Northeast US Continental Shelf Research Articles

Multispecies population-scale emergence of climate change signals in an ocean warming hotspot

Abstract Ocean waters of the Northeast US continental shelf have warmed rapidly in recent years, with sea surface temperatures rising 2.5 times faster than those of the global oceans. With this strong warming trend, the frequency and duration of marine heatwaves have increased. These temperature changes stood out as a distinct warm temperature regime during the 2010s. During this decade, fish population characteristics also differed from the past. Species distribution shifts were detected for many species, demonstrating one way species could adapt to warming conditions. However, for most species, distribution shifts were insufficient to avoid warmer surface or bottom temperatures. As species occupied warmer habitats, growth patterns aligned with expectations for warming temperatures. Consistent with the temperature-size rule, some species exhibited faster growth at early life stages but plateaued at smaller body sizes; other species, however, experienced reduced growth across all ages, indicating thermal stress. Finally, population productivity indexed by the recruit-to-spawner ratio declined significantly during the 2010s for some populations. Changes in these three processes—distribution, growth, and productivity—indicate the emergence of climate change signals across multiple Northeast US fish populations. These effects create new challenges for fishery managers and industry participants operating in the context of non-stationarity and uncertainty.

Regime change in northwest Atlantic sea surface temperatures revealed using a quantile approach

Trends in sea surface temperatures (SST) of the US Northeast Continental Shelf and the adjacent Slope Sea were analyzed using a quantile approach. SST through the period 1982–2021 were analyzed for change in annual mean and range. In addition, the mean of each 25% quantile of the data by year was calculated. Using the full time series, the climatological SSTs at each quantile was determined, which in turn were used with the annual data to determine the number of days temperature fell within the limits of each climatological quantile. The time series of the data parameters were summarized by grid location and for a series of representative index areas. The index areas were analyzed for evidence of change points or regime shifts using the STARS (Sequential T-test Analysis of Regime Shifts) algorithm. The widely reported SST warming in this region was reinforced with our analysis; our findings also revealed new aspects of the change of thermal conditions in important ways. Mean annual temperature trended at approximately 0.36 °C per decade; however, warm quantile SSTs increased by more than 1.25 °C per decade in the Slope Sea, representing a five degree increase over the study period. The change point analysis suggested the change in thermal regime began as early as 2005 or 2007 with the study region fully enveloped by regime change by 2012. A previously identified change point in 1999 appears to be related to the duration of warming as opposed to SST levels. Mean SST alone does not capture the nature of high temperature exposure for living marine species in the study area; these regions may be experiencing a month or more of stressfully higher SST. The thermal effects derived using the quantile approach suggest different types of thermal exposures compared to heat wave analyses, especially related to cumulative exposure.

The spatial correlation between trawl surveys and planned wind energy infrastructure on the US Northeast Continental Shelf

Abstract The development of wind energy on the US Northeast Continental Shelf (NES) may preclude resource-monitoring programmes from continuing in their original study designs. We considered the spatial requirements of energy developers and the spatial autocorrelation of resident species as a means to inform survey mitigation. The spatial requirements of the NES wind industry were considered in respect to the delineation of settled lease areas. We suggest access metrics ranging from 8 to 21 km representing the interquartile range of chord distances across the settled lease areas. Using survey data and concentrating on commercial species with stock assessment requirements, we computed indices of spatial autocorrelation. Tests of spatial autocorrelation using Moran’s I and join counts statistics were significant (p < 0.05) for most species, suggesting a high level of spatial correlation in their distributions. To characterize a scalar extent of spatial correlation, variograms were fit to estimate the physical range of correlated catches. These data suggest most species were spatially correlated well beyond the distance metrics derived from the lease area shapes. Sampling by a range of gears has the potential of producing spatially accurate depictions of species distributions and abundance despite the restrictions wind lease areas may place on sampling designs.

