The Scotian Shelf population of northern bottlenose whales (Hyperoodon ampullatus) is listed as Endangered under Canada’s Species at Risk Act. Partial critical habitat was identified for this population in the Recovery Strategy first published in 2010 (Fisheries and Oceans Canada 2016), and three critical habitat areas were designated along the eastern Scotian Shelf, encompassing the Gully, Shortland Canyon, and Haldimand Canyon (shapefile available online: https://open.canada.ca/data/en/dataset/db177a8c-5d7d-49eb-8290-31e6a45d786c). However, the Recovery Strategy recognized that additional areas may constitute critical habitat for the population and recommended further studies based on acoustic and visual monitoring to assess the importance of inter-canyon areas as foraging habitat and transit corridors for northern bottlenose whales.In a subsequent study of the distribution, movements, and habitat use of northern bottlenose whales on the eastern Scotian Shelf (Stanistreet et al. in press), several sources of data were assessed and additional important habitat was identified in the inter-canyon areas located between the Gully, Shortland Canyon, and Haldimand Canyon (DFO 2020). A summary of the data inputs, analyses, and limitations is provided below.Year-round passive acoustic monitoring conducted with bottom-mounted recorders at two inter-canyon sites from 2012-2014 revealed the presence and foraging activity of northern bottlenose whales in these areas throughout much of the year, with a seasonal peak in acoustic detections during the spring. Detections from acoustic recordings collected during vessel-based surveys provided additional evidence of species occurrence in inter-canyon areas during the summer months. Photo-identification data collected in the Gully, Shortland, and Haldimand canyons between 2001 and 2017 were used to model the residency and movement patterns of northern bottlenose whales within and between the canyons, and demonstrated that individuals regularly moved between the three canyons as well as to and from outside areas. Together, these results indicated a strong degree of connectivity between the Gully, Shortland, and Haldimand canyons, and provided evidence that the inter-canyon areas function as important foraging habitat and movement corridors for Scotian Shelf northern bottlenose whales. The inter-canyon habitat area polygon was delineated using the 500 m depth contour and straight lines connecting the southeast corners of the existing critical habitat areas, but these boundaries are based on limited spatial information on the presence of northern bottlenose whales in deeper waters. More data are needed to determine whether this area fully encompasses important inter-canyon habitat, particularly in regard to the deeper southeastern boundary. Similarly, the full extent of important habitat for Scotian Shelf northern bottlenose whales remains unknown, and potential critical habitat areas outside the canyons and inter-canyon areas on the eastern Scotian Shelf have not been fully assessed. See DFO (2020) for further information.References:DFO. 2020. Assessment of the Distribution, Movements, and Habitat Use of Northern Bottlenose Whales on the Scotian Shelf to Support the Identification of Important Habitat. DFO Can. Sci. Advis. Sec. Sci. Advis. Rep. 2020/008. https://www.dfo-mpo.gc.ca/csas-sccs/Publications/SAR-AS/2020/2020_008-eng.html Fisheries and Oceans Canada. 2016. Recovery Strategy for the Northern Bottlenose Whale, (Hyperoodan ampullatus), Scotian Shelf population, in Atlantic Canadian Waters [Final]. Species at Risk Act Recovery Strategy Series. Fisheries and Oceans Canada, Ottawa. vii + 70 pp. https://www.canada.ca/en/environment-climate-change/services/species-risk-public-registry/recovery-strategies/northern-bottlenose-whale-scotian-shelf.html Stanistreet, J.E., Feyrer, L.J., and Moors-Murphy, H.B. In press. Distribution, movements, and habitat use of northern bottlenose whales (Hyperoodon ampullatus) on the Scotian Shelf. DFO Can. Sci. Advis. Sec. Res. Doc. [https://publications.gc.ca/collections/collection_2022/mpo-dfo/fs70-5/Fs70-5-2021-074-eng.pdf]Cite this data as: Stanistreet, J.E., Feyrer, L.J., and Moors-Murphy, H.B. Data of: Northern bottlenose whale important habitat in inter-canyon areas on the eastern Scotian Shelf. Published: June 2021. Ocean Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/9fd7d004-970c-11eb-a2f3-1860247f53e3

