Forecasting climate change response in an alpine specialist songbird reveals the importance of considering novel climate

Aim Species persistence in the face of climate change depends on both ecological and evolutionary factors. Here, we integrate ecological and whole‐genome sequencing data to describe how populations of an alpine specialist, the Brown‐capped Rosy‐Finch ( Leucosticte australis ) may be impacted by climate change. Location Southern Rocky Mountains in North America. Methods We sampled 116 Brown‐capped Rosy‐Finches from 11 sampling locations across the breeding range. Using 429,442 genetic markers from whole‐genome sequencing, we described population genetic structure and identified a subset of 436 genomic variants associated with environmental data. We modelled future climate change impacts on habitat suitability using ecological niche models (ENMs) and impacts on putative local adaptation using gradient forest models (a genetic‐environment association analysis; GEA). We used the metric of niche margin index (NMI) to determine regions of forecasting uncertainty due to climate shifts to novel conditions. Results Population genetic structure was characterized by weak genetic differentiation, indicating potential ongoing gene flow among populations. Precipitation as snow had high importance for both habitat suitability and changes in genetic variation across the landscape. Comparing ENM and gradient forest models with future climate predicted suitable habitat contracting at high elevations and population allele frequencies across the breeding range needing to shift to keep pace with climate change. NMI revealed large portions of the breeding range shifting to novel climate conditions. Main conclusions Our study demonstrates that forecasting climate vulnerability from ecological and evolutionary factors reveals insights into population‐level vulnerability to climate change that are obfuscated when either approach is considered independently. For the Brown‐capped Rosy‐Finch, our results suggest that persistence may depend on rapid adaptation to novel climate conditions in a contracted breeding range. Importantly, we demonstrate the need to characterize novel climate conditions that influence uncertainty in forecasting methods.