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

40 Class - Canadian Ecological Domain Classification from Satellite Data. Satellite derived data including 1) topography, 2) landscape productivity based on photosynthetic activity, and 3) land cover were used as inputs to create an environmental regionalization of the over 10 million km2 of Canada’s terrestrial land base. The outcomes of this clustering consists of three main outputs. An initial clustering of 100 classes was generated using a two-stage multivariate classification process. Next, an agglomerative hierarchy using a log-likelihood distance measure was applied to create a 40 and then a 14 class regionalization, aimed to meaningfully group ecologically similar components of Canada's terrestrial landscape. For more information (including a graphical illustration of the cluster hierarchy) and to cite this data please use: Coops, N.C., Wulder, M.A., Iwanicka, D. 2009. An environmental domain classification of Canada using earth observation data for biodiversity assessment. Ecological Informatics, Vol. 4, No. 1, Pp. 8-22, DOI: https://doi.org/10.1016/j.ecoinf.2008.09.005. ( Coops et al. 2009).

The data represents an assessment of biodiversity risk for the agricultural area of Alberta in 2002. Biodiversity risk refers to the loss of biological diversity, or the variety of plant and animal life in agricultural landscapes. This map, created in ArcGIS, tries to show where biodiversity could be threatened, such as in areas with significant habitat that coincide with areas of greater agricultural economic activity. Biodiversity is believed to affect the overall health of the environment.

100 Class - Canadian Ecological Domain Classification from Satellite Data. Satellite derived data including 1) topography, 2) landscape productivity based on photosynthetic activity, and 3) land cover were used as inputs to create an environmental regionalization of the over 10 million km2 of Canada’s terrestrial land base. The outcomes of this clustering consists of three main outputs. An initial clustering of 100 classes was generated using a two-stage multivariate classification process. Next, an agglomerative hierarchy using a log-likelihood distance measure was applied to create a 40 and then a 14 class regionalization, aimed to meaningfully group ecologically similar components of Canada's terrestrial landscape. For more information (including a graphical illustration of the cluster hierarchy) and to cite this data please use: Coops, N.C., Wulder, M.A., Iwanicka, D. 2009. An environmental domain classification of Canada using earth observation data for biodiversity assessment. Ecological Informatics, Vol. 4, No. 1, Pp. 8-22, DOI: https://doi.org/10.1016/j.ecoinf.2008.09.005. ( Coops et al. 2009).

DescriptionConservation of marine biodiversity requires understanding the joint influence of ongoing environmental change and fishing pressure. Addressing this challenge requires robust biodiversity monitoring and analyses that jointly account for potential drivers of change. Here, we ask how demersal fish biodiversity in Canadian Pacific waters has changed since 2003 and assess the degree to which these changes can be explained by environmental change and commercial fishing. Using a spatiotemporal multispecies model based on fisheries independent data, we find that species density (number of species per area) and community biomass have increased during this period. Environmental changes during this period were associated with temporal fluctuations in the biomass of species and the community as a whole. However, environmental changes were less associated with changes in species’ occurrence. Thus, the estimated increases in species density are not likely to be due to environmental change. Instead, our results are consistent with an ongoing recovery of the demersal fish community from a reduction in commercial fishing intensity from historical levels. These findings provide key insight into the drivers of biodiversity change that can inform ecosystem-based management.The layers provided represent three community metrics: 1) species density (i.e., species richness), 2) Hill-Shannon diversity, and 3) community biomass. All layers are provided at a 3 km resolution across the study domain for the period of 2003 to 2019. For each metric, we provide layers for three summary statistics: 1) the mean value in each grid cell over the temporal range, 2) the probability that the grid cell is a hotspot for that metric, and 3) the temporal coefficient of variation (i.e., standard deviation/mean) across all years.Methods:The analysis that produced these layers is presented in Thompson et al. (2022). The analysis uses data from the Groundfish Synoptic Bottom Trawl Research surveys in Queen Charlotte Sound (QCS), Hecate Strait (HS), West Coast Vancouver Island (WCVI), and West Coast Haida Gwaii (WCHG) from 2003 to 2019. Cartilaginous and bony fish species caught in DFO groundfish surveys that were present in at least 15% of all trawls over the depth range in which they were caught were included. This depth range was defined as that which included 95% of all trawls in which that species was present. The final dataset used in our analysis consisted of 57 species (Table S1 in Thompson et al. 2022).The spatiotemporal dynamics of the demersal fish community were modeled using the Hierarchical Modeling of Species Communities (HMSC) framework and package (Tikhonov et al. 2021) in R. This framework uses Bayesian inference to fit a multivariate hierarchical generalized mixed model. We modeled community dynamics using a hurdle model, which consists of two sub models: a presence-absence model and a biomass model that is conditional on presence. Our list of environmental covariates included bottom depth, bathymetric position index (BPI), mean summer tidal speed, substrate muddiness, substrate rockiness, whether the trawl was inside or outside of the ecosystem-based trawling footprint, and survey region (QCS & HS vs. WCVI & WCHG)), mean summer near-bottom temperature deviation, mean summer near-bottom dissolved oxygen deviation, mean summer cross-shore and along-shore current velocities near the seafloor, mean summer depth-integrated primary production, and local-scale commercial fishing effort.Layers are provided for three community metrics. All metrics should be interpreted as the value that would be expected in the catch from an average tow in the Groundfish Synoptic Bottom Trawl Research Surveys taken in a given 3 km grid cell. Species density (sometimes called species richness) should be interpreted as the number of the 57 species that would be caught in a trawl. Hill-Shannon diversity is a measure of diversity that gives greater weight to communities where biomass is spread equally across species. Community biomass is the total biomass across all 57 species that would be expected to be caught per square km in an average tow. Data Sources:Research data was provided by Pacific Science's Groundfish Data Unit for research surveys from the GFBio database between 2003 and 2019 that occurred in four regions: Queen Charlotte Sound, Hecate Strait, West Coast Haida Gwaii, and West Coast Vancouver Island. Our analysis excludes species that are rarely caught in the research trawls and so our estimates would not include the occurrence or biomass of these rare species.Commercial fishing data was accessed through a DFO R script detailed here: https://github.com/pbsassess/gfdata. Local scale commercial fishing effort was calculated from this data. The substrate layers were obtained from a substrate model (Gregr et al. 2021). The oceanographic layers (bottom temperature, dissolved oxygen, tidal and circulation speeds, primary production) were obtained from a hindcast simulation of the British Columbia continental margin (BCCM) model (Peña et al. 2019).Uncertainties:Species that are not well sampled by the trawl surveys may not be accurately estimated by our model. The model did not include spatiotemporal random effects, which likely underestimates spatiotemporal variability in the region. It is also important to underline covariate uncertainty and model uncertainty. The hotspot estimates provide one measure of model uncertainty/certainty.

