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理解和预测种群对人为干扰的反应:当前方法与新机遇

Understanding and Predicting Population Response to Anthropogenic Disturbance: Current Approaches and Novel Opportunities.

作者信息

Speakman Cassie N, Bull Sarah, Cubaynes Sarah, Davis Katrina J, Devillard Sébastien, Fryxell John M, Gallagher Cara A, McHuron Elizabeth A, Rastello Kévan, Smallegange Isabel M, Salguero-Gómez Roberto, Bonnaud Elsa, Duchamp Christophe, Giraudoux Patrick, Lacombe Simon, Marneweck Courtney J, Schroll Louis, Tableau Adrien, Ruette Sandrine, Gimenez Olivier

机构信息

FRB-CESAB, Montpellier, France.

CEFE, Univ Montpellier, CNRS, EPHE, IRD, Montpellier, France.

出版信息

Ecol Lett. 2025 Aug;28(8):e70198. doi: 10.1111/ele.70198.

Abstract

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.

摘要

生物多样性的有效保护依赖于对野生动物种群及其栖息地的成功管理。而成功的管理又取决于我们理解并准确预测种群和群落如何应对人类活动导致的环境变化的能力。然而,量化这些压力源如何影响种群动态仍然具有挑战性。在这个交叉领域的另一个重大障碍是,根据数据类型、限制条件和预期目的,确定哪种定量方法最为合适。在此,我们对目前用于模拟人为干扰对野生动物种群影响的关键方法(如矩阵种群模型)和模型要素(如能量学)进行跨分类群概述。具体而言,我们将讨论这些建模方法在关键假设、结构和复杂性、最适合解决的问题以及数据要求方面有何不同。我们的目的是帮助克服可能在分类学专业中持续存在的一些方法偏见,识别应对现有建模挑战的新机会,并增进对人为干扰的直接和间接影响的科学理解。我们指导用户为不同的管理目的确定合适的模型配置,同时也提出模型开发和整合的关键优先事项。

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