This data layer presents the results of a modeling of net anthropogenic inputs of nitrogen and phosphorus (NANI/NAPI) carried out by Professor Roxane Maranger and Stéphanie Shousha from the University of Montreal as part of a partnership with the Ministry of the Environment, the Fight against Climate Change, Wildlife and Parks (MELCCFP). The modeling was carried out using the Net Anthropogenic Nitrogen/Phosphorus Input method applied for the first time in Quebec by ([Goyette et al., 2016]) (https://can01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fagupubs.onlinelibrary.wiley.com%2Fdoi%2F10.1002%2F2016GB005384&data=05%7C02%7CAntoine.Prince%40environnement.gouv.qc.ca%7Ce9a3e849691c4a3f9bc008de4e23f624%7C4262d4ec5a674957abb6bf78aca6a6f5%7C0%7C0%7C639034113587157844%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C 0% 7C%7C%7C&sdata=a7ktxc6ea9u4thdsbor9ojrkspdjgwno%2Fbaizkkkuaq%3D&reserved=0)) then refined in ([Shousha & Maranger, 2024] (https://can01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fbesjournals.onlinelibrary.wiley.com%2Fdoi%2Ffull%2F10.1111%2F1365-2664.14733&data=05%7C02%7CAntoine.Prince%40environnement.gouv.qc.ca%7Ce9a3e849691c4a3f9bc008de4e23f624%7C4262d4ec5a674957abb6bf78aca6a6f5%7C0%7C0%7C639034113587193473%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=AdT31R8 IHMEEYRZZ1HGMTRTUAEE8XMRMAQBRNAUJDN 4% 3D&reserved=0)). The model is based on the premise that a region imports nitrogen and phosphorus to support its population and agricultural activities.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Data from the analysis of sea surface temperature, sea surface salinity, bottom temperature, and bottom salinity, over the Gulf of Maine and Scotian Shelf, for 23 CMIP6 models. The analysis includes an evaluation of CMIP6 model performance for the CMIP6 historical (1950-2014) experiment. Future projections are summarized for CMIP6 scenarios SSP245 and SSP370 with the calculation of relative annual and seasonal changes between the historical period (1950-2014) and three future periods (2030-2039, 2040-2049, 2030-2049).Wang, Z., DeTracey, B., Maniar, A., Greenan, B., Gilbert, D. and Brickman, D., Future hydrographic state of the Scotian Shelf and Gulf of Maine from 23 CMIP6 models. Can. Tech. Rep. Hydrogr. Ocean. Sci. XXX: vii + XXXp.Cite this data as: Wang, Z., DeTracey, B., Maniar, A., Greenan, B., Gilbert, D. and Brickman, D. Future hydrographic state of the Scotian Shelf and Gulf of Maine from 23 CMIP6 Models. Published July 2022. Ocean Ecosystem Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/6247bb5a-14b3-461d-9ed3-b42553107bbc

This dataset includes the extent of the boreal forest as well as the extent of managed boreal forest worldwide. The extent of boreal forest was produced from Brandt et al. (2013) and a modified version of Goudilin (1987). Managed forest was defined as suggested by IPCC (2003) using data from FAFS (2009), Gauthier et al. (2014), See et al. (2015) and AICC maps. The extent of managed forest mostly includes areas managed for wood production, areas protected from large-scale disturbances as well as formal protected areas.Both boreal forest extent and managed boreal forest extent are available in raster and vector data.Please cite this data product as:Boucher, D., D.G. Schepaschenko, S. Gauthier, P. Bernier, T. Kuuluvainen, A. Z. Shvidenko. 2024. World boreal forest and managed boreal forest extent. DOI: 10.23687/88d70716-2600-4995-8d5f-86f96e383abfThese data were presented in the following article:Gauthier, S., P. Bernier, T. Kuuluvainen, A. Z. Shvidenko, D. G. Schepaschenko. 2015. Boreal forest health and global change. Science 349:819-822. DOI: 10.1126/science.aaa9092References:J. P. Brandt, M. D. Flannigan, D. G. Maynard, I. D. Thompson, W. J. A. Volney, Environ. Rev. 21, 207–226 (2013)I. S. Goudilin, Landscape map of the USSR. Legend to the landscape map of the USSR. Scale 1:2 500 000. Moscow, Ministry of Geology of the USSR (1987) [in Russian].Inter-governmental panel on climate change (IPCC). J. Penman, M. Gytarsky, T. Hiraishi, T. Krug, D. Kruger, et al., Eds., Good practice guidance for land use, land-use change and forestry (IPCC/NGGIP/IGES, Kanawaga, 2003)Federal Agency of Forest Service (FAFS), Forest Fund of the Russian Federation (state by 1 January 2009) (Federal Agency of Forest Service, Moscow, 2009) [in Russian]S. Gauthier et al., Environ. Rev. 22, 256–285 (2014).See et al., Harnessing the power of volunteers, the internet and Google Earth to collect and validate global spatial information using Geo-Wiki. Technological Forecasting and Social Change. (2015). doi:10.1016/j.techfore.2015.03.002 Alaska Interagency Coordination Center (AICC). Fire Information. https://fire.ak.blm.gov/content/maps/aicc/Large%20Maps/Alaska_Fire_Management_Options.pdf (the version of 2014 was used)

