{"title":"Identifying species traits that predict vulnerability to climate change.","authors":"Damien A Fordham","doi":"10.1017/ext.2024.24","DOIUrl":null,"url":null,"abstract":"<p><p>Accurately predicting the vulnerabilities of species to climate change requires a more detailed understanding of the functional and life-history traits that make some species more susceptible to declines and extinctions in shifting climates. This is because existing trait-based correlates of extinction risk from climate and environmental disturbances vary widely, often being idiosyncratic and context dependent. A powerful solution is to analyse the growing volume of biological data on changes in species ranges and abundances using process-explicit ecological models that run at fine temporal and spatial scales and across large geographical extents. These simulation-based approaches can unpack complex interactions between species' traits and climate and other threats. This enables species-responses to climatic change to be contextualised and integrated into future biodiversity projections and to be used to formulate and assess conservation policy goals. By providing a more complete understanding of the traits and contexts that regulate different responses of species to climate change, these process-driven approaches are likely to result in more certain predictions of the species that are most vulnerable to climate change.</p>","PeriodicalId":520449,"journal":{"name":"Cambridge prisms. Extinction","volume":"2 ","pages":"e21"},"PeriodicalIF":0.0000,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11895733/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cambridge prisms. Extinction","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1017/ext.2024.24","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Accurately predicting the vulnerabilities of species to climate change requires a more detailed understanding of the functional and life-history traits that make some species more susceptible to declines and extinctions in shifting climates. This is because existing trait-based correlates of extinction risk from climate and environmental disturbances vary widely, often being idiosyncratic and context dependent. A powerful solution is to analyse the growing volume of biological data on changes in species ranges and abundances using process-explicit ecological models that run at fine temporal and spatial scales and across large geographical extents. These simulation-based approaches can unpack complex interactions between species' traits and climate and other threats. This enables species-responses to climatic change to be contextualised and integrated into future biodiversity projections and to be used to formulate and assess conservation policy goals. By providing a more complete understanding of the traits and contexts that regulate different responses of species to climate change, these process-driven approaches are likely to result in more certain predictions of the species that are most vulnerable to climate change.