| Autor: |
Matthew J. Gould, Justin G. Clapp, Mark A. Haroldson, Cecily M. Costello, J. Joshua Nowak, Hans W. Martin, Michael R. Ebinger, Daniel D. Bjornlie, Daniel J. Thompson, Justin A. Dellinger, Matthew A. Mumma, Paul M. Lukacs, Frank T. van Manen |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
Global Ecology and Conservation, Vol 54, Iss , Pp e03133- (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2351-9894 |
| DOI: |
10.1016/j.gecco.2024.e03133 |
| Popis: |
Long-term wildlife research and monitoring programs strive to maintain consistent data collections and analytical methods. Incorporating new techniques is important but can render data sets incongruent and limit their potential to discern trends in demographic parameters. Integrated population models (IPMs) can address these limitations by combining data sources that may span different periods into a unified statistical framework while providing a holistic view of population dynamics. We developed an IPM in a Bayesian framework for grizzly bears (Ursus arctos) in the Greater Yellowstone Ecosystem. We coupled demographic data with multiple, independent population count data to link annual changes in abundance with vital rates over 4 decades (1983–2023). Abundance increased threefold from an estimated 270 individuals in 1984 to 1030 individuals in 2023. Parameter estimates indicated survival of bears ≥2 years of age was high, contributing to robust population growth during the 1980s (λ = 1.023 [50 % interquartile range = 0.993–1.082]) and 1990s (λ = 1.064 [1.023–1.103]). A slowing of population growth started around 2000 (2000s: λ = 1.030 [0.989–1.068]) and continued into the 2010s (λ = 1.021 [0.985–1.057]), due primarily to reductions in survival of bears |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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