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Atlantic sea scallops, Placopecten magellanicus, are the most economically important marine bivalves along the northeastern coast of North America. Wild harvest landings generate hundreds of millions of dollars, and wild-caught adults and juvenile spat are increasingly being cultured in aquaculture facilities and coastal farms. However, the last two weeks of the larval maturation phase in hatcheries are often plagued by large mortality events. Research into other scallop- and aquacultured-species point to bacterial infections or altered functionality of microbial communities which associate with the host. Despite intense filtering and sterilization of seawater, and changing tank water every 48 h, harmful microbes can still persist in biofilms and mortality is still high. There are no previous studies of the bacterial communities associated with the biofilms growing in scallop hatchery tanks, nor studies with wild or hatchery sea scallops. We characterized the bacterial communities in veliger-stage wild or hatchery larvae, and tank biofilms using the 16 S rRNA gene V3-V4 region sequenced on the Illumina MiSeq platform. Hatchery larvae had lower bacterial richness (number of bacteria taxa present) than the wild larvae and tank biofilms, and hatchery larvae had a similar bacterial community (which taxa were present) to both wild larvae and tank biofilms. Bacterial richness and community similarity between tank samples fluctuated over the trial in repeated patterns of rise and fall, which showed some correlation to lunar cycle that may be a proxy for the effects of spring tides and trends in seawater bacteria and phages which are propagated into hatchery tanks. These results along with future work, will inform hatcheries on methods that will increase larval survival in these facilities, for example, implementing additional filtering or avoiding seawater collection during spring tides, to reduce bacterial taxa of concern or promote a more diverse microbial community which would compete against pathogens.

While the number of kelp farms have steadily increased, few have been deployed with sensors to measure mooring tensions with substantial biomass. During the kelp farming season of 2018–2019 in Saco Bay, Maine USA, a field study was conducted to assess mooring loads due to environmental conditions and kelp growth. The effort included the deployment of a farm with a 122 m cultivation line and spread mooring with rope, chain, and anchors in 15.2 m of water. The system was deployed with seeded twine in late November and harvested in May. In April, with kelp biomass estimated at 7.8 kg m−1, two load cells were installed to measure mooring tensions in response to currents and waves. The currents and waves were measured with two Acoustic Doppler Current Profilers deployed adjacent to the load cells. From these measurements, we characterized the maximum loading case in response to a complex hydrodynamic environment. The maximum tension occurred on the landward side of the farm even though wave exposure was seaward. The tension in the landward side mooring was dominated by steady drag from the currents going to the east southeast. During this event, the two profilers were positioned on the leading and trailing edges of the farm relative to the prevailing current direction. Velocities measured at 0.5 m bins showed a 26.7% reduction at the depths where the kelp was located. To analyze the dynamic portion of the load cell datasets, the oscillatory components were processed into energy density spectra. Results showed that mooring tensions were not affected by waves at frequencies greater than 0.175 Hz, with most of the energy occurring near 0.12 Hz. The tension spectra did reveal energy at frequencies between 0.0075 and 0.01 Hz, indicating a low frequency response, possibly due to nonuniform velocity profiles inducing vertical motion of the cultivation line. It was also observed that the landward mooring, subjected to higher currents, was more sensitive to oscillating loads than the slack seaward side. The high-fidelity dataset will be useful for numerical modeling validation to further understand these dynamics and to optimize kelp farm designs.

Understanding the processes that influence recruitment variability in marine populations has been a long-standing challenge for resource management. Quantifying abundance at early life stages for marine fish and invertebrates with complex life histories can be difficult and require unconventional sampling approaches. However, the benefit of developing appropriate tools to sample early life stages is that, together with associated demographic and environmental information, the data can provide insights into the causes and consequences of recruitment variability, allowing prediction of older life stage abundance. Before the 1980s, the earliest benthic life stages of the American lobster (Homarus americanus) eluded quantitative field surveys. With the development of diver-based and vessel-deployed sampling methods over the past three decades, the American Lobster Settlement Index (ALSI) program has expanded into a regional, transboundary commitment to better understand lobster settlement processes and forecast future fishery trends for what has become the most valuable single-species fishery in North America. In this context, “settlement” is a shorthand for the annual recruitment of young-of-year lobster to coastal nurseries, as postlarvae settle to the seabed at the end of larval development. Here, we review the development and products of the ALSI program, first outlining the goals, methods, and data products of the program. We then highlight how the program has advanced the scientific knowledge on pre- and post-settlement processes that influence the fate of a cohort from egg hatch to harvest, which provides insight into the spawner-recruit relationship. Lastly, we provide guidance for future research recommendations building on the ALSI science to-date, some major elements of the program that have allowed for its success, and considerations for maintaining the ALSI program. By highlighting the uniqueness and contributions of the ALSI program, we hope it serves as a model for other scientists, managers, and industry collaborators aiming to understand recruitment processes for species over a broad geographic area.

