Combining animal interactions and habitat selection into models of space use: a case study with white‐tailed deer

IF 1.7 3区 生物学 Q3 ECOLOGY Wildlife Biology Pub Date : 2024-02-08 DOI:10.1002/wlb3.01211
Natasha Ellison, Jonathan R. Potts, B. Strickland, S. Demarais, Garrett M. Street
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Abstract

Animals determine their daily movement trajectories in response to a network of ecological processes, including interactions with other organisms, their memories of previous events, and the changing environment. These combine to cause the emergent space use patterns observed over longer periods of time, such as a whole season. Understanding which processes cause these patterns to emerge, and how, requires a process‐based modelling approach. Individual‐based decisions can be described as a system of partial‐differential equations (PDEs) to produce a dynamic description of space use built from the underlying movement process. Here we combine PDE‐based models with step‐selection analysis to investigate the combined effects of three established ecological processes that partially shape movement and space use: 1) a heterogeneous environment; 2) the environmental markings of moving conspecifics; and 3) the memory of direct interactions with conspecifics. We apply this framework to a large GPS‐based dataset of white‐tailed deer Odocoileus virginianus in the southeastern US. We fit models at the population level to provide predictive models, then tailor these to fit individual deer. We specifically incorporate relationships between each possible pair of deer and define each animal's responses to their unique local environments using separate integrated step‐selection analyses. We show how individual movements and decisions yield emergent patterns in animal distributions, and we provide a full generalised description of the framework so that it may be applied to any species simultaneously responding to multiple potentially interacting stimuli (e.g. sociality, morphology, etc.). We found that the population of bucks had highly varied preferences for vegetation, but were shaping their space use in response to conspecific interactions, dependent on the individual relationships between two deer. We advocate for increased consideration of individual‐based movement rules as determinants of realized animal space use, and particularly how these affect emergent distributions of entire species.
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将动物互动和栖息地选择纳入空间利用模型:白尾鹿案例研究
动物是根据一系列生态过程(包括与其他生物的相互作用、对以往事件的记忆以及不断变化的环境)来决定其日常活动轨迹的。这些过程结合在一起,就形成了在较长时期(如整个季节)内观察到的空间利用模式。要了解是哪些过程导致了这些模式的出现以及如何出现,就需要采用基于过程的建模方法。基于个体的决策可以描述为一个偏微分方程(PDE)系统,从而从基本运动过程中产生空间使用的动态描述。在这里,我们将基于偏微分方程的模型与阶跃选择分析相结合,以研究三个部分形成运动和空间利用的既定生态过程的综合影响:1)异质环境;2)移动的同类的环境标记;3)与同类直接互动的记忆。我们将这一框架应用于美国东南部基于 GPS 的大型白尾鹿数据集。我们在种群水平上拟合模型以提供预测模型,然后对这些模型进行调整以适应鹿个体。我们特别纳入了每对可能的鹿之间的关系,并通过单独的综合阶跃选择分析确定了每种动物对其独特的当地环境的反应。我们展示了个体运动和决策如何产生动物分布的新模式,并对该框架进行了全面的概括性描述,以便将其应用于同时对多种可能相互作用的刺激(如社会性、形态等)做出反应的任何物种。我们发现,公鹿种群对植被的偏好差异很大,但它们会根据同种鹿之间的相互作用来调整空间利用,这取决于两只鹿之间的个体关系。我们主张更多地考虑基于个体的运动规则,将其作为实现动物空间利用的决定因素,特别是考虑这些规则如何影响整个物种的新兴分布。
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来源期刊
Wildlife Biology
Wildlife Biology 生物-动物学
CiteScore
4.30
自引率
0.00%
发文量
33
审稿时长
>12 weeks
期刊介绍: WILDLIFE BIOLOGY is a high-quality scientific forum directing concise and up-to-date information to scientists, administrators, wildlife managers and conservationists. The journal encourages and welcomes original papers, short communications and reviews written in English from throughout the world. The journal accepts theoretical, empirical, and practical articles of high standard from all areas of wildlife science with the primary task of creating the scientific basis for the enhancement of wildlife management practices. Our concept of ''wildlife'' mainly includes mammal and bird species, but studies on other species or phenomena relevant to wildlife management are also of great interest. We adopt a broad concept of wildlife management, including all structures and actions with the purpose of conservation, sustainable use, and/or control of wildlife and its habitats, in order to safeguard sustainable relationships between wildlife and other human interests.
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