Northeast Fisheries Science Center Research Articles

Developing a hybrid model with multiview learning for acoustic classification of Atlantic herring schools

AbstractAdvances in active acoustic technology have outpaced the ability to process and analyze the data in a timely manner. Currently, scientists rely on manual scrutiny or limited automation to translate acoustic backscatter to biologically meaningful metrics useful for fisheries and ecosystem management. The National Oceanic and Atmospheric Administration Northeast Fisheries Science Center has monitored the Atlantic herring population in the Gulf of Maine and Georges Bank since 1999 due to the stocks' important economic and ecological role for the commercial lobster industry. Manual scrutinization to identify Atlantic herring schools from the water column sonar data is time‐consuming and impractical for large‐scale studies. To automate this process, a hybrid model with multiview learning was proposed for automatic Atlantic herring school detection, which consists of two steps: (1) region‐of‐interest (ROI) detection and (2) ROI classification. The ROI detection step was designed to detect school‐like objects, and the ROI classification step was designed to distinguish Atlantic herring schools from other objects. The co‐training algorithm was employed for multiview learning as well as semi‐supervised learning. Within this framework, single‐view vs. multiview learning and supervised vs. semi‐supervised learning were evaluated and compared. Our results showed that multiview learning can improve the performance of the hybrid model in Atlantic herring school detection, and the utilization of unlabeled data is also helpful when the training set is small. The best‐performed model achieved an F1‐score of 0.804. This new framework provides an efficient and effective tool for automatic Atlantic herring school detection.

Taking the bait: Environmental factors affecting bait retention and hook disposition in the Gulf of Maine Bottom Longline Survey

Longline fishery surveys are major contributors to groundfish species abundance estimates. Catchability is often assumed constant, but bait is lost or consumed at inconsistent rates during and across gear sets. Accounting for hook availability and gear saturation can improve abundance estimates, but these data are challenging to collect. Our objectives were to determine whether video camera systems can be used to collect these data from the Northeast Fisheries Science Center’s Gulf of Maine Bottom Longline Survey and to explore the associations between hook disposition percentages and environmental characteristics. Electronic monitoring camera systems were deployed on partner vessels during two fall and two spring seasons to capture video of gear retrieval. During post-survey review, individual hooks were recorded as one of the following hook dispositions: bait, empty hook, fish, and invertebrate. Percentages of these hook dispositions were characterized across categorical (season, day or night, and bottom substrata) and continuous (bottom temperature, bottom depth, and substrate rugosity) survey station variables. Nonmetric multidimensional scaling and logistic regression analyses revealed correlations between retained bait and low bottom temperatures, the spring season, shallow depths, rough bottom substrata, and high terrain rugosity. These characteristics were typical of shallow, inshore, and topographically variable survey strata, suggesting that catchability differs among habitat types. This information will be incorporated into catch rate models to develop standardized indices of abundance for groundfish stock assessments. This study is an example of the utility of electronic technologies to supplement on board data collection during cooperative fishery surveys.

The Role of Fishery‐Independent Bottom Trawl Surveys in Providing Regional and Temporal Context to Offshore Wind Farm Monitoring Studies

AbstractBottom trawl surveys are commonly used to examine potential effects on fishes and invertebrates from offshore wind (OSW) farms in Europe and in the northeastern United States. Because OSW surveys typically occur over a limited spatial footprint, comparison of OSW monitoring results to long‐term fishery‐independent surveys may provide a regional and temporal context for OSW data sets. We compared results of the Block Island Wind Farm (BIWF) bottom trawl survey (2013–2019) to three fishery‐independent bottom trawl surveys (Northeast Area Monitoring and Assessment Program, Northeast Fisheries Science Center, and Rhode Island Department of Environmental Management [RIDEM]) using catch rates of 12 federally managed species. We evaluated temporal trends in annual residual catches for each species calculated within each survey as the difference between the mean annual biomass per trawl and the long‐term mean. Regional consistency in relative catches was apparent for species exhibiting synchronous interannual variability among surveys (Black Sea Bass Centropristis striata, Scup Stenotomus chrysops, Summer Flounder Paralichthys dentatus, and Winter Flounder Pseudopleuronectes americanus) or a decreasing trend in residual catch rates across the 7‐year study period (Little Skate Leucoraja erinacea, longfin inshore squid Doryteuthis pealeii, and Winter Skate L. ocellata). For other species, catches among surveys were asynchronous (Atlantic Herring Clupea harengus, Butterfish Peprilus triacanthus, and Windowpane Scophthalmus aquosus) or anomalous catches in a single year affected the results (Red Hake Urophycis chuss and Silver Hake Merluccius bilinearis). Monitoring of BIWF occurred during a period with lower‐than‐average historical catches in a 32‐year RIDEM data set for Atlantic Herring, Butterfish, Little Skate, longfin inshore squid, Red Hake, Silver Hake, and Winter Flounder and higher‐than‐average catches for Black Sea Bass, Scup, and Summer Flounder. There was no evidence that variation in catches near BIWF differed from regional trends in a way consistent with a detrimental impact of OSW farm operation. The regional context provided from multiple bottom trawl surveys varies by species and thus may be limited for interpreting OSW monitoring results.

