Macro-spatial structure of biotic interactions in the distribution of a raptor species

Abstract

[Aim]: While the contribution of abiotic factors to species distribution is well known, the geographic structure, if any, of biotic interactions within the species range is poorly understood. Most studies neglect biotic interactions when generating Species Distribution Models (SDMs) and projecting them, using future climatic scenarios, while others argue that biotic interactions may extend species tolerances to suboptimal abiotic conditions. Elucidating the extent to which biotic interactions play a role at a macro‐scale is challenging due to its inherent complexity. In this study, we characterized the independent contribution of prey abundance distributions on the Merlin's wintering distribution (Falco columbarius). Then, to examine the hypothesis that biotic interactions may counteract other suboptimal conditions, we tested for a differential importance of physical habitat characteristics and prey abundance distributions along the species’ wintering range.

[Location]: Peninsular Spain.

[Methods]: We modelled the Merlin's geographic distribution with Boosted Classification Trees as a function of environmental predictors (environmental model) and prey relative abundances (prey model), either separately or jointly (combined model). We tested whether the predictive success of environmental and prey models differ spatially.

[Results]: Partialling out the variation into independent components we found that the prey abundance distributions explained the largest part of variation. Furthermore, the first four predictors with the highest contribution in our combined models were the abundances of prey species. Finally, our model predictions revealed a north‐to‐south increase in the importance of prey abundance distributions. Interestingly, our results suggest that biotic interactions can enable species to inhabit a wider range of suboptimal habitat conditions on range margins.

[Main conclusions]: Relevant biotic interactions may not be always fully interchangeable with environmental surrogates. Abiotic factors and biotic interactions may shape species range limits and cores of distributions differently. Neglecting biotic interactions may compromise spatiotemporal transferability of SDMs, especially on species margins, and hence their applicability.