Evidence of ecosystem overfishing in U.S. large marine ecosystems
Author(s) -
Jason S. Link
Publication year - 2021
Publication title -
ices journal of marine science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.348
H-Index - 117
eISSN - 1095-9289
pISSN - 1054-3139
DOI - 10.1093/icesjms/fsab185
Subject(s) - overfishing , marine ecosystem , ecosystem , fishing , trophic level , fishery , environmental science , ecosystem based management , environmental resource management , stock assessment , ecology , biology
Marine capture fisheries in the U.S. are important from a societal, cultural, economic, and ecological perspective. Although fisheries in the U.S. are generally well-managed, they still face some challenges as do most fisheries around the world. To address these challenges, a broader, more systematic approach is useful. There is a global need to develop measures of ecosystem overfishing (EOF) that detect overfishing of an entire ecosystem using readily available data and based on widely repeatable patterns. These EOF indicators extend the thinking beyond single stock overfishing to an entire ecosystem and are largely based on well-established trophic theory. Moreover, these EOF indicators need to be germane for both data rich and especially data limited situations, easily interpretable, and relatively simple to calculate. Here, I present the results of several of these indicators—the Ryther, Fogarty, and Friedland indices—as well as indices based on cumulative biomass-Trophic Level curve parameters for eight U.S. Large Marine Ecosystems (LMEs). Significantly, all these EOF indicators also have thresholds beyond which EOF is indicated, particularly when coupled with other evidence. Evidence for EOF is suggested for two of the eight U.S. LMEs. Even apart from EOF thresholds, detecting whether EOF is occurring, or how debatable the proposed EOF thresholds are, there are multiple benefits from monitoring these ecosystem-level indicators. Detecting patterns and trends in overall fishing changes for an ecosystem is chief among them. Additionally, EOF indicators detected changes in these LMEs at least 2–3 years, even up to 5 years prior to major impacts that might not be identified by piecing together fishing impacts on a stock-by-stock basis; thus, the EOF indicators could serve as an early warning signal. I propose that instead of starting with the history of which stocks have been assessed or even with what we deem most valuable, we look at the entire system of fisheries in an LME and if EOF is detected, explore means to address excess fishing pressure systematically before delving into the details of specific stocks. I conclude that EOF measures need to be monitored, EOF thresholds refined, and if EOF is detected then the means to mitigate total fishing pressure in an ecosystem should be explored.
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