A Tale of Two Kelp Forests: Quantitative Comparison of Species Composition Between

Madeleine Cortés BIOE 161 October 20, 2011

A Tale of Two Kelp Forests: Quantitative Comparison of Species Composition between Point Lobos State Natural Reserve and Hopkins State Marine Reserve

ABSTRACT One of the most useful methods for uncovering ecological patterns is determining species compositions between two unique study sites. We performed an observational study to compare the subtidal species composition of kelp forests in two no-take marine reserves along the Central California coast, which possess unique physical conditions. We found there was a significant difference in species composition between sites for alga and invertebrate taxa, but not for fish, which instead exhibited a significant difference between days as well as an interaction effect of both site and day combined. We concluded that the effect of site on algae and invertebrates was caused by physical conditions at the sites as well as the results of those conditions on individual species due to their unique requirements. We further concluded that the affect of day and interaction on fishes might be an artifact of insufficient data and require further investigation including additional transects on multiple days. INTRODUCTION Processes that affect kelp forest ecosystems occur at varying spatial scales (Edwards 2004). It is an established practice for ecologists to study multiple sites over relevant spatial scales in order to answer important questions about variation in ecosystems (Duggins et al. 1989, Ling et al. 2009). Ecological variability between kelp forests can be caused by a combination of physical conditions, such as reef structure, substrate composition, topography, exposure to ocean swell, and coastal upwelling (Graham et al. 1997, Carr et al. 2010) as well as species interactions (Sala and Graham 2002, Davenport and Anderson 2007, Ling et al. 2009). Determining the differences in species composition between discrete kelp forests with differing physical conditions and may provide integral information on the distinct species assemblages that result from those conditions. We were interested in determining if a difference in species composition exists between two state marine protected areas along the Central California coast: Hopkins State Marine Reserve (Hopkins) and Point Lobos State Natural Reserve (Lobos). We were further concerned whether variability resulting from sampling day might impact our results. More specifically, we asked the following three questions. Firstly, is there a difference in species composition between Hopkins and Lobos (site effect), and does it vary by taxa? Secondly, is there a difference in species composition between sampling days (day effect), and does it vary by taxa? Finally, do both site and sampling day (interaction effect) affect species composition, and does this combined effect vary by taxa? We addressed these questions by performing an observational study in two protected kelp forests at Hopkins and Lobos; both kelp forests are part of “no-take” marine reserves, but have different substrate composition and exposure to ocean swell. We collected quantitative data on

- 1 - Madeleine Cortés BIOE 161 October 20, 2011 subtidal species densities at each site, using SCUBA during October 2011, while the kelp canopy was still intact preceding any heavy winter storms. We found a strong site effect in algae and invertebrates, as well as day and interaction effects in fishes. These results indicate the presence of site effect, which may have been confounded in fishes by a lack of sufficient data. The overall implications of this study are that differences in physical conditions of a site may determine the composition of species at the site. METHODS Approach to Study We performed an observational study to characterize the difference in species composition between two no-take kelp forests. Using SCUBA, we collected density data on subtidal kelp forest species at each site to describe the differences Figure 1: Map showing Hopkins (north) and Point between the two kelp forests. Lobos (south). Study System We collected data at Hopkins State Marine Reserve in Monterey, CA (36°36’N, 121°54’W), and Point Lobos State Natural Reserve in Carmel, CA (36°31’N, 121°56’W) (Figure 1). The kelp forest at Hopkins is located inside Monterey Bay, and is highly protected from ocean swell (Graham et al. 1997) by the adjacent Point Piños. The substrate at Hopkins consists of large granite benches, and high-relief outcroppings surrounded by shell-rubble and patches of sand; the depths sampled in our study support a macro-algal canopy of M. pyrifera (Watanabe 1984). The kelp forest at Lobos is located outside of Monterey Bay, and is less protected from ocean swell by Point Lobos. The substrate at Lobos consists of high- and low-relief bedrock as well as boulders, and supports a macro-algal canopy of M. pyrifera (Carr et al. 2010) in addition to an uncharacteristically high cover of erect, geniculate coralline algae (Lovejoy 1997). We targeted 29 species representing each of three taxa: algae, fishes, and invertebrates (Table 1). The algae taxon consists of sessile primary producers, which compete for hard substrate, light, and nutrients (Kaiser 2005). The fish taxon is comprised of motile primary, secondary, and tertiary consumers. The invertebrate taxon includes sessile, sedentary, and motile species, which range from primary consumers to scavengers. Survey methods We each surveyed two 30-meter transects in pairs, within a depth zone of 33-40 feet, at both Hopkins and Lobos, resulting in a total of 32 transects. Each pair of divers surveyed

