars are one standard error from the mean.

Figure 8. Number of fish species that visited, posed and got inspected at the G. oceanops cleaning stations in the morning and the afternoon.

I observed cleaner fish switching from one client to another 5 times (Table 2). I also saw a territorial dusky damselfish, Stegastes adustus, chase away a potential client 13 times, involving 8 different client species (Table 3).

Figure 7. Mean time G. oceanops spent with the enlarged eye model and the expected (no preference) mean time with the same model (Paired t-test: t = -0.76, N = 10, P = 0.467). Bars are one standard error from the mean.

Discussion The results from the aquaria experiments show that the G. oceanops had no significant preference for any of the models. These results indicate that hypotheses one and two cannot be accepted for the set of color cues tested by this research. There are several reasons why this might be so: 1) G. oceanops do not use color cues when choosing clients.

Models tested: enlarged black eye (2x) versus normal sized black eye Chromis cyanea The time G. oceanops spent with the normal looking model was not significantly different from the time expected under the assumption of no 17

CLEANER FISH SPECIES SELECTIVITY

Fish family Pomacentridae Pomacentridae Pomacentridae Pomacentridae Pomacentridae Pomacentridae Acantharidae Acantharidae Chaetodontidae Chaetodontidae Chaetodontidae Scaridae Scaridae Scaridae Haemulidae Haemulidae Haemulidae Haemulidae Haemulidae Grammatidae Serranidae Serranidae Lutjanidae Lutjanidae Labridae Labridae Holocentridae Carangidae Sphyraenidae Myliobatidae Aulostonidae Ostraciidae Total

Fish species, morning Dusky damselfish Yellowtail damselfish Threespot damselfish Sergeant major Queen angelfish Ocean surgeonfish Blue tang Foureye butterflyfish Striped parrotfish Stoplight parrotfish Caesar grunt French grunt Smallmouth grunt White grunt Tomtate Fairy basslet Yellowtail hamlet Schoolmaster Yellowtail snapper Bluehead wrasse Pudding wife Bar jack Great barracuda Spotted eagle ray Trumpetfish Scrawled cowfish 26

Fish species, afternoon Dusky damselfish Yellowtail damselfish Threespot damselfish Sergeant major Queen angelfish French angelfish Ocean surgeonfish Blue tang Banded butterflyfish Foureye butterflyfish Spotfin butterflyfish Striped parrotfish Stoplight parrotfish Bluelip parrotfish Caesar grunt French grunt Smallmouth grunt White grunt Fairy basslet Yellowtail hamlet Coney Schoolmaster Yellowtail snapper Bluehead wrasse Squirrelfish Bar jack Trumpetfish 27

Latin species name Stegastes adustus Microspathodon chrysurus Stegastes planifrons Abudefduf saxatilis Holacanthus ciliaris Pomacanthus paru Acanthurus bahianus Acanthurus coeruleus Chaetodon striatus Chaetodon capistratus Chaetodon ocellatus Scarus iseri Sparisoma viride Cryptotomus roseus Haemulon carbonarium Haemulon flavolineatum Haemulon chrysargyreum Haemulon album Haemulon aurolineatum Gramma loreto Hypoplectrus chlorurus Cephalopholis fulva Lutjanus apodus Ocyurus chrysurus Thalassoma bifasciatum Halichoeres radiatus Holocentrus species Carangoides ruber Sphyraena barracuda Aetobatus narinari Aulostomus maculatus Acanthostracion quadricornis

Table 1. Fish species that visited cleaning stations in the two time periods (morning and afternoon).

2) G. oceanops use other cues (e.g. chemical, odor) in addition to visual cues when choosing clients.

3) G. oceanops do use visual cues when choosing clients but not the exact cues tested in these experiments.

4) G. oceanops use visual cues, but they did not recognize the models as real fish or potential clients.

5) G. oceanops were put in an unnatural situation and were too stressed to react in a meaningful way.

On the other hand, time spent in the left compartment was significantly higher than the expected time for three out of five analyzed experiments. It is unclear why this happened, as the

experimental design aimed at minimizing external influences and differences within the experimental tank. Two possible explanations are as follows: 1) The light intensity was higher on the right side of the tank due to a window that was situated 1.5 m away from the experimental tank.

