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    The Fieldnotes dataset represents the anticipated locations of DFO Science field operations for 2020-2021 in the North Pacific and Arctic oceans, as well as in the coastal and interior waters of British Columbia and the Yukon.

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    Greenland Sharks (Somniosus microcephalus) are estimated to have the highest longevity of any invertebrate (392 ± 120 years), making bycatch a significant concern (Nielsen et al. 2016). However, in the Newfoundland and Labrador (NL) region, accurate estimates of bycatch are not often available for the species (Simpson et al. 2021). To address this, species distribution models (SDMs) were generated to delineate habitat suitability for the species throughout the NL region in order to identify areas where a higher rate of bycatch is expected to occur. Observations of Greenland shark bycatch recorded by At-Sea Observers (ASOs) in NL (1983 – 2019), Spain (1999 – 2017), and by the Northwest Atlantic Fisheries Organization (NAFO) Secretariat (2014 – 2019) were compiled to generate a presence-only dataset. Multiple environmental variables were assessed for collinearity, and non-collinear variables (Bathymetry and mean monthly bottom temperature for March and November (1990 – 2015)) were retained for use in the SDM. MaxEnt (maximum entropy) software was used to model habitat suitability because it is a presence-only modelling program that is able to account for a lack of absence data by comparing the environmental conditions at occurrence locations to those at randomly selected background points. Overall, the results indicated that habitat suitability for Greenland Shark was highest in deeper waters along the shelf edge in NAFO Divisions 3OP, and the Laurentian Channel, but also extended along the edge of the Labrador shelf, the Grand Banks, and deeper areas along the continental shelf such as the Hawke Channel, Funk Island Deep, and the slopes of Saglek, Nain, and Hamilton Banks. Beyond the Economic Exclusive Zone (EEZ) and within the NAFO regulatory area (NRA), suitable habitat was also present within the Flemish Pass, and along the slope of the Flemish Cap and shelf edge in NAFO Divisions 3NO (Simpson et al. 2021). More detailed information can be found in Simpson et al. 2021. References: Nielsen, J., R. B. Hedeholm, J. Heinemeier, P. G. Bushnell, J. S. Christiansen, J. Olsen, C. B. Ramsey, R. W. Brill, M. Simon, K. F. Steffensen, J. F. Steffensen. 2016. Eye lens radiocarbon reveals centuries of longevity in the Greenland shark (Somniosus microcephalus). Science 353 (6300):702-704 Simpson, M. R., Gullage, L., Konecny, C., Ollerhead, N., Treble, M.A., Nogueira, A., González-Costas, F. 2021. Spatial-temporal variation in Greenland shark (Somniosus microcephalus) bycatch in the NAFO Regulatory Area. NAFO SCR Doc. 21/028

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    This dataset consists of three simulations from the Northeastern Pacific Canadian Ocean Ecosystem Model (NEP36-CanOE) which is a configuration of the Nucleus for European Modelling of the Ocean (NEMO) V3.6. The historical simulation is an estimate of the 1986-2005 mean climate. The future simulations project the 2046-2065 mean climate for representative concentration pathways (RCP) 4.5 (moderate mitigation scenario) and 8.5 (no mitigation scenario). Each simulation is forced by a climatology of atmospheric forcing fields calculated over these 20 year periods and the winds are augmented with high frequency variability, which introduces a small amount of interannual variability. Model outputs are averaged over 3 successive years of simulation (the last 3, following an equilibration period); standard deviation among the 3 years is available upon request. For each simulation, the dataset includes the air-sea carbon dioxide flux, monthly 3D fields for potential temperature, salinity, potential density, total alkalinity, dissolved inorganic carbon, nitrate, oxygen, pH, total chlorophyll, aragonite saturation state, total primary production, and monthly maximum and minimum values for oxygen, pH, and potential temperature. The data includes 50 vertical levels at a 1/36 degree spatial resolution and a mask is provided that indicates regions where these data should be used cautiously or not at all. For a more detailed description please refer to Holdsworth et al. 2021. The data available here are the outputs of NEP36-CanOE_RCP 4.5; a projection of the 2046-2065 climate for the moderate mitigation scenario RCP 4.5. For inquiries about this dataset, if Amber M. Holdsworth is unavailable, please contact James R. Christian (Principal Investigator) at: Email: james.christian@dfo-mpo.gc.ca Phone: 1 (250) 686-6081 Fisheries and Oceans Canada Institute of Ocean Sciences 9860 West Saanich Road P.O. Box 6000 Sidney, BC V8L 4B2 Canada

