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States in the Northeast United States have the ambitious goal of producing more than 22 GW of offshore wind energy in the coming decades. The infrastructure associated with offshore wind energy development is expected to modify marine habitats and potentially alter the ecosystem services. Species distribution models were constructed for a group of fish and macroinvertebrate taxa resident in the Northeast US Continental Shelf marine ecosystem. These models were analyzed to provide baseline context for impact assessment of lease areas in the Middle Atlantic Bight designated for renewable wind energy installations. Using random forest machine learning, models based on occurrence and biomass were constructed for 93 species providing seasonal depictions of their habitat distributions. We developed a scoring index to characterize lease area habitat use for each species. Subsequently, groups of species were identified that reflect varying levels of lease area habitat use ranging across high, moderate, low, and no reliance on the lease area habitats. Among the species with high to moderate reliance were black sea bass (Centropristis striata), summer flounder (Paralichthys dentatus), and Atlantic menhaden (Brevoortia tyrannus), which are important fisheries species in the region. Potential for impact was characterized by the number of species with habitat dependencies associated with lease areas and these varied with a number of continuous gradients. Habitats that support high biomass were distributed more to the northeast, while high occupancy habitats appeared to be further from the coast. There was no obvious effect of the size of the lease area on the importance of associated habitats. Model results indicated that physical drivers and lower trophic level indicators might strongly control the habitat distribution of ecologically and commercially important species in the wind lease areas. Therefore, physical and biological oceanography on the continental shelf proximate to wind energy infrastructure development should be monitored for changes in water column structure and the productivity of phytoplankton and zooplankton and the effects of these changes on the trophic system.

Sea surface temperature (SST), salinity, and chlorophyll concentration (CHL) have changed in the US Northeast Shelf ecosystem over recent decades. The changes in these parameters were distinctly marked by change points around the year 2012 resulting in a 0.83°C increase in SST, a 0.3 PSU increase in salinity, and decrease in CHL in excess of 0.4 mg m-3. Where temperature and salinity shifted in mean level around their respective change points, CHL declined in a more monotonic fashion. Modelled data suggest that the shift in CHL resulted in a greater contribution of pico- and nanophytoplankton and a decreased contribution of microphytoplankton to overall CHL. Complementary estimates of the contribution of different phytoplankton functional types suggest a diminished contribution of diatoms to the phytoplankton community. Hence, not only is there evidence of a decline in the overall primary production capacity of the ecosystem, but also evidence of a fundamental change in the size and quality of phytoplankton supporting food webs. Two ecosystem responses to the observed changes in SST, salinity, and CHL were analyzed. Both length and weight at age have declined for a number of species, and both measures of growth appear to be negatively associated with temperature and positively associated with CHL. Biomass of fish and macroinvertebrates has declined in recent years, with a decrease in pelagic species associated with a decrease in CHL, while the decline in demersal species was more associated with an increase in temperature. Collectively, these ecosystem changes appear to be the result of the complex interactions of both thermal effects and changes at the base of the food web.

Many fish species produce sounds as a part of their reproductive behavior. Using passive acoustic recording approaches, these sounds can be used to document temporal and spatial patterns of reproductive activity of fish populations. We conducted an 11-month passive acoustic survey at three different locations off the coasts of Georgia (40 km north of Grays Reef National Marine Sanctuary) and North Carolina (Onslow Bay) to understand the spawning phenology of two species of acoustically active fishes: black drum (Pogonias cromis) and toadfish (Opsanus sp.). Due to the depth of the recording locations, we could not confirm whether the toadfish calls were produced by O. tau, or another Opsanus species. Both taxa have readily identifiable, distinct sounds. Chorusing sounds from both species were detected at all three Georgia sites and at two of the three North Carolina locations; chorusing duration of both species was greater in Georgia. The onset and duration of chorusing activity for both species was correlated with water temperature. The abundance of calls of these two species from field recordings further demonstrates the value of long-term passive acoustic surveys for understanding the reproductive seasonality of acoustically active fish species.

As part of the Deepwater Horizon Oil Spill Natural Resource Damage Assessment in the Gulf of Mexico, we conducted a large passive acoustic survey across the eastern Gulf continental shelf edge to assess impacts to sperm whale population. In the months immediately after the spill, sperm whale occurrence was significantly higher in areas closest to the spill. Over the following seasons in 2010-2011, we documented cyclical patterns of decreased and increased occurrence suggesting that this population exhibits a seasonal occurrence pattern in the region, with seasonal movements to other regions, and not likely directly influenced by the oil spill. Unfortunately, a lack of adequately scaled, pre-spill data on sperm whales, along with limitations on the survey duration constrain our ability to infer spill-related changes in sperm whale occurrence. However, our study establishes post-disaster baseline data for continued monitoring, and an expanded study design could provide a model for continued monitoring.