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

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. 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. Population genetic structure was characterized by wea..., We sequenced feather and blood samples from 116 individuals spanning 11 sites across the Brown-capped Rosy-Finch breeding distribution (Table 1).  Samples were collected during the breeding season of 2017 and 2018.  Individuals from the Lost Man Lake and Independence Lake sites were combined as a single sampling unit for subsequent analyses based on their proximity (< 1 km) and the low sample sizes (5 and 1 individuals, respectively). Engineer Mountain and Horseshoe Basin sites were also in close proximity (< 5 km), but we retained them as separate sampling units due to the larger number of individuals per site (8 and 18 individuals, respectively).
We extracted DNA from blood samples using the standard protocol for Qiagen DNEasy Blood and Tissue Kits and we modified the protocol to maximize DNA yield from feathers. Whole genome sequencing libraries were prepared following modifications of Illumina’s Nextra Library Preparation protocol. Pooled libraries were sequenced on HiSeq 4000..., See README file for details., # Forecasting climate change response in an alpine specialist songbird reveals the importance of considering novel climate

These data are associated with the paper of the same name by DeSaix et al. (2022) published in *Diversity and Distributions* ().

## Description of the data and file structure

The data provided are described here in the order of the directory they are in the provided compressed file \"bcrf-climate.gz\".

**admixture**

Directory of data related to analyses from the [ADMIXTURE software](https://dalexander.github.io/admixture/)

* bcrf.admix.df.q2.csv = Metadata file for the 104 filtered individuals (see bcrf.nokin.ids.txt) with the ADMIXTURE results for K=2, where the file has 6 attributes (ID = unique sample ID, Lat = Latitude of sample collection site, Long = Longitude of sample collection site, Group_ID = four letter abbreviation of sample collection site, K1 = admixture proportions for cluster one, K2 = admixture proportions for cluster 2).

* bcrf.admix.df.q...