- 2 - Madeleine Cortés BIOE 161 October 20, 2011 different transects perpendicular to and along a main transect line, so that no transect area was surveyed twice during a sampling day. We individually recorded abundance data for all 29 target species (Table 1), in 10- meter increments, within our buddy pairs with one diver surveying each side of the 30-meter transect tape. We performed two transects on each of two days: October 11, 2011 (Day #1) and October 13, 2011 (Day #2), with each buddy pair sampling a different site on each day. How statistically powerful were our data? We charted the power index for the number of transects we performed as well as for each of the species we surveyed by taxa. If our data were statistically strong, we would expect to have power indices of greater than two and for the indices to asymptote at or before the number of transects we performed. On the level of individual species, we would simply expect the power indices to be greater than two. Algae – Specific methods Using the general methods described above to perform a benthic transect (30m long by 1m wide by 1m tall), we collected abundance data on seven species of algae Table 1: List of target species separated (Table 1). We additionally counted M. pyrifera stipes by taxa occurring one meter above the bottom on each 10-meter section of the transects to obtain a measurement of biomass. We used biomass data to make a more accurate comparison of M. pyrifera densities between Hopkins and Lobos as well as between sampling days, since the biomass of individual plants can vary widely. Fishes – Specific methods We each collected abundance data for the nine species of target fish (Table 1), while simultaneously running out the transect tape for the fish transect (30m long by 1m wide by 2m tall). We chose to run the tape while collecting data to minimize disturbance to the target species, since their motility may have caused their unnatural absence from our survey area. Invertebrates – Specific methods We collected abundance data on 13 species of invertebrates (Table 1) along benthic transects (30m long by 1m wide). Is there a difference in species composition between Hopkins and Lobos (site effect), and does it vary by taxa? To test this hypothesis, we used the data to produce a Multidimensional Scaling (MDS) plot for each taxa to map the similarity between each transect. We also charted the percent variance explained for each taxon due to site effect. Additionally, we analyzed the data for each taxon using a Permutation ANOVA (Permanova). If we found that there was an obvious

- 3 - Madeleine Cortés BIOE 161 October 20, 2011 separation on the MDS plot between transects performed at Hopkins and Lobos, found a considerable percent variance explained due to site effect, and found a significant (P<0.05) site effect for a taxon, we could reject the null hypothesis for that taxon. Finally, we used the data collected on our transects described above to chart the mean species abundances at each site. If we found a large difference in mean species abundance between sites for a species, we could determine which species contributed the most to site effect. Is there a difference in species composition between sampling days (day effect), and does it vary by taxa? To test our second hypothesis, we used MDS plots for all taxa to map the similarity between sampling days. We also charted the percent variance explained for each taxon due to day effect. Additionally, we analyzed the data for each taxon using a Permanova. If we found an obvious separation on the MDS plot between transects performed on Day #1 and Day #2, found a considerable percent variance explained due to day effect, and found a significant (P<0.05) day effect for a taxon, we could reject the null hypothesis for that taxon. Finally, we used the data collected during our transects described above to chart the mean species abundances for each day. If we found a large difference in mean species abundances between the two days for a species, we could determine which species contributed the most to day effect. Do both site and sampling day (interaction effect) affect species composition, and does this combined effect vary by taxa? To test our final hypothesis, we used MDS plots for all taxa to map the distance relating transects both between sites and days. We also analyzed the data for each taxon using a Permanova. If we found an obvious separation on the MDS plot both between transects performed at Hopkins and Lobos as well as those Figure 2: Power indices based on number of performed on Day #1 and Day #2, and found a transects performed for each taxa significant (P<0.05) interaction effect for a taxon, we could reject the null hypothesis for that taxon. RESULTS How statistically powerful were our data? The number of transects we performed collected more than sufficient data on algae, as the power index for algae asymptoted at a power index of three and approximately 23 transects, while we performed 32 transects (Figure 2). The power indices for number of fish and invertebrate transects, however, did not asymptote, but were continuing to climb at 32 transects (Figure 2). Although the lack of an asymptote on the graph indicates the possibility that more data is needed, the power indices for number of transects for both taxa were above 2.5. Power indices on the data collected for each species show that all but four out of the 29 target species have indices greater than two (Figure 3). The four species with power indices lower than two are the alga Dictyoneuropsis reticulata, the fish Sebastes chrysomelas, and the invertebrates Loxorhynchus grandis and Strongylocentrotus franciscanus (Figure 3).

