The purpose of the cartographic data resulting from analyses of the ecological connectivity of natural environments in the St. Lawrence lowlands is to equip users by making it possible to integrate the concepts of ecological connectivity and the quality of the habitat of natural terrestrial environments into conservation issues. It is a knowledge tool for recognizing natural environments of importance for ecological connectivity in the St. Lawrence Lowlands region. This data is the result of research conducted by McGill University and its partners (Apex Resource Management Solutions, Quebec Center for Biodiversity Science and Habitat) on behalf of the Ministry of the Environment, the Fight against Climate Change, and its partners (Apex Resource Management Solutions, Wildlife and Parks) (MELCCFP).**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Parks Canada’s National Program for Ecological Corridors was initiated to strengthen the network of protected areas across Canada through the creation of ecological corridors. To achieve this goal, Parks Canada sought out to develop tools for a common approach on the scientific and governance aspects of corridor creation and management. The National Priority Areas for Ecological Corridors (NPAECs) were developed using a scientific framework for national-scale prioritization of where ecological corridors are most urgently needed. Improving or maintaining ecological connectivity in these areas will greatly benefit biodiversity conservation and climate change adaptation. The NPAECs were identified based on a methodology that is multivariate, data driven, national in scale, and spatially explicit at a coarse resolution. The Criteria for Ecological Corridors in Canada provide a common approach to ensure ecological corridors are managed and stewarded to maintain or restore effective ecological connectivity, while upholding Indigenous stewardship values. They are derived from the internationally recognized International Union for Conservation of Nature’s Guidelines on Connectivity and adapted to the Canadian context. The NPAECs geographic data layer, the list of datasets used to identify them, the Criteria and their accompanying guidance can be found below. More details and context about both program elements are available on the Program’s webpage (https://parks.canada.ca/nature/science/conservation/corridors-ecologiques-ecological-corridors).

Elk Connectivity Corridors within the Merritt Timber Supply Area

Amalgamations of Wildlife Management Units which share similar ecological characteristics and hunter harvest patterns, and thus provide a suitable geographical framework for implementing population management strategies

Zebra Mussel (Dreissena polymorpha) and Quagga Mussel (Dreissena rostriformis bugensis) have a long history of invasion in European and North American freshwater ecosystems, with significant ecological and economic impacts. An ecological risk assessment for these two invasive species for freshwater ecosystems in Canada was completed in April 2022 with the aim to provide science-based guidance to inform management decisions and actions. These include early detection, response planning, and/or regulatory and policy measures aimed at mitigating the potential spread and risk posed by Zebra and Quagga Mussels to Canadian freshwater ecosystems (DFO 2023). The Potential for Introduction (propagule pressure and connectivity), the Potential for Establishment (habitat suitability, including a Calcium-based and Maximum Entropy (MaxEnt)-based model), the Potential for Invasion, and the Ecological Impacts were used to derive Ecological Risk for Zebra and Quagga Mussels in Canada. This assessment did not evaluate the risk to individual waterbodies but rather was conducted at a 9,260 m x 9,260 m grid cell resolution. These high resolution maps are provided here. Maps of Ecological Risk at the sub-drainage level are also provided. Fisheries and Oceans Canada is not responsible for any omissions or errors that may be contained in this dataset and shall not be liable for any losses, financial or otherwise, due to the use of these data. Please credit Wilcox et al. 2024 as the source of the data in any maps, reports, or articles that are printed or published on paper or the Internet.

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.

The Nova Scotia Hydrographic Network is an enhanced version of the Nova Scotia Topographic Database's Water Features theme. This dataset includes network spines for connectivity of water flow and various attribution for flow direction, priority of water flow and toponymic objects where applicable.

