Identifying climate refugia for high‐elevation Alpine birds under current climate warming predictions

• Published in: Global Change Biology
• Main Authors: Brambilla, Mattia, Rubolini, Diego, Appukuttan, Ojan, Calvi, Gianpiero, Karger, Dirk Nikolaus, Kmecl, Primož, Mihelič, Tomaž, Sattler, Thomas, Seaman, Benjamin, Teufelbauer, Norbert, Wahl, Johannes, Celada, Claudio
• Other Authors: M. Brambilla, D. Rubolini, O. Appukuttan, G. Calvi, D.N. Karger, P. Kmecl, T. Mihelič, T. Sattler, B. Seaman, N. Teufelbauer, J. Wahl, C. Celada
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley Blackwell Publishing 2022
• Subjects: Alp; climate change; community science; distribution; ecological realism; protected area; SDM extrapolation; Settore BIO/07 - Ecologia; Lagopus muta
• Online Access: https://hdl.handle.net/2434/924898; https://doi.org/10.1111/gcb.16187

Identifying climate refugia is key to effective biodiversity conservation under a changing climate, especially for mountain-specialist species adapted to cold conditions and highly threatened by climate warming. We combined species distribution models (SDMs) with climate forecasts to identify climate refugia for high-elevation bird species (Lagopus muta, Anthus spinoletta, Prunella collaris, Montifringilla nivalis) in the European Alps, where the ecological effects of climate changes are particularly evident and predicted to intensify. We considered future (2041-2070) conditions (SSP585 scenario, four climate models) and identified three types of refugia: (1) in-situ refugia potentially suitable under both current and future climate conditions, ex-situ refugia suitable (2) only in the future according to all future conditions, or (3) under at least three out of four future conditions. SDMs were based on a very large, high-resolution occurrence dataset (2901-12,601 independent records for each species) collected by citizen scientists. SDMs were fitted using different algorithms, balancing statistical accuracy, ecological realism and predictive/extrapolation ability. We selected the most reliable ones based on consistency between training and testing data and extrapolation over distant areas. Future predictions revealed that all species (with the partial exception of A. spinoletta) will undergo a range contraction towards higher elevations, losing 17%-59% of their current range (larger losses in L. muta). We identified similar to 15,000 km(2) of the Alpine region as in-situ refugia for at least three species, of which 44% are currently designated as protected areas (PAs; 18%-66% among countries). Our findings highlight the usefulness of spatially accurate data collected by citizen scientists, and the importance of model testing by extrapolating over independent areas. Climate refugia, which are only partly included within the current PAs system, should be priority sites for the conservation of Alpine ...