The Canadian Precipitation Analysis System (CaPA) produces a best estimate of 6 and 24 hour precipitation amounts. This objective estimate integrates data from in situ precipitation gauge measurements, radar QPEs and a trial field generated by a numerical weather prediction system. In order to produce the High Resolution Deterministic Precipitation Analysis (HRDPA) at a resolution of 2.5 km, CaPA is connected to the continental HRDPS for its trial field. CaPA-HRDPA produces four analyses of 6 hour amounts per day, valid at synoptic hours (00, 06, 12 and 18 UTC) and two 24 hour analysis valid at 06 and 12 UTC. A preliminary production is started 1 hour after valid time and a final one is launched 7 hours later. This translates into a production of 12 analyses per day.

The Canadian Precipitation Analysis System (CaPA) produces a best estimate of 6 and 24 hour precipitation amounts. This objective estimate integrates data from in situ precipitation gauge measurements, radar QPEs and a trial field generated by a numerical weather prediction system. In order to produce the High Resolution Deterministic Precipitation Analysis (HRDPA) at a resolution of 2.5 km, CaPA is connected to the continental HRDPS for its trial field. CaPA-HRDPA produces four analyses of 6 hour amounts per day, valid at synoptic hours (00, 06, 12 and 18 UTC) and two 24 hour analyses valid at 06 and 12 UTC. A preliminary production is started 1 hour after valid time and a final one is launched 7 hours later. This translates into a production of 12 analyses per day.

The Moisture Anomaly Index (Palmer-Z) is an estimate of the moisture difference from normal (a 30-year mean). It attempts to express conditions for the current month regardless of what may have occurred before the month in question.

Kernel density estimation (KDE) utilizes spatially explicit data to model the distribution of a variable of interest. It is a simple non-parametric neighbour-based smoothing function that relies on few assumptions about the structure of the observed data. It has been used in ecology to identify hotspots, that is, areas of relatively high biomass/abundance, and in 2010 was used by Fisheries and Oceans Canada to delineate significant concentrations of corals and sponges. The same approach has been used successfully in the Northwest Atlantic Fisheries Organization (NAFO) Regulatory Area. Here, we update the previous analyses with the catch records from up to 5 additional years of trawl survey data from Eastern Canada, including the Gulf of Saint Lawrence. We applied kernel density estimation to create a modelled biomass surface for each of sponges, small and large gorgonian corals, and sea pens, and applied an aerial expansion method to identify significant concentrations of these taxa. We compared our results to those obtained previously and provided maps of significant concentrations as well as point data co-ordinates for catches above the threshold values used to construct the significant area polygons. The borders of the polygons can be refined using knowledge of null catches and species distribution models of species presence/absence and/or biomass.

The data represents the relative cultivation intensity in the agricultural area of Alberta. Cultivation intensity refers to the frequency of cultivation associated with the following management systems: no till, conventional tillage and summerfallow. It is an estimate of the degree to which cultivation contributes to wind and water erosion. The classes shown on the map are ranked between 0 (lowest) and 1 (highest).This map was created in 2002 using ArcGIS.

The data represents the relative amount of manure production in the agricultural area of Alberta. It is an estimate of the degree to which livestock production may contribute to nutrient loading, pathogens and odour. The classes shown on the map are ranked between 0 (lowest) and 1 (highest). This resource was created in 2002 using ArcGIS.

This dataset includes metrics of eelgrass size, cover, and biomass from field sites along the Atlantic coast of Nova Scotia, Canada. Field sites were located across a gradient of environmental conditions, and field sampling was conducted in July to August 2022. Eelgrass percent cover, shoot density, and plants were sampled at 10 haphazardly distributed sampling stations within each eelgrass bed at approximately the same depth. Stations were ~10m apart and at least 2m from any eelgrass-bare interface. At each sampling station eelgrass leaves in a 0.5 x 0.5m quadrat were photographed for later computer image analysis to determine percent cover. The number of shoots were then counted in a 0.25 x 0.25m quadrat, and 3 vegetative shoots were collected. Shoots were measured for leaf length, width, and weight in the laboratory. These data were used to determine allometric and cover-biomass relationships for use in non-destructive estimation of bed biomass. Cite this data as: Wong, M.C., & Thomson, J. A. Data of eelgrass (Zostera marina) plant size (length, width), cover, and biomass from the Atlantic Coast of Nova Scotia. Published: February 2025. Coastal Ecosystems Science Division, Maritimes Region, Fisheries and Oceans Canada, Dartmouth NS.For additional information please see:Thomson, J. A., Vercaemer, B., & Wong, M. C. (2025). Non-destructive biomass estimation for eelgrass (Zostera marina): Allometric and percent cover-biomass relationships vary with environmental conditions. Aquatic Botany, 198, 103853. https://doi.org/10.1016/j.aquabot.2024.103853

PURPOSE:These data have been updated following a Canadian Science Advice Secretariat (CSAS) Regional Science Advisory Process. Associated publications are available in the citation section below or will be posted on the Fisheries and Oceans Canada (DFO) Science Advisory Schedule as they become available.Estimate the abundance of Striped bass spawners in the Northwest Miramichi estuary.DESCRIPTION:Spawner abundance estimates of Striped Bass in the Northwest Miramichi estuary based on Catch per unit effort (CPUE) analysis in the commercial gaspereau fishery.USE LIMITATION:To ensure scientific integrity and appropriate use of the data, we would encourage you to contact the data custodian.

This dataset includes five depth-attenuated relative wave exposure index layers in raster format. Relative Exposure Index (REI) values are calculated based on effective fetch (derived from fetch values) combined with modelled wind data. The output REI layers are attenuated by depth, resulting in greater values in shallow, nearshore areas (Bekkby et al. 2008). The cell values represent an estimate of wave exposure at bottom depth normalized between regions from 0 (protected) to 1 (exposed).The objective of this dataset is to provide an estimate of wave exposure at bottom depth, primarily for use in species distribution modelling. Each single-band raster corresponds to a marine region, which generally coincide with the following layers from the Species Distribution Modelling Boundaries (https://www.gis-hub.ca/dataset/sdm-boundaries) dataset: Nearshore_HG, Nearshore_NCC, Nearshore_QCS, Nearshore_QCS, and Shelf_SalishSea. These layers extend to 50 m depth and up to 5 km from shore.Tabular data (csv files) are also included as part of the data package. These data are the calculated Relative Exposure Index (REI) values with fields for position information. The fetch values from gridded nearshore fetch (https://gis-hub.ca/dataset/gridded-nearshore-fetch) are used as a source dataset and the locations in the REI are the same as the gridded fetch.

The Regional Deterministic Precipitation Analysis (RDPA) produces a best estimate of precipitation amounts that occurred over a period of 6 hours. The estimate integrates data from in situ precipitation gauge measurements, weather radar, satellite imagery and numerical weather prediction models. Geographic coverage is North America (Canada, United States and Mexico). Data is available at a horizontal resolution of 10 km. The 6 hour analysis is produced 4 times a day and is valid at 00, 06, 12 and 18 UTC. A preliminary analysis is available approximately 1 hour after the end of the accumulation period and a final one is generated 7 hours later in order to assimilate more gauge data.