Anthropogenic range contraction, temporal sampling bias, and the performance of species distribution models

Anthropogenic range contraction (ARC) dynamically alters species ranges, which can be problematic for correlational species distribution modelling (SDM). We used a virtual ecologist approach to simulate ARC and temporally-biased sampling, demonstrate its link to two principal forms of data misrepresentation, and investigate the outcomes to SDM performance. Occurrences sampled before ARC were mismatched against contemporary anthropogenic pressures (‘occurrence-habitat mismatching’), which impeded predictions of species responses to those pressures and produced models that underestimated the impact of human activity on species distribution. Occurrences sampled after ARC were truncated representations of historically realised niches (‘niche truncation’), which were carried over onto predictions of species-environment relationships, but were overcome by incorporating an appropriate anthropogenic predictor. Given the pervasive global human footprint and associated ARC, these data misrepresentations are likely inherent in most occurrence datasets and should be interrogated during model development. Accounting for these effects differs depending on the type of data misrepresentation.