This dataset was collected in support of a Competitive Science and Research Fund project (21-CC-05-06 Impacts of coastal acidification and climate change stressors on the Atlantic sea scallop: larval supply, recruitment and adaptive capacity to multiple global change drivers) lead by Fisheries and Oceans Canada (DFO). The objective of this research is to characterize coastal environmental conditions associated with scallop spawning and larval drift in Passamaquoddy Bay, New Brunswick. This dataset includes temperature, conductivity, salinity, sigma-theta, sea pressure, and depth information taken at weekly intervals at the sampling stations. In total, this dataset represents a total of 62 CTD profiles collected across 3 sampling stations over 22 sampling days from June to October 2022. Sampling stations were selected to compare scallop recruitment signals from Chamcook Harbour, a decommissioned scallop aquaculture site in Big Bay (MS-1077) and in the middle of Passamaquoddy Bay. Data were processed in accordance with instrumentation manufacturer guidelines and DFO Ocean Data and Information Section QAQC procedures. Cite this data as: Miller, E., Quinn, B., Azetsu-Scott, K., Childs, D., Gabriel, C-E., Newhook, M. 2025. Impacts of coastal acidification and climate change stressors on the Atlantic sea scallop. Published October 2025. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B

This dataset contains the modelled and observed data used in the publication "Fjord circulation permits persistent subsurface water mass in a long, deep mid-latitude inlet" by Laura Bianucci et al., DFO Ocean Sciences Division, Pacific Region (published in the journal Ocean Science in 2024). An application of the Finite Volume Community Ocean Model (FVCOM v4.1) was run from May 24 to June 27, 2019 in the Discovery Islands region of British Columbia, Canada. Observed temperature and salinity profiles available in this area during this time period are included in the dataset, along with the modelled values at the same times and locations.

The Beaufort Regional Environmental Assessment-Marine Fishes Project (2012-2014) and Canadian Beaufort Sea-Marine Ecosystem Assessment (CBS-MEA, 2017-present) conducted by Fisheries and Oceans Canada provide offshore surveys of marine fishes and ecosystems on the Canadian Beaufort Shelf and slope in August and early September. The projects focus on integrating oceanography, food web linkages, physical-biological couplings and spatial and inter-annual variability, within the context of ongoing climate-driven change including enhanced Ocean Acidification. Sampling was conducted from the F/V Frosti at stations along transects spanning 20-1000 m. Zooplankton was collected using a bongo or multi-net system in conjunction with oceanographic and biogeochemical sampling.

We evaluated an autonomous environmental DNA sampler produced by Dartmouth Ocean Technologies Inc (Dartmouth, Canada) compared to time-at-sample filtration in the laboratory to determine the performance of moored samplers for monitoring in the marine world. We deployed three autonomous samplers from DOT in the Bedford Basin (Canada) over a nine-week period in summer/fall 2023. The samplers filtered seawater in situ at programmed interviews over this time period, and we collected contemporaneous samples with a standard vacuum pump during each sampling period. Both eDNA sample types captured similar fish diversity, including typical diversity for the Northwest Atlantic. The invertebrate community detected using the COI marker was different between each sample type, likely due to differences in filter pore size. We found biofouling on the moored samplers was minimal over the study period, even in a high-traffic area such as the Bedford Basin, likely due to the relatively short experimental period, and copper screening covering in the inlet and outlet valves of the instruments. Overall, our results show promise to deploy autonomous eDNA samplers in marine conservation areas to contribute to monitoring in the temperate ocean, but further testing over longer periods of time is needed to determine if DNA remains well-preserved in the autonomous samplers at ambient ocean temperatures.Cite this data as: Jeffery, N.W., Van Wyngaarden, M., and Stanley, R.R.E. Evaluating an Autonomous eDNA Sampler for Marine Environmental Monitoring: Short- and Long-Term Applications. Published: December 2024. Coastal Ecosystems Science Division, Maritimes Region, Fisheries and Oceans Canada, Dartmouth NS.

