2012 11(2):G29–G35 Conservation and Management Implications Regarding Local Avian Diversity Following the Deepwater Horizon Disaster Orin J. Robinson,1,2,* J. Curtis Burkhalter2, and John J. Dindo1 Abstract - Coastal Alabama islands provide vital nesting and foraging habitat to many wading birds, shorebirds, gulls, pelicans, and waterfowl. We compared three regions of coastal Alabama for overlap of species present and species nesting using Monte Carlo simulations. The observed numbers of species present and species nesting were both less than predicted by the simulations, suggesting that local processes drive diversity on the coastline of Alabama. These findings also suggest that, in the wake of the recent oil disaster in the Gulf of Mexico, management along the coast of Alabama should consider species assemblages rather than surrogates and apply a scale of management decisions so as to manage each local community individually rather than manage the region as a whole. Introduction Nearly three quarters of the 2,500,000 ha of coastal marshes in the US are located along the shores of the Southeast and Gulf Coasts (Mitchell et al. 2006). Along with this large swath of habitat comes a great deal of natural resource management by various governmental and non-governmental agencies. Management decisions aimed at conserving biodiversity are often born out of necessity, and as such, are often based on a subset of species that we feel represents the needs of a multitude of species (Bestelmeyer et al. 2003). Action based upon a limited subset (e.g., a single functional group) may be appealing, but in actuality may or may not address the complexity of a multi-species pool. Different species view environments in a multitude of ways and thus react to environmental heterogeneity and landscapes in different ways (Wiens 2000), and translating the expanding boundaries of conservation into pragmatic and appropriate action is a continual struggle for any managing entity (Poiani et al. 2000). The idea of using a single species or a subset of species, as an indicator of large-scale dynamics has been used for a long time in conservation biology. Its appeal lies in gaining effective and efficient means to evaluate status and trends of multiple species from monitoring a few surrogate species (Cushman et al. 2010). The use of surrogate species has been proposed by some as an effective way for monitoring (Wiens et al. 2008), but the risk of bias is great if the chosen indicator does not accurately represent the dynamics of the other species (Cushman et al. 2010). Populations of differing species typically vary and fluctuate in 1Dauphin Island Sea Laboratory, 101 Bienville Boulevard Dauphin Island, AL 36528. 2Current address - Department of Ecology, Evolution, and Natural Resources, Rutgers University, 14 College Farm Road, New Brunswick, NJ 08901-8551. *Corresponding author - robinoj@eden.rutgers.edu. SOUTHEASTERN NATURALIST Gulf of Mexico Natural History and Oil Spill Impacts Special Series G30 Southeastern Naturalist Vol. 11, No. 2 complicated ways, and sites managed for a specific species or subset may fail to conserve other critical components of the ecosystem, including other species or processes that may affect the species of concern (Poiani et al. 2000). The idea that habitat heterogeneity is important for maintaining biodiversity has been shown across a wide variety of different habitat types including islands, forests, intertidal zones, deep sea, and wetlands just to name a few (Buhl-Mortensen et al. 2011, Horwitz et al. 2009, Matias et al. 2011, Ricklefs and Lovette 1999, Williams et al. 2002). However, scale is often overlooked when heterogeneity is considered; local scales are presumed to have homogeneous habitats while larger scales have many habitats (Hewitt et al. 2005). It is important to understand the scale at which processes operate to influence species co-occurrence and diversity (Pearman 2002). Blackburn and Gaston (2001) suggest that if local assemblages are shown to be no different than a random draw from the regional species pool, regional factors will structure the species assemblages. While the regional-scale processes shape the pool of species from which local communities are assembled, local processes ameliorate the larger-scale patterns to create local differences (Blake and Loiselle 2009). Failing to consider these local differences while managing for regional diversity can cause a loss in local diversity (Noss 1983). The regional scale, as defined in our study, consists of the coastal islands of Alabama, but the regional scale could be further characterized by the general conditions that prevail along the entire Northern Gulf Coast, which stretches from Louisiana to Florida. The Gulf Coast is a globally unique ecosystem characterized by a diversity of habitats, such as dunes, barrier islands, fresh/ saltwater marshes and other near-shore habitats which are essential for the annual cycles of many avian species (FWS 2010). The local scale consists of seven islands on the coast of Alabama that reflect the diverse habitats found along the Northern Gulf Coast. The objective of our study was to show the local diversity of three areas of coastal Alabama represented by seven islands. This approach allowed us to determine the role of local and/or regional processes in structuring the species assemblages in each area. With