Satellites have provided high-resolution (

Understanding shallow water biogeochemical dynamics is a challenge in coastal regions, due to the presence of highly variable land-water interface fluxes, tight coupling with sediment processes, tidal dynamics, and diurnal variability in biogeochemical processes. While the deployment of continuous monitoring devices has improved our understanding of high-frequency (12 - 24 hours) variability and spatial heterogeneity in shallow regions, mechanistic modeling of these dynamics has lagged behind conceptual and empirical models. The inherent complexity of shallow water systems is represented in the Corsica River estuary, a small basin within the Chesapeake Bay ecosystem, where abundant monitoring data have been collected from long-term monitoring stations, continuous monitoring sensors, synoptic sensor surveys, and measurements of sediment-water fluxes. A state-of-the-art modeling system, the Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM), was applied to the Corsica domain with a high-resolution grid and nutrient loads from the most recent version of the Chesapeake Bay watershed model. The Corsica SCHISM model reproduced observed high-frequency variability in dissolved oxygen, as well as seasonal variability in chlorophyll-a and sediment-water fluxes. Time-series signal analyses using Empirical Model Decomposition and spectral analysis revealed that the diurnal and M2 tide frequencies are the dominant high-frequency modes and physical transport contributes a larger share to dissolved oxygen budgets than biogeochemical processes on an hourly time scale. Heterogeneity and patchiness in dissolved oxygen resulting from phytoplankton distributions and geometry-driven eddies amplify the physical transport effect, and on longer time scales oxygen is controlled more by photosynthesis and respiration. Our simulation demonstrates that interactions among physical and biological dynamics generate complex high-frequency variability in water quality and non-linear reposes to nutrient loading and environmental forcing in shallow water systems.

To keep global surface warming below 1.5°C by 2100, the portfolio of cost-effective CDR technologies must expand. To evaluate the potential of macroalgae CDR, we developed a kelp aquaculture bio-techno-economic model in which large quantities of kelp would be farmed at an offshore site, transported to a deep water “sink site”, and then deposited below the sequestration horizon (1,000 m). We estimated the costs and associated emissions of nursery production, permitting, farm construction, ocean cultivation, biomass transport, and Monitoring, Reporting, and Verification (MRV) for a 1,000 acre (405 ha) “baseline” project located in the Gulf of Maine, USA. The baseline kelp CDR model applies current systems of kelp cultivation to deep water (100 m) exposed sites using best available modeling methods. We calculated the levelized unit costs of CO2eq sequestration (LCOC; $ tCO2eq-1). Under baseline assumptions, LCOC was $17,048 tCO2eq-1. Despite annually sequestering 628 tCO2eq within kelp biomass at the sink site, the project was only able to net 244 C credits (tCO2eq) each year, a true sequestration “additionality” rate (AR) of 39% (i.e., the ratio of net C credits produced to gross C sequestered within kelp biomass). As a result of optimizing 18 key parameters for which we identified a range within the literature, LCOC fell to $1,257 tCO2eq-1 and AR increased to 91%, demonstrating that substantial cost reductions could be achieved through process improvement and decarbonization of production supply chains. Kelp CDR may be limited by high production costs and energy intensive operations, as well as MRV uncertainty. To resolve these challenges, R&D must (1) de-risk farm designs that maximize lease space, (2) automate the seeding and harvest processes, (3) leverage selective breeding to increase yields, (4) assess the cost-benefit of gametophyte nursery culture as both a platform for selective breeding and driver of operating cost reductions, (5) decarbonize equipment supply chains, energy usage, and ocean cultivation by sourcing electricity from renewables and employing low GHG impact materials with long lifespans, and (6) develop low-cost and accurate MRV techniques for ocean-based CDR.

Aquaculture of seaweeds, particularly in emerging farming regions such as North America, Europe, and South America, is steadily increasing. The growth of the sector has been supported by public and private R&D investment with the long-term goal of reducing farm-gate production costs. Reducing expenses would potentially allow growers to target high volume, low value markets, such as hydrocolloids, animal feeds, food thickening agents, biofuels, and carbon dioxide removal (CDR), as well as the higher value, “whole foods” markets. Regardless of the eventual fate of farmed seaweed, nursery production must increase in parallel with ocean cultivation to support the raw materials needs of the expanding industry. We quantified S. latissima (hereafter kelp) nursery production costs and identified potential barriers to cost-effective scaling using a techno-economic model (TEM). Semi-structured interviews with nursery operators in the U.S. and Europe were supplemented by an extensive literature review to parameterize the TEM. Reducing the sporophyte grow-out duration, increasing labor capacity, de-risking energy efficient flow-through systems, and optimizing tank and PVC “spool” size emerged as the most important research priorities based on our analysis. We point towards expanded gametophyte culture, and an associated policy framework to protect wild kelp population structure from monocultures, as necessary elements to support these potential improvements. The results of this work, as well as the open-source nursery TEM, are relevant to seaweed aquaculture producers, policy makers, and researchers, and can be used to guide future decision making regarding the cost-benefit of best available nursery technology.

