Department of Fish and Wildlife Conservation, College of Natural Resources, Virginia Polytechnic Institute and State University Blacksburg, Virginia ; Freshwater Mollusk Conservation Center, Virginia Polytechnic Institute and State University Blacksburg, Virginia.
Department of Fish and Wildlife Conservation, College of Natural Resources, Virginia Polytechnic Institute and State University Blacksburg, Virginia.
Ecol Evol. 2015 Mar;5(5):1076-87. doi: 10.1002/ece3.1348. Epub 2015 Feb 13.
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.
联邦濒危坎伯兰扇贝(Epioblasma brevidens)经过繁殖和饲养,达到可标记大小(5-10 毫米),并被释放到田纳西州鲍威尔河,以增加一个遗留种群。在这些贻贝上使用被动集成标签(PIT)的方法极大地促进了检测过程。在 2 年的研究期间,在连续 9 次重新捕获的情况下,无论季节性如何,释放个体的总体平均检测概率和存活率分别达到 97.8%至 98.4%和 99.7%至 99.9%(每月)。通过贝叶斯方法纳入个体和季节性变化的非层次模型和层次模型在预测贻贝的检测概率和存活率方面表现相似。这是首次应用标记重捕法结合 PIT 标签和随机模型对实验室饲养贻贝进行的研究。个体异质性的定量分析允许检查人口动态的人口统计学差异和异质性的影响,尽管在这项研究中个体和季节性变化很小。我们的研究结果为实施该动物群的保护策略和其他物种或类似研究的框架提供了有用的信息。