“Summer” missions occur in June, July and August and these focus on the Scotian Shelf and Bay of Fundy (i.e. 4VWX 5Yb, expanding recently to include the Laurentian Channel and Georges Bank (5Zc). Collected data includes total catch in numbers and weights by species. Length frequency data is available for most species, as are the age, sex, maturity and weight information for a subset of the individual animals. Other data such as ageing material, genetic material, and stomach contents are often also collected, but are stored elsewhere.“Summer” cruises occur in May, June, July and August and these focus on the Scotian Shelf and Bay of Fundy (i.e. 4VWX).Cite this data as: Clark, D., Emberley, J. Data of MARITIMES SUMMER RESEARCH VESSEL SURVEYS. Published January 2021. Population Ecology Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/1366e1f1-e2c8-4905-89ae-e10f1be0a164

This catalog contains annual 30 m spatial resolution snow dynamics metrics for each snow-year from 2018-2019 to 2023-2024 for all of Canada. We gather all Landsat and Sentinel-2 images collected over Canada and identify the status of each pixel observation on the image collection date: snow (and ice), non-snow (i.e., land, water), unclear (i.e., clouds, shadows). We built an algorithm to calculate snow cover metrics for each pixel during each winter: start date of the first (and biggest) snow period [startF, startB], end date of the last (and biggest) snow period [endL, endB], number of days with snow cover in total (or in the biggest snow period) [lengthT, lengthB], number of snow periods (i.e., separated times with multiple confirmed snow observations) [periods], and a status classification (e.g., continuous snow, snow free) [status]. We do not obtain a clear observation every day because of satellite orbit frequencies and clouds. This means that timing-based metrics are identified by the middle date between two clear observations, with uncertainty quantified as half the length of the gap (i.e., ± days) [startF_u, startB_u, endL_u, endB_u, lengthT_u, lengthB_u].

To support improved groundwater geoscience knowledge for southern Ontario, a regional 3-D model of the surficial geology of southern Ontario has been developed as a part of a collaboration between the Ontario Geological Survey and the Geological Survey of Canada. Covering approximately 66,870 km2 in area, the model is a synthesis of existing geological models, surficial geology mapping, and subsurface data. The model is a simplified 9-layer reclassification of numerous mapped local surficial sediment formations in places over 200 m thick with a total volume of approximately 2,455 km3. The model integrates 1:50,000 scale surficial geology mapping with 90 m bathymetrically corrected topographic digital elevation model (DEM) and 8 existing local 3-D models. Archival subsurface data include 10,237 geotechnical and stratigraphic boreholes, 3,312 picks from geophysical surveys, 15,902 field mapping sites and sections, 537 monitoring and water supply wells and 282,995 water well records. Roughly corresponding to regional aquifer and aquitard layers, primary model layers are (from oldest to youngest): Bedrock, Basal Aquifer, Lower Sediment, Regional Till, Post Regional Till Channel Fill, Glaciofluvial Sediment, Post Regional Till Mud, Glaciolacustrine Sand and Recent Sediment / Organics. Modelling was completed using an implicit modelling application (LeapFrog®) complemented by an expert knowledge approach to data classification and rules-based Expert System procedure for data interpretation and validation. An iterative cycle of automated data coding, intermediate model construction and manual data corrections, expert evaluations, and revisions lead to the final 3-D model. A semi-quantitative confidence assessment has been made for each model layer surface based on data quality, distribution and density. This surficial geology model completes the development of a series of regional 3-D geological and hydrogeological models for southern Ontario.

