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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. [ABSTRACT FROM AUTHOR]

The Northeast U.S. shelf (NES) is an oceanographically dynamic marine ecosystem and supports some of the most valuable demersal fisheries in the world. A reliable prediction of NES environmental variables, particularly ocean bottom temperature, could lead to a significant improvement in demersal fisheries management. However, the current generation of climate model‐based seasonal‐to‐interannual predictions exhibits limited prediction skill in this continental shelf environment. Here, we have developed a hierarchy of statistical seasonal predictions for NES bottom temperatures using an eddy‐resolving ocean reanalysis data set. A simple, damped local persistence prediction model produces significant skill for lead times up to ∼5 months in the Mid‐Atlantic Bight and up to ∼10 months in the Gulf of Maine, although the prediction skill varies notably by season. Considering temperature from a nearby or upstream (i.e., more poleward) region as an additional predictor generally improves prediction skill, presumably as a result of advective processes. Large‐scale atmospheric and oceanic indices, such as Gulf Stream path indices (GSIs) and the North Atlantic Oscillation Index, are also tested as predictors for NES bottom temperatures. Only the GSI constructed from temperature observed at 200 m depth significantly improves the prediction skill relative to local persistence. However, the prediction skill from this GSI is not larger than that gained using models incorporating nearby or upstream shelf/slope temperatures. Based on these results, a simplified statistical model has been developed, which can be tailored to fisheries management for the NES. Plain Language Summary: Reliable prediction of bottom temperature could improve fisheries stock assessments on the Northeast U.S. shelf (NES), where some of the most commercially valuable fisheries are located. In this study, we have developed a collection of statistical models that produce seasonal predictions of NES bottom temperature with 1–12 months lead time. Variables considered in these prediction models include local persistence of bottom temperature from prior months, bottom temperature from an upstream or nearby region, and large‐scale atmospheric and oceanic indices representing the North Atlantic Oscillation or position of the Gulf Stream (GS). Only considering local persistence provides significant skill for lead times up to ∼5 months in the Mid‐Atlantic Bight and up to ∼10 months in the Gulf of Maine, although the skill varies by season. Using upstream or nearby bottom temperature and the GS index both generally improve the prediction skill. However, the GS index does not provide higher prediction skill than those upstream or nearby bottom temperatures. A simplified statistical model has been developed, which can be tailored to fisheries management on the NES. Key Points: A local persistence model for bottom temperature provides prediction skill up to ∼10 months with strong variation by region and seasonIncluding upstream or nearby bottom temperature as a predictor largely improves prediction skill, mainly attributed to ocean advectionAn index of Gulf Stream position produces skillful predictions in fall [ABSTRACT FROM AUTHOR]

It is well established that sea turtles are vulnerable to atmospheric and oceanographic shifts associated with climate change. However, few studies have formally projected how their seasonal marine habitat may shift in response to warming ocean temperatures. Here we used a high-resolution global climate model and a large satellite tagging dataset to project changes in the future distribution of suitable thermal habitat for loggerheads along the northeastern continental shelf of the United States. Between 2009 and 2018, we deployed 196 satellite tags on loggerheads within the Middle Atlantic Bight (MAB) of the Northwest Atlantic continental shelf region, a seasonal foraging area. Tag location data combined with depth and remotely sensed sea surface temperature (SST) were used to characterize the species' current thermal range in the MAB. The best-fitting model indicated that the habitat envelope for tagged loggerheads consisted of SST ranging from 11.0° to 29.7 °C and depths between 0 and 105.0 m. The calculated core bathythermal range consisted of SSTs between 15.0° and 28.0 °C and depths between 8.0 and 92.0 m, with the highest probability of presence occurred in regions with SST between 17.7° and 25.3 °C and at depths between 26.1 and 74.2 m. This model was then forced by a high-resolution global climate model under a doubling of atmospheric CO2 to project loggerhead probability of presence over the next 80 years. Our results suggest that loggerhead thermal habitat and seasonal duration will likely increase in northern regions of the NW Atlantic shelf. This change in spatiotemporal range for sea turtles in a region of high anthropogenic use may prompt adjustments to the localized protected species conservation measures. [ABSTRACT FROM AUTHOR]