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Figure 3: Power indices of data on target species by taxa: algae (A), fishes (F), and invertebrates (I)

Is there a difference in species composition between Hopkins and Lobos (site effect), and does it vary by taxa? Algae We found a strong site effect on the species composition of algal assemblage (Table 2, Permanova: site effect [Si], Table 2: Permanova results for site effect (Si), day effect P=0.001). Site effect was apparent in the (Sa), and interaction effect (SixSa) for all three taxa distinct separation between transects performed at Hopkins and Lobos on an MDS plot of algae transects including both sampling days (Figure 4). The percent of variance explained due to the site effect was approximately 100%, strongly indicating the presence of site effect (Figure 5). Based upon a comparison of the mean species abundances between sites (Figure 6), it appears that Pterygophora californica, Cystoceira osmundacea, Chondracanthus corymbifera, and Dictyoneuropsis reticulata contributed the greatest algal variation between the two sites, with P. californica contributing the highest at 12.34% (Table 3).

Figure 4: MDS plot of algae transects performed at Hopkins Figure 5: Percent variance (green) and Point Lobos (blue) on Day #1 (1) and Day #2 (2) explained showing a strong site effect on algae

Figure 7: MDS plot of fish transects performed at Hopkins (green) and Point Lobos (blue) on Day #1 (1) and Day #2 (2) Figure 6: Mean species abundance of algae at Hopkins and Point Lobos on Day #1 and Day #2

Fishes We did not find a significant site effect in the species composition of fishes (Table 2, Permanova: site effect [Si], P=0.319). Site effect was not readily apparent in the mixed MDS plot of fish transects at both sites (Figure 7). The percent of variance explained due to site effect was just under 25%, indicating the weakness of site effect on fishes (Figure 8). Invertebrates

We found a strong site effect in the species Figure 8: Percent variance explained showing composition of invertebrate assemblages (Table 2, weakness of site effect on fishes Permanova: site effect [Si], P=0.001). Site effect was readily apparent in the distinct separation between transects performed at Hopkins and Lobos on an MDS plot of invertebrate transects including both sampling days (Figure 9). The percent of variance explained due to site effect was approximately 100%, strongly indicating the presence of site effect (Figure 10). Based upon a comparison of the mean species abundances between sites (Figure 11), Balanophyllia elegans, Patiria miniata, and Pachycerianthus fimbriatus greatly contributed to site effect, with B. elegans contributing the most at 31.54% (Table 3). Is there a difference in species composition between sampling days (day effect), and does it vary by taxa? Algae We did not find a significant day effect in the species composition of algal assemblages (Table 2, Permanova: day effect [Sa], P=0.724). Day effect was not apparent in the mixed MDS plot of algae transects on both days (Figure 4). Additionally, the percent of variance explained

- 6 - Madeleine Cortés BIOE 161 October 20, 2011 due to day effect was approximately 0%, indicating the absence of day effect altogether on algae (Figure 5). Fishes We did, however, find a significant day effect in the species composition of fish assemblages (Table 2, Permanova: day effect [Sa], Table 3: Percent contribution of all species to dissimilarity between P=0.043). While the day effect was sites based upon mean abundance not obvious in the MDS plot of fish transects (Figure 7), it showed its strength in the percent of variance explained, which was just over 75% (Figure 8). Sebastes atrovirons and Embiotoca lateralis contributed most to day effect: 32.68% and 18.16%

Figure 10: Percent variance explained showing a strong site effect on invertebrates Figure 9: MDS plot of invertebrate transects performed at Hopkins (green) and Point Lobos (blue) on Day #1 (1) and Day #2 (2) respectively (Table 4).

