Broad Ecosystem Units were mapped using predictive modeling methods from various data sources (ranging from 1:50,000 to 1:250,000 in scale) and are referenced to the CanVec digital spatial framework (1:50,000). Broad Ecosystem Units (BEU) are a level in the Yukon bioclimate ecosystem classification system that represents areas with similar broad vegetation communities, terrain type (soils and topography) within bioclimate zones. Broad Ecosystem Units are described in the accompanying report "Regional Ecosystems of West-Central Yukon, Part 1: Ecosystem descriptions ".The intended application for mapped broad ecosystem units is 1:100,000 or smaller (1:100,000 - 1:250,000 scale) - interpretations derived from the map products should not be applied at more detailed scales, even though the resultant 30m raster map allows users to view results at more detailed resolutions. With new information, boundaries and designations of Broad Ecosystem Units can change. Updates to Broad Ecosystem Units occur only periodically. For the most current information, or if you have questions, please contact the Ecological and Landscape Classification Program (ELC@yukon.ca).Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)

This dataset is used to: * assess biodiversity levels * define seed zones * map ecosystem types * set targets for the identification of natural heritage systems

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.

Species distribution models (SDMs) are tools that combine species observations of occurrence, abundance, or biomass with environmental variables to predict the distribution of a species in unsampled locations. To produce accurate predictions of occurrence, abundance or biomass distribution, a wide range of physical and/or biological variables is desirable. Such data is often collected over limited or irregular spatial scales, and require the application of geospatial techniques to produce continuous environmental surfaces that can be used for modelling at all spatial scales. Here we provide a review of 102 environmental data layers that were compiled for the entire spatial extent of Fisheries and Oceans Canada’s (DFO) Maritimes Region. Variables were obtained from a broad range of physical and biological data sources and spatially interpolated using geostatistical methods. For each variable we document the underlying data distribution, provide relevant diagnostics of the interpolation models and an assessment of model performance, and present the final standard error and interpolation surfaces. These layers have been archived in a common (raster) format at the Bedford Institute of Oceanography to facilitate future use. Based on the diagnostic summaries in this report, a subset of these variables has subsequently been used in species distribution models to predict the distribution of deep-water corals, sponges, and other significant benthic taxa in the Maritimes Region.Cite this data as: Beazley, Lindsay; Guijarro, Javier, Lirette; Camille; Wang, Zeliang; Kenchington, Ellen (2020). Characteristics of Environmental Data Layers for Use in Species Distribution Modelling in the Maritimes Region. Published July 2023. Ocean Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/34a917cb-a0e3-403c-91c7-af3dc20628b1

An ecoprovince is an area with consistent climatic or oceanography, relief and regional landforms. There one oceanic, two marine / terrestrial and seven terrestrial ecoprovinces occurring within British Columbia. Ecoprovinces are meant to be mapped at 1:2,000,000 for use in provincial state of the environment reporting

Effective fisheries and habitat management processes require knowledge of the distribution of areas of high ecological or biological significance. On the Scotian Shelf and Slope, a number of benthic ecologically or biologically significant areas consisting of habitat-forming species such as sponges and deep-water corals have been identified. However, knowledge of their spatial distribution is largely based on targeted surveys that are limited in their spatial extent. We used a species distribution modelling approach called random forest (RF) to predict the probability of occurrence and biomass of sponges, sea pens, and large and small gorgonian corals across the entire spatial extent of Fisheries and Oceans Canada’s (DFO) Maritimes Region. We also modelled the rare sponge Vazella pourtalesi, which forms the largest known aggregation of its kind on the Scotian Shelf. We utilized a number of data sources including DFO multispecies trawl catch data and in situ benthic imagery observations. Most models had excellent predictive capacity with cross-validated Area Under the Receiver Operating Characteristic Curve (AUC) values ranging from 0.760 to 0.977. Areas of suitable habitat were identified for each taxon and were contrasted against their known distribution and when applicable, the location of closure areas designated for their protection. Generalized additive models (GAMs) were developed to predict the biomass distribution of each taxonomic group and serve as a comparison to the RF models. The RF and GAM models provided comparable results, although GAMs provided superior predictions of biomass along the continental slope for some taxonomic groups. In the absence of data observations, the results of this study could be used to identify the potential distribution of sensitive benthic taxa for use in fisheries and habitat management applications. These results could also be used to refine significant concentrations of these taxa as identified through the kernel density analyses.Cite this data as: Beazley, Lindsay; Kenchington, Ellen; Murillo-Perez, Javier; Lirette, Camille; Guijarro-Sabaniel, Javier; McMillan, Andrew; Knudby, Anders (2019). Species Distribution Modelling of Corals and Sponges in the Maritimes Region for Use in the Identification of Significant Benthic Areas. Published July 2023. Ocean Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/356e92f3-5bf3-4810-98b1-3e10cd7742aa

