Journal article

Incorporating spatial autocorrelation into species distribution models alters forecasts of climate-mediated range shifts

Beth Crase, Adam Liedloff, Peter A Vesk, Yusuke Fukuda, Brendan A Wintle



Species distribution models (SDMs) are widely used to forecast changes in the spatial distributions of species and communities in response to climate change. However, spatial autocorrelation (SA) is rarely accounted for in these models, despite its ubiquity in broad-scale ecological data. While spatial autocorrelation in model residuals is known to result in biased parameter estimates and the inflation of type I errors, the influence of unmodeled SA on species' range forecasts is poorly understood. Here we quantify how accounting for SA in SDMs influences the magnitude of range shift forecasts produced by SDMs for multiple climate change scenarios. SDMs were fitted to simulated data with a k..

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Awarded by Australian Research Council Future Fellowship

Funding Acknowledgements

BC was supported by an Australian Postgraduate Award, and the National Environmental Research Program (NERP) Decisions Hub. BW is supported by an Australian Research Council Future Fellowship (FT 100100819) and the ARC Centre of Excellence for Environmental Decisions. We thank Pablo Luis Sordo Martinez and Tak Fung for their assistance in running the boot-strapped models with the High Performance Computing Center at the National University of Singapore. Comments from Simon Ferrier, Reid Tingley, Michael Bode and Chris Jones improved earlier versions of the manuscript.