An evaluation of eight global ocean reanalyses for the Northeast U.S. Continental shelf

The Northeast U.S. continental Shelf (NES) extending from the Gulf of Maine to Cape Hatteras, is a dynamic region supporting some of the most commercially valuable fisheries in the world. This study aims to provide a systematic assessment of eight widely used, intermediate-to-high spatial resolution global ocean reanalysis products (CFSR, ECCO, ORAS, SODA, BRAN, GLORYS, GOFS3.0, and GOFS3.1) against available in situ and satellite ocean observations. In situ observations include water level from tide gauges, and temperature and salinity from various sources including shipboard hydrographic data, and moorings on the NES. Overall, the coarser resolution products exhibit limited skill in the coastal environment, with the high-resolution products better representing the temperature and salinity on the NES. Common biases are found in all reanalyses and in some regions within the NES; for example, biases in temperature and salinity are larger in the southern Mid-Atlantic Bight than in the rest of the NES. There is no single reanalysis that performs well across all parameters in all regions within the NES, but GLORYS and BRAN stand out for their superior performance across the largest number of metrics, outperforming other products in 22 and 25 of the 65 metrics examined, respectively. SODA is the top performer among the coarser resolution products (CFSR, ECCO, ORAS and SODA). The Gulf Stream and local bathymetry are critical factors leading to differences between the reanalyses. Conditions in summer are less well represented than in winter. In particular, the Mid-Atlantic Bight Cold Pool is not reproduced in four (CFSR, ECCO, ORAS, BRAN) of the eight reanalyses.

Offshore wind project-level monitoring in the Northeast U.S. continental shelf ecosystem: evaluating the potential to mitigate impacts to long-term scientific surveys

Offshore wind will generate much needed renewable energy in the U.S. and worldwide, but this industry will also affect other ocean uses. In the Northeast U.S. continental shelf (NES) ecosystem, these effects include the impact that wind development will have on the design and execution of long running scientific surveys conducted by National Marine Fisheries Service of the National Oceanic and Atmospheric Administration (NOAA Fisheries) which play a critical role in the provision of scientific information for stock assessment and advice for fisheries management. Recognizing these impacts, the federal government has established a Survey Mitigation Strategy that identifies a need to evaluate whether the information yielded from project-level monitoring studies conducted by wind developers might be suitable for integration with data from NOAA Fisheries surveys, thereby ameliorating the impacts to the surveys. To address this need, we compiled and tabulated information from all currently available project-level monitoring studies and compared elements of the design and methodology of each study with that of the comparable NOAA Fisheries survey. Based on this information, we evaluated their suitability for filling expected gaps in long term surveys, for addressing impacts at the population level, and for understanding interactions between fish stocks and habitat alterations. We found that project-level monitoring studies as currently designed for the NES ecosystem will not yield information that can mitigate impacts to NOAA Fisheries scientific survey time series from offshore wind development. We provide recommendations on how to enhance the ability of project-level monitoring studies to mitigate impacts to long term scientific surveys.

Surface and subsurface oceanographic features drive forage fish distributions and aggregations: Implications for prey availability to top predators in the US Northeast Shelf ecosystem.

Forage fishes are a critical food web link in marine ecosystems, aggregating in a hierarchical patch structure over multiple spatial and temporal scales. Surface-level forage fish aggregations (FFAs) represent a concentrated source of prey available to surface- and shallow-foraging marine predators. Existing survey and analysis methods are often imperfect for studying forage fishes at scales appropriate to foraging predators, making it difficult to quantify predator-prey interactions. In many cases, general distributions of forage fish species are known; however, these may not represent surface-level prey availability to predators. Likewise, we lack an understanding of the oceanographic drivers of spatial patterns of prey aggregation and availability or forage fish community patterns. Specifically, we applied Bayesian joint species distribution models to bottom trawl survey data to assess species- and community-level forage fish distribution patterns across the US Northeast Continental Shelf (NES) ecosystem. Aerial digital surveys gathered data on surface FFAs at two project sites within the NES, which we used in a spatially explicit hierarchical Bayesian model to estimate the abundance and size of surface FFAs. We used these models to examine the oceanographic drivers of forage fish distributions and aggregations. Our results suggest that, in the NES, regions of high community species richness are spatially consistent with regions of high surface FFA abundance. Bathymetric depth drove both patterns, while subsurface features, such as mixed layer depth, primarily influenced aggregation behavior and surface features, such as sea surface temperature, sub-mesoscale eddies, and fronts influenced forage fish diversity. In combination, these models help quantify the availability of forage fishes to marine predators and represent a novel application of spatial models to aerial digital survey data.