this data, we can make better decisions regarding the scale of our management efforts in coastal Alabama in the aftermath of the oil disaster. Methods The study area consisted of seven islands on the coast of Alabama: Gaillard Island, Cat Island, Marsh Island, Isle Aux Herbes (also referred to as Coffee Island), Robinson Island, Walker’s Island , and Bird Island (Fig. 1). These seven islands represent the three areas (West, Central, and East) that were analyzed in the study. Cat Island, Marsh Island, and Isle Aux Herbes are situated in the Portersville Bay area of the Mississippi Sound and make up the West sample. The Central sample is from Gaillard Island, a dredge spoil island in Mobile Bay and the East sample is from Robinson, Bird, and Walker’s islands, located inside of the Perdido Pass. See Robinson and Dindo (2008) for a detailed description of each island. 2012 O.J. Robinson, J.C. Burkhalter, and J.J. Dindo G31 Each island was surveyed at least twice each month from January 2007 until September 2007 (3–5 times each month after March 2007) for the presence of species. Nest searches were done to determine the species nesting on each island. The total species present and nesting represent the regional (coastal Alabama) pools from which random samples were drawn for each analysis. 1000 Monte Carlo simulations were conducted for each species pool (species present and species nesting), and the amount of overlap among areas was compared to the amount of overlap observed (Figs. 2, 3). Results The amount of overlap observed among the three areas for species observed was 25 species, outside of the critical values at the 95.0% level (27–39). The amount of overlap observed among the three areas for species nesting was 8 species, again, outside of the critical values at the 95.0% level (9–16). The amount of species overlap for both species observed and species nesting was fewer species than would be expected by a random sampling, suggesting that the species assemblages that we observed in each area were not there by chance and that local processes play an important role in forming these communities. Discussion Having examined the patterns of co-occurrence for both observed species and species nesting among the various islands of coastal Alabama using both actual field data and the simulated Monte Carlo data, the need for management Figure 1. Coastal Alabama. Circles indicate areas included in the survey. G32 Southeastern Naturalist Vol. 11, No. 2 Figure 2. Example of 1000 Monte Carlo simulations comparing the overlap of species at three regions of coastal Alabama from January 2007–September 2007. The species pool was 43. The test statistic for this simulation is the number of co-occurrences among sites. A species occurring at 2 or 3 areas is a co-occurrence. Lines at x = 27 and x = 39 indicate critical values at the 95.0% level. The arrow indicates observed overlap. 2012 O.J. Robinson, J.C. Burkhalter, and J.J. Dindo G33 of discrete local communities, as opposed to managing for a regional suite of surrogate species, is supported. To lump all species across the different regions of the Alabama coastline into one group is an oversimplification of the dynamics occurring within the region by discounting the local-scale processes as evidenced by the lower-than-expected rates of species co-occurrence between the different regions of the coastline. The information contained within this study highlights the continued need for detailed analyses of scale that accurately reflect true biological patterns and recognize how seemingly homogenous environments can result in different patterns of species occurrence at a smaller scale. An important implication for conservation is that caution is vital when attempting to extrapolate the dynamics of one area to another (Hansen and Urban 1992), and a “one size fits all” approach could fail to meet the necessary prerequisites for conservation of each local assemblage and thus the greater regional species pool. This study provides insight into the local diversity of avian assemblages that existed along the coast of Alabama before the Deepwater Horizon (DWH) oil spill. Our analysis shows that the assemblages found in each area in the study are different than one would expect by a random draw from the regional species pool. This finding suggests that management decisions should be made with the consideration of scale in the wake of the recent oil disaster in the Gulf of Mexico. Failure to do so may result in the loss of local diversity of avian species that inhabit the coast of Alabama. Future monitoring of these areas is required during the recovery from the oil spill to ensure that local diversity is preserved. A number of specific oil spill mitigation strategies have been developed and implemented in the wake of the DWH spill, e.g., berm construction to protect coastal marshes, but we are unsure of the long-term ecological impacts of these measures (Martinez et al. 2011). Due to the fact that we are advocating for local-scale management, a better use of the limited resources dedicated to restoring/conserving habitats and species of the Gulf might be for local and state governments to first conduct rapid biodiversity assessments post-spill to determine the biological value of an area. Large non-profits, e.g., Conservation International, have pioneered the approach of rapid biodiversity assessments over