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Taphonomic indicators are often used to assess time-since-death of skeletal remains. These indicators frequently have limited accuracy, resulting in the reliance of other methodologies to age remains. Arctica islandica, commonly known as the ocean quahog, is a relatively widespread bivalve in the North Atlantic, with an extended lifespan that often exceeds two hundred years; hence, their shells are often studied to evaluate climate change over time. This report evaluates taphonomic age using 117 A. islandica shells collected from the Mid-Atlantic Bight offshore of the Delmarva Peninsula with radiocarbon dates extending from 60–4,400 cal years BP. These shells had varying degrees of taphonomic alteration produced by discoloration and degradation of periostracum. To determine if a relationship exists between taphonomic condition and time-since-death, radiocarbon ages were compared with the amount of remaining periostracum and type of discoloration. Old shells (individuals that died long ago) were discolored orange with no periostracum while younger shells (individuals that died more recently) had their original color, with some periostracum. Both the disappearance of periostracum and appearance of discoloration followed a logistic process, with 50% of shells devoid of periostracum and 50% discolored in about 1,000 years. The logistic form of long-term taphonomic processes degrading shell condition is first reported here, as are the longest time series for taphonomic processes in death assemblages within the Holocene record. This relationship can be utilized for triage when deciding what shells to age from time-averaged assemblages, permitting more efficient application of expensive methods of aging such as radiocarbon dating.

Rising water temperatures along the northeastern U.S. continental shelf have resulted in an offshore range shift of the Atlantic surfclamSpisula solidissimato waters still occupied by ocean quahogsArctica islandica. Fishers presently are prohibited from landing both Atlantic surfclams and ocean quahogs in the same catch, thus limiting fishing to locations where the target species can be sorted on deck. Wind energy development on and around the fishing grounds will further restrict the fishery. A spatially explicit model of the Atlantic surfclam fishery (Spatially Explicit Fishery Economics Simulator) has the ability to simulate the consequences of fishery displacement due to wind energy development in combination with fishery and stock dynamics related to the species' overlap with ocean quahogs. Five sets of simulations were run to determine the effect of varying degrees of species overlap due to Atlantic surfclam range shifts in conjunction with fishing constraints due to wind farm development. Simulations tracked changes in relative stock status, fishery performance, and the economic consequences for the fishery. Compared to a business‐as‐usual scenario, all scenarios with less‐restrictive fishing penalties due to species overlap exhibited higher raw catch numbers but also greater reductions in revenue and increases in cost after the implementation of wind farms. This analysis serves to demonstrate the response of the Atlantic surfclam fishery to combined pressures from competing ocean uses and climate change and emphasizes the potential for economic disruption of fisheries as climate change interacts with the evolution of ocean management on the continental shelf.

The Atlantic surfclamSpisula solidissimafishery, 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 simulatedFincreased by 7% but was still less than the acceptedFthreshold. 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.