2) The inner surface of the tank’s far left corner might have been lined with a thicker layer of transparent glue that was keeping the tank sides together, causing the G. oceanops to use this as a preferred substrate.

The nature of G. oceanops’ vision is still unknown and there have been no studies to present any evidence of color vision in the fish. Given the variety of colors that reef fish exhibit though, it 18

CLEANER FISH SPECIES SELECTIVITY

seems probable that G. oceanops would have color vision. Poulin and Grutter (1996) suggested that good vision is one of the characteristics fish need to have to evolve into obligate cleaners. The eyes of the G. oceanops appear qualitatively to be large in relation to the rest of its body, another indication of good vision. Color diversity plays a role in various fish speciesâ&#x20AC;&#x2122; interactions and could have evolved in response to more than one selective pressure (Marshall 2000). Considering the large number of daily interactions a cleaner fish has with different species that all have distinct color patterns, it seems probable that G. oceanops have evolved color vision to recognize clients. The results of this study suggest that G. oceanops do not use color cues to select clients and therefore may be indicative of the absence of color vision in this cleaner fish.

However, other factors may account for the same results and the ability of G. oceanops to perceive colors will have to be left for future studies.

If other cues are used by G. oceanops to recognize fish as clients, such as body movement or odor, then my experiments may not be the best way of examining the cleanersâ&#x20AC;&#x2122; client selectivity. The stiff wooden models did not move in the same way a real fish would move next to a cleaner. All of the models were presented to cleaners in a horizontal posture. But, both the slight movements by the client and its bodily orientation during the pose may play a large role in both initial recognition of a fish as a potential client and as a subsequent choice to inspect that fish as well. It has been shown that some behavior in some fish species is governed primarily by olfactory cues such as female association preferences in wild guppies (Shohet and Watt 2004). It may be the case that neon gobies choose their clients on the basis of olfaction alone or in combination with other factors. A further study with live clients presented in the same (olfaction allowed) or adjacent (olfaction prevented) tanks might be useful for elucidating this issue.

Times chased away

Chaetodon capistratus Chaetodon ocellatus Sparisoma viride Ocyurus chrysurus Acanthurus bahianus Scarus iseri Abudefduf saxatilis Microspathodon chrysurus

3

Activity preceding chase Swimming by

2

Swimming by

1 2 1

Swimming by Swimming by Being inspected

1 1 2

Swimming by Posing Being inspected or swimming by

Table 3. Identity of fish species that were chased away by S. adustus while approaching the station, posing or being inspected at the station.

Figure 9. Number of fish that visited (swam within 1 m of station), posed, and were inspected by G. oceanops in the morning and afternoon.

Switch from H. chrysargyreum A. bahianus (x2) H. flavolineatum C. striatus

Fish

G. oceanops might be using visual cues in their choice of clients, but they might not be using contrasting outlines of the fish that were the main area of interest in the present study. They may also be using color cues in combination with UV color cues. Painting the models so the colors are visible to humans and seem equivalent to the colors of the wild client fish might not have the same effect on G. oceanops: they may perceive the model colors differently due to a different vision spectrum. UV color vision may be present in many reef fish and

Switch to H. carbonarium H. carbonarium (x2) A. bahianus A. bahianus

Table 2. Instances of G. oceanops switching clients.

19

CLEANER FISH SPECIES SELECTIVITY

may play an important role in communication (Losey 2003). Unfortunately, UV vision was beyond the scope of my research. G. oceanops could be using color to distinguish ectoparasites from the background of the client body color.

The wooden models may not have been realistic enough for the G. oceanops to recognize as clients.

This may have been due to the lack of other cues normally associated with a client fish and may further indicate the absence of innate response to color stimuli and point towards more complex perception of the client fish by the cleaner (e.g.

Grutter et al. 2005). Maybe then, the fish may have been too stressed to act naturally in the experimental environment. In the wild, G. oceanops have established cleaning stations where they advertise on a certain substratum, such as brain corals, but in the experimental tanks the only substratum present was smooth glass. G. oceanops were introduced to a new environment shortly before their behavior was tested; perhaps this did not give them enough time to establish the behavior they would normally show at a cleaning station.

Future research with these and similar fish species may be improved if the cleaners are allowed to establish their cleaning stations within the tank before models are introduced.

