Natasha Ellison, Jonathan R. Potts, B. Strickland, S. Demarais, Garrett M. Street
{"title":"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","authors":"Natasha Ellison, Jonathan R. Potts, B. Strickland, S. Demarais, Garrett M. Street","doi":"10.1002/wlb3.01211","DOIUrl":null,"url":null,"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.","PeriodicalId":54405,"journal":{"name":"Wildlife Biology","volume":null,"pages":null},"PeriodicalIF":1.7000,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Combining animal interactions and habitat selection into models of space use: a case study with white‐tailed deer\",\"authors\":\"Natasha Ellison, Jonathan R. Potts, B. Strickland, S. Demarais, Garrett M. Street\",\"doi\":\"10.1002/wlb3.01211\",\"DOIUrl\":null,\"url\":null,\"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. 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Combining animal interactions and habitat selection into models of space use: a case study with white‐tailed deer
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.
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.