Description:Biophysical Units: Under the Pacific Marine Ecological Classification System (PMECS; DFO 2016; Rubidge et al. 2016), biophysical units are areas of distinct physiographic and oceanographic conditions and processes that shape species composition at spatial extents of 1000s of km. Geomorphic units:Geomorphic units or geozones are discrete geomorphological structures at the scale of 100s of km that are assumed to have distinctive biological assemblages (e.g., plateaus, ridges, seamounts, canyons). Although the spatial scale of geomorphic units is nested within biophysical units, a single geomorphic unit such as a trough may span more than one biophysical unit. The following 5 layers are included in this geodatabase:1. Biophysical_Units_L4A - Predicted PMECS Biophysical Units (Level 4A) output from the random forest analysis2. Biophysical_Units_L4B - Predicted PMECS Biophysical Units (Level 4B) output from the random forest analysis3. Biophysical_Units_ProbAssign_L4AB - Layer showing the probability that a grid cell was assigned to a given biophysical unit in the final random forest predictive modelling step4. Cluster_L4AB - Layer showing the output of species assemblage cluster analysis5. Geomorphic_Units - Geomorphic units for the BC coast that combines geomorphic units produced by Rubidge et al. 2016) and Proudfoot and Robb (2022).Methods:Biophysical Units:Rubidge et al. (2016) used a two-step process to identify biophysical units in British Columbia. First, a cluster analysis based on the similarity of species composition was used to group sites with similar species into distinct biological assemblages. Second, a random forest analysis was used to identify environmental correlates of the biological assemblages identified by the cluster analysis and to predict and assign the biological assemblage present in areas with too few biological data. Two different similarity thresholds were used to identify two levels (4A, 4B) of biophysical units; see Rubidge et al. (2016) for details. Indicator species for each assemblage (biophysical unit) were also identified.Geomorphic units:Rubidge et al. (2016) used the benthic terrain modeller (BTM) tool with broad and fine-scale benthic positioning index (BPI) parameters to define geomorphic units on the continental shelf in the Northern Shelf Bioregion and the continental slope in both the Northern Shelf Bioregion and Southern Shelf Bioregion. In 2022, geomorphic units were produced for the Strait of Georgia and Southern Shelf Bioregions following the same methods as Rubidge et al. (2016) (Proudfoot and Robb 2022). The geomorphic units produced as part of the PMECS process were merged with the geomorphic units produced for the Strait of Georgia and Southern Shelf bioregions to produce a continuous spatial data product representing geomorphic units for the Canadian Pacific continental shelf and slope. After merging, the geomorphic units produced in 2016 were unchanged (i.e., they are consistent with the original geomorphic units described in Rubidge et al. 2016).Data Sources:From Rubidge et al. (2016): Species data was taken from Fisheries and Oceans Canada (DFO) standardized fisheries-independent research surveys: groundfish trawl and long-line (2003-2013), Tanner Crab trawl and trap (2000–2006), and Dungeness Crab trap (2000–2014). Environmental data came from NASA, the Canadian Hydrographic Service, Fisheries and Oceans Canada, Bio-ORACLE, and elsewhere (details in Rubidge et al. 2016). From Proudfoot and Robb (2022): bathymetry data came from Natural Resources Canada (details in Proudfoot and Robb 2022).Uncertainties:The data is intended for use at the bioregional scale, and caution should be used for finer-scale analyses.