G. oceanops’ preference for the left side of the tank is surprising – the experimental tank had symmetric left and right sides except for a small 1 cm high circular (radius 0.5 cm) protrusion on the left side that was inherent in the tank design and could not be removed. Fish did not spend much time at this protrusion and it is unlikely to be the cause of preference for the left side. The window to the left side of the tank was further away from the tank than the window on the right side but shutters were closed on both windows and the main light source was a translucent roof cover that let in a lot of light. The light that reached the tank from the window may have played a role in deterring gobies from the right side of the tank.

When fish spent a lot of time in the left compartment they seemed to mainly occupy the far bottom edge or the far corner of the tank and on subsequent examination of these places a layer of glue was found that was holding the tank together.

Although transparent and small, this layer may have been a preferable substrate to the smooth glass for neon gobies and it may have caused significant

preference for the left side. It is unclear why this was not the case in all of the experiments though, considering the same fish were tested in all instances.

Observations Côté and Molloy (2003) found that clients were most often observed at the stations in the afternoon when they had fewer ectoparasites, hence challenging the hypothesis that clients visit the cleaning stations due to irritation caused by ectoparasites. By contrast, my data show that the numbers of fish species visiting stations were similar (26 and 27 in the morning and the afternoon, respectively) and that the number of fish visiting the stations was higher in the morning (230 and 191 in the morning and the afternoon respectively). The proportion of fish species and individuals that posed in the afternoon was higher than in the morning: 54% of species in the morning and 66% in the afternoon, 28% of fish individuals in the morning (78% of which were inspected), and 52% in the afternoon (77% of which were inspected). These data agree with Côté and Molloy’s (2003) conclusion that the proximate cause of visiting cleaners might not be the number of parasites a client carries.

My observational data only notes twelve instances of clients queuing and five cases of cleaners switching in mid-cleaning to a client of a different species. This may be an indication that G. oceanops are rarely offered choice of clients on the coral reefs around Cayo Menor. An alternative explanation may be that the fish were afraid of mesome species may be underrepresented and others may be absent from my results altogether if they would normally visit cleaning stations in the absence of human observers. This may be due to similarity of a human snorkeler to predators or general cautious behavior by some client fish when encountering a novel situation. The study reef is visited frequently by student snorkelers working so it is unclear as to whether or not the fish are disturbed by the presence of a snorkeler.

Perhaps different species of cleaner fish have been exposed to different degrees of selective pressure to deal with choices between clients. In the fourteen hours of observation, G. oceanops only had the option to choose between clients of different 20

CLEANER FISH SPECIES SELECTIVITY

species 17 times. Given that 164 fish posed at the station in the same period of time, this suggests that in about 10% of all potential inspection instances do G. oceanops have a choice of clients. It is difficult to see how much G. oceanops can benefit from making a choice or how much it has to lose if it makes a wrong choice in this ten percent of its interactions.

The fact that out of 164 instances of client posing, interaction followed in only 127 instances (77.4%) suggests that a single interaction might not be of great importance to the cleaner. On the other hand, perhaps inspecting a client that does not carry enough ectoparasites or whose mucus is of low nutritional quality involves higher costs than benefits to G. oceanops and this is why they miss out on such a large percentage of posing clients.

Following the same line of argument, one may see that a client carrying a large number of ectoparasites and/or high quality mucus might offer disproportionately greater benefits than costs to the cleaner. This would mean that G. oceanops might be selected for making an appropriate choice in those 10% of cases when they have a choice. To make any substantial conclusions on costs and benefits associated with G. oceanops’ choice, further studies quantifying energetic and other costs of inspection and benefits associated with inspecting different species of clients would have to be completed. If choice of client was one of the major selective pressures operating on G. oceanops, then one would expect to see effective fish species recognition abilities in G. oceanops.

Grutter (2001) found that experimentally manipulated clients carrying more parasites spent more time next to a cleaner than control clients.

This is evidence for parasitic load being a proximate cause of clients seeking cleaners. My results seem to contradict this conclusion given that G. oceanops ignore such a large proportion of clients that pose. If the clients were indeed posing because they had high levels of parasitic infestation, then G. oceanops would be expected to inspect them as they could be carrying lots of food for cleaners, which they did not do in 22.6% of all observed cases.

