Application of a Bayesian hierarchical model to estimate trends in Atlantic harbor seal (Phoca vitulina vitulina) abundance in Maine, USA, 1993-2018

MARINE MAMMAL SCIENCE(2022)

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摘要
The population of harbor seals (Phoca vitulina vitulina) along the coast of Maine, U.S.A., has experienced rapid growth in abundance following passage of the Marine Mammal Protection Act in 1972 but current information on trends in abundance is lacking. In this study, we apply a Bayesian hierarchical model to aerial survey data of nonpups and pups. Prior to 2001, estimates of growth rates from 8-year moving averages reached a high of 2.1% and 9.4% per year with posterior probabilities of positive growth of .97 and >.99 for nonpups and pups, respectively. Between 2001 and 2012, estimated growth rates for nonpups decreased to a low of -1.9% per year with a posterior probability of negative growth of .95. Between 2012 and 2018, posterior estimates of growth were close to zero suggesting little change in abundance of nonpups. Estimates of growth for pups were close to zero between 2001 and 2012 but reached a low of -2.5% per year with a posterior probability of negative growth of 0.94 at the end of the time series suggesting a decrease in pup abundance between 2012 and 2018. The total abundance estimate for 2018 is 61,336 (CV = 0.08).
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关键词
Bayesian hierarchical model, harbor seals, informative priors, P, vitulina vitulina, trend analysis
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