Aquaculture of the eastern oyster, Crassostrea virginica, is an expanding industry in the US, particularly in the Gulf of Maine. High resolution ocean color satellites launched in the last decade potentially provide aquaculture-relevant water-quality parameters at farm scales. However, these parameters, such as temperature, suspended particulate matter (SPM), and Chlorophyll a (Chl a), need to be derived by interested users. Water quality parameters are derived first by applying an atmospheric correction and then estimating the target parameter with a specific algorithm. Here, we use five atmospheric correction schemes and two algorithms to derive SPM and Chl a from the Sentinel 2A&B satellites’ multispectral instrument data. The best estimates of SPM and Chl a are determined by comparison with in situ observations from buoys. Together with SST from Landsat-8, we estimated an Oyster Suitability Index (OSI) along the transects in five estuaries in the Gulf of Maine as well as applied a novel particulate organic matter algorithm, a function of Chl a and SPM in low turbidity estuaries. We then apply the optimal approaches to derive water quality parameters to study five different estuaries in Maine and find that existing high-yield oyster aquaculture farms are found in areas with elevated OSI values. Additionally, we suggest new areas, currently under-exploited, where oyster aquaculture is likely to succeed, showcasing the utility of the approach.

Despite the profitability of the wild Atlantic Sea Scallop, Placopecten magellanicus, fishery, the U.S. still imports more than 26,000 tonnes of various scallop products annually. Atlantic Sea Scallop (hereafter referred to as scallop) aquaculture is one method of mitigating this imbalance. We examined scallop growth at three sites across the mouth of Penobscot Bay, Maine to determine the coupled effects of lantern net stocking density and temperature on growth and mortality. Scallops were held in high and low (20 and 10 individuals tier−1, respectively) density treatments, and shell height measurements were recorded monthly for one year. We divided the growth rate analysis into three periods: winter - spring, summer, and fall. During summer across all sites, growth rates were 75 % higher in low-density nets than in high-density nets. We observed significant nonlinear relationships between shell height growth rate, temperature, and stocking density. Optimal growth occurred within a window of 10–15 °C. Above this threshold, there was a distinct negative relationship between temperature and growth. Our results highlight the importance of maintaining low densities within nets, particularly during periods of high temperature and growth. However, handling in summer and early fall may lead to mortality. Therefore, we recommend that growers stock nets at low densities in the spring, ensuring that they will not require thinning during peak temperatures. Similarly, finding sites that maximize time within a thermal envelope of 10–15 °C will be critical, which in the case of the Gulf of Maine will most likely warrant leasing sites at the mouths of estuaries and bays. These locations offer a combination of sufficient depth and space for sparsely stocked nets, adequate food levels, and optimal salinity and temperature.

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.

Coastal ecosystems are experiencing degradation from compound impacts of climate change and multiple anthropogenic disturbances. These pressures often act synergistically and complicate designing effective conservation measures; consequently, large-scale coastal restoration actions become a wicked problem. The purpose of this study was to use two different food web models in a coordinated manner to inform resource managers in their assessment of the ecological effects of a large-scale marsh restoration project. A team was formed that included the model developers and outside scientists, who were asked to use available model results of the calibrated simulations of an Ecopath with Ecosim (EwE) model and a Comprehensive Aquatic Systems Model (CASM), both designed to describe the structure and energetics of the Barataria Bay, Louisiana, United States food web. Both models offer somewhat different depictions of the predator-prey and competitive interactions of species within the food web, and how environmental conditions affect the species biomass pools and energetics. Collectively, the team evaluated the strengths of each model and derived a common set of indicator variables from model outputs that provided information on the structure and energy flow of the simulated food web. Considering the different modeling structures and calibration approaches, indicators were interpreted within and between models. Use of both models enabled a robust determination that: (1) Detritus plays a vital role in the energetics of the system; (2) The food web responds to spring high flow seasons by increasing productivity through specific, dominant pathways; (3) The trophic pyramid is truncated; (4) Compared to other estuaries, this system has redundant pathways for energy transfer. These findings indicate that the food web appears to be resilient to disturbance because of a detritus energy reserve, most consumer biomass consists of low trophic level, high turnover species, and redundant energy pathways exist. This information provides context to decision-makers for assessing possible basin-scale impacts on fish and shellfish resources of a proposed large-scale restoration project. The use of multiple models in a coordinated but not overly constrained way, as demonstrated here, provides a significant step toward co-production of knowledge for use in resource management decisions.

