Suppr超能文献

评估模型高估了全球渔业的可持续性。

Stock assessment models overstate sustainability of the world's fisheries.

机构信息

Institute for Marine and Antarctic Studies, University of Tasmania, Hobart, TAS 7001, Australia.

Biology Department, University of Victoria, Victoria, BC V8P 5C2, Canada.

出版信息

Science. 2024 Aug 23;385(6711):860-865. doi: 10.1126/science.adl6282. Epub 2024 Aug 22.

Abstract

Effective fisheries management requires accurate estimates of stock biomass and trends; yet, assumptions in stock assessment models generate high levels of uncertainty and error. For 230 fisheries worldwide, we contrasted stock biomass estimates at the time of assessment with updated hindcast estimates modeled for the same year in later assessments to evaluate systematic over- or underestimation. For stocks that were overfished, low value, or located in regions with rising temperatures, historical biomass estimates were generally overstated compared with updated assessments. Moreover, rising trends reported for overfished stocks were often inaccurate. With consideration of bias identified retrospectively, 85% more stocks than currently recognized have likely collapsed below 10% of maximum historical biomass. The high uncertainty and bias in modeled stock estimates warrants much greater precaution by managers.

摘要

有效的渔业管理需要准确估计种群生物量和趋势;然而,种群评估模型中的假设会产生高水平的不确定性和误差。我们对比了全球 230 个渔业的数据,在同一时间评估了种群生物量的估计值,并对同年的后续评估进行了更新,以评估系统的高估或低估。对于过度捕捞、低值或位于温度上升地区的种群,与更新后的评估相比,历史生物量估计值通常偏高。此外,报告的过度捕捞种群的上升趋势往往不准确。考虑到回顾性识别的偏差,目前被认为已经崩溃的种群数量可能比历史上最大生物量的 10%还多 85%。模型中对种群估计的高度不确定性和偏差要求管理者更加谨慎。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验