Shelf break exchange processes influence the availability of the northern shortfin squid, Illex illecebrosus, in the Northwest Atlantic

AbstractThe United States Northern Shortfin squid fishery is known for its large fluctuations in catch at annual scales. In the last 5 years, this fishery has experienced increased availability of Illex illecebrosus along the Northeast US continental shelf (NES), resulting in high catch per unit effort (CPUE) and early fishery closures due to quota exceedance. The fishery occurs within the Northwest Atlantic, whose complex dynamics are set up by the interplay between the large‐scale Gulf Stream, mesoscale eddies, Shelfbreak Jet, and shelf‐slope exchange processes. Our ability to understand and quantify this regional variability is requisite for understanding the availability patterns of Illex, which are largely influenced by oceanographic conditions. In an effort to advance our current understanding of the seasonal and interannual variability in this species' relative abundance on the NES, we used generalized additive models to examine the relationships between the physical environment and hotspots of productivity to changes in CPUE of I. illecebrosus in the Southern stock component, which comprises the US fishery. Specifically, we derived oceanographic indicators by pairing high‐resolution remote sensing data and global ocean reanalysis physical data to high‐resolution fishery catch data. We identified a suite of environmental covariates that were strongly related to instances of higher catch rates. In particular, bottom temperature, warm core rings, subsurface features, and frontal dynamics together serve as indicators of habitat condition and primary productivity hotspots, providing great utility for understanding the distribution of Illex with the potential for forecasting seasonal and interannual availability.

Forage Fish Species Prefer Habitat within Designated Offshore Wind Energy Areas in the U.S. Northeast Shelf Ecosystem

AbstractAs the world develops sources of renewable energy, there is an intensifying interest in offshore wind energy production. The Northeast U.S. Continental Shelf (NES) ecosystem has favorable wind dynamics, with active development of wind energy. In this study, we present species distribution models that consider both occupancy and biomass responses for a broad spectrum of fish and macroinvertebrate taxa (n = 177). Building upon prior analyses, habitat was differentiated into overall and core habitats based on statistical distributions of habitat scores. Overall habitat was used to show each species' regional distribution based on fishery‐independent survey captures between 1976 and 2019, whereas core habitat represented where the focus of the species' abundance was located as a subset of overall habitat. Wind energy developments may modify the water column in ways that impact lower‐trophic‐level productivity; therefore, added attention was given to the response of forage species. Over 20% of species showed preferential use of putative and potential wind development areas, including a disproportionate number of forage taxa. Principal usage varied by season, with forage species like Atlantic Menhaden Brevoortia tyrannus and Atlantic Mackerel Scomber scombrus preferentially using the lease areas in spring and Round Herring Etrumeus teres and longfin inshore squid Doryteuthis pealeii using lease areas in autumn. For species with relatively low usage of the lease areas, there was a tendency for the usage related to overall habitat to be lower than usage for core habitat; in contrast, for species with high usage of the lease areas, that usage was higher for overall habitat than for core habitat. The area of habitat tended to have positive trends across species, with these positive trends being disproportionately higher among forage taxa. These results frame the importance of wind lease areas for species in the NES, particularly forage taxa that fulfill many important ecological functions.

