Estimating encounter location distributions from animal tracking data

Detalhes bibliográficos
Autor(a) principal: Noonan, Michael J.
Data de Publicação: 2021
Outros Autores: 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.
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.
id UNSP_d8b7531f7ae50150999b3633d3195e15
oai_identifier_str oai:repositorio.unesp.br:11449/207635
network_acronym_str UNSP
network_name_str Repositório Institucional da UNESP
repository_id_str 2946
spelling 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