Contains 2 datasets: * lower and single tier municipalities * upper tier municipalities and districts.

This dataset shows the boundaries of systems of natural heritage features and areas, lands and waters that support connectivity and have significant ecological value. It includes areas defined in provincial plans such as the: * [Greenbelt Plan](https://www.ontario.ca/document/greenbelt-plan-2017) * [Oak Ridges Moraine Conservation Plan](https://www.ontario.ca/page/oak-ridges-moraine-conservation-plan-2017) * [Niagara Escarpment Plan](https://www.escarpment.org/LandPlanning/NEP) * [Growth Plan for the Greater Golden Horseshoe](https://www.ontario.ca/document/place-grow-growth-plan-greater-golden-horseshoe)  This dataset does not include modifications to systems made by municipal governments as part of their official plans.

Hazardous forest types for wildland fire means forest types assessed as being associated with the risk of high to extreme wildland fire. This data is intended to help inform where further assessment is required and is to be used in conjunction with guidance from the Ministry of Natural Resources and Forestry .

Likelihood of Presence of Finback Whales in the Bay of Fundy and Port Hawkesbury Area Response Plan. The Coastal Oceanography and Ecosystem Research section (DFO Science) reviewed reported opportunistic whale sightings and local knowledge sources to estimate areas where Finback whales are seasonally present and delineate these areas. A version of this dataset was created for the National Environmental Emergency Center (NEEC) following their data model and is available for download in the Resources section. Cite this data as: Lazin, G., Hamer, A.,Corrigan, S., Bower, B., and Harvey, C. Data of: Likelihood of presence of Finback Whale in Area Response Planning pilot areas. Published: June 2018. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B. https://open.canada.ca/data/en/dataset/7e2f85b3-19eb-4ecf-8557-69c8df1bc084

The flood magnitude statistics can be used for applications such as flood plain delineation and design of hydraulic structures. The drought severity statistics can be used for applications such as water abstraction and effluent dilution.

Anthropogenic and natural constraints of the revised land use and development plan of the City of Laval.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

The data layer (.tif) presented are the results of using MaxEnt to produce a single species habitat map for Sea Scallop (Placopecten magellanicus) on German Bank (off South West Nova Scotia, Canada). Presence data derived from videos and still images were compared against environmental variables derived from multibeam bathymetry (Slope, Curvature, Aspect and Bathymetric Position Index (BPI)), and backscatter data (principal components: Q1, Q2, and Q3). Results represent a probability of habitat suitability for Sea Scallop on German Bank. Probability of suitability: The probability that a given habitat is suitable for a species based on presence data and underlying environmental variables (i.e. probability of species occurrence). Reference: Brown, C. J., Sameoto, J. A., & Smith, S. J. (2012). Multiple methods, maps, and management applications: Purpose made seafloor maps in support of ocean management. Journal of Sea Research, 72, 1–13. https://doi.org/10.1016/j.seares.2012.04.009 Cite this data as: Brown, C. J., Sameoto, J. A., & Smith, S. J. Data of: Distribution of Sea Scallop on German Bank. Published: February 2021. Population Ecology Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/2bb98a09-5daf-42c4-94e8-e5de718b821d

The European Green Crab (EGC) is a high-risk global invader that can devastate coastal marine ecosystems by displacing native species, degrading and disturbing native habitats (including eelgrass), and altering food webs. EGC has recently been detected in the Canadian portion of the Salish Sea. As EGC continue to establish in the region, identifying locations on which to focus limited monitoring resources is an ongoing problem given the vast amount of coastal habitat that could be occupied by the species. A variety of methods can be used to identify highly suitable habitats for EGC at a range of spatial scales. However, none have been evaluated in the context of informing EGC management, nor for the Canadian portion of the Salish Sea. Here we evaluate five individual methods developed to assess habitat suitability for EGC (i.e., MaxEnt, stochastic gradient boosted linear and logistic regression models, a rapid site selection tool, and a qualitative site assessment and ranking tool) and five derived models generated by multiplying the outputs of these individual models. Each model relied on slightly different environmental and habitat input variables affecting EGC invasion success. Thus, rather than identifying a single preferred model, we used a multi-model ensemble approach to identify sites that are expected to be most suitable for the species. The ensemble approach likely increases predictive power by including both environmental and habitat characteristics when identifying priority sites for early detection/monitoring for EGC in the Canadian waters of the Salish Sea. Finally, we describe how the models evaluated here, alone or in combination, could be used to identify additional sites either within the Salish Sea or into new areas. This dataset contains predicted habitat suitability from five models for European Green Crab at beaches in the Salish Sea (British Columbia, Pacific Region).

IDMI project boundary

Location of the municipal court of the city of Repentigny.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**