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    The Fieldnotes dataset represents the anticipated locations of DFO Science field operations for 2022-2023 in the North Pacific and Arctic oceans, as well as in the coastal and interior waters of British Columbia and the Yukon.

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    This dataset consists of three simulations from the Northeastern Pacific Canadian Ocean Ecosystem Model (NEP36-CanOE) which is a configuration of the Nucleus for European Modelling of the Ocean (NEMO) V3.6. The historical simulation is an estimate of the 1986-2005 mean climate. The future simulations project the 2046-2065 mean climate for representative concentration pathways (RCP) 4.5 (moderate mitigation scenario) and 8.5 (no mitigation scenario). Each simulation is forced by a climatology of atmospheric forcing fields calculated over these 20 year periods and the winds are augmented with high frequency variability, which introduces a small amount of interannual variability. Model outputs are averaged over 3 successive years of simulation (the last 3, following an equilibration period); standard deviation among the 3 years is available upon request. For each simulation, the dataset includes the air-sea carbon dioxide flux, monthly 3D fields for potential temperature, salinity, potential density, total alkalinity, dissolved inorganic carbon, nitrate, oxygen, pH, total chlorophyll, aragonite saturation state, total primary production, and monthly maximum and minimum values for oxygen, pH, and potential temperature. The data includes 50 vertical levels at a 1/36 degree spatial resolution and a mask is provided that indicates regions where these data should be used cautiously or not at all. For a more detailed description please refer to Holdsworth et al. 2021. For inquiries about this dataset, if Amber M. Holdsworth is unavailable, please contact James R. Christian (Principal Investigator) at: Email: james.christian@dfo-mpo.gc.ca Phone: 1 (250) 686-6081 Fisheries and Oceans Canada Institute of Ocean Sciences 9860 West Saanich Road P.O. Box 6000 Sidney, BC V8L 4B2 Canada

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    A relative exposure index (REI), unweighted fetch, effective fetch, and other fetch-based indices (i.e., sum, minimum) were calculated for the Newfoundland and Labrador (NL) Shelves bioregion. Due to the extensive coastline of the study region, this analysis was conducted for a 5km buffered region along the coast at a spatial resolution of 250m. Detailed methods on the selection of input points for the NL bioregion are included below. Methods Preprocessing and input point selection: Land boundary files were obtained for Eastern Canada and the Canadian Arctic (NrCan 2017) at a scale of 1:50,000 as well as for Saint Pierre and Miquelon (Hijmans 2015), and the New England states (GADM 2012) however the scale at which these layers were produced is unknown. Land boundary files were merged into a single land polygon layer and watercourses reaching for in-land and/or above sea level were clipped from this polygon layer (Greyson 2021). A 5km buffer was generated around the NL provincial boundary. This buffer was then clipped by all land polygons to remove areas overlapping land polygons within the study area. All buffer segments intersecting the NAFO divisions within the NL bioregion were selected and the Union tool in ArcGIS Pro (v. 2.7.2) was used to fill-in gaps within the buffered area, creating a more continuous polygon. The buffered layer was then dissolved, and the NL provincial boundary polygon was erased from the buffered layer to create the study area polygon. A 250m fishnet was created and clipped to the study area (5km buffer layer) and the feature to point tool was used (with the “inside parameter checked”) to convert this grid into a point layer (approx. 1,000,000 points). The spatial resolution for all subsequent analyses was matched to the fishnet grid at 250m. References GADM database of Global Administrative Areas (2012). Global Administrative Areas, version 2.0. (accessed 2 December 2020). www.gadm.org Greyson, P (2021) Land boundary file for Eastern Canada, the Canadian Arctic, the New England States and Saint Pierre and Miquelon. [shapefile]. Unpublished data. Hijmans, R. and University of California, Berkeley, Museum of Vertebrate Zoology. (2015). First-level Administrative Divisions, Saint Pierre and Miquelon, 2015. UC Berkeley, Museum of Vertebrate Zoology. Available at: http://purl.stanford.edu/bz573nv9230 Natural Resources Canada (2017) Administrative Boundaries in Canada - CanVec Series - Administrative Features - Open Government Portal. (accessed 2 December 2020). https://open.canada.ca/data/en/dataset/306e5004-534b-4110-9feb-58e3a5c3fd97.