The Canadian Wildlife Service - Ontario Region Biodiversity Atlas represents the Canadian Wildlife Service biodiversity portfolio across the Ontario portions of the Boreal Hardwood Shield (Bird Conservation Region 12) and Mixedwood Plains (Bird Conservation Region 13) ecozones. These data are the derived product from an extensive landscape assessment that assessed the Canadian Wildlife Service biodiversity portfolio (Species at Risk, migratory birds, habitat) at various resolutions. Biodiversity is mapped by forest, grassland (open country) and wetland quality and quantity, and then progressively combined to identify local High Value Biodiversity Areas. At the finest resolution, scores were applied to each unit of analysis (5 hectare hexagon in Bird Conservation Region 12; 2 hectare hexagon in Bird Conservation Region 13), based on over 30 criteria for landscape habitat condition, Species at Risk and migratory birds. Habitat condition scores were derived from guidance in Environment and Climate Change Canada's existing How Much Habitat is Enough? and in Bird Conservation Region 12, where the landscape is less fragmented, habitat was also based on draft guidance in How Much Disturbance is too Much? Individual scores were summed and various combinations (e.g. top 25% of forest scores + top 25% of Species at Risk (SAR) scores) were calculated to identify areas with multiple conservation value. For each habitat type (forest, grassland and wetland), study units with more than one conservation value were aggregated into High Value Habitat which were subsequently aggregated into High Value Biodiversity Areas (HVBA). The results are areas on the landscape that have high value from a Canadian Wildlife Service specific lens; that is, they are high quality habitats that are important for Species at Risk and/or migratory birds. High value habitats are those forests, grasslands and wetlands with potential high conservation value (PHCV). They contain at least 1 of a possible 3 potential high conservation values: top 25% of overall habitat scores, top 25% of Species at Risk (SAR) scores, and/or top 25% of relevant migratory bird scores. High value forest, grassland and wetland were derived by combining landscape, Species at Risk (SAR) and migratory bird elements (see Table 1). Overall habitat scores were assigned to each study unit based on the combined scores for each forest, grassland and wetland. These overall habitat scores were divided into quartiles, and the top 25% of each total score (overall forest, overall grassland and overall wetland) are considered to be potential high conservation value. Similarly, SAR scores were assigned for each study unit, totalled and broken into quartiles. The top 25% of SAR scores that intersect each of forest, grassland and wetland are considered to be the highest quality habitats important to SAR and have potential high conservation value. Finally, relevant migratory bird scores were totalled within each study unit, divided into quartiles and the top 25% of migratory bird scores that intersect each of forest, grassland and wetland are considered to be the highest quality habitats important to migratory birds and have potential high conservation value. Study units with a PHCV greater than 0 (i.e., contains at least 1 of the possible 3 potential high conservation values) were aggregated together by 750 m to create High Value Habitats. High value biodiversity areas (HVBAs) are those study units that contain multiple high value habitats (high value forest and/or high value grassland and/or high value wetland). High value biodiversity areas (HVBA) were derived by aggregating high value forest, grassland and wetland. Study units with a potential high conservation value greater than 1 were aggregated together by 750 m. Biodiversity sites are areas greater than 20 ha, and secondary biodiversity sites are areas less than 20 ha in area.