STE_SCANNED_MAP_BOUNDARY_SP includes an index of the mapsheet grid location of Soils, Terrain, Ecosystems and related scanned maps (including Agriculture Capability and Climate Capability maps). These maps are intended for on-screen viewing or printing. The majority of the maps have been geo-referenced. Mapping may not cover the whole map grid area. Some maps are interim or draft and may have been superseded. Some files are of related legends and map project text. Associated scanned map boundary attributes describe the project map (project level metadata) and provide a link for downloading the map, plus links to related reports, geo-referenced maps, and GIS digital data available from other sources. ATTENTION - The IMAGE_URL link is only useable by BC government staff. Public users can download the scanned maps by using the ECOCAT_URL link. There is no charge for the scanned map files. Please note that some maps and more recent mapping may also be available in digital GIS format. See - Ecosystem and Terrain Mapping Data Inventory.

Ecosections are areas with minor physiographic and macroclimatic or oceanographic variations. There are 114 ecosections in British Columbia varying from pure marine units to pure terrestrial units. Ecosections are meant to be mapped at small scales (1:250,000) for resource emphasis and area planning

Leaf area index (LAI) quantified the density of vegetation irrespective of land cover. LAI quantifies the total foliage surface area per groud surface area. LAI has been identified by the Global Climate Observing System as an essential climate variable required for ecosystem,weather and climate modelling and monitoring. This product consists of annual maps of the maximum LAI during a grownig season (June-July-August) at 100m resolution covering Canada's land mass.

Bivalve aquaculture has direct and indirect effects on plankton communities, which are highly sensitive to short-term (seasonal, interannual) and long-term climate changes, although how these dynamics alter aquaculture ecosystem interactions is poorly understood. Here, we investigate seasonal patterns in plankton abundance and community structure spanning several size fractions from 0.2 µm up to 5 mm, in a deep aquaculture embayment in northeast Newfoundland, Canada. Using flow cytometry and FlowCam imaging, we observed a clear seasonal relationship between fraction sizes driven by water column stratification (freshwater input, nutrient availability, light availability, water temperature). Plankton abundance decreased proportionally with increasing size fraction, aligning with size spectra theory. Within the bay, greater mesozooplankton abundance, and a greater relative abundance of copepods, was observed closest to the aquaculture lease. No significant spatial effect was observed for phytoplankton composition. While the months of August to October showed statistically similar plankton composition and size spectra slopes (i.e., food chain efficiency) and could be used for interannual variability comparisons of plankton composition, sampling for longer periods could capture long-term phenological shifts in plankton abundance and composition related to various processes, including climate change. Conclusions provide guidance on optimal sampling to monitor and assess aquaculture pathways of effects.Cite this data as: Sharpe H, Lacoursière-Roussel A, Gallardi D (2024). Ecological insight of seasonal plankton succession to monitor shellfish aquaculture ecosystem interactions. Version 3.2. Fisheries and Oceans Canada. Sampling event dataset. https://doi.org/10.25607/2ujdvh