Somatic growth is an integrated, individual-based response to environmental conditions, especially in ectotherms. Growth dynamics of large, mobile animals are particularly useful as bio-indicators of environmental change at regional scales. We assembled growth rate data from throughout the West Atlantic for green turtles, Chelonia mydas, which are long-lived, highly migratory, primarily herbivorous mega-consumers that may migrate over hundreds to thousands of kilometers. Our dataset, the largest ever compiled for sea turtles, has 9690 growth increments from 30 sites from Bermuda to Uruguay from 1973 to 2015. Using generalized additive mixed models, we evaluated covariates that could affect growth rates; body size, diet, and year have significant effects on growth. Growth increases in early years until 1999, then declines by 26% to 2015. The temporal (year) effect is of particular interest because two carnivorous species of sea turtles-hawksbills, Eretmochelys imbricata, and loggerheads, Caretta caretta-exhibited similar significant declines in growth rates starting in 1997 in the West Atlantic, based on previous studies. These synchronous declines in productivity among three sea turtle species across a trophic spectrum provide strong evidence that an ecological regime shift ( ERS) in the Atlantic is driving growth dynamics. The ERS resulted from a synergy of the 1997/1998 El Niño Southern Oscillation ( ENSO)-the strongest on record-combined with an unprecedented warming rate over the last two to three decades. Further support is provided by the strong correlations between annualized mean growth rates of green turtles and both sea surface temperatures ( SST) in the West Atlantic for years of declining growth rates ( r = −.94) and the Multivariate ENSO Index ( MEI) for all years ( r = .74). Granger-causality analysis also supports the latter finding. We discuss multiple stressors that could reinforce and prolong the effect of the ERS. This study demonstrates the importance of region-wide collaborations. [ABSTRACT FROM AUTHOR]

Sea turtles are vulnerable to climate change impacts in both their terrestrial (nesting beach) and oceanic habitats. From 1982 to 2012, air and sea surface temperatures at major high use foraging and nesting regions (n = 5) of loggerhead turtles (Caretta caretta) nesting in Greece have steadily increased. Here, we update the established relationships between sea surface temperature and nesting data from Zakynthos (latitude: 37.7°N), a major nesting beach, while also expanding these analyses to include precipitation and air temperature and additional nesting data from two other key beaches in Greece: Kyparissia Bay (latitude: 37.3°N) and Rethymno, Crete (latitude: 35.4°N). We confirmed that nesting phenology at Zakynthos has continued to be impacted by breeding season temperature; however, temperature has no consistent relationship with nest numbers, which are declining on Zakynthos and Crete but increasing at Kyparissia. Then using statistically downscaled outputs of 14 climate models assessed by the Intergovernmental Panel on Climate Change (IPCC), we projected future shifts in nesting for these populations. Based on the climate models, we projected that temperature at the key foraging and breeding sites (Adriatic Sea, Aegean Sea, Crete, Gulf of Gabès and Zakynthos/Kyparissia Bay; overall latitudinal range: 33.0°—45.8°N) for loggerhead turtles nesting in Greece will rise by 3–5°C by 2100. Our calculations indicate that the projected rise in air and ocean temperature at Zakynthos could cause the nesting season in this major rookery to shift to an earlier date by as much as 50–74 days by 2100. Although an earlier onset of the nesting season may provide minor relief for nest success as temperatures rise, the overall climatic changes to the various important habitats will most likely have an overall negative impact on this population. [ABSTRACT FROM AUTHOR]

Somatic growth dynamics are an integrated response to environmental conditions. Hawksbill sea turtles ( Eretmochelys imbricata) are long-lived, major consumers in coral reef habitats that move over broad geographic areas (hundreds to thousands of kilometers). We evaluated spatio-temporal effects on hawksbill growth dynamics over a 33-yr period and 24 study sites throughout the West Atlantic and explored relationships between growth dynamics and climate indices. We compiled the largest ever data set on somatic growth rates for hawksbills - 3541 growth increments from 1980 to 2013. Using generalized additive mixed model analyses, we evaluated 10 covariates, including spatial and temporal variation, that could affect growth rates. Growth rates throughout the region responded similarly over space and time. The lack of a spatial effect or spatio-temporal interaction and the very strong temporal effect reveal that growth rates in West Atlantic hawksbills are likely driven by region-wide forces. Between 1997 and 2013, mean growth rates declined significantly and steadily by 18%. Regional climate indices have significant relationships with annual growth rates with 0- or 1-yr lags: positive with the Multivariate El Niño Southern Oscillation Index (correlation = 0.99) and negative with Caribbean sea surface temperature (correlation = −0.85). Declines in growth rates between 1997 and 2013 throughout the West Atlantic most likely resulted from warming waters through indirect negative effects on foraging resources of hawksbills. These climatic influences are complex. With increasing temperatures, trajectories of decline of coral cover and availability in reef habitats of major prey species of hawksbills are not parallel. Knowledge of how choice of foraging habitats, prey selection, and prey abundance are affected by warming water temperatures is needed to understand how climate change will affect productivity of consumers that live in association with coral reefs. [ABSTRACT FROM AUTHOR]