The Marine Biodiversity Observation Network Pole to Pole (MBON P2P) effort seeks to develop a framework for the collection, use and sharing of marine biodiversity data in a coordinated, standardized manner leveraging on existing infrastructure managed by the Global Ocean Observing System (GOOS; IOC-UNESCO), the GEO Biodiversity Observation Network (GEO BON), and the Ocean Biogeographic Information System (OBIS). The MBON Pole to Pole aims to become a key resource for decision-making and management of living resource across countries in the Americas for reporting requirements under the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), Aichi Targets of the Convention of Biological Diversity (CBD), and the UN 2030 Agenda for Sustainable Development Goals (SDGs).This collection corresponds to the species registered on sandy beaches of the Musquash Harbour, Mispec Bay, and New River Beach, New Brunswick, Canada, using the MBON P2P sampling protocol for sandy beaches, with funding from the Government of Canada's Coastal Environmental Baseline Program.Citation: Reinhart B, Jonah L (2025). MBON POLE TO POLE: SANDY BEACH BIODIVERSITY OF SOUTHWEST NEW BRUNSWICK, CANADA. Version 1.7. Caribbean OBIS Node. Samplingevent dataset. https://ipt.iobis.org/mbon/resource?r=sandybeachesbayoffundynb&v=1.7

The Marine Biodiversity Observation Network Pole to Pole (MBON P2P) effort seeks to develop a framework for the collection, use and sharing of marine biodiversity data in a coordinated, standardized manner leveraging on existing infrastructure managed by the Global Ocean Observing System (GOOS; IOC-UNESCO), the GEO Biodiversity Observation Network (GEO BON), and the Ocean Biogeographic Information System (OBIS). The MBON Pole to Pole aims to become a key resource for decision-making and management of living resource across countries in the Americas for reporting requirements under the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), Aichi Targets of the Convention of Biological Diversity (CBD), and the UN 2030 Agenda for Sustainable Development Goals (SDGs).This collection corresponds to the species registered on rocky shores of the Musquash Harbour, Passamaquoddy Bay and Mispec Bay, New Brunswick, Canada, using the MBON P2P sampling protocol for rocky shores, with funding from the Government of Canada's Coastal Environmental Baseline Program.Citation: Reinhart B, Cooper A, Nason R, Jonah L (2025). MBON POLE TO POLE: ROCKY SHORE BIODIVERSITY OF MUSQUASH HARBOUR, PASSAMAQUODDY BAY AND MISPEC BAY. Version 1.7. Caribbean OBIS Node. Samplingevent dataset. https://ipt.iobis.org/mbon/resource?r=rockyshoresbayoffundynb&v=1.7

The Canadian Wildlife Service - Ontario Region Biodiversity Atlas represents the Canadian Wildlife Service biodiversity portfolio across the Ontario portions of the Boreal Hardwood Shield (Bird Conservation Region 12) and Mixedwood Plains (Bird Conservation Region 13) ecozones. These data are the derived product from an extensive landscape assessment that assessed the Canadian Wildlife Service biodiversity portfolio (Species at Risk, migratory birds, habitat) at various resolutions. Biodiversity is mapped by forest, grassland (open country) and wetland quality and quantity, and then progressively combined to identify local High Value Biodiversity Areas. At the finest resolution, scores were applied to each unit of analysis (5 hectare hexagon in Bird Conservation Region 12; 2 hectare hexagon in Bird Conservation Region 13), based on over 30 criteria for landscape habitat condition, Species at Risk and migratory birds. Habitat condition scores were derived from guidance in Environment and Climate Change Canada's existing How Much Habitat is Enough? and in Bird Conservation Region 12, where the landscape is less fragmented, habitat was also based on draft guidance in How Much Disturbance is too Much? Individual scores were summed and various combinations (e.g. top 25% of forest scores + top 25% of Species at Risk (SAR) scores) were calculated to identify areas with multiple conservation value. For each habitat type (forest, grassland and wetland), study units with more than one conservation value were aggregated into High Value Habitat which were subsequently aggregated into High Value Biodiversity Areas (HVBA). The results are areas on the landscape that have high value from a Canadian Wildlife Service specific lens; that is, they are high quality habitats that are important for Species at Risk and/or migratory birds. High value habitats are those forests, grasslands and wetlands with potential high conservation value (PHCV). They contain at least 1 of a possible 3 potential high conservation values: top 25% of overall habitat scores, top 25% of Species at Risk (SAR) scores, and/or top 25% of relevant migratory bird scores. High value forest, grassland and wetland were derived by combining landscape, Species at Risk (SAR) and migratory bird elements (see Table 1). Overall habitat scores were assigned to each study unit based on the combined scores for each forest, grassland and wetland. These overall habitat scores were divided into quartiles, and the top 25% of each total score (overall forest, overall grassland and overall wetland) are considered to be potential high conservation value. Similarly, SAR scores were assigned for each study unit, totalled and broken into quartiles. The top 25% of SAR scores that intersect each of forest, grassland and wetland are considered to be the highest quality habitats important to SAR and have potential high conservation value. Finally, relevant migratory bird scores were totalled within each study unit, divided into quartiles and the top 25% of migratory bird scores that intersect each of forest, grassland and wetland are considered to be the highest quality habitats important to migratory birds and have potential high conservation value. Study units with a PHCV greater than 0 (i.e., contains at least 1 of the possible 3 potential high conservation values) were aggregated together by 750 m to create High Value Habitats. High value biodiversity areas (HVBAs) are those study units that contain multiple high value habitats (high value forest and/or high value grassland and/or high value wetland). High value biodiversity areas (HVBA) were derived by aggregating high value forest, grassland and wetland. Study units with a potential high conservation value greater than 1 were aggregated together by 750 m. Biodiversity sites are areas greater than 20 ha, and secondary biodiversity sites are areas less than 20 ha in area.