Jointly modeling marine species to inform the effects of environmental change on an ecological community in the Northwest Atlantic

Single species distribution models (SSDMs) are typically used to understand and predict the distribution and abundance of marine fish by fitting distribution models for each species independently to a combination of abiotic environmental variables. However, species abundances and distributions are influenced by abiotic environmental preferences as well as biotic dependencies such as interspecific competition and predation. When species interact, a joint species distribution model (JSDM) will allow for valid inference of environmental effects. We built a joint species distribution model of marine fish and invertebrates of the Northeast US Continental Shelf, providing evidence on species relationships with the environment as well as the likelihood of species to covary. Predictive performance is similar to SSDMs but the Bayesian joint modeling approach provides two main advantages over single species modeling: (1) the JSDM directly estimates the significance of environmental effects; and (2) predicted species richness accounts for species dependencies. An additional value of JSDMs is that the conditional prediction of species distributions can use not only the environmental associations of species, but also the presence and abundance of other species when forecasting future climatic associations.

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.

Optimization and assessment of phytoplankton size class algorithms for ocean color data on the Northeast U.S. continental shelf

The size structure of phytoplankton communities influences important ecological and biogeochemical processes, including the transfer of energy through marine food webs. A variety of algorithms have been developed to estimate phytoplankton size classes (PSCs) from satellite ocean color data. However, many of these algorithms were developed for application to the global ocean, and their performance in more productive, optically complex coastal and continental shelf regions warrants evaluation. In this study, several existing PSC models were applied in the Northeast U.S. continental shelf (NES) region and compared with in situ PSC estimates derived from a local HPLC pigment data set. The effect of regional re-parameterization and incorporation of sea surface temperature (SST) into existing abundance-based model frameworks was investigated and model performance was assessed using an independent data set. Abundance-based model re-parameterization alone did not result in significant improvement in model performance compared with other models. However, the inclusion of SST led to a consistent reduction in model error for all size classes. Of two absorption-based algorithms tested, the best performing approach displayed similar performance metrics to the regional SST-dependent abundance-based model. The SST-dependent model and the absorption-based method were applied to monthly composites of the NES region for April and September 2019 and qualitatively compared. The results highlight the benefit of considering SST in abundance-based models and the applicability of absorption-based PSC methods in optically complex regions.

Resource Occurrence and Productivity in Existing and Proposed Wind Energy Lease Areas on the Northeast US Shelf

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.

Machine learning highlights the importance of primary and secondary production in determining habitat for marine fish and macroinvertebrates

Abstract Species distribution models for marine organisms are increasingly used for a range of applications, including spatial planning, conservation, and fisheries management. These models have been constructed using a variety of mathematical forms and drawing on both physical and biological independent variables; however, what might be called first‐generation models have mainly followed the form of linear models, or smoothing splines, informed by data collected in the context of fish surveys. The performance of different classes of variables were tested in a series of species occurrence models built with machine learning methods, specifically evaluating the potential contribution of lower trophic level data. Random forest models were fitted based on the classification of the absence/presence for fish and macroinvertebrates surveyed on the US Northeast Continental Shelf. The potential variables included physical, primary production, secondary production, and terrain variables. For accepted model fits, six variable importance measures were computed, which collectively showed that physical and secondary production variables make the greatest contribution across all models. In contrast, terrain variables made the least contribution to these models. Multivariable analyses that account for all performance measures reinforce the role of water depth and temperature in defining species presence and absence; however, chlorophyll concentration and some specific zooplankton taxa, such as Metridia lucens and Paracalanus parvus, also make important contributions with strong seasonal variations. Our results suggest that lower trophic level variables, if available, are valuable in the creation of species distribution models for marine organisms.

