Cassie N. Speakman, Sarah Bull, Sarah Cubaynes, Katrina J. Davis, Sébastien Devillard, John M. Fryxell, Cara A. Gallagher, Elizabeth A. McHuron, Kévan Rastello, Isabel M. Smallegange, Roberto Salguero-Gómez, Elsa Bonnaud, Christophe Duchamp, Patrick Giraudoux, Simon Lacombe, Courtney J. Marneweck, Louis Schroll, Adrien Tableau, Sandrine Ruette, Olivier Gimenez
{"title":"理解和预测种群对人为干扰的反应:当前的方法和新的机会","authors":"Cassie N. Speakman, Sarah Bull, Sarah Cubaynes, Katrina J. Davis, Sébastien Devillard, John M. Fryxell, Cara A. Gallagher, Elizabeth A. McHuron, Kévan Rastello, Isabel M. Smallegange, Roberto Salguero-Gómez, Elsa Bonnaud, Christophe Duchamp, Patrick Giraudoux, Simon Lacombe, Courtney J. Marneweck, Louis Schroll, Adrien Tableau, Sandrine Ruette, Olivier Gimenez","doi":"10.1111/ele.70198","DOIUrl":null,"url":null,"abstract":"<p>Effective conservation of biodiversity depends on the successful management of wildlife populations and their habitats. Successful management, in turn, depends on our ability to understand and accurately forecast how populations and communities respond to human-induced changes in their environments. However, quantifying how these stressors impact population dynamics remains challenging. Another significant hurdle at this interface is determining which quantitative approach(es) are most appropriate given data types, constraints and the intended purpose. Here, we provide a cross-taxa overview of key methodological approaches (e.g., matrix population models) and model elements (e.g., energetics) that are currently used to model the effects of anthropogenic disturbance on wildlife populations. Specifically, we discuss how these modelling approaches differ in their key assumptions, in their structure and complexity, in the questions they are best poised to address and in their data requirements. Our intention is to help overcome some of the methodological biases that might persist across taxonomic specialisations, identify new opportunities to address existing modelling challenges and improve scientific understanding of the direct and indirect impacts of anthropogenic disturbance. We guide users through the identification of appropriate model configurations for different management purposes, while also suggesting key priorities for model development and integration.</p>","PeriodicalId":161,"journal":{"name":"Ecology Letters","volume":"28 8","pages":""},"PeriodicalIF":7.9000,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/ele.70198","citationCount":"0","resultStr":"{\"title\":\"Understanding and Predicting Population Response to Anthropogenic Disturbance: Current Approaches and Novel Opportunities\",\"authors\":\"Cassie N. Speakman, Sarah Bull, Sarah Cubaynes, Katrina J. Davis, Sébastien Devillard, John M. Fryxell, Cara A. Gallagher, Elizabeth A. McHuron, Kévan Rastello, Isabel M. Smallegange, Roberto Salguero-Gómez, Elsa Bonnaud, Christophe Duchamp, Patrick Giraudoux, Simon Lacombe, Courtney J. 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Understanding and Predicting Population Response to Anthropogenic Disturbance: Current Approaches and Novel Opportunities
Effective conservation of biodiversity depends on the successful management of wildlife populations and their habitats. Successful management, in turn, depends on our ability to understand and accurately forecast how populations and communities respond to human-induced changes in their environments. However, quantifying how these stressors impact population dynamics remains challenging. Another significant hurdle at this interface is determining which quantitative approach(es) are most appropriate given data types, constraints and the intended purpose. Here, we provide a cross-taxa overview of key methodological approaches (e.g., matrix population models) and model elements (e.g., energetics) that are currently used to model the effects of anthropogenic disturbance on wildlife populations. Specifically, we discuss how these modelling approaches differ in their key assumptions, in their structure and complexity, in the questions they are best poised to address and in their data requirements. Our intention is to help overcome some of the methodological biases that might persist across taxonomic specialisations, identify new opportunities to address existing modelling challenges and improve scientific understanding of the direct and indirect impacts of anthropogenic disturbance. We guide users through the identification of appropriate model configurations for different management purposes, while also suggesting key priorities for model development and integration.
期刊介绍:
Ecology Letters serves as a platform for the rapid publication of innovative research in ecology. It considers manuscripts across all taxa, biomes, and geographic regions, prioritizing papers that investigate clearly stated hypotheses. The journal publishes concise papers of high originality and general interest, contributing to new developments in ecology. Purely descriptive papers and those that only confirm or extend previous results are discouraged.