Shifting trends: Detecting changes in cetacean population dynamics in shifting habitat.
The ability to monitor population dynamics and detect major changes in population trend is essential for wildlife conservation and management. However, this is often challenging for cetaceans as surveys typically cover only a portion of a population's range and conventional stock assessment met...
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| Autores principales: | , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Public Library of Science (PLoS)
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/4fa6fb5f4a9e43cb9598421d959a540e |
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| Sumario: | The ability to monitor population dynamics and detect major changes in population trend is essential for wildlife conservation and management. However, this is often challenging for cetaceans as surveys typically cover only a portion of a population's range and conventional stock assessment methods cannot then distinguish whether apparent changes in abundance reflect real changes in population size or shifts in distribution. We developed and tested methods for estimating population size and trend and detecting changes in population trend in the context of shifting habitat by integrating additional data into distance-sampling analysis. Previous research has shown that incorporating habitat information can improve population size estimates for highly mobile species with dynamic spatial distributions. Here, using simulated datasets representative of a large whale population, we demonstrate that incorporating individual mark-recapture data can increase the accuracy and precision of trend estimation and the power to distinguish whether apparent changes in abundance reflect changes in population trend or distribution shifts. We recommend that similar simulation studies are conducted for specific cetacean populations to assess the potential for detecting changes in population dynamics given available data. This approach is especially important wherever population change may be confounded with long-term change in distribution patterns associated with regime shifts or climate change. |
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