the last 20 years and may provide a logical model from which to gain information (Alonso et al. 2011). Once this initial assessment is done, it will be possible to then direct funds towards management projects in certain “hotspots” that are of high biological value, i.e., species diverse and currently/ potentially productive in terms of ecological function, which will increase the long-term ecological sustainability of a number of different locales and thus benefit the region as a whole. Figure 3 (opposite page). Example of 1000 Monte Carlo simulations comparing the overlap of nesting species at three regions of coastal Alabama from January 2007–September 2007. The species pool was 19. The test statistic for this simulation is the number of co-occurrences of nesting species among sites. A species nesting at 2 or 3 areas is a cooccurrence. Lines at x = 9 and x = 16 indicate critical values at the 95.0% level. The arrow indicates observed overlap. G34 Southeastern Naturalist Vol. 11, No. 2 Acknowledgments Funding for this project was provided in part by the Coastal Zone Management Act of 1972, as amended, administered by the Office of Ocean and Coastal Resource Management, National Oceanic and Atmospheric Administration, and the Alabama State Lands Division, Department of Conservation and Natural Resources, State Lands Division, Coastal Section. Literature Cited Alonso, L.E., J.L. Deichmann, S.A. McKenna, P. Naskrecki, and S.J. Richards. 2011. Still counting … Biodiversity exploration for conservation. The first 20 years of the Rapid Assessment Program. Available online at https://learning.conservation.org/ biosurvey/RAP/Pages/default.aspx. Accessed 12 January 2012. Bestelmeyer, B.T., J.R. Miller, and J.A. Wiens. 2003. Applying species diversity theory to land management. Ecological Applications 13(6):1750–1761. Blackburn, T.M., and K.J. Gaston. 2001. Local avian assemblages as random draws from regional pools. Ecography 24:50–58. Blake, J.G., and B.A. Loiselle. 2009. Species composition of neotropical understory bird communities: Local versus regional perspectives based on capture data. Biotropica 41(1):85–94. Buhl-Mortensen, L., A. Vanreusel, A.J. Gooday, L.A. Levin, I.G. Priede, P. Buhl- Mortensen, H. Gheerardyn, N.J. King, and M. Raes. 2011. Biological structures as a source of habitat heterogeneity and biodiversity on the deep ocean margins. Marine Ecology 31:21–50. Cushman, S.A., K.S. McKelvey, B.R. Noon, and K. McGarigal. 2010. Use of abundance of one species as a surrogate for abundance of others. Conservation Biology 24:830–840. Hansen, A.J., and D.L. Urban. 1992. Avian response to landscape pattern: The role of species’ life histories. Landscape Ecology 7(3):163–180. Hewitt, J.E., S.F. Thrush, J. Halliday, and C. Duffy. 2005. The importance of small-scale habitat structure for maintaining beta diversity. Ecology 86(6):1619–1626. Horwitz, P., R. Rogan, S. Halse, J. Davis, and B. Sommer. 2009. Wetland invertebrate richness and endemisim of the Swan Coastal Plain, Western Australia. Marine and Freshwater Research 60:1006–1020. Martinez, M.L., R.A. Feagin, K.M. Yeager, J. Day, R. Costanza, J.A. Harris, R.J. Hobbs, J. Lopez-Portillo, I.J. Walker, E. Higgs, P. Moreno-Casasola, J. Sheinbaum, and A. Yanez-Arancibia. 2011. Artificial modifications to the coast in response to the Deepwater Horizon oil spill: Quick solutions or long-term liabilities? Frontiers in Ecology and the Environment 10:44–49. Matias, M.G., A.J. Underwood, D.F. Hochli, and R.A. Coleman. 2011. Habitat identity influences species-area relationships in heterogeneous habitats. Marine Ecology Progress Series 437:135–145. Mitchell, L.R., S. Gabrey, P.P. Marra, and R.M. Erwin. 2006. Impacts of marsh management on coastal-marsh bird habitat. Studies in Avian Biology 32:155–175. Noss, R.F. 1983. A regional approach to maintain diversity. BioScience 33(11):700–706. Pearman, P.B. 2002. The scale of community structure: Habitat variation and avian guilds in tropical forest understory. Ecological Monographs 72(1):19–39. Poiani, K.A., B.D. Richter, M.G. Anderson, and H.E. Richter. 2000. Biodiversity conservation at multiple scales: Functional sites, landscapes, and networks. BioScience 50(2):133–146. 2012 O.J. Robinson, J.C. Burkhalter, and J.J. Dindo G35 Ricklefs, R.E., and I.J. Lovette. 1999. The roles of island area per se and habitat diversity in the species-area relationships of four Lesser Antillean faunal groups. Journal of Animal Ecology 68:1142–1160. Robinson, O.J., and J.J. Dindo. 2008. Survey for colonial nesting birds on seven islands of coastal Alabama. Alabama Birdlife 54(2):37–43. US Fish and Wildlife Service (FWS). 2010. Beach-nesting birds of the Gulf. Available online at http://www.fws.gov/home/dhoilspill/pdfs/DHBirdsOfTheGulf.pdf. Accessed 12 January 2012. Wiens J.A. 2000. Ecological heterogeneity: An ontogeny of concepts and approaches. Pp. 9–31, In M.J. Hutchings, E.A. John, and A.J.A. Stewart (Eds.). The Ecological Consequences of Environmental Heterogeneity. Blackwell Science, Oxford, UK. 452 pp. Wiens, J.A., G.D. Hayward, R.S. Holthausen, and M.J. Wisdom. 2008. Using surrogate species and groups for conservation planning and management. BioScience 58(3):241–252. Williams, S.E., H. Marsh, and J. Winter. 2002. Spatial scale, species diversity, and habitat structure: Small mammals in Australian tropical rain forest. Ecology 83(5):1317–1329.