Estimation of survey efficiency and biomass for commercially important species from industry-based paired gear experiments

Fishery-independent surveys provide valuable information about trends in population abundance for management of commercially important fish stocks. A critical component of the relationship of the catches of the survey to the size of a fish stock is the catch efficiency of the survey gear. Using a general hierarchical model we estimated the relative efficiency of a chain sweep to the rockhopper sweep used by the Northeast Fisheries Science Center bottom trawl survey from paired-gear experimental tows carried out between 2015 and 2017 using a twin-trawl vessel. For 10 commercially important species, we fitted and compared a set of models with alternative assumptions about variation of relative efficiency between paired gear tows, size and diel effects on the relative efficiency, and extra-binomial variation of observations within paired gear tows. These analyses provided evidence of changes in relative efficiency with size for all species and diel effects were important for all but one species. We then used the bottom trawl survey data from surveys between 2009 and 2019 with the relative catch efficiency estimates from the best performing models to estimate annual and seasonal chain sweep-based swept area biomass for 17 managed stocks. We estimated uncertainty in all results using bootstrap procedures for each data component. We also assessed the effect of calibration on uncertainty and correlation of the annual biomass estimates.

Acoustic observations of nekton and zooplankton along the Northeast continental shelf break

Observations of fish and squid (nekton) and crustacean and gelatinous animals (zooplankton) at the shelf break using active acoustic systems (e.g., echosounders) have been made along the United States shelf break from the mid-Atlantic to New England since the early 2000s as part of a biennial bottom trawl survey (NOAA’s Northeast Fisheries Science Center), since 2012 as part of the Atlantic Marine Assessment Program for Protected Species (AMAPPS), and recently as part of the Task Force Ocean New England Shelf Break Acoustic project. The shelf break can be a boundary between seabed-oriented species on the continental shelf and pelagic species in the open ocean, as well as transitional habitat for some species to exploit. These data have been collected using multifrequency, narrowband (e.g., 18, 38, 70, 120, and 200 kHz) and wideband (18–250 kHz) scientific echosounders with hull-mounted transducers to primarily map the prey species of mid- to upper-trophic level foragers and predators. Classification of acoustic data to biologically meaningful metrics and how these can be integrated with oceanographic features and spatial and temporal distributions of predators will be explored in relation to the broader goals of developing ocean acoustic networks. [Work supported by the Office of Naval Research.]

Broadband acoustic quantification of mixed biological aggregations at the New England shelf break.

At the New England shelf break, cold, less saline shelf water collides with warmer saltier slope water to form a distinct oceanographic front. During the Office of Naval Research Sediment Characterization Experiment in 2017, the front was mapped by narrowband (18 and 38 kHz) and broadband (70-280 kHz) shipboard echo sounders. The acoustically determined cross-shelf velocity of the front ranged in amplitude from 0.02 to 0.33 m/s. Acoustic surveys revealed aggregations of scatterers near the foot of the front. Acoustic backscatter in conjunction with Northeast Fisheries Science Center bottom trawl surveys identified longfin squid (Doryteuthis pealeii) and mackerel (Scomber scombrus) as the most likely scatterers in the aggregations. A mixed species scattering model was developed and further refined by the use of a matching method used for distribution of the lengths of each species. The mean length of squid and mackerel, respectively, using the matching method was 4.45 ± 1.00 and 20.25 ± 1.25 cm compared with 6.17 ± 2.58 and 22.76 ± 1.50 cm from the trawl data. The estimated total biomass of the aggregation was a factor of 1.64 times larger when using the matching method estimated length distribution compared to the trawl length distribution.

