Transferability of predictive models of coral reef fish species richness

Title: Transferability of predictive models of coral reef fish species richness Author: Sequeira, A.M.M.; Mellin, C.; Lozano-Montes, H.M.; Vanderklift, M.A.; Babcock, R.C.; Haywood, M.D.E.; Meeuwig, J.J.; Caley, M.J. Abstract: 1. Understanding biodiversity patterns depends on data collection, which in marine environments can be prohibitively expensive. Transferable predictive models could therefore provide time- and cost-effective tools for understanding biodiversity–environment relationships. 2. We used fish species counts and spatial and environmental predictors to develop predictive models of fish species richness (S) for two major coral reefs located in separate ocean basins: Australia’s Great Barrier Reef (GBR; Queensland) and Ningaloo Reef (NR; Western Australia). We tested the ability of the GBR model to predict S at NR (its transferability) under various scenarios using different sampling durations, years sampled and transect sizes. 3. Based on R², the GBR model poorly predicted S at NR (R²