Making ecological indicators management ready: Assessing the specificity, sensitivity, and threshold response of ecological indicators

垂钓 环境科学 海洋生态系统 生态系统 生态指标 生物量(生态学) 渔业管理 营养水平 渔业 生态学 环境资源管理 过度捕捞 持续性 生物
作者
Caihong Fu,Yi Xu,Alida Bundy,Arnaud Grüss,Marta Coll,Johanna J. Heymans,Elizabeth A. Fulton,Lynne Shannon,Ghassen Halouani,Laure Velez,Ekin Akoğlu,Christopher P. Lynam,Yunne‐Jai Shin
出处
期刊:Ecological Indicators [Elsevier BV]
卷期号:105: 16-28 被引量:60
标识
DOI:10.1016/j.ecolind.2019.05.055
摘要

Moving toward ecosystem-based fisheries management (EBFM) necessitates a suite of ecological indicators that are responsive to fishing pressure, capable of tracking changes in the state of marine ecosystems, and related to management objectives. In this study, we employed the gradient forest method to assess the performance of 14 key ecological indicators in terms of specificity, sensitivity and the detection of thresholds for EBFM across ten marine ecosystems using four modelling frameworks (Ecopath with Ecosim, OSMOSE, Atlantis, and a multi-species size-spectrum model). Across seven of the ten ecosystems, high specificity to fishing pressure was found for most of the 14 indicators. The indicators biomass to fisheries catch ratio (B/C), mean lifespan and trophic level of fish community were found to have wide utility for evaluating fishing impacts. The biomass indicators, which have been identified as Essential Ocean Variables by the Global Ocean Observing System (GOOS), had lower performance for evaluating fishing impacts, yet they were most sensitive to changes in primary productivity. The indicator B/C was most sensitive to low levels of fishing pressure with a generally consistent threshold response around 0.4*FMSY (fishing mortality rate at maximum sustainable yield) across nine of the ten ecosystems. Over 50% of the 14 indicators had threshold responses at, or below ∼0.6* FMSY for most ecosystems, indicating that these ecosystems would have already crossed a threshold for most indicators when fished at FMSY. This research provides useful insights on the performance of indicators, which contribute to facilitating the worldwide move toward EBFM.
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