Learning From the Study Fleet: Maintenance of a Large-Scale Reference Fleet for Northeast U.S. Fisheries

Logbook data from commercial fisheries are a vital component in the machinery of management, including tracking the volume of catches and allocating catch spatially. At the same time, logbooks can provide a unique window into the ecological and sociological conditions in marine fisheries, where fishermen interact with marine species and environments frequently and broadly. Traditional logbooks, however, often are not sufficiently standardized (when personal logs), or lack the detail (when regulatory documents) required to adequately understand fisheries ecosystems. The Study Fleet program, operated by the Northeast Fisheries Science Center’s Cooperative Research Branch, was developed to address these shortfalls by engaging members of the fishing industry in collecting high-resolution catch, effort, and environmental data using electronic logbooks. Since its inception, the Study Fleet has expanded from a small project focused on collecting detailed catch information from the New England multispecies groundfish fishery to a program with a wider scope encompassing a variety of fisheries, gears, and environmental parameters from North Carolina to Maine U.S. Over the years, a number of lessons have been learned about recruiting and supporting industry partners, managing the data, evolving technical specifications, and the challenges associated with analyzing and applying self-reported fisheries data. Here we describe the current state of the program and provide summaries of the Study Fleet program operations and outcomes from 2007-2020, with an eye towards successes, challenges, and applicability of the approach in other regions. We suggest other reference fleet programs, as well as other developing fishery dependent data collections (e.g., electronic monitoring programs), develop detailed roadmaps for each data collection to keep participants engaged as collaborators, target specific fisheries to keep resources from being stretched too thin, and partner with data users early. Additionally, we suggest programs invest in the long-term participation of individual fishermen, carefully weigh the pros and cons of involvement in regulatory reporting, and plan data products and applications well in advance to ensure that the sampling scheme and granularity of the data meet the needs of stock assessment, ecosystem, and oceanographic scientists.

COI Metabarcoding of Zooplankton Species Diversity for Time-Series Monitoring of the NW Atlantic Continental Shelf

Marine zooplankton are rapid-responders and useful indicators of environmental variability and climate change impacts on pelagic ecosystems on time scales ranging from seasons to years to decades. The systematic complexity and taxonomic diversity of the zooplankton assemblage has presented significant challenges for routine morphological (microscopic) identification of species in samples collected during ecosystem monitoring and fisheries management surveys. Metabarcoding using the mitochondrial Cytochrome Oxidase I (COI) gene region has shown promise for detecting and identifying species of some – but not all – taxonomic groups in samples of marine zooplankton. This study examined species diversity of zooplankton on the Northwest Atlantic Continental Shelf using 27 samples collected in 2002-2012 from the Gulf of Maine, Georges Bank, and Mid-Atlantic Bight during Ecosystem Monitoring (EcoMon) Surveys by the NOAA NMFS Northeast Fisheries Science Center. COI metabarcodes were identified using the MetaZooGene Barcode Atlas and Database (https://metazoogene.org/MZGdb) specific to the North Atlantic Ocean. A total of 181 species across 23 taxonomic groups were detected, including a number of sibling and cryptic species that were not discriminated by morphological taxonomic analysis of EcoMon samples. In all, 67 species of 15 taxonomic groups had ≥ 50 COI sequences; 23 species had >1,000 COI sequences. Comparative analysis of molecular and morphological data showed significant correlations between COI sequence numbers and microscopic counts for 5 of 6 taxonomic groups and for 5 of 7 species with >1,000 COI sequences for which both types of data were available. Multivariate statistical analysis showed clustering of samples within each region based on both COI sequence numbers and EcoMon counts, although differences among the three regions were not statistically significant. The results demonstrate the power and potential of COI metabarcoding for identification of species of metazoan zooplankton in the context of ecosystem monitoring.