The Canadian Wildlife Service - Ontario Region Biodiversity Atlas represents the Canadian Wildlife Service biodiversity portfolio across the Ontario portions of the Boreal Hardwood Shield (Bird Conservation Region 12) and Mixedwood Plains (Bird Conservation Region 13) ecozones. These data are the derived product from an extensive landscape assessment that assessed the Canadian Wildlife Service biodiversity portfolio (Species at Risk, migratory birds, habitat) at various resolutions. Biodiversity is mapped by forest, grassland (open country) and wetland quality and quantity, and then progressively combined to identify local High Value Biodiversity Areas. At the finest resolution, scores were applied to each unit of analysis (5 hectare hexagon in Bird Conservation Region 12; 2 hectare hexagon in Bird Conservation Region 13), based on over 30 criteria for landscape habitat condition, Species at Risk and migratory birds. Habitat condition scores were derived from guidance in Environment and Climate Change Canada's existing How Much Habitat is Enough? and in Bird Conservation Region 12, where the landscape is less fragmented, habitat was also based on draft guidance in How Much Disturbance is too Much? Individual scores were summed and various combinations (e.g. top 25% of forest scores + top 25% of Species at Risk (SAR) scores) were calculated to identify areas with multiple conservation value. For each habitat type (forest, grassland and wetland), study units with more than one conservation value were aggregated into High Value Habitat which were subsequently aggregated into High Value Biodiversity Areas (HVBA). The results are areas on the landscape that have high value from a Canadian Wildlife Service specific lens; that is, they are high quality habitats that are important for Species at Risk and/or migratory birds. High value habitats are those forests, grasslands and wetlands with potential high conservation value (PHCV). They contain at least 1 of a possible 3 potential high conservation values: top 25% of overall habitat scores, top 25% of Species at Risk (SAR) scores, and/or top 25% of relevant migratory bird scores. High value forest, grassland and wetland were derived by combining landscape, Species at Risk (SAR) and migratory bird elements (see Table 1). Overall habitat scores were assigned to each study unit based on the combined scores for each forest, grassland and wetland. These overall habitat scores were divided into quartiles, and the top 25% of each total score (overall forest, overall grassland and overall wetland) are considered to be potential high conservation value. Similarly, SAR scores were assigned for each study unit, totalled and broken into quartiles. The top 25% of SAR scores that intersect each of forest, grassland and wetland are considered to be the highest quality habitats important to SAR and have potential high conservation value. Finally, relevant migratory bird scores were totalled within each study unit, divided into quartiles and the top 25% of migratory bird scores that intersect each of forest, grassland and wetland are considered to be the highest quality habitats important to migratory birds and have potential high conservation value. Study units with a PHCV greater than 0 (i.e., contains at least 1 of the possible 3 potential high conservation values) were aggregated together by 750 m to create High Value Habitats. High value biodiversity areas (HVBAs) are those study units that contain multiple high value habitats (high value forest and/or high value grassland and/or high value wetland). High value biodiversity areas (HVBA) were derived by aggregating high value forest, grassland and wetland. Study units with a potential high conservation value greater than 1 were aggregated together by 750 m. Biodiversity sites are areas greater than 20 ha, and secondary biodiversity sites are areas less than 20 ha in area.