Landbird trends in protected areas using time‐to‐event occupancy models
| Autor: | Julien St-Amand, James Kimo Rogala, Cameron Gillies, Rhonda Owchar, Jennifer L. Greenwood, Anne Forshner, Brenda Shepherd, Jesse Whittington, Barb Johnston, Derek Petersen |
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| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Ecology
biology Occupancy Event (relativity) Species distribution detection Climate change biology.organism_classification songbird Hierarchical database model Songbird Geography climate change lcsh:QH540-549.5 hierarchical model protected areas lcsh:Ecology Cartography Ecology Evolution Behavior and Systematics occupancy |
| Zdroj: | Ecosphere, Vol 10, Iss 11, Pp n/a-n/a (2019) |
| ISSN: | 2150-8925 |
| Popis: | Global populations of wildlife are affected by human activity, land cover change, and climate change. Long‐term monitoring programs across large spatial scales are required to understand how these and other factors affect wildlife populations. Occupancy models are frequently used to monitor changes in species distribution while accounting for imperfect detection. Occupancy surveys can be expensive because they typically require multiple surveys to estimate the probability of detection. Time‐to‐detection models provide a promising approach for estimating occupancy because they require just one visit; however, few studies have tested or applied these models to wildlife data. We ran a simulation study to assess biases of time‐to‐event occupancy models for standardized avian point‐count surveys and then applied the models to 10 yr of data. Time to first detection occupancy models had minimal bias and almost nominal coverage for species with a mean time to first detection |
| Databáze: | OpenAIRE |
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