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Abstract Global change is impacting biodiversity across all habitats on earth. New selection pressures from changing climatic conditions and other anthropogenic activities are creating heterogeneous ecological and evolutionary responses across many species' geographic ranges. Yet we currently lack standardised and reproducible tools to effectively predict the resulting patterns in species vulnerability to declines or range changes.We developed an informatic toolbox that integrates ecological, environmental and genomic data and analyses (environmental dissimilarity, species distribution models, landscape connectivity, neutral and adaptive genetic diversity, genotype‐environment associations and genomic offset) to estimate population vulnerability. In our toolbox, functions and data structures are coded in a standardised way so that it is applicable to any species or geographic region where appropriate data are available, for example individual or population sampling and genomic datasets (e.g. RAD‐seq, ddRAD‐seq, whole genome sequencing data) representing environmental variation across the species geographic range.To demonstrate multi‐species applicability, we apply our toolbox to three georeferenced genomic datasets for co‐occurring East African spiny reed frogs (Afrixalus fornasini, A. delicatusandA. sylvaticus) to predict their population vulnerability, as well as demonstrating that range loss projections based on adaptive variation can be accurately reproduced from a previous study using data for two European bat species (Myotis escaleraiandM. crypticus).Our framework sets the stage for large scale, multi‐species genomic datasets to be leveraged in a novel climate change vulnerability framework to quantify intraspecific differences in genetic diversity, local adaptation, range shifts and population vulnerability based on exposure, sensitivity and landscape barriers.
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Generating continuous maps of genetic diversity using moving windows
Abstract Genetic diversity plays a key role in maintaining population viability by preventing inbreeding depression and providing the building blocks for adaptation. Understanding how genetic diversity varies across space is, therefore, of key interest in conservation and population genetics.Here, we introducewingen, anrpackage for calculating continuous maps of genetic diversity, including nucleotide diversity, allelic richness, and heterozygosity, from standard genotypic and spatial data using a spatial moving window approach. We provide functions to account for variation in sample size across space using rarefaction, to create kriging‐interpolated maps of genetic diversity, and to mask any areas that are outside the area of interest.Tests with simulated and empirical datasets demonstrate thatwingencan successfully capture variation in genetic diversity across landscapes from both reduced‐representation and whole genome sequencing datasets. For reduced‐representation datasets,wingen's functions can be run easily on a standard laptop computer, and we provide options for parallelization to increase the efficiency of running larger whole genome datasets.wingenprovides novel and computationally tractable tools for creating informative maps of genetic diversity with applications for conservation prioritization as well as population and landscape genetic analyses.
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- Award ID(s):
- 1845682
- PAR ID:
- 10401324
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Methods in Ecology and Evolution
- Volume:
- 14
- Issue:
- 5
- ISSN:
- 2041-210X
- Page Range / eLocation ID:
- p. 1175-1181
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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