Higher frequencies of posing, rather than being inspected, for most client species might be due to their seeking tactile stimulation instead of removal of parasites by the cleaners. The aforementioned theory also supports an observation of terminal

phase striped parrotfish posing inside sea plumes for 6 seconds in the absence of any cleaners (pseudoposing) (Deloach and Humann 2003).

Bshary (2001) found that cleaners switched to larger clients more often than to smaller clients within each category of clients, size ceased to influence the cleaners’ choice. Bshary (2001) also demonstrated that the overall significance in clients’ size was due to cleaners’ preference for harmless floaters (fish with access to more than one cleaning station) over harmless residents (fish with access to a single cleaning station only). He accounted this to the fact that floaters tend to be longer than residents (40 out of 51 fish). Interestingly, cleaners also switched more often from a larger resident to a smaller floater than the other way around. These observations were corroborated by resident clients queueing significantly more often than floaters when both were present at the station at the same time (Bshary 2001). Even a larger resident has to queue significantly more often while a smaller floater is being inspected than vise versa (Bshary 2001).

Bshary’s (2001) data support the idea that the cleaners’ selectivity of clients is based on their recognition of clients as being either floaters or residents, rather than simply choosing the bigger client. While size has been found to be correlated to parasite levels (Sikkel et al. 2000), it may not be as important in client species selectivity as other factors (Bshary 2001), though some evidence suggests that species with higher parasite levels do indeed visit cleaning stations more often than those with lower parasite levels (Côté and Morand 2001).

The latter research was done on cleaning stations with cleaner fish from the genus Evelynae in Barbados so it may be more indicative of what is happening with G. oceanops in Honduras than the research with Labroides wrasses in the Indo-Pacific.

The five instances of client switching that I observed included G. oceanops switching from Haemulon chrysargyreum and A. bahianus to Haemulon carbonarium, and from Haemulon flavolineatum and Chaetodon striatus to A. bahianus. In all of these instances the preferred client was larger although other factors may play a more important role. In all cases the cleaner had already associated with the client for 15-39 s so it may have been close to ending the inspection anyway. In the case of H. flavolineatum being 21

CLEANER FISH SPECIES SELECTIVITY

switched for Acanthurus bahianus, the latter had posed for 5 s prior to the switch. The small number of switching between clients and also the influence of other factors that have not been controlled (e.g. whether the fish is a floater or resident, the parasite load) prevents me from making any strong conclusions about which client species are preferred

by G. oceanops in the wild.

Most observed G. oceanops cleaning stations were shared with resident territorial S. adustus.

These fish acted violently towards visiting fish when they were present at the station. They chased away twelve different fish from eight different species that were either present at the station (A. bahianus and Microspathodon chrysurus being inspected by a cleaner fish and an Abudefduf saxatilis posing) or arriving at the station. This may have a negative influence on G. oceanops’ feeding opportunities and the extent to which it does so may be a topic of a future research. Arnal and Côté (1998) found that significantly fewer client species and individuals visited cleaner fish (Elacatinus spp.) stations that were within S. adustus territories than those that were not. On the other hand, they also found that S. adustus encountered increased costs due to lower foraging rate, more time spent chasing intruders and increased risk of egg predation on territories within the cleaning stations (Arnal & Côté, 1998). This poses questions of the potential benefit to these two fish species of sharing a territory. Further research may elucidate whether G. oceanops and S. adustus share territories due to necessity in spite of the costs, or whether there are actual benefits that compensate the costs.

Two out of the eight species observed as being chased away by S. adustus were never observed being inspected by G. oceanops: banded butterflyfish, C. striatus, and foureye butterflyfish, Chaetodon capistratus. An innovative topic for future research might include examining parasite levels and parasite species composition of these clients to try and establish whether it is the absence of gnathiid parasites on their bodies or the aggression of S. adustus that discourages them from visiting G. oceanops stations. It may be possible for clients to visit different cleaner species to have different types of parasites removed. I have observed H. flavolineatum clients on several occasions at the cleaning stations posing by hovering horizontally in front of G. oceanops. I

have also observed a H. flavolineatum posing vertically in a head-down position to a juvenile french angelfish cleaner. Perhaps visits to different cleaners include different posing behavior by the clients; this might indicate that the species-specific cleaning interactions have been evolving separately due to similar selection pressures: different types of parasites. Parasites may play an important role in structuring interactions involved in the cleaning symbioses because they are a living and evolving third party in these interactions (Grutter 2002).