• A bottom temperature product for the northeast U.S. continental shelf. • Long-term high-resolution bottom temperature between 1959 and 2021. • Three ocean products were combined. • Warming of the northeast U.S. shelf is estimated at + 0.36 °C decade-1. • Large warming variations among seasons and regions. • Potential use for a wide range of applications from fisheries to marine ecology. The northeast U.S. continental shelf is a highly productive and socio-economically important marine ecosystem in which annual and seasonal variations of bottom temperature play a major role in the distribution, phenology, and productivity of its predominately demersal marine taxa. However, bottom temperature measurements are limited spatially and temporally and thus do not provide the required resolution to assess sub-seasonal variability and trends. Here we combined three ocean products, a regional ocean model (ROMS) and two global ocean data assimilated models (GLORYS12v1 and PSY4V3R1) to build a high-resolution, long-term bottom temperature product for the northeast U.S. continental shelf between 1959 and 2021. We bias-corrected ROMS using monthly decadal climatologies from ocean observations and analyzed long-term changes in the combined time series. Model skill was assessed using a large number of in situ observations. The combined bottom temperature product showed a long-term warming of the northeast U.S. continental shelf of + 0.36 °C decade-1 over the past 63 years, with notable variations among seasons and regions. The strongest long-term warming occurred during the summer months and in the Gulf of Maine. Although biases were observed, the bottom temperature product exhibited good performance reproducing seasonal and annual variability in observed temperature. This high-resolution product could be used in a wide range of applications from local to regional spatial scales, from long-term to near-term time scales, and from fisheries to marine ecology. [ABSTRACT FROM AUTHOR]

The U.S. Northeast Continental Shelf marine ecosystem has warmed much faster than the global ocean and it is expected that this enhanced warming will continue through this century. Complex bathymetry and ocean circulation in this region have contributed to biases in global climate model simulations of the Shelf waters. Increasing the resolution of these models results in reductions in the bias of future climate change projections and indicates greater warming than suggested by coarse resolution climate projections. Here, we used a high-resolution global climate model and historical observations of species distributions from a trawl survey to examine changes in the future distribution of suitable thermal habitat for various demersal and pelagic species on the Shelf. Along the southern portion of the shelf (Mid-Atlantic Bight and Georges Bank), a projected 4.1 °C (surface) to 5.0 °C (bottom) warming of ocean temperature from current conditions results in a northward shift of the thermal habitat for the majority of species. While some southern species like butterfish and black sea bass are projected to have moderate losses in suitable thermal habitat, there are potentially significant increases for many species including summer flounder, striped bass, and Atlantic croaker. In the north, in the Gulf of Maine, a projected 3.7 °C (surface) to 3.9 °C (bottom) warming from current conditions results in substantial reductions in suitable thermal habitat such that species currently inhabiting this region may not remain in these waters under continued warming. We project a loss in suitable thermal habitat for key northern species including Acadian redfish, American plaice, Atlantic cod, haddock, and thorney skate, but potential gains for some species including spiny dogfish and American lobster. We illustrate how changes in suitable thermal habitat of important commercially fished species may impact local fishing communities and potentially impact major fishing ports along the U.S. Northeast Shelf. Given the complications of multiple drivers including species interactions and fishing pressure, it is difficult to predict exactly how species will shift. However, observations of species distribution shifts in the historical record under ocean warming suggest that temperature will play a primary role in influencing how species fare. Our results provide critical information on the potential for suitable thermal habitat on the U.S. Northeast Shelf for demersal species in the region, and may contribute to the development of ecosystem-based fisheries management strategies in response to climate change. [ABSTRACT FROM AUTHOR]