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Published on: July 30, 2019
Can Species Distribution Models Aid Bioassessment when Reference Sites are Lacking? Tests Based on Freshwater Fishes
Ben J Labay1, Dean A Hendrickson, Adam E Cohen
1Department of Integrative Biology, Biodiversity Collections, University of Texas, Austin, TX, USA, benlabay@utexas.edu.
Abstract:
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.
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