Estimating encounter location distributions from animal tracking data
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1111/2041-210X.13597 http://hdl.handle.net/11449/207635 |
Resumo: | Ecologists have long been interested in linking individual behaviour with higher level processes. For motile species, this ‘upscaling’ is governed by how well any given movement strategy maximizes encounters with positive factors and minimizes encounters with negative factors. Despite the importance of encounter events for a broad range of ecological processes, encounter theory has not kept pace with developments in animal tracking or movement modelling. Furthermore, existing work has focused primarily on the relationship between animal movement and encounter rates while the relationship between individual movement and the spatial locations of encounter events in the environment has remained conspicuously understudied. Here, we bridge this gap by introducing a method for describing the long-term encounter location probabilities for movement within home ranges, termed the conditional distribution of encounters (CDE). We then derive this distribution, as well as confidence intervals, implement its statistical estimator into open-source software and demonstrate the broad ecological relevance of this distribution. We first use simulated data to show how our estimator provides asymptotically consistent estimates. We then demonstrate the general utility of this method for three simulation-based scenarios that occur routinely in biological systems: (a) a population of individuals with home ranges that overlap with neighbours; (b) a pair of individuals with a hard territorial border between their home ranges; and (c) a predator with a large home range that encompassed the home ranges of multiple prey individuals. Using GPS data from white-faced capuchins Cebus capucinus, tracked on Barro Colorado Island, Panama, and sleepy lizards Tiliqua rugosa, tracked in Bundey, South Australia, we then show how the CDE can be used to estimate the locations of territorial borders, identify key resources, quantify the potential for competitive or predatory interactions and/or identify any changes in behaviour that directly result from location-specific encounter probability. The CDE enables researchers to better understand the dynamics of populations of interacting individuals. Notably, the general estimation framework developed in this work builds straightforwardly off of home range estimation and requires no specialized data collection protocols. This method is now openly available via the ctmm R package. |
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Estimating encounter location distributions from animal tracking dataanimal movementCebus capucinuscontacthome rangeinteractionsTiliqua rugosaEcologists have long been interested in linking individual behaviour with higher level processes. For motile species, this ‘upscaling’ is governed by how well any given movement strategy maximizes encounters with positive factors and minimizes encounters with negative factors. Despite the importance of encounter events for a broad range of ecological processes, encounter theory has not kept pace with developments in animal tracking or movement modelling. Furthermore, existing work has focused primarily on the relationship between animal movement and encounter rates while the relationship between individual movement and the spatial locations of encounter events in the environment has remained conspicuously understudied. Here, we bridge this gap by introducing a method for describing the long-term encounter location probabilities for movement within home ranges, termed the conditional distribution of encounters (CDE). We then derive this distribution, as well as confidence intervals, implement its statistical estimator into open-source software and demonstrate the broad ecological relevance of this distribution. We first use simulated data to show how our estimator provides asymptotically consistent estimates. We then demonstrate the general utility of this method for three simulation-based scenarios that occur routinely in biological systems: (a) a population of individuals with home ranges that overlap with neighbours; (b) a pair of individuals with a hard territorial border between their home ranges; and (c) a predator with a large home range that encompassed the home ranges of multiple prey individuals. Using GPS data from white-faced capuchins Cebus capucinus, tracked on Barro Colorado Island, Panama, and sleepy lizards Tiliqua rugosa, tracked in Bundey, South Australia, we then show how the CDE can be used to estimate the locations of territorial borders, identify key resources, quantify the potential for competitive or predatory interactions and/or identify any changes in behaviour that directly result from location-specific encounter probability. The CDE enables researchers to better understand the dynamics of populations of interacting individuals. Notably, the general estimation framework developed in this work builds straightforwardly off of home range estimation and requires no specialized data collection protocols. This method is now openly available via the ctmm R package.Department of Biology The Irving K. Barber Faculty of Science The University of British ColumbiaSmithsonian Conservation Biology Institute National Zoological ParkICTP South American Institute for Fundamental Research & Instituto de Fisica Teorica – UNESPDepartment of Anthropology University of CaliforniaSmithsonian Tropical Research InstituteDepartment for the Ecology of Animal Societies Max Planck Institute of Animal BehaviorDepartment of Biology University of KonstanzCentre for the Advanced Study of Collective Behaviour University of KonstanzNorth Carolina Museum of Natural Sciences and North Carolina State UniversityCollege of Science and Engineering James Cook UniversityDepartment of Environmental Science and Policy University of California DavisSchool of Zoology Faculty of Life Sciences Tel Aviv UniversityDepartment of Biology University of MarylandCenter for Advanced Systems Understanding (CASUS)Helmholtz-Zentrum Dresden Rossendorf (HZDR)Department of Ecological Modelling Helmholtz Centre for Environmental Research (UFZ)ICTP South American Institute for Fundamental Research & Instituto de Fisica Teorica – UNESPThe University of British ColumbiaNational Zoological ParkUniversidade Estadual Paulista (Unesp)University of CaliforniaSmithsonian Tropical Research InstituteMax Planck Institute of Animal BehaviorUniversity of KonstanzNorth Carolina Museum of Natural