Integrated movement models for individual tracking and species distribution data
Abstract While the quantity, quality, and variety of movement data has increased, methods that jointly allow for population‐ and species‐level movement parameters to be estimated are still needed. We present a formal data integration approach to combine individual‐level movement and population‐level...
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| Format: | Article |
| Language: | English |
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Wiley
2025-02-01
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| Series: | Methods in Ecology and Evolution |
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| Online Access: | https://doi.org/10.1111/2041-210X.14482 |
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| author | Frances E. Buderman Ephraim M. Hanks Viviana Ruiz‐Gutierrez Michael Shull Robert K. Murphy David A. W. Miller |
| author_facet | Frances E. Buderman Ephraim M. Hanks Viviana Ruiz‐Gutierrez Michael Shull Robert K. Murphy David A. W. Miller |
| author_sort | Frances E. Buderman |
| collection | DOAJ |
| description | Abstract While the quantity, quality, and variety of movement data has increased, methods that jointly allow for population‐ and species‐level movement parameters to be estimated are still needed. We present a formal data integration approach to combine individual‐level movement and population‐level distribution data. We show how formal data integration can be used to improve precision of individual and population‐level movement parameters and allow additional population‐level metrics (e.g., connectivity) to be formally quantified. We describe three components needed for an Integrated Movement Model (IMM): a model for individual movement, a model for among‐individual heterogeneity, and a model to quantify changes in species distribution. We outline a general IMM framework and develop and apply a specific stochastic differential equation model to a case study of telemetry and species distribution data for golden eagles in western North American during spring migration. We estimate eagle movements during spring migration from data collected between 2011 and 2019. Individual heterogeneity in migration behaviour was modelled for two subpopulations, individuals that make significant northward migrations and those that remained in the southern Rocky Mountain region through the summer. As is the case with most tracking studies, the sample population of individual telemetered birds is not representative of the population and underrepresents the proportion of long‐distance migrants in the population. The IMM was able to provide a more biological accurate subpopulation structure using joint estimation. In addition, the integrated approach (a) improves accuracy of other estimated movement parameters, (b) allows us to estimate the proportion of migratory and non‐migratory birds in a given location and time, and (c) estimate future spatiotemporal distributions of birds given a wintering location, which provide estimates of seasonal connectivity and migratory routes. We demonstrate how IMMs can be successfully used to address the challenge of estimating accurate population‐level movement parameters. Our approach can be generalized to a broad range of available movement models and data types, allowing us to significantly improve our knowledge of migration ecology across taxonomic groups, and address population and continental level information needs for conservation and management. |
| format | Article |
| id | doaj-art-efc1e5e7f8704620bd60855a4be9a1b5 |
| institution | Kabale University |
| issn | 2041-210X |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Wiley |
| record_format | Article |
| series | Methods in Ecology and Evolution |
| spelling | doaj-art-efc1e5e7f8704620bd60855a4be9a1b52025-02-05T05:43:20ZengWileyMethods in Ecology and Evolution2041-210X2025-02-0116234536110.1111/2041-210X.14482Integrated movement models for individual tracking and species distribution dataFrances E. Buderman0Ephraim M. Hanks1Viviana Ruiz‐Gutierrez2Michael Shull3Robert K. Murphy4David A. W. Miller5Department of Ecosystem Science and Management Pennsylvania State University University Park Pennsylvania USADepartment of Statistics Pennsylvania State University University Park Pennsylvania USACornell Lab of Ornithology Cornell University Ithaca New York USADepartment of Statistics Pennsylvania State University University Park Pennsylvania USAEagle Environmental, Inc. Santa Fe New Mexico USADepartment of Ecosystem Science and Management Pennsylvania State University University Park Pennsylvania USAAbstract While the quantity, quality, and variety of movement data has increased, methods that jointly allow for population‐ and species‐level movement parameters to be estimated are still needed. We present a formal data integration approach to combine individual‐level movement and population‐level distribution data. We show how formal data integration can be used to improve precision of individual and population‐level movement parameters and allow additional population‐level metrics (e.g., connectivity) to be formally quantified. We describe three components needed for an Integrated Movement Model (IMM): a model for individual movement, a model for among‐individual heterogeneity, and a model to quantify changes in species distribution. We outline a general IMM framework and develop and apply a specific stochastic differential equation model to a case study of telemetry and species distribution data for golden eagles in western North American during spring migration. We estimate eagle movements during spring migration from data collected between 2011 and 2019. Individual heterogeneity in migration behaviour was modelled for two subpopulations, individuals that make significant northward migrations and those that remained in the southern Rocky Mountain region through the summer. As is the case with most tracking studies, the sample population of individual telemetered birds is not representative of the population and underrepresents the proportion of long‐distance migrants in the population. The IMM was able to provide a more biological accurate subpopulation structure using joint estimation. In addition, the integrated approach (a) improves accuracy of other estimated movement parameters, (b) allows us to estimate the proportion of migratory and non‐migratory birds in a given location and time, and (c) estimate future spatiotemporal distributions of birds given a wintering location, which provide estimates of seasonal connectivity and migratory routes. We demonstrate how IMMs can be successfully used to address the challenge of estimating accurate population‐level movement parameters. Our approach can be generalized to a broad range of available movement models and data types, allowing us to significantly improve our knowledge of migration ecology across taxonomic groups, and address population and continental level information needs for conservation and management.https://doi.org/10.1111/2041-210X.14482connectivitygolden eagleintegrated data modelmigrationmovement modelspecies distribution data |
| spellingShingle | Frances E. Buderman Ephraim M. Hanks Viviana Ruiz‐Gutierrez Michael Shull Robert K. Murphy David A. W. Miller Integrated movement models for individual tracking and species distribution data Methods in Ecology and Evolution connectivity golden eagle integrated data model migration movement model species distribution data |
| title | Integrated movement models for individual tracking and species distribution data |
| title_full | Integrated movement models for individual tracking and species distribution data |
| title_fullStr | Integrated movement models for individual tracking and species distribution data |
| title_full_unstemmed | Integrated movement models for individual tracking and species distribution data |
| title_short | Integrated movement models for individual tracking and species distribution data |
| title_sort | integrated movement models for individual tracking and species distribution data |
| topic | connectivity golden eagle integrated data model migration movement model species distribution data |
| url | https://doi.org/10.1111/2041-210X.14482 |
| work_keys_str_mv | AT francesebuderman integratedmovementmodelsforindividualtrackingandspeciesdistributiondata AT ephraimmhanks integratedmovementmodelsforindividualtrackingandspeciesdistributiondata AT vivianaruizgutierrez integratedmovementmodelsforindividualtrackingandspeciesdistributiondata AT michaelshull integratedmovementmodelsforindividualtrackingandspeciesdistributiondata AT robertkmurphy integratedmovementmodelsforindividualtrackingandspeciesdistributiondata AT davidawmiller integratedmovementmodelsforindividualtrackingandspeciesdistributiondata |