Large-scale distribution models for optimal prediction of Eastern black rail habitat within tidal ecosystems
Eastern black rails (Laterallus jamaicensis jamaicensis) are among the rarest and least-studied birds in North America and were recently listed as threatened under the U.S. Endangered Species Act. Spatial models that predict habitat quality across the subspecies range are therefore needed to inform...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-10-01
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| Series: | Global Ecology and Conservation |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2351989422002244 |
| _version_ | 1811294220753829888 |
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| author | Bryan S. Stevens Courtney J. Conway Kirsten Luke Aimee Weldon Christine E. Hand Amy Schwarzer Fletcher Smith Craig Watson Bryan D. Watts |
| author_facet | Bryan S. Stevens Courtney J. Conway Kirsten Luke Aimee Weldon Christine E. Hand Amy Schwarzer Fletcher Smith Craig Watson Bryan D. Watts |
| author_sort | Bryan S. Stevens |
| collection | DOAJ |
| description | Eastern black rails (Laterallus jamaicensis jamaicensis) are among the rarest and least-studied birds in North America and were recently listed as threatened under the U.S. Endangered Species Act. Spatial models that predict habitat quality across the subspecies range are therefore needed to inform conservation, recovery, and monitoring efforts for this rare bird. We used data from 47,585 call-broadcast surveys collected at 7906 sites over a 3-decade period (1990s, 2000s, 2010s; 23 total years) to build species distribution models for eastern black rails. We used hierarchical Bayesian occupancy models and predictive model selection to develop multi-scale models that optimally predict habitat suitability for eastern black rails within tidal wetlands while also accounting for imperfect detection of these cryptic birds during field surveys. We also used raster regression techniques to translate model predictions into 30-m resolution maps of habitat suitability for eastern black rails within tidal wetlands along the eastern seaboard of the United States. The model predicted suitability of breeding habitat as a function of wetland attributes (e.g., cover of high marsh and terrestrial border), hydrologic modification, and disturbance from human development measured over multiple spatial scales. We also found differences in habitat relationships for eastern black rails when compared to models that included both North American subspecies of black rail. Important results included negative effects of shrub-scrub wetlands, and strong positive effects of high marsh, terrestrial border, and impoundments on breeding season occupancy. Our study provides an example of integrating detection-non-detection data and modern statistical methods to build predictive distribution models for an extremely rare species, while also providing rigorous predictions of breeding habitat quality for the eastern black rail within tidal wetlands. These models will facilitate optimal monitoring, habitat conservation, and recovery planning efforts for eastern black rails and provide a foundation for future research and conservation of this imperiled bird. |
| first_indexed | 2024-04-13T05:14:10Z |
| format | Article |
| id | doaj.art-e05d553e084b43468b8b5f5d2325d2b7 |
| institution | Directory Open Access Journal |
| issn | 2351-9894 |
| language | English |
| last_indexed | 2024-04-13T05:14:10Z |
| publishDate | 2022-10-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Global Ecology and Conservation |
| spelling | doaj.art-e05d553e084b43468b8b5f5d2325d2b72022-12-22T03:00:57ZengElsevierGlobal Ecology and Conservation2351-98942022-10-0138e02222Large-scale distribution models for optimal prediction of Eastern black rail habitat within tidal ecosystemsBryan S. Stevens0Courtney J. Conway1Kirsten Luke2Aimee Weldon3Christine E. Hand4Amy Schwarzer5Fletcher Smith6Craig Watson7Bryan D. Watts8Idaho Cooperative Fish and Wildlife Research Unit, Department of Fish and Wildlife Sciences, University of Idaho, Moscow, ID 83844-1141, USA; Correspondence to: Idaho Cooperative Fish and Wildlife Research Unit, 875 Perimeter Drive MS 1141, Moscow, ID 83844-1141, USA.US Geological Survey, Idaho Cooperative Fish and Wildlife Research Unit, University of Idaho, Moscow, ID 83844-1141, USAAtlantic Coast Joint Venture, US Fish and Wildlife Service, Panama City, FL 32405, USAAtlantic Coast Joint Venture, US Fish and Wildlife Service, Hadley, MA 01035, USASouth Carolina Department of Natural Resources, Green Pond, SC 29446, USAFlorida Fish and Wildlife Conservation Commission, Gainesville, FL 32601, USAGeorgia Department of Natural Resources, Brunswick, GA 31520, USAAtlantic Coast Joint Venture, US Fish and Wildlife Service, Charleston, SC 29407, USACenter for Conservation Biology, College of William & Mary, Williamsburg, VA 23187, USAEastern black rails (Laterallus jamaicensis jamaicensis) are among the rarest and least-studied birds in North America and were recently listed as threatened under the U.S. Endangered Species Act. Spatial models that predict habitat quality across the subspecies range are therefore needed to inform conservation, recovery, and monitoring efforts for this rare bird. We used data from 47,585 call-broadcast surveys collected at 7906 sites over a 3-decade period (1990s, 2000s, 2010s; 23 total years) to build species distribution models for eastern black rails. We used hierarchical Bayesian occupancy models and predictive model selection to develop multi-scale models that optimally predict habitat suitability for eastern black rails within tidal wetlands while also accounting for imperfect detection of these cryptic birds during field surveys. We also used raster regression techniques to translate model predictions into 30-m resolution maps of habitat suitability for eastern black rails within tidal wetlands along the eastern seaboard of the United States. The model predicted suitability of breeding habitat as a function of wetland attributes (e.g., cover of high marsh and terrestrial border), hydrologic modification, and disturbance from human development measured over multiple spatial scales. We also found differences in habitat relationships for eastern black rails when compared to models that included both North American subspecies of black rail. Important results included negative effects of shrub-scrub wetlands, and strong positive effects of high marsh, terrestrial border, and impoundments on breeding season occupancy. Our study provides an example of integrating detection-non-detection data and modern statistical methods to build predictive distribution models for an extremely rare species, while also providing rigorous predictions of breeding habitat quality for the eastern black rail within tidal wetlands. These models will facilitate optimal monitoring, habitat conservation, and recovery planning efforts for eastern black rails and provide a foundation for future research and conservation of this imperiled bird.http://www.sciencedirect.com/science/article/pii/S2351989422002244Bayesian model selection, habitat modelhierarchical occupancy model, marsh bird, predicting habitat qualityspecies distribution model |
| spellingShingle | Bryan S. Stevens Courtney J. Conway Kirsten Luke Aimee Weldon Christine E. Hand Amy Schwarzer Fletcher Smith Craig Watson Bryan D. Watts Large-scale distribution models for optimal prediction of Eastern black rail habitat within tidal ecosystems Global Ecology and Conservation Bayesian model selection, habitat model hierarchical occupancy model, marsh bird, predicting habitat quality species distribution model |
| title | Large-scale distribution models for optimal prediction of Eastern black rail habitat within tidal ecosystems |
| title_full | Large-scale distribution models for optimal prediction of Eastern black rail habitat within tidal ecosystems |
| title_fullStr | Large-scale distribution models for optimal prediction of Eastern black rail habitat within tidal ecosystems |
| title_full_unstemmed | Large-scale distribution models for optimal prediction of Eastern black rail habitat within tidal ecosystems |
| title_short | Large-scale distribution models for optimal prediction of Eastern black rail habitat within tidal ecosystems |
| title_sort | large scale distribution models for optimal prediction of eastern black rail habitat within tidal ecosystems |
| topic | Bayesian model selection, habitat model hierarchical occupancy model, marsh bird, predicting habitat quality species distribution model |
| url | http://www.sciencedirect.com/science/article/pii/S2351989422002244 |
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