Differences in the size at maturity of female American lobsters (Homarus americanus) from offshore Southern New England and eastern Georges Bank, USA

Female reproductive dynamics of the offshore American lobster fishery are not well understood due to the difficulties associated with biological sampling offshore. This lack of knowledge limits our understanding of population dynamics and the impacts of fishery removals on the offshore lobster resource. Addressing needs identified by stock assessment scientists, we determined the size at which female lobsters reach sexual maturity for two offshore areas (offshore Southern New England and eastern Georges Bank) utilizing data from commercial lobster gear and the Northeast Fisheries Science Center bottom trawl survey. A total of 491 female lobsters were collected and assigned a maturity status based on standard ovarian staging techniques. The size at which 50% of females in the population are mature (L50) occurred at a smaller size (L50 = 79.5 mm) in Southern New England compared to eastern Georges Bank (L50 = 91.9 mm). Comparisons of our results to historical data from nearby regions show only a slight decline in Southern New England, but, depending on the data source, a larger decline in size at maturity for Georges Bank. These maturity estimates for offshore lobsters provide new information for assessment scientists and managers on lobster population demographics in a data-poor region of the fishery, and reinforce the value achieved by working collaboratively with the fishing industry to address data gaps in the offshore lobster fishery.

Tracking shifts in the vulnerability and resiliency of commercial fishing vessel crew and hired captains in New England and the Mid-Atlantic

Commercial fisheries are important to the social, cultural, and economic well-being of coastal communities throughout the New England and Mid-Atlantic regions of the United States. Fishing vessel crew and hired captains comprise a significant portion of fishing industry employment, yet very few studies have inquired about the social and demographic characteristics of the individuals who make up this segment of the industry. Moreover, virtually no data exists that tracks the characteristics of crew and hired captains over time in order to capture trends in socio-demographics, employment, and fishing practices, among other factors. This study is a follow-up to a baseline survey conducted in 2012 by the National Oceanic and Atmospheric Administration’s (NOAA) Northeast Fisheries Science Center (NEFSC). During late 2018 and early 2019, NEFSC staff conducted interviews with commercial fishing vessel crew and hired captains at ports from Maine to North Carolina. Interviewers asked respondents questions regarding their demographic background, the availability of work, and fishing trip characteristics, among other topics of interest related to employment in commercial fishing. Results indicate an increasing fragility of fishing communities in the region related to the aging of fishing crews and low levels of new individuals entering into the occupation, in addition to other social and economic vulnerabilities of commercial crews and hired captains.

Mixed layer depth climatology over the northeast U.S. continental shelf (1993–2018)

The Northeast U.S. (NEUS) continental shelf has experienced rapid warming in recent decades. Over the NEUS continental shelf, the circulation and annual cycle of heating and cooling lead to local variability of water properties. The mixed layer depth (MLD) is a key factor that determines the amount of upper ocean warming. A detailed description of the MLD, particularly its seasonal cycle and spatial patterns, has not been developed for the NEUS continental shelf. We compute the MLD using an observational dataset from the Northeast Fisheries Science Center hydrographic monitoring program. The MLD exhibits clear seasonal cycles across five eco-regions on the NEUS continental shelf, with maxima in January–March and minima in July or August. The seasonal cycle is largest in the western Gulf of Maine (71.9 ± 24.4 m), and smallest in the southern Mid-Atlantic Bight (34.0 ± 7.3 m). Spatial variations are seasonally dependent, with greatest homogeneity in summer. Interannual variability dominates long-term linear trends in most regions and seasons. To evaluate the sensitivity of our results, we compare the MLDs calculated using a 0.03 kg/m3 density threshold with those using a 0.2 °C temperature threshold. Temperature-based MLDs are generally consistent with density-based MLDs, although a small number of temperature-based MLDs are biased deep compared to density-based MLDs particularly in spring and fall. Finally, we compare observational MLDs to the MLDs from a high-resolution ocean reanalysis GLORYS12V1. While the mean values of GLORYS12V1 MLDs compare well with the observed MLDs, their interannual variability are not highly correlated, particularly in summer. These results can be a starting point for future studies on the drivers of temporal and spatial MLD variability on the NEUS continental shelf.

Sensitivity of marine fish thermal habitat models to fishery data sources.