A test of the provisioning hypothesis of recruitment control in Georges Bank haddock

The haddock (Melanogrammus aeglefinus) stock of the Georges Bank region of the US Northeast Continental Shelf displays a pattern of large, episodic recruitments. Among the hypothesized controlling mechanisms is the idea that recruitment events are related to provisioning of prespawning haddock by the fall bloom the year before. With the occurrence of a recent large recruitment event in 2013, it would be prudent to retest this hypothesis. Fall bloom magnitude was positively correlated (r = 0.645, p = 0.005) with haddock survivor ratio (recruits per spawning biomass), including data from the 2013 recruitment. This relationship identifies a pathway of bottom-up control of a resource species, thus focusing concern over recent changes in lower trophic-level productivity.

Modeling the impacts of climate change on thorny skate (Amblyraja radiata) on the Northeast US shelf using trawl and longline surveys

AbstractClimate change has been shown to impact marine fish populations and communities. With small population sizes, long reproduction times, and a rapidly warming habitat, thorny skate (Amblyraja radiata) could be particularly vulnerable. To examine this possibility, we used a two‐stage generalized additive model to project future thorny skate abundances under two different climate scenarios. This is the first study in the northeastern United States to compare projections based on different survey methods (bottom trawl and longline), and results were heavily impacted by survey methodology. Models trained with the NOAA Bottom Trawl Survey projected a decrease in abundance of ~60%–80% in the Gulf of Maine and Georges Bank under the RCP 8.5 climate scenario. With aggressive mitigation (RCP 4.5), these decreases could be reduced to ~35%–45%. Models trained with a recent NOAA longline survey indicated that thorny skate abundance would be reduced 22% and 37% under business as usual and mitigation, respectively. There are substantial methodological differences between the two data sets, including capture technique and efficiency, total habitat coverage, and spatio‐temporal coverage. This underscores the importance of continued, methodologically diverse surveys on the Northeast US continental shelf. Our results indicate that climate change will continue to negatively impact thorny skate populations by reducing the amount of thermally suitable habitat in the southern extent of their range. This information should be considered in future management decisions.

Trends and change points in surface and bottom thermal environments of the US Northeast Continental Shelf Ecosystem

AbstractTemperature is an important factor in defining the habitats of marine resource species. While satellite sensors operationally measure ocean surface temperatures, we depend on in situ measurements to characterize benthic habitats. Ship‐based measurements were interpolated to develop a time series of gridded spring and fall, surface and bottom temperature fields for the US Northeast Shelf. Surface and bottom temperatures have increased over the study period (1968–2018) at rates between 0.18–0.31°C per decade and over a shorter time period (2004–2018) at rates between 0.26–1.49°C per decade. A change point analysis suggests that a warming regime began in the surface waters in 2011 centered on Georges Bank and the Nantucket Shoals; in following years, most of the Northeast Shelf had experienced a shift in surface temperature. A similar analysis of bottom temperature suggests a warming regime began in 2008 in the eastern Gulf of Maine; in following years, change points in temperature occurred further to the west in the Gulf of Maine, finally reaching the Middle Atlantic Bight by 2010. The spatial pattern in bottom water warming is consistent with well‐known oceanographic patterns that advect warming North Atlantic waters into the Gulf of Maine. The varying spatial and temporal progression of warming in the two layers suggests they were actuated by different sets of forcing factors. We then compared these trends and change points to responses of lower and higher trophic level organisms and identified a number of coincident shifts in distribution and biomass of key forage and fisheries species.

Multispecies functional responses reveal reduced predation at high prey densities and varied responses among and within trophic groups

