Abstract
AbstractThe Atlantic surfclam Spisula solidissima fishery, which spans the U.S. Northeast continental shelf, is among the most exposed to offshore wind energy development impacts because of the overlap of fishing grounds with wind energy lease areas, the hydraulic dredges used by the fishing vessels, and the location of vessel home ports relative to the fishing grounds. The Atlantic surfclam federal assessment survey is conducted using a commercial fishing vessel in locations that overlap with the offshore wind energy development. Once wind energy turbines, cables, and scour protection are installed, survey operations within wind energy lease areas may be curtailed or eliminated due to limits on vessel access, safety requirements, and assessment survey protocols. The impact of excluding the federal assessment survey from wind energy lease areas was investigated using a spatially explicit, agent‐based modeling framework that integrates Atlantic surfclam stock biology, fishery captain and fleet behavior, and federal assessment survey and management decisions. Simulations were designed to compare assessment estimates of spawning stock biomass (SSB) and fishing mortality (F) for scenarios that excluded the survey from (1) wind energy lease areas or (2) wind energy lease areas and potential wind energy lease areas (“call areas”). For the most restricted scenario, the simulated stock assessment estimated 17% lower SSB relative to an unrestricted survey, placing it below the SSB target. The simulated F increased by 7% but was still less than the accepted F threshold. Changes in biological reference points were driven by the inability to access the Atlantic surfclam biomass within the wind energy lease areas. Deviations in reference points reflected the proportion of the population excluded from the survey. Excluding the Atlantic surfclam assessment surveys from the regions designated for offshore wind development can alter long‐term stock assessments by increasing uncertainty in metrics that are used to set fishing quotas.
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