Statistical models built using different data sources and methods can exhibit conflicting patterns. We used the northern stock of black sea bass (Centropristis striata) as a case study to assess the impacts of using different fisheries data sources and laboratory‐derived physiological metrics in the development of thermal habitat models for marine fishes. We constructed thermal habitat models using generalized additive models (GAMs) based on various fisheries datasets as input, including the NOAA Northeast Fisheries Science Center (NEFSC) bottom trawl surveys, various inshore fisheries‐independent trawl surveys (state waters), NEFSC fisheries‐dependent observer data, and laboratory‐based physiological metrics. We compared each model's GAM response curve and coupled them to historical ocean conditions in the U.S. Northeast Shelf using bias‐corrected ocean temperature output from a regional ocean model. Thermal habitat models based on shelf‐wide data (NEFSC fisheries‐dependent observer data and fisheries‐independent spring and fall surveys) explained the most variation in black sea bass presence/absence data at ~15% deviance explained. Models based on a narrower range of sampled thermal habitat from inshore survey data in the Northeast Area Monitoring and Assessment Program (NEAMAP) and the geographically isolated Long Island Sound data performed poorly. All models had similar lower thermal limits around 8.5℃, but thermal optima, when present, ranged from 16.7 to 24.8℃. The GAMs could reliably predict habitat from years excluded from model training, but due to strong seasonal temperature fluctuations in the region, could not be used to predict habitat in seasons excluded from training. We conclude that survey data source can greatly impact development and interpretation of thermal habitat models for marine fishes. We suggest that model development be based on data sources that sample the widest range of ocean temperature and physical habitat throughout multiple seasons when possible, and encourage thorough consideration of how data gaps may influence model uncertainty.

Experimental assessment of the effect of net wing spread on relative catch efficiency of four flatfishes by a four seam bottom trawl

The northeast US fishing industry and other stakeholders have considerable interest in the quality of bottom trawl survey results because of their importance in the setting of quotas, especially those directly derived from bottom trawl indices measured in catch per area swept by the survey net. Net spread (also referred to as wing spread) impacts catches and thus indices and, for the federal northeast bottom trawl survey, it is correlated with the depth at which a tow is performed. As part of an ongoing partnership between the Northeast Fisheries Science Center, the New England and Mid-Atlantic Fisheries Management Councils, members of the fishing industry, and academics in the region, an experiment to evaluate the impact of wing spread on the catchability of a number of species was conducted in the Fall of 2019 on the F/V Karen Elizabeth. The experiment targeted four species of flatfishes using a twin trawl rigging to collect simultaneous observations of catch and wing spread relative to a controlled optimal net spread. We analyzed these data to estimate the effect of net spread on relative catch efficiency and to evaluate the hypothesis that relative catch efficiency decreases as net spread departs from the optimal configuration. We found that, while the total catch was impacted by net wing spread (catches increased with increasing swept-area), there was no evidence of a wing spread effect on relative catch efficiency for any of the flatfish species. These results suggest that bottom trawl surveys should account for swept-area of individual tows, but that it is not necessary to incorporate species- or length-specific efficiency conversions based on the width of the net.

What can you do with twenty years of water column sonar data? Plenty!

Collection of multifrequency fisheries acoustic data began at the NOAA Northeast Fisheries Science Center (NEFSC) in 1998. Over the past 20 + years, data have been collected on the NOAA fisheries survey vessels as well as commercial vessels during numerous surveys and research cruises. Many lessons in cooperation, initiative, persistence, and compromise have been learned, resulting in data sets with plenty of potential. Some of these data have been rejected and then resuscitated for stock assessments, used to estimate biomass of undersampled biota, and used to study catchability of commercial species. Until recently, data were limited to those at the NEFSC with sufficient expertise and access to the data—i.e., me, which has restricted application of the data. But now the data are searchable and available to the world via NOAA’s National Center for Environmental Information (NCEI). The evolution of acoustic technology and software from costly and proprietary to inexpensive and open-source has expanded the utility of these, and other long-term, data sets to the broader scientific community. An overarching goal has been to collect consistently high-quality data, yet only through incorporating innovation can long-term data collection survive in a dynamic environment and ever-changing scientific landscape.

Science, social networks, and collaboration: an analysis of publications in fisheries science from 1990 to 2018

Abstract Understanding the nature of collaboration underpinning scientific work in fisheries is critical to building the social foundations for effective scientific progress in addressing complex socio-ecological systems. We examine the nature of interdisciplinary work in fisheries through an analysis of nearly three decades of peer-reviewed papers authored by researchers affiliated with NOAA Fisheries’ Northeast Fisheries Science Center in the United States. Using social network analysis, and approaches novel to scientometrics such as grounded theory building, we map and analyse the relationships between authors of different disciplinary backgrounds, visualize these changing networks over time, and evaluate the nature of collaboration with a particular emphasis given to the integration of the social sciences. Our analysis suggests that areas of research such as ecosystem-based management and climate change have helped create synergies between the natural and social sciences, pointing to the importance of organizational changes promoting multiple perspectives, the institutionalization of integrated approaches, and openness to diverse understandings.