AbstractUnderstanding predator–prey interactions is critical for marine fisheries and ecosystem management as they shape community structure, regulate prey populations and present energy demands critical for community sustainability. We examined multispecies functional responses of 17 fishes (48 predator‐size combinations) spanning piscivores, planktivores and benthivores for the northeast US continental shelf. Similar to previous work, linear relationships between predation and prey density (Holling type I response) were not supported, since model estimates of handling time were greater than zero for the prey considered. Instead, a clear majority of the predators sampled were Holling type III feeders (sigmoidal; prey switching or learning). For piscivores, nearly all responses were Holling type III with the exception of one being Holling type II (hyperbolic; satiation). Planktivores and benthivores exhibited a combination of type IV (feeding confusion at high prey density) and Holling type III responses. The relationships were predator‐ and prey‐dependent, which is counter to assumptions that are often made of trophic groups. Decreased predation at high prey densities (type IV response) present among planktivores and benthivores suggests an overestimation of predation can occur if ignored. This contrasts with fish and squid prey which primarily invoked a Holling type III response. Functional responses are key to modelling trophic interactions for multispecies and ecosystem models. By refining these inputs in a multispecies context with empirical data, we can advance our understanding of whole‐shelf ecology and improve decision‐making tools for resource management.

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.

Complex patterns of temperature sensitivity, not ecological traits, dictate diverse species responses to climate change

Despite widespread interest in describing and forecasting the impacts of climate change on species distributions, poor understanding of the climate variables that shape distributions and conflicting perspectives on the role that species traits play in mediating shifts have limited our ability to interpret and project changes in species distributions. Using standardized survey data along the northeast US continental shelf, we assessed the historical exposure and sensitivity of 81 species of marine chordates, arthropods, and molluscs to 24 sea surface temperature (SST) variables in two seasons. By comparing temperature trends in geographies available to species against temperature trends in geographies used by them we were able to identify which variables species track consistently through space and time. Logistic regression analyses were then used to assess whether species traits affected the likelihood of niche tracking while accounting for the season and temporal window in which temperatures were summarized and methodological constraints that might have limited our ability to detect tracking responses. A slight majority of species (52%) clearly shifted their distributions to track at least one temperature variable through space and time. Tracking rates were much lower on a per variable basis (5.1% of 3432 variables), despite widespread exposure to changing temperatures (89.2% of 3432 variables). None of the twelve ecological traits we investigated – including traits related to dispersal ability, ecological specialization, reproductive capacity, and commercial harvest – accounted for differences in tracking responses across species even after accounting for differences in climate exposure. Our results suggest widespread behavioral or physiological flexibility among our study species, or ongoing genetic adaptation to changing temperatures. They also suggest that divergent selection on climate sensitivities of close relatives may limit the utility of ecological traits for predicting distributional responses to future climate change.

Feeding dynamics of Northwest Atlantic small pelagic fishes

Small pelagic fishes represent a critical link between zooplankton and large predators. Yet, the taxonomic resolution of the diets of these important fishes is often limited, especially in the Northwest Atlantic. We examined the diets, along with stable isotope signatures, of five dominant small pelagic species of the northeast US continental shelf ecosystem (Atlantic mackerel Scomber scombrus, Atlantic herring Clupea harengus, alewife Alosa pseudoharengus, blueback herring Alosa aestivalis, and Atlantic butterfish Peprilus triacanthus). Diet analyses revealed strong seasonal differences in most species. Small pelagic fishes predominantly consumed Calanus copepods, small copepod genera (Pseudocalanus/Paracalanus/Clausocalanus), and Centropages copepods in the spring, with appendicularians also important by number for most species. Krill, primarily Meganyctiphanes norvegica, and hyperiid amphipods of the genera Hyperia and Parathemisto were common in the stomach contents of four of the five species in the fall, with hyperiids common in the stomach contents of butterfish in both seasons and krill common in the stomach contents of alewife in both seasons. Depth and region were also found to be sources of variability in the diets of Atlantic mackerel, Atlantic herring, and alewife (region but not depth) with krill being more often in the diet of alewife in more northerly locations, primarily the Gulf of Maine. Stable isotope data corroborate the seasonal differences in diet but overlap of isotopic niche space contrasts that of dietary overlap, highlighting the differences in the two methods. Overall, the seasonal variability and consumer-specific diets of small pelagic fishes are important for understanding how changes in the zooplankton community could influence higher trophic levels.