There’s nothing fishy about functional diversity! I am pleased to announce that back in October (2018), my co-authors and I published a research article in Transactions of the American Fisheries Society titled “State and Regional-Scale Patterns and Drivers of Freshwater Fish Functional Diversity in the Southeastern US.” This work was primarily conducted to assess the utility of South Atlantic LCC freshwater aquatic ecosystem indicators from a functional trait perspective, but evolved into a larger assessment of freshwater fish functional diversity patterns across the South Atlantic and South Carolina wadeable streams. Back in January 2016, I presented some preliminary results on this work during a Third Thursday Web Forum (view a recording of the webinar here and see the presentation slides here). Additionally, we submitted a final report summarizing our results to the South Atlantic LCC , and you can download this report here. With this blog post, I wanted to provide a brief overview of our work and highlight some of our findings, but please feel free to explore our manuscript and supplementary materials for more details.
Functional diversity represents the overall diversity of evolutionary traits (i.e., associated with feeding, reproduction, and habitat use) in an ecosystem or community. Two communities containing the same number of species may have very different levels of functional diversity; one community may contain species all having unique traits (i.e., high functional diversity) while the other may contain species that share some or all of their traits (i.e., low functional diversity). These functional attributes of species are what drive ecosystem services and functions (Tilman 2001; Hooper et al. 2005), and even govern how species respond to environmental change and disturbance (Suding et al. 2008). This recognition has led to an expansion of diversity measurements beyond the taxonomic level to include quantitative measures of functional diversity when assessing biodiversity and ecosystem integrity. In this regard, we decided that it would be informative to relate South Atlantic LCC aquatic indicators to measures of freshwater fish functional diversity across the region to assess the utility of the selected indicators.
We began by obtaining HUC8-level fish sampling data from the Multistate Aquatic Resources Information System (MARIS) and the USGS Nonindigenous Aquatic Species (NAS) databases. We then compiled trophic and reproductive fish trait information for the present species using the Virginia Tech FishTraits Database (Frimpong and Angermeier 2009), primary literature, U.S. Fish and Wildlife Service reports, state and regional fish identification texts, and expert opinion. Next, we measured trophic and reproductive functional diversity across South Atlantic HUC8s using the functional dispersion metric (Laliberté and Legendre 2010) and related these values to HUC8-level ecosystem indicator values. We also determined how imperiled and invasive species affect functional diversity estimates and if differences in functional diversity exist among EPA level III ecoregions. During this process, we collaborated with folks from the South Carolina Department of Natural Resources to run the same set of analyses using standardized fish sampling data from their South Carolina Stream Assessment (Scott et al. 2009). Here I synthesize some general findings from these two analyses, but a more thorough discussion of the data limitations and tradeoffs associated with using datasets of different sampling intensity and time duration for a functional diversity assessment exists in our manuscript.
Despite our inability to find significant associations between South Atlantic LCC aquatic indicators and functional diversity at the HUC8 scale (i.e., the original intent of our work), we did find informative functional diversity patterns across the South Atlantic and South Carolina wadeable streams and developed maps to depict these patterns (Figures 1 and 2). In general, trophic functional diversity was greater in high elevation ecoregions while reproductive functional diversity decreased or showed no pattern. Additionally, a surplus of environmental and land cover data (Scott et al. 2009; Marion et al. 2015) were collected in stream reaches as part of the South Carolina Stream Assessment, and we were able to identify significant associations between functional diversity and a subset of these variables (e.g., forest cover, elevation, conductivity). In almost all cases (the exception being South Atlantic reproductive functional diversity), functional diversity was significantly greater without invasive species, and in all cases, functional diversity was less without imperiled species. This makes sense because invasive species are often generalists exhibiting redundant traits, while imperiled species are specialists exhibiting unique traits (Warren et al. 2000; Olden 2006).
Overall, these functional diversity patterns and drivers (South Carolina dataset) are useful for informing conservation planning efforts in the southeastern United States. Along with other measures of biodiversity and ecosystem integrity, our results can be coupled with projected human population growth patterns and climate change models to develop conservation related decisions associated with maintaining biodiversity and ecosystem functioning. Additionally, we hope that our work can serve as a template for similar efforts in other geographic areas or LCCs to identify functional diversity trends and hotspots that may then be coupled with similar types of data on regionally specific biodiversity threats.
Figure 2. (A) Trophic and (B) reproductive functional diversity across South Carolina sampling points. Warm colors indicate high functional diversity and cool colors indicate low functional diversity. Maps are standardized independently. Note: no sampling points were in the Southern Coastal Plain. Data source: U.S. Environmental Protection Agency, 2013. Level III Ecoregions of the Conterminous United States.
Frimpong, E. A. and P. L. Angermeier. 2009. Fish traits: a database of ecological and life-history traits of freshwater fishes of the United States. Fisheries 34:487-495.
Hooper, D. U., F. S. Chapin, J. J. Ewel, A. Hector, P. Inchausti, S. Lavorel, J. H. Lawton, D. M. Lodge, M. Loreau, S. Naeem, B. Schmid, H. Setala, A. J. Symstad, J. Vandermeer, and D. A. Wardle. 2005. Effects of biodiversity on ecosystem functioning: A consensus of current knowledge. Ecological Monographs 75:3-35.
Laliberté, E. and P. Legendre. 2010. A distance-based framework for measuring functional diversity from multiple traits. Ecology 91:299-305.
Marion, C. A., M. C. Scott, and K. M. Kubach. 2015. Multiscale environmental influences on fish assemblage structure of South Atlantic Coastal Plain streams. Transactions of the American Fisheries Society 114:1040-1057.
Nystrom, M., C. Folke, and F. Moberg. 2000. Coral reef disturbance and resilience and in a human-dominated environment. Trends in Ecology and Evolution 15:413-417.
Olden, J. D. 2006. Biotic homogenization: a new research agenda for conservation biogeography. Journal of Biogeography 33:2027-2039.
Scott, M. C., L. Rose, C. A. Marion, K. M. Kubach, C. Thomason, and J. Price. 2009. The South Carolina stream assessment standard operating procedures, South Carolina Department of Natural Resources, Columbia.
Suding, K. N., S. Lavorel, F. S. Chapin, J. H. C. Cornelissen, S. Díaz, E. Garnier, D. Goldberg, D. U. Hooper, S. T. Jackson, and M. L. Navas. 2008. Scaling environmental change through the community-level: a trait-based response-and-effect framework for plants. Global Change Biology 14:1125-1140.
Tilman, D. 2001. Functional diversity. Pages 109-120 in Encyclopedia of Biodiversity Volume 3. S. A. Levin, editor. Academic Press, New York.
Warren, M. L. (Jr.)., B. M. Burr, S. J. Walsh, H. L. Bart (Jr.), R. C. Cashner, D. A. Etnier, B. J. Freeman, B. R. Kuhajda, R. L. Mayden, H. W. Robison, S. T. Ross, and W. C. Starnes. 2000. Diversity, distribution, and conservation status of the native freshwater fishes of the southern United States. Fisheries 25:7-31.