The RVI/CVI database is derived from the CanEcumene 3.0 GDB (Eddy, et. al. 2023) using a selection of socio-economic variables identified in Eddy and Dort (2011) that aim to capture the overall state of socio-economic conditions of communities as ‘human habitats’. This dataset was developed primarily for application in mapping socio-economic conditions of communities and regions for environmental and natural resource management, climate change adaptation, Impact Assessments (IAs) and Regional Assessments (RAs), and Cumulative Effects Assessment (CEA).The RVI/CVI is comprised of five sub-indicators: 1) population change, 2) age structure, 3) education levels, 4) employment levels, and 5) real estate values. Index values are based on percentile ranks of each sub-indicator, and averaged for each community, and for three ranked groups: 1) all of Canada, 2) by province, and 3) by population size. The data covers the Census periods of 2001, 2006, 2011 (NHS), 2016, and 2021.The index is mapped in two ways: 1) as ‘points’ for individual communities (CVI), and 2) as ‘rasters’ for spatial interpolation of point data (RVI). These formats provide an alternative spatial framework to conventional StatsCan CSD framework. (For more information on this approach see Eddy, et. al. 2020).============================================================================================Eddy, B.G., Muggridge, M., LeBlanc, R., Osmond, J., Kean, C., and Boyd, E. 2023. The CanEcumene 3.0 GIS Database. Federal Geospatial Platform (FGP), Natural Resources Canada. https://gcgeo.gc.ca/viz/index-en.html?keys=draft-3f599fcb-8d77-4dbb-8b1e-d3f27f932a4bEddy B.G., Muggridge M, LeBlanc R, Osmond J, Kean C, Boyd E. 2020. An Ecological Approach for Mapping Socio-Economic Data in Support of Ecosystems Analysis: Examples in Mapping Canada’s Forest Ecumene. One Ecosystem 5: e55881. https://doi.org/10.3897/oneeco.5.e55881Eddy, B.G.; Dort, A. 2011. Integrating Socio-Economic Data for Integrated Land Management (ILM): Examples from the Humber River Basin, western Newfoundland. Geomatica, Vol. 65, No. 3, p. 283-291. doi:10.5623/cig2011-044.

Effective conservation planning relies on understanding population connectivity which can be informed by genomic data. This is particularly important for sessile species like the horse mussel (Modiolus modiolus), a key habitat-forming species and conservation priority in Atlantic Canada), yet little genomic information is available to describe horse mussel connectivity patterns. We used more than 8000 restriction-site associated DNA sequencing-derived single nucleotide polymorphisms and a panel of 8 microsatellites to examine genomic connectivity among horse mussel populations in the Bay of Fundy, along the Scotian Shelf, and in the broader northwestern Atlantic extending to Newfoundland. Despite phenotypic differences between sampling locations, we found an overall lack of genetic diversity and population structure in horse mussels in the Northwest Atlantic Ocean. All sampled locations had low heterozygosity, very low FST, elevated inbreeding coefficients, and deviated from Hardy-Weinberg Equilibrium, highlighting generally low genetic diversity across all metrics. Principal components analysis, Admixture analysis, pairwise FST calculations, and analysis of outlier loci (potentially under selection) all showed no independent genomic clusters within the data, and an analysis of molecular variance showed that less than 1% of the variation within the SNP dataset was found between sampling locations. Our results suggest that connectivity is high among horse mussel populations in the Northwest Atlantic, and coupled with large effective population sizes, this has resulted in minimal genomic divergence across the region. These results can inform conservation design considerations in the Bay of Fundy and support further integration into the broader regional conservation network.Cite this data as: Van Wyngaarden, Mallory et al. (2024). Widespread genetic similarity between Northwest Atlantic populations of the horse mussel, Modiolus modiolus. Published: May 2025. Coastal Ecosystem Science Division, Maritimes Region, Fisheries and Oceans Canada, Dartmouth, NS.

This dataset shows length weighted connectivity values summarized by hydrologic unit code (HUC) for a provincial stream connectivity indicator that assesses connectivity for aquatic organisms in stream networks. The stream connectivity indicator supports evaluation and reporting on indicator condition over time and provides information to support management of watercourse crossings. The stream connectivity indicator produces an estimate of the average connectivity in a stream network, considering the movement requirements of local species and the locations of watercourse crossings. The indicator is calculated and summarized using hydrologic unit codes (HUCs). Indicator values are calculated at a HUC 6 scale, and summarized for HUC 8 watersheds at four timesteps: 2010, 2014, 2016 and 2018.