In 2016-17, DFO Maritimes Region undertook a Marine Protected Area (MPA) network analysis for the Scotian Shelf-Bay of Fundy Bioregion. The analysis considered available bioregional-scale ecological and human use data in an effort to identify a draft MPA network design that would protect biodiversity while minimizing any potential impacts on commercial fishing and other industries. The data layers used for the offshore component of the MPA network analysis are provided here. These layers are not presented in their original forms and were modified (e.g. clipped, reclassified, etc.) specifically for use in the MPA network analysis. They should not be used for any other purpose. Please see Serdynska et al. 2021 for details on how each layer was created.Serdynska, A.R., Pardy, G.S., and King, M.C. 2021. Offshore Ecological and Human Use Information considered in Marine Protected Area Network Design in the Scotian Shelf Bioregion. Can. Tech. Rep. Fish. Aquat. Sci. 3382: xi + 100 p. https://publications.gc.ca/collections/collection_2021/mpo-dfo/Fs97-6-3382-eng.pdfCite this data as: Serdynska, A.R., Pardy, G.S., and King, M.C. Data of: Offshore Ecological and Human Use Information considered in Marine Protected Area Network Design in the Scotian Shelf Bioregion. Published: January 2022. Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/2d9cce9a-d634-4b49-879f-87c40c52acf2

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.

This geodatabase includes hotspot maps of 1) nearshore habitat richness, 2) diversity (fish and invertebrates), and 3) biomass (using catch per unit effort of fish and invertebrates), as well as two layers showing the spatial extent of the diversity and biomass hotspot analyses. Full details and methods can be found in the Rubidge et al. 2018 CSAS Research Document 2018/053 available here or at https://waves-vagues.dfo-mpo.gc.ca/Library/40759842.pdf. These data were reviewed as part of a Canadian Science Advisory Secretariat (CSAS) regional peer review process on Nov 1-2, 2017.Habitat Richness Hotspots: Because there are no systematic surveys of nearshore species that span the entire coastline of Northern Shelf Bioregion, the nearshore habitat richness hotspots were developed as a proxy for species diversity in nearshore areas. Habitat richness was calculated from eight habitat features: eelgrass, surfgrass, canopy-forming kelp, estuaries, areas of high rugosity, and hard, mixed, and soft substrate. The number of features within 1 km x 1 km planning units was counted, and hotspots were identified using the Getis-Ord G* tool in ArcGIS. Planning units with Gi_Bin values of 3 (99% confidence) were classified as habitat richness hotspots.Diversity and Biomass Hotspots: Hotspots of fish and invertebrate diversity and biomass were developed as proxies for spatial patterns of productivity in the Northern Shelf Bioregion. Diversity (Shannon diversity) and biomass (kg/hour or count/hook/hour) were calculated from DFO synoptic trawl and outside hard-bottom longline (HBLL) survey catch records. The outside HBLL survey was previously referred to as Pacific Halibut Management Area (PHMA) survey. The synoptic trawl and HBLL surveys have complementary spatial coverage, with the HBLL surveys occurring in more coastal areas (20–260 m) and the synoptic trawl surveys occurring on deeper shelf areas (50–1300 m). Hotspots were identified using the Getis-Ord G* tool in ArcGIS for five separate analyses: fish biomass (trawl), fish diversity (trawl), fish diversity (longline), invertebrate biomass (trawl), and invertebrate diversity (trawl). Using the Minimum Bounding Geometry Tool, convex hull polygons were drawn around groups of hotspot points (Gi_Bin values of 1, 2, or 3; confidence ≥90%) containing 10 or more points. The resulting polygons were then buffered by 1 km and manually edited where needed to exclude any large areas of the polygons that did not include hotspot points.

