Predictive models of distribution and abundance of a threatened mountain species show that impacts of climate change overrule those of land use change

Barras, Arnaud G.; Braunisch, Veronika; Arlettaz, Raphaël (2021). Predictive models of distribution and abundance of a threatened mountain species show that impacts of climate change overrule those of land use change. Diversity and Distributions, 27(6), pp. 989-1004. Wiley 10.1111/ddi.13247

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Aim: Climate is often the sole focus of global change research in mountain ecosystems although concomitant changes in land use might represent an equally important threat. As mountain species typically depend on fine‐scale environmental characteristics, integrating land use change in predictive models is crucial to properly assess their vulnerability. Here, we present a modelling framework that aims at providing more comprehensive projections of both species’ distribution and abundance under realistic scenarios of land use and climate change, and at disentangling their relative effects.

Location: Switzerland.

Methods: We used the ring ouzel (Turdus torquatus), a red‐listed and declining mountain bird species, as a study model. Based on standardized monitoring data collected across the whole country, we fitted high‐resolution ensemble species distribution models to predict current occurrence probability, while spatially explicit density estimates were obtained from N‐mixture models. We then tested for the effects of realistic scenarios of land use (land abandonment versus farming intensification) and climate change on future species distribution and abundance.

Results: Occurrence probability was mostly explained by climatic conditions, so that climate change was predicted to have larger impacts on distribution and abundance than any scenarios of land use change. In the mid‐term (2030–2050), predicted effects of environmental change show a high spatial heterogeneity due to regional differences in climate and dominant land use, with farming intensification identified as an important threat locally. In the long term (2080–2100), climate models forecast a marked upward range shift (up to +560 m) and further population decline (up to −35%).

Main conclusions: Our innovative approach highlights the spatio‐temporal heterogeneity in the relative effects of different environmental drivers on species distribution and abundance. The proposed framework thus provides a useful tool not only for better assessing species’ vulnerability in the face of global change, but also for identifying key areas for conservation interventions at a meaningful scale.

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