DFO Maritimes Region has conducted a cumulative human impact mapping analysis for the Scotian Shelf-Bay of Fundy management area to support ongoing Marine Spatial Planning initiatives (Murphy et al. 2024). Cumulative human impact mapping (CIM) combines spatial information on human activities and habitats with a matrix of vulnerability weights, into an intuitive relative ‘cumulative impact score’ that shows where cumulative human impacts are greatest and least. To map cumulative impacts in DFO’s Maritimes Region, a recently developed ecosystem vulnerability assessment for Atlantic Canadian waters (Murray et al. 2022) was combined with spatial information on 21 different habitat types and 45 human activities across five different sectors (climate change, land-based, marine-based, coastal, commercial fishing) following the methodology from Halpern et al. (2008). An uncertainty analysis of the cumulative impact map was conducted to assess the robustness of results and identify hot and cold spots of cumulative impacts. This dataset provides: 1) cumulative impact maps for the DFO Maritimes Region at 1 km2 resolution: a total cumulative impact map (i.e. including all 45 human activities), as well as cumulative impact maps for each of the five sectors, 2) a layer that identifies which grid cells are considered hot and cold spots of cumulative human impacts, and 3) the habitat layers included in the CIM.For further information concerning specifics of the maps and methods see Murphy et al. (2024) or contact the data provider. References:Halpern, B.S., Walbridge, S., Selkoe, K.A., Kappel, C.V., Micheli, F., D'Agrosa, C., Bruno, J.F., Casey, K.S., Ebert, C., Fox, H.E., Fujita, R., Heinemann, D., Lenihan, H.S., Madin, E.M.P., Perry, M.T., Selig, E.R., Spalding, M., Steneck, R., and Watson, R. 2008. A Global Map of Human Impact on Marine Ecosystems. Science. 319(5865): 948-952. doi:10.1126/science.1149345.Murray, C.C., Kelly, N.E., Nelson, J.C., Murphy, G.E.P., and Agbayani, S. 2022. Cumulative impact mapping and vulnerability of Canadian marine ecosystems to anthropogenic activities and stressors. DFO Can. Sci. Advis. Sec. Res. Doc. 2022/XXX. vi. + 52 p.Murphy, G.E.P., Stock, A., and Kelly, N.E. 2024 (in press). From land to deep sea: A continuum of cumulative human impacts on marine habitats in Atlantic Canada. Ecosphere.Cite this data as: Murphy, Grace; Kelly, Noreen (2023) Cumulative human impact maps for the Bay of Fundy and Scotian Shelf. Published September 2023. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/37b59b8b-1c1c-4869-802f-c09571cc984b

This dataset contains the data reported in Wesley R Ogloff, Randi A Anderson, David J Yurkowski, Cassandra D Debets, W Gary Anderson, Steven H Ferguson, Spatiotemporal variation of ringed seal blubber cortisol levels in the Canadian Arctic, Journal of Mammalogy, 2022;, gyac047, https://doi.org/10.1093/jmammal/gyac047Cite this data as:Wesley R Ogloff, Randi A Anderson, David J Yurkowski, Cassandra D Debets, W Gary Anderson, Steven H Ferguson. 2022 Spatiotemporal variation of ringed seal blubber cortisol levels in the Canadian Arctic. Arctic and Aquatic Research Division, Fisheries and Oceans Canada, Winnipeg, MB. https://open.canada.ca/data/en/dataset/e1c6b350-0159-11ed-8212-1860247f53e3