PURPOSE:In this study, we examined the structure and function of the Southampton Island marine food web across 149 species of benthic and pelagic invertebrates, fishes, marine mammals and seabirds collected from 2016 to 2019, to provide a baseline for future studies that aim to quantify temporal changes in food web structuring. More specifically,we used a multi-biomarker approach combining stable isotopes and HBIs to: (i) determine the vertical trophic structure of the marine food web, (ii) investigate the contribution of benthic and pelagic-derived prey to the higher trophic level species of the Arctic food web, and (iii) determine the role of ice algae and phytoplankton carbon source use across different trophic levels and compartments (pelagic and benthic). By shedding new light on the functioning of the Southampton Island food web and specifically how the contribution of ice algae and benthic habitat shapes its structure, these results will be relevant to adaptive management and conservation initiatives implemented in response to anthropogenic stressors and climate change. DESCRIPTION:Climate-driven alterations of the marine environment are most rapid in Arctic and subarctic regions, including Hudson Bay in northern Canada, where declining sea ice, warming surface waters and ocean acidification are occurring at alarming rates. These changes are altering primary production patterns that will ultimately cascade up through the food web. Here, we investigated (i) the vertical trophic structure of the Southampton Island marine ecosystem in northern Hudson Bay, (ii) the contribution of benthic and pelagic-derived prey to the higher trophic level species, and (iii) the relative contribution of ice algae and phytoplankton derived carbon in sustaining this ecosystem. For this purpose, we measured bulk stable carbon, nitrogen and sulfur isotope ratios as well as highly branched isoprenoids in samples belonging to 149 taxa, including invertebrates, fishes, seabirds and marine mammals. We found that the benthic invertebrates occupied 4 trophic levels and that the overall trophic system went up to an average trophic position of 4.8. The average δ34S signature of pelagic organisms indicated that they exploit both benthic and pelagic food sources, suggesting there are many interconnections between these compartments in this coastal area. The relatively high sympagic carbon dependence of Arctic marine mammals (53.3 ± 22.2 %) through their consumption of benthic invertebrate prey, confirms the important role of the benthic subweb for sustaining higher trophic level consumers in the coastal pelagic environment. Therefore, a potential decrease in the productivity of ice algae could lead to a profound alteration of the benthic food web and a cascading effect on this Arctic ecosystem.Collaborators:Centre for Earth Observation Science, University of Manitoba, Winnipeg, Manitoba, Canada - R´emi Amiraux, C.J. Mundy, Jens K. Ehn, Z.A. Kuzyk.Quebec-Ocean, Sentinel North and Takuvik, Biology Department, Laval University, Quebec, Quebec, Canada - Marie Pierrejean.Scottish Association for Marine Science, Oban, UK - Thomas A. Brown.Department of Natural Resource Sciences, McGill University, Ste. Anne de Bellevue, Quebec, Canada - Kyle H. Elliott.Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada - Steven H. Ferguson, Cory J.D. Matthews, Cortney A. Watt, David J. Yurkowski.School of the Environment, University of Windsor, Windsor, Ontario, Canada - Aaron T. Fisk.Science and Technology Branch, Environment and Climate Change Canada, Ottawa, Ontario, Canada - Grant Gilchrist.College of Fisheries and Ocean Sciences, University of Alaska Fairbanks, Fairbanks, AK, USA - Katrin Iken.Department of Earth Sciences, University of New Brunswick, Fredericton, NB, Canada - Audrey Limoges.Department of Integrative Biology, University of Windsor, Windsor, Ontario, Canada - Oliver P. Love, Wesley R. Ogloff.Department of Arctic Biology, The University Centre in Svalbard, Longyearbyen, Norway - Janne E. Søreide.

