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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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Turnover importance: Operationalizing beta diversity to quantify the generalism continuum
Abstract Generalization is difficult to quantify, and many classifications exist. A beta diversity framework can be used to establish a numeric measure of generalist tendencies that jointly describes many important features of species interactions, namely spatiotemporal heterogeneity. This framework is promising for studying generalized symbiotic relationships of any form.We formulated a novel index, turnover importance (T).Tdescribes spatiotemporal heterogeneity in interactor assemblages, an inherent feature of generalist relationships that is not captured by available metrics. We simulated the behaviour ofTrelative to other available metrics, calculatedTfor native North American orchid‐insect relationships, and tested correlations betweenTand eco‐geographic variables. We performed case studies to demonstrate applications ofTfor conservation and eco‐evolutionary studies.Tbehaves predictably across simulations, and dynamically interacts with site number, gamma diversity, and species range sizes.Tis moderately sensitive to sampling depth. Orchids with higherTscores occupy larger ranges and broader climatic niches.Alternative interactor‐specific measures of generalism are best employed for local‐level community networks over short timespans. While these interactor metrics can assess use versus availability in local communities,Tcan be used to measure spatiotemporal patterns of variation in interactor assemblages across a focal species' range. This study provides a roadmap for future work focused on better understanding the patterns and consequences of generalized relationships.
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- PAR ID:
- 10500336
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Methods in Ecology and Evolution
- Volume:
- 15
- Issue:
- 5
- ISSN:
- 2041-210X
- Format(s):
- Medium: X Size: p. 951-964
- Size(s):
- p. 951-964
- Sponsoring Org:
- National Science Foundation
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