Resale or republication not permitted without written consent of the publisherOyster reefs reduce eutrophication by enhancing denitrification rates and assimilating nutrients into macrofauna.

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Estuaries around the world are in a state of decline following decades or more of overfishing, pollution, and climate change. Oysters (Ostreidae), ecosystem engineers in many estuaries, influence water quality, construct habitat, and provide food for humans and wildlife. In North America's Chesapeake Bay, once-thriving eastern oyster (Crassostrea virginica) populations have declined dramatically, making their restoration and conservation extremely challenging. Here we present data on oyster size and human harvest from Chesapeake Bay archaeological sites spanning ∼3,500 y of Native American, colonial, and historical occupation. We compare oysters from archaeological sites with Pleistocene oyster reefs that existed before human harvest, modern oyster reefs, and other records of human oyster harvest from around the world. Native American fisheries were focused on nearshore oysters and were likely harvested at a rate that was sustainable over centuries to millennia, despite changing Holocene climatic conditions and sea-level rise. These data document resilience in oyster populations under long-term Native American harvest, sea-level rise, and climate change; provide context for managing modern oyster fisheries in the Chesapeake Bay and elsewhere around the world; and demonstrate an interdisciplinary approach that can be applied broadly to other fisheries.historical baseline | archaeological shellfish | fossil shellfish | marine fisheries | environmental management

Restoration of ecologically important marine species and habitats is restricted by funding constraints and hindered by lack of information about trade-offs among restoration goals and the effectiveness of alternative restoration strategies. Because ecosystems provide diverse human and ecological benefits, achieving one restoration benefit may take place at the expense of other benefits. This poses challenges when attempting to allocate limited resources to optimally achieve multiple benefits, and when defining measures of restoration success. We present a restoration decision-support tool that links ecosystem prediction and human use in a flexible "optimization" framework that clarifies important restoration trade-offs, makes location-specific recommendations, predicts benefits, and quantifies the associated costs (in the form of lost opportunities). The tool is illustrated by examining restoration options related to the eastern oyster, Crassostrea virginica, which supported an historically important fishery in Chesapeake Bay and provides a range of ecosystem services such as removing seston, enhancing water clarity, and creating benthic habitat. We use an optimization approach to identify the locations where oyster restoration efforts are most likely to maximize one or more benefits such as reduction in seston, increase in light penetration, spawning stock enhancement, and harvest, subject to funding constraints and other limitations. This proof-of-concept Oyster Restoration Optimization model (ORO) incorporates predictions from three-dimensional water quality (nutrients-phytoplankton zooplankton-detritus [NPZD] with oyster filtration) and larval transport models; calculates size- and salinity-dependent growth, mortality, and fecundity of oysters; and includes economic costs of restoration efforts. Model results indicate that restoration of oysters in different regions of the Chesapeake Bay would maximize different suites of benefits due to interactions between the physical characteristics of a system and nonlinear biological processes. For example, restoration locations that maximize harvest are not the same as those that would maximize spawning stock enhancement. Although preliminary, the ORO model demonstrates that our understanding of circulation patterns, single-species population dynamics and their interactions with the ecosystem can be integrated into one quantitative framework that optimizes spending allocations and provides explicit advice along with testable predictions. The ORO model has strengths and constraints as a tool to support restoration efforts and ecosystem approaches to fisheries management.

During May 2015, passive acoustic recorders were deployed at eight subtidal oyster reefs within Harris Creek Oyster Sanctuary in Chesapeake Bay, Maryland USA. These sites were selected to represent both restored and unrestored habitats having a range of oyster densities. Throughout the survey, the soundscape within Harris Creek was dominated by the boatwhistle calls of the oyster toadfish, Opsanus tau. A novel, multi-kernel spectral correlation approach was developed to automatically detect these boatwhistle calls using their two lowest harmonic bands. The results provided quantitative information on how call rate and call frequency varied in space and time. Toadfish boatwhistle fundamental frequency ranged from 140 Hz to 260 Hz and was well correlated (r = 0.94) with changes in water temperature, with the fundamental frequency increasing by ~11 Hz for every 1°C increase in temperature. The boatwhistle call rate increased from just a few calls per minute at the start of monitoring on May 7th to ~100 calls/min on May 10th and remained elevated throughout the survey. As male toadfish are known to generate boatwhistles to attract mates, this rapid increase in call rate was interpreted to mark the onset of spring spawning behavior. Call rate was not modulated by water temperature, but showed a consistent diurnal pattern, with a sharp decrease in rate just before sunrise and a peak just after sunset. There was a significant difference in call rate between restored and unrestored reefs, with restored sites having nearly twice the call rate as unrestored sites. This work highlights the benefits of using automated detection techniques that provide quantitative information on species-specific call characteristics and patterns. This type of non-invasive acoustic monitoring provides long-term, semi-continuous information on animal behavior and abundance, and operates effectively in settings that are otherwise difficult to sample.