Continental Shelf Large Marine Ecosystem Research Articles

An ensemble high‐resolution projection of changes in the future habitat of American lobster and sea scallop in the Northeast US continental shelf

AbstractAimTo address the uncertainty associated with climate‐driven biogeographical changes in commercial fisheries species through an ensemble species distribution modelling (SDM) approach.LocationNortheast US Continental Shelf Large Marine Ecosystem (NEUS‐LME).MethodsWe combined an ensemble SDM platform (BIOMOD 2) and a high‐resolution global climate model (NOAA GFDL CM2.6) to quantify spatiotemporal changes in habitat of two commercially important species in the Northeast US Continental Shelf Large Marine Ecosystem (NEUS‐LME); American lobster (Homarus americanus); and sea scallop (Placopecten magellanicus). An ensemble SDM was calibrated using multi‐decadal fisheries‐independent surveys (1984–2016). Statistically weighted species‐specific ensemble SDM outputs were combined with 80 years of projected bottom temperature and salinity changes in response to a high greenhouse gas emissions scenario (an annual 1% increase in atmospheric CO2).ResultsStatistically significant changes (p < .05) in habitat suitability for both species were found over a large portion of the study area. Sea scallop undergoes a northward shift over the study period, while American lobster moves further offshore. The ensemble projections showed that several management zones were identified with increases and decreases in species‐specific habitat. Uncertainty due to variations in ensemble member models was also found in the direction of change within each management zone.Main conclusionsThis study provides ensemble estimates of climate‐driven changes and associated uncertainties in the biogeography of two economically important species in the United States. Projected climate change in the NEUS‐LME will pose management challenges, and our ensemble projections provide useful information for climate‐ready management of commercial fisheries.

Multi‐decadal climate and fishing predictors of abundance for U.S. South Atlantic coastal fishes and invertebrates

AbstractAbundance of marine stocks fluctuates in response to both internal processes (e.g., density dependence) and exogenous drivers, including the physical environment, fishing, and trophodynamic interactions. In the United States, research investigating ecosystem drivers has been focused in data‐rich systems, primarily in the North Atlantic and North Pacific. To develop a more holistic understanding of important ecosystem drivers in the Southeast U.S. continental shelf Large Marine Ecosystem, we applied generalized linear and dynamic linear modeling to investigate the effects of climate and fishing covariates on the relative abundance trends of 71 demersal fish and invertebrate species sampled by a coastal trawl survey during 1990–2013. For the assemblage as a whole, fishing effects predominated over climate effects. In particular, changes in trawling effort within the penaeid shrimp fishery governed abundance trends of bony fishes, invertebrates, and elasmobranchs, a likely result of temporal changes in bycatch mortality. Changes in trawling intensity induced changes in overall community composition and appear to have altered trophic interactions among particular species. Among climate indices investigated, the Pacific Decadal Oscillation and the Western Bermuda High Index were most prevalent in well‐supported dynamic linear models. Observed annual abundance trends were synchronous among some taxonomically related species, highlighting similar responses to exogenous influences based on life history. This study strengthens the foundation for generating hypotheses and advancing ecosystem‐based fisheries research within the region.

Response of marine communities to local temperature changes

As global climate change and variability drive shifts in species’ distributions, ecological communities are being reorganized. One approach to understand community change in response to climate change has been to characterize communities by a collective thermal preference, or community temperature index (CTI), and then to compare changes in CTI with changes in temperature. However, important questions remain about whether and how responsive communities are to changes in their local thermal environments. We used CTI to analyze changes in 160 marine assemblages (fish and invertebrates) across the rapidly‐changing Northeast U.S. Continental Shelf Large Marine Ecosystem and calculated expected community change based on historical relationships between species presence and temperature from a separate training dataset. We then compared interannual and long‐term temperature changes with expected community responses and observed community responses over both temporal scales. For these marine communities, we found that community composition as well as composition changes through time could be explained by species associations with bottom temperature. Individual species had non‐linear responses to changes in temperature, and these nonlinearities scaled up to a nonlinear relationship between CTI and temperature. On average, CTI increased by 0.36°C (95% CI: 0.34–0.38°C) for every 1°C increase in bottom temperature, but the relationship between CTI and temperature also depended on community composition. In addition, communities responded more strongly to interannual variation than to long‐term trends in temperature. We recommend that future research into climate‐driven community change accounts for nonlinear responses and examines ecological responses across a range of temporal and geographical scales.

