Distance weighting avoids erroneous scale effects in species‐habitat models

Summary 1.  In species‐habitat models, curves describing the changes in correlation strength between habitat cover and species occurrence over a continuum of spatial scales tend to be hump‐shaped, and the correlation maximum is generally assumed to indicate the ecologically most meaningful scale of habitat influence on the species. This approach does not take account of the fact that distant habitat is overrated by increasing area with larger buffer sizes whilst habitat influence decays with distance. We devised four levels of distance weighting, down‐weighting more distant habitat with increasing realism. 2.  We analysed correlation strength across scale (200 m − 50 km) in simulations assuming a Gaussian distance kernel of habitat influence and in empirical data for Eurasian lynx ( Lynx lynx ) covering Central Europe. Regressions were run with the four levels of distance weighting. 3.  Both in the simulated data and the empirical data distance weighting transformed humped correlation curves into saturation curves with high correlations at large scales, thereby eliminating a well‐defined correlation maximum. 4.  We argue that saturation curves naturally reflect the integration of habitat influence over increasing buffer areas. We conclude that without distance weighting, the correlation strength between habitat cover and species occurrence is prone to misinterpretation. We present two approaches to implementing distance weighting in species‐habitat regressions.