Can Species Distribution Models Aid Bioassessment when Reference Sites are Lacking? Tests Based on Freshwater Fishes
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Recent literature reviews of bioassessment methods raise questions about use of least-impacted reference sites to characterize natural conditions that no longer exist within contemporary landscapes. We explore an alternate approach for bioassessment that uses species site occupancy data from museum archives as input for species distribution models (SDMs) stacked to predict species assemblages of freshwater fishes in Texas. When data for estimating reference conditions are lacking, deviation between richness of contemporary versus modeled species assemblages could provide a means to infer relative biological integrity at appropriate spatial scales. We constructed SDMs for 100 freshwater fish species to compare predicted species assemblages to data on contemporary assemblages acquired by four independent surveys that sampled 269 sites. We then compared site-specific observed/predicted ratios of the number of species at sites to scores from a multimetric index of biotic integrity (IBI). Predicted numbers of species were moderately to strongly correlated with the numbers observed by the four surveys. We found significant, though weak, relationships between observed/predicted ratios and IBI scores. SDM-based assessments identified patterns of local assemblage change that were congruent with IBI inferences; however, modeling artifacts that likely contributed to over-prediction of species presence may restrict the stand-alone use of SDM-derived patterns for bioassessment and therefore warrant examination. Our results suggest that when extensive standardized survey data that include reference sites are lacking, as is commonly the case, SDMs derived from generally much more readily available species site occupancy data could be used to provide a complementary tool for bioassessment.
KeywordsBioassessment Community modeling Conservation Fish biodiversity Species distribution modeling Reference sites
This study was supported by The University of Texas at Austin, Texas Parks and Wildlife Department State Wildlife Grant (Data standardization and georeferencing of the Fishes of Texas database, F06AF00007) made available through the United States Fish and Wildlife Service’s State Wildlife Grant program (T-106), and Texas Commission on Environmental Quality (Digital Fish Atlas grant contract No. 582-11-99736). Thanks to the thousands of collectors who contributed to the Fishes of Texas database. We also thank Gary Garrett, Tim Birdsong, Kevin Mayes, and Josh Perkin for early discussions and concept reviews, 6 anonymous reviewers, and Meagan Bean, Preston Bean, Steven Curtis, Thom Heard, Douglas Knabe, Kristy Kollaus, Doug Martin, Allison Pease, Zach Shattuck, Jason Taylor, and Gene Wilde for help in compiling portions of the survey databases used in our analyses.
Conflict of interest
The authors declare that they have no conflicts of interest.
- Baselga A, Araujo MB (2010) Do community-level models describe community variation effectively? J Biogeogr 37:1842–1850Google Scholar
- Bean PT, Bonner TH, Littrell BM (2007) Spatial and temporal patterns in the fish assemblage of the Blanco River, Texas. Tex J Sci 59:179Google Scholar
- Bowman M, Somers K (2005) Considerations when using the reference condition approach for bioassessment of freshwater ecosystems. Water Qual Res J Can 40:347–360Google Scholar
- Hendrickson DA, Cohen AE (2012) Fishes of Texas project and online database. Published by Texas Natural History Collection, a division of the Department of Integrative Biology, University of Texas at AustinGoogle Scholar
- Hubbs C, Edwards RJ, Garrett GP (2008) An annotated checklist of the freshwater fishes of Texas, with keys to identification of species. Tex J Sci 43:1–87Google Scholar
- Karr JR, Chu EW (1999) Restoring life in running waters: better biological monitoring. Island Press, Washington, D.C.Google Scholar
- King RS, KO Winemiller, JM Taylor, JA Back, A Pease (2009) Development of biological indicators of nutrient enrichment for application in texas streams. Final report to Texas Commission on Environmental Quality, §106 Water Pollution Control Grant #98665304Google Scholar
- Kleinsasser LJ, Jurgensen T, Bowles D, Boles S, Aziz K, Saunders K, Linam G, Trungale J, Mayes K, Rector J et al (2004) Status of biotic integrity, water quality, and physical habitat in wadeable east Texas streams. Resources Protection Division, Texas Parks and Wildlife Department River Studies Report 19Google Scholar
- Labay B (2010) The influence of land use, zoogeographic history, and physical habitat on fish community diversity in the lower Brazos watershed. Theses and Dissertations-Biology 27, Texas State University, San MarcosGoogle Scholar
- Linam GW, Kleinsasser LJ, Mayes KB (2002) Regionalization of the index of biotic integrity for Texas streams. Resources Protection Division, Texas Parks and Wildlife Department River Studies Report 17Google Scholar
- Peppler-Lisbach C, Schröder B (2004) Predicting the species composition of Nardus stricta communities by logistic regression modelling. J Veg Sci 15:623–634Google Scholar
- Peterson AT, Soberon J, Pearson RG, Anderson RP, Martinez-Meyer E, Nakamura M, Araujo M (2011) Ecological niches and geographic distributions. Princeton University Press, New JerseyGoogle Scholar
- R Development Core Team (2012) A language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
- Scott JM (2002) Predicting species occurrences: issues of accuracy and scale. Island Press, Washington, D.C.Google Scholar
- Wilde GR (2011) Reproductive ecology and population dynamics of fishes in the upper Brazos river. Texas Parks and Wildlife State Wildlife Grant annual reportGoogle Scholar
- Winemiller KO, King RS, Taylor J, Pease A (2009) Refinement and validation of habitat quality indices (HQI) and aquatic life use (ALU) indices for application to assessment and monitoring of texas surface waters. final project report, Texas Commission on Environmental Quality Contract 582-6-80304, 81 ppGoogle Scholar