Invertebrates We did not find a significant day effect in the species composition of invertebrates (Table 2, Permanova: day effect [Sa], P=0.505). Day effect was also not apparent in the mixed MDS plot of invertebrate transects on both days (Figure 9). Additionally, the percent of variance explained due to day effect was approximately 0%, indicating the total absence of day effect on invertebrates (Figure 10). Do both site and sampling day (interaction effect) affect species composition, and does this combined effect vary by taxa? Algae We did not find an interaction effect in algal species composition (Table 2, Permanova: interaction effect [SixSa], P=0.926).

Table 4: Percent contribution of species of fishes to dissimilarity between days based upon mean abundance

Figure 11: Mean species abundance of invertebrates at Hopkins and Point Lobos on Day #1 and Day #2

Fishes We did, however, find a significant interaction effect in fish species composition (Table 2, Permanova: interaction effect [SixSa], P=0.015), due to the weak site effect and strong day effect observed (Figure 8). Invertebrates The interaction effect was not significant for invertebrate species composition (Table 2, Permanova: interaction effect [SixSa], P=0.569).

Great results section. DISCUSSION There were two major results from this study. Firstly, both the alga and invertebrate taxa displayed site effect, while fish did not. Secondly, the fish taxon displayed day and interaction effects, while algae and invertebrates did not. What does this mean? If there is an interaction, the main effect is largely uninterpretable because it means that abundances varied among sites depending on the day. The presence of site effect in algae and invertebrates was not surprising, due to the differing physical conditions between Hopkins and Lobos. While both sites have considerable hard substrate to maintain thriving kelp forests, Hopkins has more patchiness than Lobos with shell-rubble and sandy substrate surrounding rocky outcroppings. Additionally, Hopkins is more protected from ocean swell, while Lobos is more exposed. These differences may be responsible for the site effect described by the study. Characteristics among the species targeted in this study may ideally suit them to either one or the other of these two kelp forests. The main contributors to site effect in mean

- 8 - Madeleine Cortés BIOE 161 October 20, 2011 abundance in this study were: Balanophyllia elegans, Pterygophora californica, Cystoceira osmundacea, Chondracanthus corymbifera, Dictyoneuropsis reticulata, and Pachycerianthus fimbriatus. B. elegans was found in significantly higher abundance at Hopkins than at Lobos. Given that B. elegans settles less than 0.5 meters from its parent (Gerrodette 1981), the dense cover of erect, geniculate coralline algae may discourage the spread of B. elegans at Lobos. The exposure to ocean swells at Lobos, however, makes it an ideal site for the higher abundance of sub-canopy forming P. californica observed in our study. This light-usurping sub-canopy of P. californica at Lobos in turn explains the relative lack of abundance of surface canopy forming C. osmundacea (MBARI 2009b) and turf algae D. reticulata, but not necessarily that of the turf algae C. corymbifera, which can tolerate very little light (MBARI 2009a). The site effect in C. corymbifera may have been an artifact of species identification by our divers. Finally, the lack of P. fimbriatus at Lobos could be explained by the site’s lack of sand and soft substrate, which P. fimbriatus requires to burrow its body a meter or more beneath the sediment (Cowles 2010). The weakness of site effect and presence of day/interaction effect in fishes was a surprising result since the expectation might be to simply see the presence or absence of a site effect across all three taxa. There are several factors that may be responsible for these results: the number of transects performed, the number of days transects were performed, and the differing characteristics between species of each taxa. Too vague….what characteristics of fishes might contribute to higher variation? The power index for the number of transects performed for each taxa showed that algae was the only taxa for which enough transects were performed (Figure 2). Further transects should be performed to determine if our data for the fish and invertebrate taxa were accurately depicting the presence of site, day, and interaction effects. It is possible that with more transects, the data will cease to indicate the presence of day effect in fishes. The presence of the day effect in our results for the fish taxon may be explained by the limited number of days we sampled in our study. On the first day, the ocean swell was notably smaller at both sites than it was on the second day. This may have contributed to the presence of the day effect in the fish taxon. OK- good Due to the motility of fishes, some may have hidden in crevices for shelter on the second day and not been equally represented in the data collected when compared to the first day. Sampling on additional days would clarify this point. The lack of day effect in algae and invertebrates is reasonably expected, due to their lack of immediate motility. In conclusion, the site effect seen in the algae and invertebrate taxa during this study seems readily explicable by differences in physical conditions between the two sites. The day and interaction effect seen in the fishes, however, seems to indicate the need for continued data collection on more days to obtain a more accurate understanding as to the presence of the two effects. Big picture, why do we care about Hopkins and lobos? Sampling procedures? Leave us with something inspirational!

