Use of PIT tags to assess individual heterogeneity of laboratory‐reared juveniles of the endangered Cumberlandian combshell (Epioblasma brevidens) in a mark–recapture study

Ecology and Evolution

Dan Hua¹  Yan Jiao¹  Richard Neves¹ 

[1] Department of Fish and Wildlife Conservation, College of Natural Resources, Virginia Polytechnic Institute and State University, Blacksburg, Virginia

关键词: Bayesian;    Cumberlandian combshell (Epioblasma brevidens);    detection probability;    heterogeneity;    hierarchic model;    mark–recapture;    PIT tag;    survival rate;   

DOI  :  10.1002/ece3.1348

来源: Wiley

【 摘 要 】

Abstract

The federally endangered Cumberlandian combshell (Epioblasma brevidens) was propagated and reared to taggable size (5–10 mm), and released to the Powell River, Tennessee, to augment a relict population. Methodology using passive integrated transponder (PIT) tags on these mussels greatly facilitated the detection process. The overall mean detection probability and survival rate of released individuals reached 97.8 to 98.4% and 99.7 to 99.9% (per month), respectively, during nine successive recapture occasions in the 2-year study period, regardless of seasonality. Nonhierarchical models and hierarchical models incorporating individual and seasonal variations through a Bayesian approach were compared and resulted in similar performance of prediction for detection probability and survival rate of mussels. This is the first study to apply the mark–recapture method to laboratory-reared mussels using PIT tags and stochastic models. Quantitative analyses for individual heterogeneity allowed examination of demographic variance and effects of heterogeneity on population dynamics, although the individual and seasonal variations were small in this study. Our results provide useful information in implementing conservation strategies of this faunal group and a framework for other species or similar studies.

【 授权许可】

CC BY   
© 2015 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.