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How can we track population trends when monitoring data are sparse? Population declines can go undetected, despite ongoing threats. For example, only one of every 200 harvested species are monitored. This gap leads to uncertainty about the seriousness of declines and hampers effective conservation. Collecting more data is important, but we can also make better use of existing information. Prior knowledge of physiology, life history, and community ecology can be used to inform population models. Additionally, in multispecies models, information can be shared among taxa based on phylogenetic, spatial, or temporal proximity. By exploiting generalities across species that share evolutionary or ecological characteristics within Bayesian hierarchical models, we can fill crucial gaps in the assessment of species' status with unparalleled quantitative rigor.
hierarchical models, Data Analysis, QL, Bayesian state-space models, Conservation of Natural Resources, Population Dynamics, extinction risk, Bayes Theorem, Biodiversity, Models, Biological, species assessment, integrated population models, Life History Traits, data-poor fisheries
hierarchical models, Data Analysis, QL, Bayesian state-space models, Conservation of Natural Resources, Population Dynamics, extinction risk, Bayes Theorem, Biodiversity, Models, Biological, species assessment, integrated population models, Life History Traits, data-poor fisheries
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| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 1% |
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