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Coping with information gaps in stock productivity for rebuilding and achieving maximum sustainable yield for grouper–snapper fisheries
Author(s) -
Harford William J,
Sagarese Skyler R,
Karnauskas Mandy
Publication year - 2019
Publication title -
fish and fisheries
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.747
H-Index - 109
eISSN - 1467-2979
pISSN - 1467-2960
DOI - 10.1111/faf.12344
Subject(s) - maximum sustainable yield , stock (firearms) , fishing , fishery , fisheries management , demersal zone , stock assessment , environmental science , fish stock , business , environmental resource management , geography , biology , archaeology
Maintaining fish stocks at optimal levels is a goal of fisheries management worldwide; yet, this goal remains somewhat elusive, even in countries with well‐established fishery data collection, assessment and management systems. Achieving this goal often requires knowledge of stock productivity, which can be challenging to obtain due to both data limitations and the complexities of marine populations. Thus, scientific information can lag behind fishery policy expectations in this regard. Steepness of the stock–recruitment relationship affects delineation of target biomass level reference points, a problem which is often circumvented by using a proxy fishing mortality rate ( F ) in place of the rate associated with maximum sustainable yield ( F MSY ). Because MSY is achieved in the long term only if an F proxy is happenstance with F MSY , characterizing productivity information probabilistically can support reference point delineation. For demersal stocks of equatorial and tropical regions, we demonstrate how the use of a prior probability distribution for steepness can help identify suitable F proxies. F proxies that reduce spawning biomass per recruit to a target percentage of the unfished quantity (i.e., SPR ) of 40% to 50% SPR had the highest probabilities of achieving long‐term MSY . Rebuilding was addressed through closed‐loop simulation of broken‐stick harvest control rules. Similar biomass recovery times were demonstrated for these rules in comparison with more information‐intensive rebuilding plans. Our approach stresses science‐led advancement of policy through a lens of information limitations, which can make the assumptions behind rebuilding plans more transparent and align management expectations with biological outcomes.