Toward cyberinfrastructure to facilitate collaboration and reproducibility for marine integrated ecosystem assessments

There is a growing need for cyberinfrastructure to support science-based decision making in management of natural resources. In particular, our motivation was to aid the development of cyberinfrastructure for Integrated Ecosystem Assessments (IEAs) for marine ecosystems. The IEA process involves analysis of natural and socio-economic information based on diverse and disparate sources of data, requiring collaboration among scientists of many disciplines and communication with other stakeholders. Here we describe our bottom-up approach to developing cyberinfrastructure through a collaborative process engaging a small group of domain and computer scientists and software engineers. We report on a use case evaluated for an Ecosystem Status Report, a multi-disciplinary report inclusive of Earth, life, and social sciences, for the Northeast U.S. Continental Shelf Large Marine Ecosystem. Ultimately, we focused on sharing workflows as a component of the cyberinfrastructure to facilitate collaboration and reproducibility. We developed and deployed a software environment to generate a portion of the Report, retaining traceability of derived datasets including indicators of climate forcing, physical pressures, and ecosystem states. Our solution for sharing workflows and delivering reproducible documents includes IPython (now Jupyter) Notebooks. We describe technical and social challenges that we encountered in the use case and the importance of training to aid the adoption of best practices and new technologies by domain scientists. We consider the larger challenges for developing end-to-end cyberinfrastructure that engages other participants and stakeholders in the IEA process.

Distinct zooplankton regime shift patterns across ecoregions of the U.S. Northeast continental shelf Large Marine Ecosystem

We investigated regime shifts in seasonal zooplankton communities of the Northeast continental shelf Large Marine Ecosystem (NES) and its subcomponent ecoregions over a multi-decadal period (1977–2013). Our cross ecoregion analysis shows that regime shifts in different ecoregions often exhibited very distinct characteristics, emphasizing more granular fluctuations in NES plankton communities relative to previous work. Shifts early in the time series generally reflected an increase in abundance levels. The response of zooplankton abundance within fall communities was more similar among ecoregions than for spring communities. The Gulf of Maine exhibited highly distinct patterns from other ecoregions, with regime shifts identified in the early 1980s, early 2000s, and mid-2000s for spring communities. Regime shifts were identified in the early to mid-1990s for the NES, Georges Bank, and the Mid-Atlantic Bight ecoregions, while the fall communities experienced shifts in the early 1990s and late 1980s for the NES and Georges Bank, but in the late 1990s in the Mid-Atlantic Bight. A constrained correspondence analysis of zooplankton community against local and basin-scale climatological indices suggests that water temperature, stratification, and the Atlantic multidecadal oscillation (AMO) were the predominant factors in driving the zooplankton community composition.

Diel Variations in Survey Catch Rates and Survey Catchability of Spiny Dogfish and their Pelagic Prey in the Northeast U.S. Continental Shelf Large Marine Ecosystem

This study examines the potential uncertainty in survey biomass estimates of Spiny Dogfish Squalus acanthias in the Northeast U.S. Continental Shelf Large Marine Ecosystem (NES LME). Diel catch-per-unit-effort (CPUE) estimates are examined from the Northeast Fisheries Science Center bottom trawl surveys conducted during autumn (1963–2009) and spring (1968–2009). Influential environmental variables on survey catchability are identified for Spiny Dogfish life history stages and five pelagic prey species: Butterfish Peprilus triacanthus, Atlantic Herring Clupea harengus, shortfin squid Illex spp., longfin squid Doryteuthis spp., and Atlantic Mackerel Scomber scombrus. Daytime survey catchability was significantly higher than nighttime catchability for most species during autumn and for mature male Spiny Dogfish, shortfin squid, and longfin squid during spring in the NES LME. For most stages and species examined, breakpoint analyses identified significant increases in CPUE in the morning, peak CPUE during the day, and significant declines in CPUE in the late afternoon. Seasonal probabilities of daytime catch were largely driven by solar zenith angle for most species, with stronger trends identified during autumn. Unadjusted CPUE estimates appear to overestimate absolute abundance, with adjustments resulting in reductions in absolute abundance ranging from 41% for Spiny Dogfish to 91% for shortfin and longfin squids. These findings have important implications for Spiny Dogfish regarding estimates of population consumption of key pelagic prey species and their ecological footprint within the NES LME. Received February 25, 2015; accepted December 16, 2015

Comparison of trap and underwater video gears for indexing reef fish presence and abundance in the southeast United States

It is challenging to manage reef fish species in the Southeast U.S. Continental Shelf Large Marine Ecosystem (SUSLME) due to life history strategies that make them vulnerable to overexploitation, difficulty of sampling reef fish in high-relief hard bottom habitats, and fluctuations in utility of fishery-dependent data. In response to declines in fishery-dependent data due to fishery closures, fishery-independent sampling of reef fish has become even more critical to stock assessment. Here we test whether a long-term chevron trapping survey could benefit from the addition of underwater video cameras. Sampling occurred on continental shelf and shelf break habitats (15–83m deep) between northern Georgia and central Florida. Reef fish frequency of occurrence was significantly higher on video compared to traps for 11 of 15 species analyzed, and the increase ranged from 38% to infinity for these 11 species. Frequency of occurrence for the four remaining species was not significantly different between traps and video. Although positive relationships were observed between log-transformed trap and video indices of abundance for five selected reef fish species, considerable amounts of unexplained variation existed and the relationship for three species was nonlinear. Underwater video can be a beneficial addition to a long-term trapping survey by increasing the frequency of occurrence for most reef fish species, which should translate into improved indices of reef fish abundance in the SUSLME.

