Average grid cell density is a polygon feature class containing the average density value for each grid cell per species/groups and season.

Percent of Average Precipitation represents the accumulation of precipitation for a location, divided by the long term average value. The long term average value is defined as the average amount over the 1981 – 2010 period. Products are produced for the following timeframes: Agricultural Year, Growing Season, Winter Season, as well as rolling products for 30, 60, 90, 180, 270, 365, 730, 1095, 1460 and 1825 days.

Percent of average precipitation represents the total amount of precipitation for a particular location over a specific time period, divided by the long-term average precipitation (1991-2020) for the same period and location, expressed as a percentage.Percent of average precipitation is to provide a clear and standardized way to compare how much precipitation has fallen during a specific time period relative to the long-term average for the same location and time period. Time periods calculated for monthly precipitation percentiles are 1, 2, 3, 6, 9, 12, 18, 24 months. Each ISO week is numbered from 1 to 52 (sometimes 53) within a year. An ISO week starts on Monday and ends on Sunday. Long-term average is 1991-2020.The National Agroclimate Series of Derived Indicators (NASDI) products provide a collection of comprehensive and regularly updated datasets on key agroclimatic variables, including accumulated precipitation, standardized precipitation index, and difference from normal temperature, among others. These datasets incorporate both real-time and historical climate information, offering enhanced insight into conditions and trends across Canada’s diverse agricultural regions.

Difference from Average Precipitation represents the accumulated precipitation value for a location, subtracted by the long-term average value. A negative value indicates that the location has received less than the normal amount of precipitation (mm) for that timeframe. A positive value indicates that the location has received more than the normal amount of precipitation (mm).Time periods calculated for difference from average precipitation are 1, 2, 3, 6, 9, 12, 18, 24 months.Long-term average is 1991-2020. Each ISO week is numbered from 1 to 52 (sometimes 53) within a year. An ISO week starts on Monday and ends on Sunday.The National Agroclimate Series of Derived Indicators (NASDI) products provide a collection of comprehensive and regularly updated datasets on key agroclimatic variables, including accumulated precipitation, standardized precipitation index, and difference from normal temperature, among others. These datasets incorporate both real-time and historical climate information, offering enhanced insight into conditions and trends across Canada’s diverse agricultural regions.

Identification of significant concentrations of sea pens in the Gulf of St. Lawrence biogeographic unit using Kernel density estimation (KDE).This method was applied to create a modelled biomass surface for each taxa and an aerial expansion method was permitted to identify significant concentrations. Only geo-referenced biomass data have been used to identify the “hot spots”. The borders of the areas were refined using knowledge of null catches and species distribution models. Predictive models were produced using a random forest machine-learning technique. For more details, please refer to this report: Kenchington, E., L. Beazley, C. Lirette, F.J. Murillo, J. Guijarro, V. Wareham, K. Gilkinson, M. Koen Alonso, H. Benoît, H. Bourdages, B. Sainte-Marie, M. Treble, and T. Siferd. 2016. Delineation of Coral and Sponge Significant Benthic Areas in Eastern Canada Using Kernel Density Analyses and Species Distribution Models. DFO Can. Sci. Advis. Sec. Res. Doc. 2016/093. vi + 178 p.http://waves-vagues.dfo-mpo.gc.ca/Library/40577806.pdfThe present layer only contains the analysis results for sea pens. Purpose:As part of the Canada's commitment to the identification and protection of sensitive benthic marine ecosystems, maps of the location of significant concentrations of corals and sponges on the east coast of Canada were produced through quantitative analyses of research vessel trawl survey data, supplemented with other data sources where available. The taxa analyzed are sponges (Porifera), large and small gorgonian corals (Alcyonacea), and sea pens (Pennatulacea). However, only the sponges (Porifera) and sea pens (Pennatulacea) have been considered in the analysis concerning the Gulf of St. Lawrence biogeographic unit.