Bibliography

Carr, M., D. Malone, S. Lonhart, and h. Selbie. 2010. Monitoring MPAs by SCUBA in waters off Central California. Pages 1-13 in P. f. I. S. o. C. O. (PISCO), editor. PISCO. Cowles, D. 2010. Pachycerianthis fimbriatus. Walla Walla Univeristy. Davenport, A. C. and T. W. Anderson. 2007. Positive indirect effects of reef fishes on kelp performance: The importance of mesograzers. Ecology 88:1548-1561. Duggins, D. O., C. A. Simenstad, and J. A. Estes. 1989. MAGNIFICATION OF SECONDARY PRODUCTION BY KELP DETRITUS IN COASTAL MARINE ECOSYSTEMS. Science 245:170-173. Edwards, M. S. 2004. Estimating scale-dependency in disturbance impacts: El Ninos and giant kelp forests in the northeast Pacific. Oecologia 138:436-447. Gerrodette, T. 1981. DISPERSAL OF THE SOLITARY CORAL BALANOPHYLLIA- ELEGANS BY DEMERSAL PLANULAR LARVAE. Ecology 62:611-619. Graham, M. H., C. Harrold, S. Lisin, K. Light, J. M. Watanabe, and M. S. Foster. 1997. Population dynamics of giant kelp Macrocystis pyrifera along a wave exposure gradient. Marine Ecology-Progress Series 148:269-279. Kaiser, M. J. 2005. Marine ecology : processes, systems, and impacts. Oxford University Press, Oxford ; New York. Ling, S. D., C. R. Johnson, S. D. Frusher, and K. R. Ridgway. 2009. Overfishing reduces resilience of kelp beds to climate-driven catastrophic phase shift. Proceedings of the National Academy of Sciences of the United States of America 106:22341-22345. Lovejoy, P. 1997. Cannery Point.in P. L. Foundation, editor. MBARI. 2009a. Marine Botany: Chondracanthus corymbifera.in MBARI, editor. Monterey Bay Aquarium Research Institute. MBARI. 2009b. Marine Botany: Cystoseira osmundacea.in MBARI, editor. Monterey Bay Aquarium Research Institute. Sala, E. and M. H. Graham. 2002. Community-wide distribution of predator-prey interaction strength in kelp forests. Proceedings of the National Academy of Sciences of the United States of America 99:3678-3683. Watanabe, J. M. 1984. THE INFLUENCE OF RECRUITMENT, COMPETITION, AND BENTHIC PREDATION ON SPATIAL DISTRIBUTIONS OF 3 SPECIES OF KELP FOREST GASTROPODS (TROCHIDAE, TEGULA). Ecology 65:920-936.

Results (25) __4__/4 Figure legends Accurate __4__/4 Figure Legends well composed (complete and concise) __5__/5 Results organized according to questions __4__/4 Graphs presented in a logical order, case made for the order

- 10 - Madeleine Cortés BIOE 161 October 20, 2011 __4__/4 Grammar, sentence structure and spelling __4__/4 Clarity and conciseness of writing

Discussion (25) ____/11 How well did they answer the questions they present in the Intro? 1) __2__/2 Discuss the results from the specific to the general. 2) __3__/3 Answered question about how sites differ in community composition? 3) __3__/3 Assessed sources of variation and made a strong case for whether we are able to detect differences among sites. 4) __3__/3 Presented sound logic as to why certain taxa or species were sampled well.

__2__/2 Grammar and Spelling __3__/3 General Thoughtfulness __2__/2 Clarity and conciseness ___5_/5 Organization of discussion ___1_/2 Context and Bigger Picture

General Notes: Excellent.

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