The relative impact of warming and removing top predators on the Northeast US large marine biotic community

Ecosystem-based fisheries management necessitates that we take a more holistic view of the many factors affecting ecosystems. All too often, perturbations to fisheries ecosystems are studied in isolation even though there may be important interactions among them that yield unexpected ecosystem states. The Northeast US continental shelf large marine ecosystem (NES LME) has undergone a number of changes in biophysical processes, trophic structure, and exploitation rates over the last fifty years. Changes in community assemblages, shifts in spatial distribution of many species, and the failure of fisheries to fully recover from overexploitation in the NES LME have been attributed to both the removal of large demersal fish predators and climate variability, as well as indirect effects cascading through the food web. As with many ecosystems, it is difficult to separate the effects of multiple perturbations that can affect marine ecosystems. However, recent advances in ecosystem modeling allow us to explore the relative and synergistic effects of these perturbations in silico that would otherwise be impossible in situ or experimentally. We examined the relative effects of warming and removal of large predators by modeling both of these effects separately and then in combination. Interactions amongst such changes tended to be additive, but the magnitude of synergistic effects was potentially very large in some cases. These results demonstrate the power of ecosystem models in evaluating management options.

The northeast US application of ATLANTIS: A full system model exploring marine ecosystem dynamics in a living marine resource management context

Understanding marine ecosystem dynamics is a key challenge and opportunity facing us. One of the ways we can continue to unravel and understand marine ecosystem dynamics is via ecosystem modeling. We used one such model, ATLANTIS, to help explore the dynamics of the Northeast United States (NEUS) Continental Shelf Large Marine Ecosystem (LME). We have parameterized ATLANTIS for the NEUS LME by including major functional groups across a range of biota, the physiographic dynamics of the ecosystem, and the major fishing fleets. The objectives of this work were to describe the application of this ATLANTIS NEUS model; briefly highlight modeling skill; note areas for further improvement, data gaps, major lessons learned, and how our understanding of the ecosystem was enhanced as we executed the modeling process; and note how these model outputs could inform living marine resource management in this region. The preliminary results we show here describe outputs from a multivariate, multispecies, multifactorial modeling approach. Our modeling skill is reasonable, as determined by the fact that over 90% of our fleet effort estimates, nearly 80% of our functional group catches, and 100% of our main functional group biomasses were within limits of tolerance. Moreover, the general patterns and phenology of major events were replicated consistently, both in space and time across a broad suite of physical, chemical, biological and human factors. These include several taxa groups such as primary producers, zooplankton, benthos, fishes, marine mammals, as well as nutrients, landings, and fishing effort. Conversely, as expected, there were some groups or fleets that did exceed levels of tolerance. These were mostly invertebrate groups such as shrimp, squid or gelatinous zooplankton, groups which are notorious for being difficult to model. Yet the major taxa groups and main fishing fleets were all well within levels of tolerance. Thus, we assert that with the majority of all main processes and state variables simulated, this ATLANTIS model can indeed reasonably approximate observations for the NEUS LME across a range of factors, and more importantly can be used to evaluate the relative prominence across a range of factors that contribute to the dynamics of this marine ecosystem.

Shifting species assemblages in the Northeast US Continental Shelf Large Marine Ecosystem

The Northeast US Continental Shelf Large Marine Ecosystem (NES LME) has experienced 2 major pressures: fishing and climate. The magnitude and rate of response to these pressures are species-specific and depend on each individual species’ behavior, physiology and life histories. Thus, species assemblages can be expected to change as a result of the sum of each individual species’ response. In previous studies, distinct species assemblages have been identified in each of the 4 subregions by which the NES LME has traditionally been assessed: Mid-Atlantic Bight (MAB), Southern New England (SNE), Georges Bank (GB), and Gulf of Maine (GOM). In this study, we confirm that each subregion has a distinct species assemblage, but found that those assemblages are shifting over time. The shift appears to be towards species that prefer warmer water. The result is a species assemblage within each subregion that more closely resembles the historic assemblage found in the adjacent subregion to the south. These shifts have occurred in response to a combination of both fishing and climate, and are highly nonlinear. Therefore, current reductions in fishing pressure may not be adequate to return the system to a more historic species assemblage.