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    Seasonal mean salinity from the British Columbia continental margin model (BCCM) were averaged over the 1981 to 2010 period to create seasonal mean climatology of the Canadian Pacific Exclusive Economic Zone. Salinities at up to forty-six linearly interpolated vertical levels from surface to 2400 m and at the sea bottom are included. Spring months were defined as April to June, summer months were defined as July to September, fall months were defined as October to December, and winter months were defined as January to March. The data available here contain raster layers of seasonal salinity climatology for the Canadian Pacific Exclusive Economic Zone at 3 km spatial resolution and 47 vertical levels.

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    Polar cod (Boreogadus saida), Atlantic cod (Gadus morhua), and Greenland cod (Gadus macrocephalus) are prominent gadid species within the northwest Atlantic Ocean in terms of their ecological and socio-economic importance but it is unclear how climate-induced changes in ocean temperature may alter their distributions by the end of the century (2100). We used physiologically based species distribution models to predict how ocean warming will influence the availability of suitable habitat for early life-stages in these marine gadids. We applied CMIP5 ocean temperature projections to egg survival and juvenile growth models for Polar cod, Atlantic cod, and Greenland cod to create predicted suitability raster surfaces for these metrics across four climatology periods (1981–2005, 2026–2050, 2051–2075, 2076–2100). The analysis focused on the projected changes in temperature in ocean shelf areas where ocean depth is ≤400 m. We created an integrated habitat suitability index by combining the suitability surfaces for egg survival and growth potential to predict areas and periods where thermal conditions were suitable for both life stages. The resulting surfaces indicate that suitable thermal habitat for the juvenile life stages of all three species will shift poleward, but the magnitude of the shift and the overall area of thermally suitable habitat remaining will differ across species and life stages through time. Modelled layers are provided in NetCDF format by metric (egg survival, growth potential, habitat suitability). Data layers for Polar cod, Atlantic cod, and Greenland cod are included within each NetCDF file as variables across time. Note that in this study we refer to Gadus macrocephalus/ogac as Greenland cod since Gadus ogac is thought to be a junior synonym of Gadus macrocephalus (Carr et al., 1999). For more details on the methods and results for this analysis see Cote et al. (2021). References: Carr, S. M., Kivlichan, D. S., Pepin, P., & Crutcher, D. C. (1999). Molecular systematics of gadid fishes: implications for the biogeographic origins of Pacific species. Canadian Journal of Zoology, 77(1), 19–26. https://doi.org/10.1139/cjz-77-1-19 Cote, D., Konecny, C. A., Seiden, J., Hauser, T., Kristiansen, T., & Laurel, B. J. (2021). Forecasted Shifts in Thermal Habitat for Cod Species in the Northwest Atlantic and Eastern Canadian Arctic. Frontiers in Marine Science, 8(November), 1–15. https://doi.org/10.3389/fmars.2021.764072

