4.6 Article

The interim management procedure approach for assessed stocks: Responsive management advice and lower assessment frequency

期刊

FISH AND FISHERIES
卷 21, 期 3, 页码 663-679

出版社

WILEY
DOI: 10.1111/faf.12453

关键词

fisheries management; management strategy evaluation; simulation; stock assessment; total allowable catch

向作者/读者索取更多资源

Stock assessments are often used to provide management advice, such as a total allowable catch (TAC), to fishery managers. Many stocks are not assessed annually, and the TAC from the previous assessment is often maintained in years between assessments. We developed two interim management procedures (MPs) that update the estimate of current vulnerable biomass from a surveyed index of abundance to adjust the TAC from a previous assessment. These MPs differ in how they handle uncertainty in observed indices. Using closed-loop simulation, we evaluated the two interim MPs (with 10- and 5-year assessment intervals) against several status quo approaches: (1) an annual assessment, and (2) a stock assessment every 5 or 10 years with (a) fixed TACs or (b) projections between assessments. We evaluated performance across three life-history types and six operating model scenarios. The interim MPs performed similarly to annual assessments in terms of trends in biomass and yield, regardless of the assessment interval of the interim MPs. The interim MPs often produced more yield than the Fixed TAC MP with 10-year assessment intervals, for example, in depleted scenarios. The Fixed TAC MP performed more similarly to interim MPs when the assessment interval for the Fixed TAC MP was decreased to five years. The interim MPs can also perform well when circumstances arise that are not accounted for in the Projection MP. Our results show that interim MPs should be considered for infrequently assessed stocks or rebuilding stocks, and highlight potential cost savings of interim MPs over annual assessments.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据