Muradian Melissa L, Branch Trevor A, Moffitt Steven D, Hulson Peter-John F
Quantitative Ecology and Resource Management, University of Washington, Seattle, Washington, United States of America.
School of Aquatic and Fishery Sciences, University of Washington, Seattle, Washington, United States of America.
PLoS One. 2017 Feb 21;12(2):e0172153. doi: 10.1371/journal.pone.0172153. eCollection 2017.
The Pacific herring (Clupea pallasii) population in Prince William Sound, Alaska crashed in 1993 and has yet to recover, affecting food web dynamics in the Sound and impacting Alaskan communities. To help researchers design and implement the most effective monitoring, management, and recovery programs, a Bayesian assessment of Prince William Sound herring was developed by reformulating the current model used by the Alaska Department of Fish and Game. The Bayesian model estimated pre-fishery spawning biomass of herring age-3 and older in 2013 to be a median of 19,410 mt (95% credibility interval 12,150-31,740 mt), with a 54% probability that biomass in 2013 was below the management limit used to regulate fisheries in Prince William Sound. The main advantages of the Bayesian model are that it can more objectively weight different datasets and provide estimates of uncertainty for model parameters and outputs, unlike the weighted sum-of-squares used in the original model. In addition, the revised model could be used to manage herring stocks with a decision rule that considers both stock status and the uncertainty in stock status.
阿拉斯加威廉王子湾的太平洋鲱（Clupea pallasii）种群于1993年崩溃，至今尚未恢复，这影响了该海湾的食物网动态，并对阿拉斯加社区产生了影响。为帮助研究人员设计并实施最有效的监测、管理和恢复计划，通过重新构建阿拉斯加鱼类和野生动物部目前使用的模型，对威廉王子湾的鲱鱼进行了贝叶斯评估。贝叶斯模型估计，2013年3龄及以上鲱鱼的捕捞前产卵生物量中位数为19410公吨（95%可信区间为12150 - 31740公吨），2013年生物量低于用于管理威廉王子湾渔业的管理限额的概率为54%。贝叶斯模型的主要优点是，与原始模型中使用的加权平方和不同，它可以更客观地权衡不同数据集，并为模型参数和输出提供不确定性估计。此外，修订后的模型可用于通过考虑种群状态和种群状态不确定性的决策规则来管理鲱鱼种群。