Spatial distribution of the Thorny Skate presence expressed by catch weight based on the annual Department of Fisheries and Oceans (DFO) groundfish research surveys realised between 2004 and 2010.Catch data (kg/nautical mile) were aggregated by 100 km² cells. They are derived from processed data used for the production of: Chouinard, P-M., J-D. Dutil, S. Proulx, D. Borcard and J. Crocker. 2014. A spatial approach to matching marine fish diversity and abundance with habitat features. Hydrobiologia. Volume 734, Issue 1: 39-55.Associated publication: Dutil, J.-D., Proulx, S., Chouinard, P.-M., and Borcard, D. 2011. A hierarchical classification of the seabed based on physiographic and oceanographic features in the St. Lawrence. Can. Tech. Rep. Fish. Aquat. Sci. 2916: vii + 72 pages.PurposeSince 1990, the Department of Fisheries and Oceans has been conducting an annual multidisciplinary survey in the Estuary and northern Gulf of St. Lawrence using a standardized protocol. In the southern Gulf of St. Lawrence, these bottom trawl surveys has been carrying out each September since 1971. These missions are an important source of information about the status of the marine ressources.The objectives of the surveys are multiple: to estimate the abundance and biomass of groundfish and invertebrates, to identify the spatial distribution and biological characteristics of these species, to monitor the biodiversity of the Estuary and Gulf and finally, to describe the environmental conditions observed in the area at the moment of the sampling.The southern Gulf surveys are realized using the following standardized protocol:Hurlbut,T. and D.Clay (eds) 1990. Protocols for Research Vessel Cruises within the Gulf Region (Demersal Fish) (1970-1987). Can. MS Rep. Fish. Aquat. Sci. No. 2082: 143p.The sampling protocols used for the Estuary and northern Gulf surveys are described in details in the following publications:Bourdages, H., Archambault, D., Bernier, B., Fréchet, A., Gauthier, J., Grégoire, F., Lambert, J., et Savard, L. 2010. Résultats préliminaires du relevé multidisciplinaire de poissons de fond et de crevette d’août 2009 dans le nord du golfe du Saint-Laurent. Rapp. stat. can. sci. halieut. aquat. 1226 : xii+ 72 p. Bourdages, H., Archambault, D., Morin, B., Fréchet, A., Savard, L., Grégoire, F., et Bérubé, M. 2003. Résultats préliminaires du relevé multidisciplinaire de poissons de fond et de crevette d’août 2003 dans le nord du golfe du Saint-Laurent. Secr. can. consult. sci. du MPO. Doc. rech. 2003/078. vi + 68 p.Annual reports are available at the Canadian Science Advisory Secretariat (CSAS), (http://www.dfo-mpo.gc.ca/csas-sccs/index-eng.htm).

Spatial distribution of the relative occurrence of Spotted Wolffish in the annual DFO groundfish research surveys conducted by the Québec (1978-2008) and Gulf (1971-2008) regions. Catch and effort data were aggregated by 100 km² cells. The probability of catching an Spotted Wolffish in a set and within a cell (relative occurrence) was calculated as the ratio of the number of sets in which a species was recorded and the total number of sets made. This method allows the mapping of catch and effort for numerous time series based on data from different programs in both the whole study area (research surveys and Sentinel Fisheries using bottom trawls and a random stratified design) or in specific areas within the Gulf.Source: Dutil, J.-D., S. Proulx, S. Hurtubise, and J. Gauthier 2011. Recent findings on the life history and catches of wolffish (Anarhichas sp.) in research surveys and in the Sentinel Fisheries and Observer Program for the Estuary and Gulf of St-Lawrence. DFO Can. Sci. Advis. Sec. Res. Doc. 2010/126: x + 71 pages.Associated publication:Dutil, J.-D., Proulx, S., Chouinard, P.-M., and Borcard, D. 2011. A hierarchical classification of the seabed based on physiographic and oceanographic features in the St. Lawrence. Can. Tech. Rep. Fish. Aquat. Sci. 2916: vii + 72 pages. http:/ / www.dfo-mpo.gc.ca/ Library/ 342703.pdf.