气候变化
工具箱
脆弱性(计算)
人口
GSM演进的增强数据速率
地理
环境科学
环境资源管理
自然地理学
气候学
计算机科学
生态学
生物
地质学
环境卫生
医学
人工智能
计算机安全
程序设计语言
作者
Christopher D. Barratt,Renske E. Onstein,Malin L. Pinsky,Sebastian Steinfartz,Hjalmar S. Kühl,Brenna R. Forester,Orly Razgour
标识
DOI:10.1111/2041-210x.14429
摘要
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. delicatus and A. 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 escalerai and M. 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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