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    Seasonal climatologies of the Canadian Pacific Exclusive Economic Zone (CPEEZ) were computed from a numerical simulation of the British Columbia continental margin (BCCM) model for the 1981 to 2010 period, which can be considered as a representation of the climatological state of the region. The BCCM model is an ocean circulation-biogeochemical model implementation of the Regional Ocean Modelling System (ROMS version 3.5). The horizontal resolution is eddy-resolving at 3 km and the vertical discretization is based on a terrain-following coordinate system with 42 depth levels of increasing resolution near the surface. A detailed description of the BCCM model is given in Peña et al. (2019). Spring months were defined as April to June, summer months were defined as July to September, fall months were defined as October to December, and winter months were defined as January to March. The data available here contain raster layers of seasonal climatology of temperature, salinity, current speed, nitrate, oxygen, total alkalinity, dissolved inorganic carbon, pH, aragonite saturation state, phytoplankton, and primary production. The data include 47 vertical levels (surface, bottom, and 45 more selected depths), except for total phytoplankton (surface values only) and primary production (depth-integrated values). Model grids were set to NaN values in regions where the model output is highly uncertain, such as inlets, nearshore areas, and the Strait of Georgia. Model results have been compared against tide gauge data, altimetry, CTD and nutrient profiles, observed geostrophic currents, and seasonal temperature and salinity climatologies over the 1981 to 2010 period. The model is successful in reproducing the main features of the region including salient features of the seasonal cycle and the vertical structure of density and nutrients.

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    Pepin et al. (2014) stated that three nested spatial scales were identified as relevant for the development of ecosystem summaries and management plans: Bioregion, Ecosystem Production Unit (EPU), and Ecoregion. A bioregion is composed by one or more EPUs, while an EPU consists of a combination of ecoregions, which represent elements with different physical and biological characteristics based on the analytical criteria applied. Pepin et al. (2014) reported on the consolidation of data and analyses of ecoregion structure for the continental shelf areas from the Labrador Sea to the mid-Atlantic Bight and provided recommendations on the definition of EPUs in the NAFO Convention Area. The results of two K-means clustering analyses (one geographically constrained and one un-constrained) and expert knowledge (including and considering location of ecoregions, knowledge of the distribution of major marine resources and fish stocks, and geographic proximity for delineation/definition of potential management units) served as guides for evaluation by NAFO’s (North Atlantic Fisheries Organization) working group on ecosystem science and assessments (WG-ESA). The final consensus from the discussions identified eight (8) major EPUs that can serve as practical candidate management units (from the 50 m isobaths, where research vessel data were available, seaward to the 1500 m isobaths) that consist of the Labrador Shelf (NAFO subareas 2GH), the northeast Newfoundland Shelf (subareas 2J3K), the Grand Banks (subareas 3LNO), Flemish Cap (subarea 3M), the Scotian Shelf (subareas 4VnsWX), Georges Bank (parts of subareas 5Ze and 5Zw), the Gulf of Maine (subarea 5Y and part of 5Ze) and the mid-Atlantic Bight (part of subarea 5Zw and subareas 6ABC). Southern Newfoundland (subarea 3Ps) was not included in the original analysis because fall survey data were unavailable. However, it was later added as an EPU after additional analysis of the fish community structure and trends using survey data from the spring, which indicated that this area is heavily influenced by the surrounding EPUs (NAFO 2015). The proposed candidate management units correspond to the EPUs that define major areas within the bioregions which contain a reasonably well defined food web/production system. The working group noted that the consensus solution represents a compromise that aims to define management units based on the boundaries of existing NAFO subareas that are appropriate for estimation of ecosystem and fishery production. References: NAFO. 2015. Report of the 8th Meeting of the NAFO Scientific Council (SC) Working Group on Ecosystem Science and Assessment (WGESA). 17-26 November 2015, Dartmouth, Canada. NAFO SCS Doc. 15/19. Pepin, P., Higdon, J., Koen-Alonso, M., Fogarty, M., and N. Ollerhead. 2014. Application of ecoregion analysis to the identification of Ecosystem Production Units (EPUs) in the NAFO Convention Area. NAFO SCR Doc. 14/069.