Estimation of the maximum utilization area including home range and peripheral sites
Abstract There is increasing evidence that occasional utilization area (peripheral sites), in addition to typical utilization area (home range), is important for wildlife conservation and management. Here we estimated the maximum utilization area (MUA), including both typical and occasional utilizat...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-05-01
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| Series: | Ecology and Evolution |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/ece3.8893 |
| _version_ | 1817986378460299264 |
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| author | Kana Terayama Hiroshi Ebihara Hironori Seino Motomi Genkai‐Kato |
| author_facet | Kana Terayama Hiroshi Ebihara Hironori Seino Motomi Genkai‐Kato |
| author_sort | Kana Terayama |
| collection | DOAJ |
| description | Abstract There is increasing evidence that occasional utilization area (peripheral sites), in addition to typical utilization area (home range), is important for wildlife conservation and management. Here we estimated the maximum utilization area (MUA), including both typical and occasional utilization areas, based on asymptotic curves of utilization area plotted against sample size. In previous studies, these curves have conventionally been plots of cumulative utilization area versus sample size, but this cumulative method is sensitive to stochastic effects. We propose a new method based on simulation studies where outcomes of replicated simulations are averaged to reduce stochastic effects. In this averaged method, possible combinations of sample size with the same number of location data replicated from a dataset were averaged and applied to the curves of utilization area. The cumulative method resulted in a large variation of MUA estimates, depending on the start date as well as total sample size of the dataset. In the averaged method, MUA estimates were robust against changes in the start date and total sample size. The large variation of MUA estimates arose because location data on any day including the start date are affected by unpredictable effects associated with animal activity and environmental conditions. In the averaged method, replicates of sample size resulted in a reduction of temporal stochasticity, suggesting that the method stably provides reliable estimates for MUA. |
| first_indexed | 2024-04-14T00:08:33Z |
| format | Article |
| id | doaj.art-4f06e56d94cf469d92d86c865c962960 |
| institution | Directory Open Access Journal |
| issn | 2045-7758 |
| language | English |
| last_indexed | 2024-04-14T00:08:33Z |
| publishDate | 2022-05-01 |
| publisher | Wiley |
| record_format | Article |
| series | Ecology and Evolution |
| spelling | doaj.art-4f06e56d94cf469d92d86c865c9629602022-12-22T02:23:25ZengWileyEcology and Evolution2045-77582022-05-01125n/an/a10.1002/ece3.8893Estimation of the maximum utilization area including home range and peripheral sitesKana Terayama0Hiroshi Ebihara1Hironori Seino2Motomi Genkai‐Kato3Graduate School of Kuroshio Science Kochi University Kochi JapanWildlife Management Office Kobe JapanWildlife Management Office Kobe JapanGraduate School of Kuroshio Science Kochi University Kochi JapanAbstract There is increasing evidence that occasional utilization area (peripheral sites), in addition to typical utilization area (home range), is important for wildlife conservation and management. Here we estimated the maximum utilization area (MUA), including both typical and occasional utilization areas, based on asymptotic curves of utilization area plotted against sample size. In previous studies, these curves have conventionally been plots of cumulative utilization area versus sample size, but this cumulative method is sensitive to stochastic effects. We propose a new method based on simulation studies where outcomes of replicated simulations are averaged to reduce stochastic effects. In this averaged method, possible combinations of sample size with the same number of location data replicated from a dataset were averaged and applied to the curves of utilization area. The cumulative method resulted in a large variation of MUA estimates, depending on the start date as well as total sample size of the dataset. In the averaged method, MUA estimates were robust against changes in the start date and total sample size. The large variation of MUA estimates arose because location data on any day including the start date are affected by unpredictable effects associated with animal activity and environmental conditions. In the averaged method, replicates of sample size resulted in a reduction of temporal stochasticity, suggesting that the method stably provides reliable estimates for MUA.https://doi.org/10.1002/ece3.8893asymptotemaximum utilization areaminimum convex polygonperipherywildlife |
| spellingShingle | Kana Terayama Hiroshi Ebihara Hironori Seino Motomi Genkai‐Kato Estimation of the maximum utilization area including home range and peripheral sites Ecology and Evolution asymptote maximum utilization area minimum convex polygon periphery wildlife |
| title | Estimation of the maximum utilization area including home range and peripheral sites |
| title_full | Estimation of the maximum utilization area including home range and peripheral sites |
| title_fullStr | Estimation of the maximum utilization area including home range and peripheral sites |
| title_full_unstemmed | Estimation of the maximum utilization area including home range and peripheral sites |
| title_short | Estimation of the maximum utilization area including home range and peripheral sites |
| title_sort | estimation of the maximum utilization area including home range and peripheral sites |
| topic | asymptote maximum utilization area minimum convex polygon periphery wildlife |
| url | https://doi.org/10.1002/ece3.8893 |
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