Species-specific patterns of distribution and abundance of the cryptic copepods Pseudocalanus moultoni and P. newmani on Georges Bank (NW Atlantic Ocean) during spring 1995–2012

Time-series analysis of zooplankton species diversity, distribution, and abundance are essential for ecosystem assessment and fisheries management on continental shelves. This study analyzed two morphologically cryptic species of the calanoid copepod Pseudocalanus, P. moultoni and P. newmani, in zooplankton samples collected during May–June 1995–2012 over Georges Bank, NW Atlantic Ocean. Samples were collected 1995–1999 by US Global Ocean Ecosystem Dynamics (US GLOBEC) and 2002–2012 by NOAA Northeast Fisheries Science Center Ecosystem Monitoring (EcoMon). The species were discriminated by real-time quantitative PCR (qPCR) based on DNA sequence variation of the mitochondrial cytochrome oxidase I (COI). Multivariate statistical analysis revealed significant positive correlation between the geometric mean abundance of P. moultoni and depth-averaged temperature at the collection locations; P. newmani abundances showed no relationship to temperature, suggesting different temperature niches and potential responses to environmental conditions. Interannual patterns of variation of the species-specific abundances of P. moultoni and P. newmani differed significantly from pooled Pseudocalanus spp. Nonmetric multidimensional (NMDS) and regression analyses confirmed significant interannual differences between P. moultoni and P. newmani geometric mean abundances during 1995–2012. This study demonstrates the need for discrimination of closely-related and cryptic zooplankton species to understand and predict impacts of environmental variation and climate change on marine ecosystems.

Possible climate-induced environmental impacts on parasite-infection rates of northern shrimp Pandalus borealis eggs in the Gulf of Maine.

The Gulf of Maine northern shrimp Pandalus borealis population once supported a significant commercial winter fishery for the New England states. However, the fishery has been on moratorium since 2014 due to consecutive recruitment failures. The issue of parasite-infected eggs, so-called 'white eggs,' has long been identified for the Gulf of Maine northern shrimp, which makes shrimp eggs nonviable and subsequently hampers the recruitment potential. Furthermore, the proportion of infected females was observed to increase with water temperature. As Gulf of Maine temperatures have been increasing for decades, it is important to re-visit issues related to white eggs to evaluate possible impacts of climate-induced environmental changes on the white egg infection rates. We used biological samples collected by the Northeast Fisheries Science Center in 2012-2016 to evaluate the probability that a female shrimp was infected (Pinf) and the proportion of white eggs in an infected female shrimp (pwe). Although Pinf was high, with an average of 73.81% over the Gulf of Maine, pwe was mostly <5%. The variation in both Pinf and pwe examined in this study was not well explained by environmental factors or female body size. However, the average rates of both Pinf and pwe observed in this study were higher than those observed in the 1960s when the bottom temperatures were cooler. The results can be used to account for egg mortality and provide information on potential impacts of possible climate-induced variability on shrimp population dynamics.

Fisheye Lens: Data Stewardship and Privacy Rights Under the Northeast Multispecies Fishery Management Plan's Amendment 23's Proposed Electronic Monitoring