Description:In the coming decades, warming and deoxygenation of marine waters are anticipated to result in shifts in the distribution and abundance of fishes, with consequences for the diversity and composition of fish communities. Here, we combine fisheries-independent trawl survey data spanning the west coast of the USA and Canada with high-resolution regional ocean models to make projections of how 34 groundfish species will be impacted by changes in temperature and oxygen in British Columbia (BC) and Washington. In this region, species that are projected to decrease in occurrence are roughly balanced by those that are projected to increase, resulting in considerable compositional turnover. Many, but not all, species are projected to shift to deeper depths as conditions warm, but low oxygen will limit how deep they can go. Thus, biodiversity will likely decrease in the shallowest waters (less than 100 m), where warming will be greatest, increase at mid-depths (100–600 m) as shallow species shift deeper, and decrease at depths where oxygen is limited (greater than 600 m). These results highlight the critical importance of accounting for the joint role of temperature, oxygen and depth when projecting the impacts of climate change on marine biodiversity.The rasters available in this dataset project the occurrence of each of the 34 groundfish species in a 3 km^2 grid cell for the historical baseline, as well as for two emissions scenarios, from each of the two regional ocean models (BCCM and NEP36). Each projection layer is provided as the mean projected occurrence as well as the lower and upper 95% confidence interval of projected occurrence.Methods:Estimated species response curves:We estimated how the observed distribution of groundfish species is determined by temperature, dissolved oxygen and seafloor depth using data from fisheries-independent scientific research trawls spanning the entire American and Canadian west coast. We included data from 4 surveys (NOAA West Coast, NOAA Alaska, NOAA Bering or DFO Pacific) from 2000 to 2019. For each species, we modelled occurrences in the coastwide trawl dataset using a generalized linear model (GLM) using the sdmTMB package in R v. 4.0.2. The predictors were temperature, log dissolved oxygen, log depth and survey. We included quadratic terms for temperature and log depth to allow species occurrences to peak at intermediate values. We fitted a breakpoint function for log dissolved oxygen to reflect the fact oxygen is a limiting factor. We assessed the forecasting accuracy of the SDM by comparing how well a model fitted to only data from 2000 to 2010 could forecast species’ occurrences in trawls within our focal region for the period of 2011–2019. We assessed all 77 groundfish species that were present in the overall trawl dataset, however the final analysis included only the 34 species for which the models had adequate forecasting ability.Projecting groundfish biodiversity changes:We based our groundfish biodiversity change projections on two regional models that downscale climate projections: the British Columbia Continental Margin model (BCCM) and the North-Eastern Pacific Canadian Ocean Ecosystem model (NEP36-CanOE). We used a historical baseline of 1986–2005 and future projected values for 2046–2065 based on RCP 4.5 and 8.5 emissions scenarios. Using the models that we validated in our forecasting accuracy assessment, we projected the occurrence of each species in each 3 km^2 grid cell for the historical baseline, as well as for two emissions scenarios, from each of the two regional ocean models.Uncertainties:Source survey data was collected by consistent methods with survey-grade GPS for all years included. Data quality is expected to be high. Modeled data are at 3 km resolution. Outputs are as accurate as source input models and are deemed to be of high quality and accurate based upon the precision of model inputs.Projecting biodiversity responses to climate change involves considerable uncertainty and our approach allows us to quantify some aspects of this. Of the uncertainty that we could quantify, roughly half was due to uncertainty in our SDMs and the remainder was due to regional ocean model uncertainty or scenario uncertainty. This amount of uncertainty in the SDMs is typical, stemming from the fact that contemporary species distributions are also influenced by other factors that we have not included in our model. In addition, although oxygen demand is understood to vary with temperature, limitations in the implementation of breakpoint models prevented us from estimating a temperature-dependent oxygen breakpoint. However, although somewhat unrealistic, this limitation is unlikely to have greatly increased the uncertainty in our SDMs because low oxygen concentrations occurred almost exclusively at depths where temperature variation and projected change was small.To reduce uncertainty due to year-to-year variation in climate, our model projections are based on 20-year climatologies with a future period that is far enough ahead to ensure that changes are unambiguously due to greenhouse gases. We have made projections based on two different emissions scenarios, and two different regional ocean models that are both downscaled from the same global model, the second generation Canadian Earth System Model (CanESM2), using different downscaling techniques. While the BCCM model was run inter-annually and then averaged to produce the climatologies, the NEP36 model used atmospheric climatologies with augmented winds to force the ocean model and produce representative climatologies. Comparing these regional projections provides an estimate of the uncertainty across different regional downscaling models and methods. We find that the projected impacts of climate change on the groundfish community are more sensitive to the differences in the regional ocean models than they are to the emissions scenarios used. However, these differences are in magnitude (changes tend to be larger based on NEP36 compared with the BCCM) rather than in direction, with both models resulting in similar overall patterns of biodiversity change and turnover for the groundfish community. Over the 60-year time period (1986–2005 versus 2046–2065) used in our study, our projections suggest that groundfish community changes are similar regardless of the scenario used.

The Global Ice-Ocean Prediction System (GIOPS) produces global sea ice and ocean analyses and 10 day forecasts daily. This product contains time-mean sea ice and ocean forecast fields interpolated to two grids. One of the grids is a 0.2° resolution regular latitude-longitude grid covering the global ocean (north of 80° S). The other grid is in north-polar stereographic projection with a 5-km spacing at the standard parallel 60° N and covers the Arctic Ocean and the neighbouring sub-polar seas. Data is available for 50 depths. The data files are in netCDF format and comply with the Climate and Forecast Conventions.

This dataset provides 1/36-degree monthly mean ocean current climatology (October - March) in the Northeast Pacific. The climatological fields are derived from hourly ocean currents for the perid from 1993 to 2020, simulated using a high-resolution Northeast Pacific Ocean Model (NEPOM).

This dataset provides 1/36-degree monthly-mean ocean current climatology (April - September) in the Northeast Pacific. The climatological fields are derived from hourly ocean currents for the period from 1993 to 2020, simulated using a high-resolution Northeast Pacific Ocean Model (NEPOM).

The Coastal Ice Ocean Prediction System (CIOPS) provides a 48 hour ocean and ice forecast over different domains (East, West, Salish Sea) four times a day at 1/36° resolution. A pseudo-analysis component is forced at the ocean boundaries by the Regional Ice Ocean Prediction System (RIOPS) forecasts and spectrally nudged to the RIOPS solution in the deep ocean. Fields from the pseudo-analysis are used to initialize the 00Z forecast, whilst the 06, 12 and 18Z forecasts use a restart files saved at hour 6 from the previous forecast. The atmospheric fluxes for both the pseudo-analysis and forecast components are provided by the High Resolution Deterministic Prediction System (HRDPS) blended both spatially and temporally with either the Global Deterministic Prediction System (GDPS) (for CIOPS-East) or an uncoupled component of the Global Deterministic Prediction System (GDPS) at 10km horizontal resolution (for CIOPS-West) for areas not covered by the HRDPS.