Estimating Wildlife Density as a Function of Environmental Heterogeneity Using Unmarked Data
Recent developments to spatial-capture recapture models have allowed their use on species whose members are not uniquely identifiable from photographs by including individual identity as a latent, unobserved variable in the model. These ‘unmarked’ spatial capture recapture (uSCR) models have also be...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/14/5/1087 |
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| author | Thomas Connor Wildlife Division Emilio Tripp William T. Bean B. J. Saxon Jessica Camarena Asa Donahue Daniel Sarna-Wojcicki Luke Macaulay William Tripp Justin Brashares |
| author_facet | Thomas Connor Wildlife Division Emilio Tripp William T. Bean B. J. Saxon Jessica Camarena Asa Donahue Daniel Sarna-Wojcicki Luke Macaulay William Tripp Justin Brashares |
| author_sort | Thomas Connor |
| collection | DOAJ |
| description | Recent developments to spatial-capture recapture models have allowed their use on species whose members are not uniquely identifiable from photographs by including individual identity as a latent, unobserved variable in the model. These ‘unmarked’ spatial capture recapture (uSCR) models have also been extended to presence-absence data and modified to allow categorical environmental covariates on density, but a uSCR model, which allows fitting continuous environmental covariates to density, has yet to be formulated. In this paper, we fill this gap and present an extension to the uSCR modeling framework by modeling animal density on a discrete state space as a function of continuous environmental covariates and investigate a form of Bayesian variable selection to improve inference. We used an elk population in their winter range within Karuk Indigenous Territory in Northern California as a case study and found a positive credible effect of increasing forb/grass cover on elk density and a negative credible effect of increasing tree cover on elk density. We posit that our extensions to uSCR modeling increase its utility in a wide range of ecological and management applications in which spatial counts of wildlife can be derived and environmental heterogeneity acts as a control on animal density. |
| first_indexed | 2024-03-09T20:24:46Z |
| format | Article |
| id | doaj.art-ee248f40744d4824a42de61b27a894a6 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T20:24:46Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-ee248f40744d4824a42de61b27a894a62023-11-23T23:41:13ZengMDPI AGRemote Sensing2072-42922022-02-01145108710.3390/rs14051087Estimating Wildlife Density as a Function of Environmental Heterogeneity Using Unmarked DataThomas Connor0Wildlife Division1Emilio Tripp2William T. Bean3B. J. Saxon4Jessica Camarena5Asa Donahue6Daniel Sarna-Wojcicki7Luke Macaulay8William Tripp9Justin Brashares10Department of Environmental Science, Policy, and Management, University of California, Berkeley, CA 94720, USAKaruk Tribe, Department of Natural Resources, P.O. Box 282, Orleans, CA 95556, USAKaruk Tribe, Department of Natural Resources, P.O. Box 282, Orleans, CA 95556, USABiological Sciences Department, College of Science and Mathematics, San Luis Obispo, CA 93407, USAKaruk Tribe, Department of Natural Resources, P.O. Box 282, Orleans, CA 95556, USAKaruk Tribe, Department of Natural Resources, P.O. Box 282, Orleans, CA 95556, USAKaruk Tribe, Department of Natural Resources, P.O. Box 282, Orleans, CA 95556, USADepartment of Environmental Science, Policy, and Management, University of California, Berkeley, CA 94720, USADepartment of Environmental Science, Policy, and Management, University of California, Berkeley, CA 94720, USAKaruk Tribe, Department of Natural Resources, P.O. Box 282, Orleans, CA 95556, USADepartment of Environmental Science, Policy, and Management, University of California, Berkeley, CA 94720, USARecent developments to spatial-capture recapture models have allowed their use on species whose members are not uniquely identifiable from photographs by including individual identity as a latent, unobserved variable in the model. These ‘unmarked’ spatial capture recapture (uSCR) models have also been extended to presence-absence data and modified to allow categorical environmental covariates on density, but a uSCR model, which allows fitting continuous environmental covariates to density, has yet to be formulated. In this paper, we fill this gap and present an extension to the uSCR modeling framework by modeling animal density on a discrete state space as a function of continuous environmental covariates and investigate a form of Bayesian variable selection to improve inference. We used an elk population in their winter range within Karuk Indigenous Territory in Northern California as a case study and found a positive credible effect of increasing forb/grass cover on elk density and a negative credible effect of increasing tree cover on elk density. We posit that our extensions to uSCR modeling increase its utility in a wide range of ecological and management applications in which spatial counts of wildlife can be derived and environmental heterogeneity acts as a control on animal density.https://www.mdpi.com/2072-4292/14/5/1087SECRcapture-recapturecamera trappingpopulation ecologylandscape ecologywildlife management |
| spellingShingle | Thomas Connor Wildlife Division Emilio Tripp William T. Bean B. J. Saxon Jessica Camarena Asa Donahue Daniel Sarna-Wojcicki Luke Macaulay William Tripp Justin Brashares Estimating Wildlife Density as a Function of Environmental Heterogeneity Using Unmarked Data Remote Sensing SECR capture-recapture camera trapping population ecology landscape ecology wildlife management |
| title | Estimating Wildlife Density as a Function of Environmental Heterogeneity Using Unmarked Data |
| title_full | Estimating Wildlife Density as a Function of Environmental Heterogeneity Using Unmarked Data |
| title_fullStr | Estimating Wildlife Density as a Function of Environmental Heterogeneity Using Unmarked Data |
| title_full_unstemmed | Estimating Wildlife Density as a Function of Environmental Heterogeneity Using Unmarked Data |
| title_short | Estimating Wildlife Density as a Function of Environmental Heterogeneity Using Unmarked Data |
| title_sort | estimating wildlife density as a function of environmental heterogeneity using unmarked data |
| topic | SECR capture-recapture camera trapping population ecology landscape ecology wildlife management |
| url | https://www.mdpi.com/2072-4292/14/5/1087 |
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