Jones et al. (2004) suggested a novel way of transmission of parasites (Digenea) through cleaning behavior: a labrid cleaner may become infected by the parasite having ingested it off the client. My research did not examine the effect that parasitic presence might have on cleaner choice.

Nevertheless, I have not come across research describing color changes that may result from high levels of parasites on the client fish but it seems reasonable to assume that the existence of parasites may indeed have an effect on color. Color changes have been reported for some clients when visiting cleaning stations but have never been decisively researched (Trivers 1971; Deloach and Humann 2003).

Summary This project examined species selectivity of clients by the cleaner fish Gobiosoma oceanops in the Cayos Cohinos Marine Reserve Area off of the north coast of Honduras. The study incorporated laboratory-based choice experiments and in situ observations. The experiments presented the cleaners with a choice of two wooden models that were painted differently in an attempt to elucidate potential color cues that the cleaners use when choosing a client. The snorkeling observations included 28 different cleaning stations at two time periods (morning and afternoon). Number of clients, client species, and amount of time each client spent posing and/or being inspected were recorded.

Unusual behaviors were also examined in an attempt to look into client availability and the choice cleaners have at different times of day.

The choice experiments yielded no positive preferences for any of the models. This finding may be due to more complex perception mechanisms of G. oceanops than simple recognition of color 22

CLEANER FISH SPECIES SELECTIVITY

Hammerstein P.), pp. 146-172 Cambridge: Cambridge University Press.

patterns visible to humans or due to stress related to the unnatural conditions the fish encountered in the aquaria. The snorkeling observations found similar numbers of fish species visiting stations in both time periods, as well as more individual fish visiting in the morning. The posing frequency was higher in the afternoon: the number of individuals that posed was higher, and more fish were inspected in the afternoon. This discovery seems to contradict the idea that fish visit stations when they have a higher level of parasites, which occurs in the early morning due to gnathiid parasites’ activity patterns. In about 10% of interactions with clients in the wild, G. oceanops had an opportunity to make a choice between at least two clients – a choice with potential fitness consequences.

Bshary, R. 2003. The cleaner wrasse, Labroides dimidiatus, is a key organism for reef fish diversity at Ras Mohammed National Park, Egypt. Journal of Animal Ecology 72, 169-176.

Bshary, R. and Grutter, A. S. 2002a. Asymmetric cheating opportunities and partner control in a cleaner fish mutualism.

Animal Behaviour 63: 547-555.

Bshary, R. and Grutter, A. S. 2002b. Experimental evidence that partner choice is a driving force in the payoff distribution among cooperators or mutualists: the cleaner fish case.

Ecology Letters 5(1): 130-136.

Bshary, R. and Grutter, A. S. 2003. Cleaner wrasse prefer client mucus: support for partner control mechanisms in cleaning interactions. Proceedings of the Royal Society of London B-Biological Sciences (Suppl.). 270: S242-S244.

Acknowledgements

Bshary, R. and Schaffer, D. 2002. Choosy reef fish select cleaner fish that provide high-quality service. Animal Behaviour 63: 557-564.

I would like to thank all the foundations that helped me fund the expedition: Alan-Palgrave Brown Foundation, Barcapel Foundation, City of Rijeka and Keble Association. I would also like to thank Operation Wallacea staff for making this and similar research projects possible, and Patrick Denning who supervised my project in the field and caught all the fish. I would especially like to thank Dr. Theresa Burt de Perera for patiently supervising my project at the University. I am grateful to Christopher Taylor and James Fox for snorkeling with me, and to Dr. Christine Booth for first alerting me to the existence of undergraduate research journals.

Bshary, R. and Würth, M. 2001. Cleaner fish, Labroides dimidiatus, manipulate client reef fish by providing tactile stimulation. Proceedings of the Royal Society of London BBiological Sciences 268: 1495-1501.

Colin, P. 1975. The Neon Gobies; the comparative biology of the genus Gobiosoma, subgenus Elacatinus (Pisces, Gobiidae) in the Tropical Western Atlantic Ocean. T.F.H. Publications, New York.

Côté, I. M. and Molloy, P. P. 2003. Temporal variation in cleanerfish and client behaviour: does it reflect ectoparasite availability? Ethology 109: 487-499.

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25