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Scholarly Works, Freshwater Mollusk Conservation Center

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https://hdl.handle.net/10919/52252
Research articles, presentations, and other scholarship

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Browsing Scholarly Works, Freshwater Mollusk Conservation Center by Subject "Freshwater mussels"

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    Periodic growth and growth cessations in the federally endangered freshwater mussel Cumberlandian combshell using a hierarchical Bayesian approach
    Hua, Dan; Jiao, Yan; Neves, Richard; Jones, Jess W. (Inter-Research, 2016-12-29)
    Understanding and monitoring life history traits is often important in endangered species conservation. Populations of the endangered mussel Cumberlandian combshell Epioblasma brevidens have continued to decline in the Powell River, USA. Understanding and modeling mussel growth is critical for effective reintroduction of this endangered species. In this study, 2 yr old E. brevidens that were produced in our laboratory were released to the Powell River in 2009 to augment this declining population. A mark-recapture monitoring approach using passive integrated transponder (PIT) tags was used to assess the survival and growth of the released mussels. Hierarchical Bayesian growth models incorporating individual growth variations, periodic growth and growth cessations, along with multiple release occasions were developed and compared to the classic von Bertalanffy growth model. Our results showed that the hierarchical model that incorporated individual growth variation gave the best estimates of model parameters, yielding the lowest deviance information criterion value. Mussels exhibited different growth rates (K), including 0.015, 0.026, 0.110 and 0.050 (mo⁻¹), corresponding to the duration of laboratory culture (ages 2, 3 and 4 yr old) and a growth cessation (GC) for 5.98 mo, respectively. The other parameters of asymptotic length (L∞) and age at zero length (t₀) were 51.36 mm and −0.648 mo. The flexible structure of Bayesian hierarchical models allowed us to examine growth characteristics of E. brevidens in a changing environment to better understand the details of its growth and lifespan, thus providing useful data for conservation management.