Climate change is impacting the function and distribution of habitats used by marine, coastal, and diadromous species. These impacts often exacerbate the anthropogenic stressors that habitats face, particularly in the coastal environment. We conducted a climate vulnerability assessment of 52 marine, estuarine, and riverine habitats in the Northeast U.S. to develop an ecosystem-scale understanding of the impact of climate change on these habitats. The trait-based assessment considers the overall vulnerability of a habitat to climate change to be a function of two main components, sensitivity and exposure, and relies on a process of expert elicitation. The climate vulnerability ranks ranged from low to very high, with living habitats identified as the most vulnerable. Over half of the habitats examined in this study are expected to be impacted negatively by climate change, while four habitats are expected to have positive effects. Coastal habitats were also identified as highly vulnerable, in part due to the influence of non-climate anthropogenic stressors. The results of this assessment provide regional managers and scientists with a tool to inform habitat conservation, restoration, and research priorities, fisheries and protected species management, and coastal and ocean planning.

Detritus is a frequent, poorly defined, component of bivalve growth and carrying capacity models. The purpose of this study was to determine the proportional contributions of detrital material derived from primary producers (phytoplankton, macroalgae, Spartina alterniflora, and terrestrial leaf litter) to particulate organic matter (POM) and blue mussel’s (Mytilus edulis) diet within a temperate bay (Saco Bay, ME, United States). We assessed which detrital sources, if any, warranted incorporation into modeling efforts. Stable isotopes (δ13C and δ15N) and fatty acid biomarkers (FA) of mussels, size fractionated (

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. Modeled 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 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.

The response of estuarine ecosystems to long-term changes in external forcing is strongly mediated by interactions between the biogeochemical cycling of carbon, oxygen, and inorganic nutrients. Although long-term changes in estuaries are often assessed at the annual scale, phytoplankton biomass, dissolved oxygen concentrations, and biogeochemical rate processes have strong seasonal cycles at temperate latitudes. Thus, changes in the seasonal timing, or phenology, of these key processes can reveal important features of long-term change and help clarify the nature of coupling between carbon, oxygen, and nutrient cycles. Changes in the phenology of estuarine processes may be difficult to assess, however, because many organisms are mobile and migratory, key primary and secondary producers have relatively rapid physiological turnover rates, sampling in time and space is often limited, and physical processes may dominate variability. To overcome these challenges, we have analyzed a 32-year record (1985–2016) of relatively frequent and consistent measurements of chlorophyll-a, dissolved oxygen, nitrogen, and physical drivers to understand long-term change in Chesapeake Bay. Using a suite of metrics that directly test for altered phenology, we quantified changes in the seasonal timing of key biogeochemical events, which allowed us to illustrate spatially- and seasonally-dependent shifts in the magnitude of linked biogeochemical parameters. Specifically, we found that a modest reduction in nitrate input was linked to a suppression of spring phytoplankton biomass in seaward Bay regions. This was, in turn, associated with an earlier breakup in hypoxia and decline in late-summer NH4+ accumulation in seaward waters. In contrast, we observed an increase in winter phytoplankton biomass in landward regions, which was associated with elevated early summer hypoxic volumes and NH4+ accumulation. Seasonal shifts in oxygen depletion and NH4+ accumulation are consistent with reduced nitrogen inputs, spatial patterns of chlorophyll-a, and increases in temperature. In addition, these temperature increases have likely elevated rates of organic matter degradation, thus “speeding-up” the typical seasonal cycle. The causes for the recent landward shift in phytoplankton biomass and NH4+ accumulation are less clear; however, these altered patterns are analyzed here and discussed in terms of numerous physical, climatic, and biological changes in the estuary.

Climate change is impacting the function and distribution of habitats used by marine, coastal, and diadromous species. These impacts often exacerbate the anthropogenic stressors that habitats face, particularly in the coastal environment. We conducted a climate vulnerability assessment of 52 marine, estuarine, and riverine habitats in the Northeast U.S. to develop an ecosystem-scale understanding of the impact of climate change on these habitats. The trait-based assessment considers the overall vulnerability of a habitat to climate change to be a function of two main components, sensitivity and exposure, and relies on a process of expert elicitation. The climate vulnerability ranks ranged from low to very high, with living habitats identified as the most vulnerable. Over half of the habitats examined in this study are expected to be impacted negatively by climate change, while four habitats are expected to have positive effects. Coastal habitats were also identified as highly vulnerable, in part due to the influence of non-climate anthropogenic stressors. The results of this assessment provide regional managers and scientists with a tool to inform habitat conservation, restoration, and research priorities, fisheries and protected species management, and coastal and ocean planning.