The Atlantic Cod, Gadus morhua, once held a prime ecological and economic presence in the North Atlantic Ocean, and European colonizers capitalized on this resource by establishing a cod fishery in Newfoundland as far back as 1517. In 1992, Newfoundland’s fishery nearly eliminated its cod stocks, and the Gulf of Maine’s stocks were dying three times as fast as managers predicted. The fishery became one of the world’s most concrete examples of the tragedy of the commons, where harvesters exhaust an open-access resource. Guiding the New England Fisheries Management Council (NEFMC) cod fishery rebuilding effort is a tremendous amount of fisheries modeling aimed at estimating a requisite fishery’s stock size, using landings, discards, and survey data. The Northeast Fisheries Science Center (NEFSC) sources and verifies data partly through the Northeast Fisheries Observer Program (NEFOP). Among the observers’ duties is physically boarding industry vessels to record data. The observers’ physical bias, however, could produce inaccurate data, leading the NEFMC to make inaccurate decisions and hinder the northeastern U.S. cod fishery’s recovery. Inaccurate data would thus hinder managers’ ability to rebuild this historically profitable fishery and the lack of cod would continue to deprive the Northeast’s ecosystem of a key predator. In response to the concern over bias, the NEFMC is currently considering several alternatives to the traditional human observer program in Amendment 23 to the Northeast Multispecies Fisheries Management Plan. One such alternative is electronic monitoring (EM). EM is a system of cameras that captures video of fishing activities onboard vessels, a crucial tool to produce high-quality and low-cost fisheries data to better inform management decisions. However, Northeast fishers have several concerns about EM. EM is a seemingly simple solution to human observers but produces highly detailed video and image data instead of pure numbers, which could identify private individuals, business, or their trade secrets. EM thus presents uncertainty in fishers’ private information, leading to apprehension of EM systems. The opportunity to design a program that is amenable to fishers could speed up implementing EM and its benefits to the northeast’s ecological and economic marine communities. Amending the Magnuson Stevens Act, promulgating strong privacy regulations and internal rules, and ensuring privacy guarantees in third-party contracts would best protect fishers’ privacy, which the National Oceanic and Atmospheric Administration should consider in light of their broad authority to collect EM data. Strong fisheries management requires strong cooperation and mutual respect; guaranteeing strong privacy rights for EM data furthers everyone’s interests. The goal of this Note is to provide a framework to promote the recovery of New England’s marine environment through coastal stakeholder and federal management cooperation.

Windowpane Seasonal Distribution and Survey Availability on the Southern Portion of Georges Bank, USA

AbstractThe Windowpane Scophthalmus aquosus stock in Georges Bank and the Gulf of Maine is considered overfished despite the lack of a directed fishery. Windowpane stocks are assessed using an index‐based method relying on the Northeast Fisheries Science Center's (NEFSC; National Oceanic and Atmospheric Administration) fall trawl survey. From 2013 to 2016, the School for Marine Science and Technology (SMAST; University of Massachusetts Dartmouth) conducted a fisheries‐independent trawl survey on the southern portion of Georges Bank, including part of Closed Area II. Using both the NEFSC and SMAST survey catches, we examined seasonal variations in CPUE of Windowpanes as well as their relationship with depth and temperature. Windowpane CPUE was significantly higher in the spring than in the fall and was linked with temperature changes. On the southern portion of Georges Bank, the NEFSC and SMAST surveys had similar relationships between Windowpane catch and temperature. In the spring, Windowpanes were abundant at water temperatures less than 7°C, and they moved out of the area as the temperature increased. In the fall, Windowpane CPUE was higher in warmer water temperatures and decreased as the temperature decreased. As Windowpanes moved out of the area, Fourspot Flounder Paralichthys oblongus replaced them in the habitat. This distribution pattern seems to occur across the whole stock. Our findings suggest that environmental factors can affect the CPUE indices from surveys that are assumed to be consistent, and this should be considered in future assessments.

Time-series metabarcoding analysis of zooplankton diversity of the NW Atlantic continental shelf

Abstract Biodiversity of zooplankton is central to the functioning of ocean ecosystems, yet morphological taxonomic analysis requires teams of experts and detailed examination of many samples. Metabarcoding (DNA sequencing of short amplified regions of one or a few genes from environmental samples) is a powerful tool for analysis of the composition and diversity of natural communities. The 18S rRNA V9 hypervariable region was sequenced for 26 zooplankton samples collected from the Gulf of Maine, Georges Bank, and Mid-Atlantic Bight during ecosystem monitoring surveys by the U.S. Northeast Fisheries Science Center during 2002–2012. A total of 7 648 033 sequences and 22 072 operational taxonomic units (OTUs) were identified and classified into 28 taxonomic groups of plankton. Comparative analysis of molecular (V9 sequence numbers) and morphological (abundance counts) focused on seven taxonomic groups and revealed similar patterns of variation among years and regions. Sequence numbers and abundance counts showed positive correlation for all groups, with significant correlations (p &amp;lt; 0.05) for Calanoida, Gastropoda, and Chaetognatha. Shannon diversity index values calculated using sequence numbers and abundance counts showed highly significant correlation (r = 0.625; p &amp;lt; 0.001) across all regions during 2002–2012. This study demonstrates the potential of metabarcoding for time-series analysis of zooplankton biodiversity, ocean ecosystem assessment, and fisheries management.