Identification of significant concentrations of sponges in the Gulf of St. Lawrence biogeographic unit using Kernel density estimation (KDE).This method was applied to create a modelled biomass surface for each taxa and an aerial expansion method was permitted to identify significant concentrations. Only geo-referenced biomass data have been used to identify the “hot spots”. The borders of the areas were refined using knowledge of null catches and species distribution models. Predictive models were produced using a random forest machine-learning technique. For more details, please refer to this report: Kenchington, E., L. Beazley, C. Lirette, F.J. Murillo, J. Guijarro, V. Wareham, K. Gilkinson, M. Koen Alonso, H. Benoît, H. Bourdages, B. Sainte-Marie, M. Treble, and T. Siferd. 2016. Delineation of Coral and Sponge Significant Benthic Areas in Eastern Canada Using Kernel Density Analyses and Species Distribution Models. DFO Can. Sci. Advis. Sec. Res. Doc. 2016/093. vi + 178 p.http://waves-vagues.dfo-mpo.gc.ca/Library/40577806.pdfThe present layer only contains the analysis results for sponges. Purpose:As part of the Canada's commitment to the identification and protection of sensitive benthic marine ecosystems, maps of the location of significant concentrations of corals and sponges on the east coast of Canada were produced through quantitative analyses of research vessel trawl survey data, supplemented with other data sources where available. The taxa analyzed are sponges (Porifera), large and small gorgonian corals (Alcyonacea), and sea pens (Pennatulacea). However, only the sponges (Porifera) and sea pens (Pennatulacea) have been considered in the analysis concerning the Gulf of St. Lawrence biogeographic unit.

Predicted bulk density (g/cm3) at defined depth ranges (0–5 cm, 5–15 cm, 15–30 cm, 30–60 cm, 60–100 cm). The mass of dry soil per unit bulk volume.

Percent of normal soil moisture is the modelled amount of plant available water (mm) in the root zone of the soil, divided by the average amount that has historically been available on that day. This value is intended to provide users with a representation of conditions above or below normal as a percentage.Values are computed using the Versatile Soil Moisture Budget (VSMB)

The Automatic Identification System (AIS) is a global, satellite-based and terrestrial-based ship tracking system that uses shipborne equipment to remotely track vessel identification and positional information and is typically required on vessels of 300 gross tonnage or more on an international voyage, of 500 gross tonnage or more not on an international voyage, and passenger ships of all sizes. AIS tracking technologies are primarily used in support of real-time maritime domain awareness and for maritime security and safety of life at sea. This report describes a geographic information system (GIS) analysis of 2019 AIS data to produce yearly and monthly vessel density maps of all vessel classes combined and yearly density maps of each vessel class. The year 2019 was selected to portray shipping densities in a pre-COVID 19 pandemic depiction of the maritime transport sector in the Northwest Atlantic. Vessel density map applications include use in spatial analysis and decision support for marine spatial planning.In 2023 the process was applied to the years 2013 through to 2022 and were made available using the same processes that were applied to the original 2019 datasets.

The Automatic Identification System (AIS) is a global, satellite-based and terrestrial-based ship tracking system that uses shipborne equipment to remotely track vessel identification and positional information and is typically required on vessels of 300 gross tonnage or more on an international voyage, of 500 gross tonnage or more not on an international voyage, and passenger ships of all sizes. AIS tracking technologies are primarily used in support of real-time maritime domain awareness and for maritime security and safety of life at sea. This report describes a geographic information system (GIS) analysis of 2019 AIS data to produce yearly and monthly vessel density maps of all vessel classes combined and yearly density maps of each vessel class. The year 2019 was selected to portray shipping densities in a pre-COVID 19 pandemic depiction of the maritime transport sector in the Northwest Atlantic. Vessel density map applications include use in spatial analysis and decision support for marine spatial planning. In 2023 the process was applied to the years 2013 through to 2022 and were made available using the same processes that were applied to the original 2019 datasets.