Developing a two-step fishery-independent design to estimate the relative abundance of deepwater reef fish: Application to a marine protected area off the southeastern United States coast

Reliable data on reef fishes inhabiting the southeastern United States (North Carolina to Florida) continental shelf large marine ecosystem are difficult to obtain; catch quotas and time and area closures limit the collection of fishery-dependent samples. Further, unbiased fishery-independent samples are expensive to collect with conventional fishing gear. Consequently, stock assessments are often data-limited, especially for deepwater reef species. We estimated the relative abundance of deepwater reef fish with a double sampling approach using fisheries acoustics and conventional fishing gear (hook and line and chevron traps). Double sampling occurred within the newly-created Snowy Wreck Marine Protected Area and a nearby control site. Reef fish concentrations were identified by a single-beam Simrad ES60 transceiver with a transducer operating at 38 kHz. Hook and line samples were collected at 73 acoustic events, and chevron trap samples were collected at 20 acoustic events. The relationship between fisheries acoustic data and catch-per-unit-effort (CPUE) data was examined to develop a model to predict species-generic CPUE at unfished locations. Akaike's Information Criteria (AIC) found equal support for linear, exponential, and power relationships between acoustic backscatter and CPUE for each conventional fishing gear. Further model development would be aided by refining acoustic target information and applying complimentary fish sampling gears (i.e., split-beam fisheries acoustics gear, underwater video). Given further development, a double sampling design should be useful to estimate the relative abundance of important deepwater reef species over a wide area of the shelf break off the southeastern United States, utilizing either survey vessels or vessels-of-opportunity to rapidly collect acoustic samples.

Synchronous multidecadal fish recruitment patterns in Chesapeake Bay, USA

Multispecies fish recruitment patterns within Chesapeake Bay were investigated in four fishery-independent survey data sets (one primary and three ancillary data sets) that together span the years 1968–2004. These independently conducted surveys record interannual recruitment variability for 15 ecologically and economically important fish species of the Northeast US Continental Shelf Large Marine Ecosystem. Principal component analyses revealed that the strongest multispecies recruitment pattern (first principal component) present in each data set describes a negative recruitment relationship between anadromous and coastal shelf-spawning species. Among the data sets, the first principal component accounted for 31%–42% of multispecies variance. Locally weighted regression modeling revealed that the decadal-scale variability accounted for 62% of the variance in the primary data set’s first principal component’s (annual) scores, whereas interannual variability accounted for only 38%. Despite strong differences in sampling methods, sampled habitats, and sampling locations, this pattern of antagonistic recruitment between Chesapeake Bay anadromous and shelf-spawning (CBASS) species was synchronously correlated among data sets at both decadal and interannual scales. The CBASS pattern has tended to persist in one mode for periods lasting longer than a decade and tends to reverse sign rather within only 2–3 years. A statistically significant regime shift occurred in 1992, when recruitment in anadromous fishes became favored at the expense of recruitment of shelf-spawning estuarine-dependant fishes.

The Northeast U.S. continental shelf Energy Modeling and Analysis exercise (EMAX): Ecological network model development and basic ecosystem metrics

During the past half-century notable changes have occurred in the Northeast U.S. (NEUS) Continental Shelf Large Marine Ecosystem (LME). To understand how the system functions as a whole, to evaluate the potential responses of this ecosystem to numerous human-induced perturbations, and to elucidate the relative magnitude of key biota and processes, the Northeast Fisheries Science Center instituted the Energy Modeling and Analysis eXercise (EMAX). The primary goal of EMAX was to establish an ecological network model (i.e., a more nuanced energy budget) of the entire Northeast U.S. food web. The EMAX work focused on the interdisciplinary development of a network model which reflected contemporary conditions (1996–2000) in four major regions of the ecosystem:, Gulf of Maine, Georges Bank, Southern New England and Middle Atlantic Bight. The model had 36 network “nodes” or biomass state variables across a broad range of the biological hierarchy within each trophic level and incorporated a wide range of key rate processes. Because this ecosystem has been relatively well studied many of the biomass estimates were based on field measurements and biomass estimates from the scientific literature were required only for a relatively small number of nodes. The emphasis of EMAX was to explore the particular role of small pelagic fishes in the ecosystem. Our results show that small pelagic fishes are indeed keystone species in the ecosystem. We examined a suite of novel ecosystem metrics as we compared the four regions and provided a general, system-level description of the NEUS ecosystem. The general patterns of the network properties in the four regions were similar; however the network indices and metrics did reveal some noteworthy differences among regions reflecting their different oceanographic and faunal characteristics. The process of compiling and evaluating available data required by an ecosystem network model identified important gaps in our understanding which should be addressed during future ecosystem surveys. Moreover, exercises like EMAX will be a valuable starting point as we continue to progress towards ecosystem-based fisheries management (EBFM).