Sciences and North Carolina State UniversityJames Cook UniversityUniversity of California DavisTel Aviv UniversityUniversity of MarylandCenter for Advanced Systems Understanding (CASUS)Helmholtz-Zentrum Dresden Rossendorf (HZDR)Helmholtz Centre for Environmental Research (UFZ)Noonan, Michael J.Martinez-Garcia, Ricardo [UNESP]Davis, Grace H.Crofoot, Margaret C.Kays, RolandHirsch, Ben T.Caillaud, DamienPayne, EricSih, AndrewSinn, David L.Spiegel, OrrFagan, William F.Fleming, Christen H.Calabrese, Justin M.2021-06-25T10:58:24Z2021-06-25T10:58:24Z2021-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1111/2041-210X.13597Methods in Ecology and Evolution.2041-210Xhttp://hdl.handle.net/11449/20763510.1111/2041-210X.135972-s2.0-85104578184Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengMethods in Ecology and Evolutioninfo:eu-repo/semantics/openAccess2021-10-23T17:45:50Zoai:repositorio.unesp.br:11449/207635Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-23T17:45:50Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Estimating encounter location distributions from animal tracking data |
title |
Estimating encounter location distributions from animal tracking data |
spellingShingle |
Estimating encounter location distributions from animal tracking data Noonan, Michael J. animal movement Cebus capucinus contact home range interactions Tiliqua rugosa |
title_short |
Estimating encounter location distributions from animal tracking data |
title_full |
Estimating encounter location distributions from animal tracking data |
title_fullStr |
Estimating encounter location distributions from animal tracking data |
title_full_unstemmed |
Estimating encounter location distributions from animal tracking data |
title_sort |
Estimating encounter location distributions from animal tracking data |
author |
Noonan, Michael J. |
author_facet |
Noonan, Michael J. Martinez-Garcia, Ricardo [UNESP] Davis, Grace H. Crofoot, Margaret C. Kays, Roland Hirsch, Ben T. Caillaud, Damien Payne, Eric Sih, Andrew Sinn, David L. Spiegel, Orr Fagan, William F. Fleming, Christen H. Calabrese, Justin M. |
author_role |
author |
author2 |
Martinez-Garcia, Ricardo [UNESP] Davis, Grace H. Crofoot, Margaret C. Kays, Roland Hirsch, Ben T. Caillaud, Damien Payne, Eric Sih, Andrew Sinn, David L. Spiegel, Orr Fagan, William F. Fleming, Christen H. Calabrese, Justin M. |
author2_role |
author author author author author author author author author author author author author |
dc.contributor.none.fl_str_mv |
The University of British Columbia National Zoological Park Universidade Estadual Paulista (Unesp) University of California Smithsonian Tropical Research Institute Max Planck Institute of Animal Behavior University of Konstanz North Carolina Museum of Natural Sciences and North Carolina State University James Cook University University of California Davis Tel Aviv University University of Maryland Center for Advanced Systems Understanding (CASUS) Helmholtz-Zentrum Dresden Rossendorf (HZDR) Helmholtz Centre for Environmental Research (UFZ) |
dc.contributor.author.fl_str_mv |
Noonan, Michael J. Martinez-Garcia, Ricardo [UNESP] Davis, Grace H. Crofoot, Margaret C. Kays, Roland Hirsch, Ben T. Caillaud, Damien Payne, Eric Sih, Andrew Sinn, David L. Spiegel, Orr Fagan, William F. Fleming, Christen H. Calabrese, Justin M. |
dc.subject.por.fl_str_mv |
animal movement Cebus capucinus contact home range interactions Tiliqua rugosa |
topic |
animal movement Cebus capucinus contact home range interactions Tiliqua rugosa |
description |
Ecologists have long been interested in linking individual behaviour with higher level processes. For motile species, this ‘upscaling’ is governed by how well any given movement strategy maximizes encounters with positive factors and minimizes encounters with negative factors. Despite the importance of encounter events for a broad range of ecological processes, encounter theory has not kept pace with developments in animal tracking or movement modelling. Furthermore, existing work has focused primarily on the relationship between animal movement and encounter rates while the relationship between individual movement and the spatial locations of encounter events in the environment has remained conspicuously understudied. Here, we bridge this gap by introducing a method for describing the long-term encounter location probabilities for movement within home ranges, termed the conditional distribution of encounters (CDE). We then derive this distribution, as well as confidence intervals, implement its statistical estimator into open-source software and demonstrate the broad ecological relevance of this distribution. We first use simulated data to show how our estimator provides asymptotically consistent estimates. We then demonstrate the general utility of this method for three simulation-based scenarios that occur routinely in biological systems: (a) a population of individuals with home ranges that overlap with neighbours; (b) a pair of individuals with a hard territorial border between their home ranges; and (c) a predator with a large home range that encompassed the home ranges of multiple prey individuals. Using GPS data from white-faced capuchins Cebus capucinus, tracked on Barro Colorado Island, Panama, and sleepy lizards Tiliqua rugosa, tracked in Bundey, South Australia, we then show how the CDE can be used to estimate the locations of territorial borders, identify key resources, quantify the potential for competitive or predatory interactions and/or identify any changes in behaviour that directly result from location-specific encounter probability. The CDE enables researchers to better understand the dynamics of populations of interacting individuals. Notably, the general estimation framework developed in this work builds straightforwardly off of home range estimation and requires no specialized data collection protocols. This method is now openly available via the ctmm R package. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-06-25T10:58:24Z 2021-06-25T10:58:24Z 2021-01-01 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1111/2041-210X.13597 Methods in Ecology and Evolution. 2041-210X http://hdl.handle.net/11449/207635 10.1111/2041-210X.13597 2-s2.0-85104578184 |
url |
http://dx.doi.org/10.1111/2041-210X.13597 http://hdl.handle.net/11449/207635 |
identifier_str_mv |
Methods in Ecology and Evolution. 2041-210X 10.1111/2041-210X.13597 2-s2.0-85104578184 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Methods in Ecology and Evolution |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1803046618935590912 |