Polygons denoting concentrations of sea pens, small and large gorgonian corals and sponges on the east coast of Canada have been identified through spatial analysis of research vessel survey by-catch data following an approach used by the Northwest Atlantic Fisheries Organization (NAFO) in the Regulatory Area (NRA) on Flemish Cap and southeast Grand Banks. Kernel density analysis was used to identify high concentrations and the area occupied by successive catch weight thresholds was used to identify aggregations. These analyses were performed for each of the five biogeographic zones of eastern Canada. The largest sea pen fields were found in the Laurentian Channel as it cuts through the Gulf of St. Lawrence, while large gorgonian coral forests were found in the Eastern Arctic and on the northern Labrador continental slope. Large ball-shaped Geodia spp. sponges were located along the continental slopes north of the Grand Banks, while on the Scotian Shelf a unique population of the large barrel-shaped sponge Vazella pourtalesi was identified. The latitude and longitude marking the positions of all tows which form these and other dense aggregations are provided along with the positions of all tows which captured black coral, a non-aggregating taxon which is long-lived and vulnerable to fishing pressures.These polygons identify large gorgonian coral fields from the broader distribution of large gorgonian corals in the region as sampled by Western II A trawl gear in the Scotian Shelf biogeographic zone. A 0.5 kg minimum threshold for the large gorgonian coral catch was identified as the weight that separated the large gorgonian field habitat from the broader distribution of large gorgonian corals with these research vessel tow data and gear type.

Polygons denoting concentrations of sea pens, small and large gorgonian corals and sponges on the east coast of Canada have been identified through spatial analysis of research vessel survey by-catch data following an approach used by the Northwest Atlantic Fisheries Organization (NAFO) in the Regulatory Area (NRA) on Flemish Cap and southeast Grand Banks. Kernel density analysis was used to identify high concentrations and the area occupied by successive catch weight thresholds was used to identify aggregations. These analyses were performed for each of the five biogeographic zones of eastern Canada. The largest sea pen fields were found in the Laurentian Channel as it cuts through the Gulf of St. Lawrence, while large gorgonian coral forests were found in the Eastern Arctic and on the northern Labrador continental slope. Large ball-shaped Geodia spp. sponges were located along the continental slopes north of the Grand Banks, while on the Scotian Shelf a unique population of the large barrel-shaped sponge Vazella pourtalesi was identified. The latitude and longitude marking the positions of all tows which form these and other dense aggregations are provided along with the positions of all tows which captured black coral, a non-aggregating taxon which is long-lived and vulnerable to fishing pressures.These polygons identify sea pen fields from the broader distribution of sea pens in the region as sampled by Western II A trawl gear in the Scotian Shelf biogeographic zone. A 0.1 kg minimum threshold for the sea pen catch was identified as the weight that separated the sea pen field habitat from the broader distribution of sea pens with these research vessel tow data and gear type.

Polygons denoting concentrations of sea pens, small and large gorgonian corals and sponges on the east coast of Canada have been identified through spatial analysis of research vessel survey by-catch data following an approach used by the Northwest Atlantic Fisheries Organization (NAFO) in the Regulatory Area (NRA) on Flemish Cap and southeast Grand Banks. Kernel density analysis was used to identify high concentrations and the area occupied by successive catch weight thresholds was used to identify aggregations. These analyses were performed for each of the five biogeographic zones of eastern Canada. The largest sea pen fields were found in the Laurentian Channel as it cuts through the Gulf of St. Lawrence, while large gorgonian coral forests were found in the Eastern Arctic and on the northern Labrador continental slope. Large ball-shaped Geodia spp. sponges were located along the continental slopes north of the Grand Banks, while on the Scotian Shelf a unique population of the large barrel-shaped sponge Vazella pourtalesi was identified. The latitude and longitude marking the positions of all tows which form these and other dense aggregations are provided along with the positions of all tows which captured black coral, a non-aggregating taxon which is long-lived and vulnerable to fishing pressures.These polygons identify sponge grounds from the broader distribution of sponges in the region as sampled by Western II A trawl gear in the Scotian Shelf biogeographic zone. A 2 kg minimum threshold for the sponge catch was identified as the weight that separated the sponge ground habitat from the broader distribution of sponges with these research vessel tow data and gear type.

Concentrations of sea pens, small and large gorgonian corals and sponges on the east coast of Canada have been identified through spatial analysis of research vessel survey by-catch data following an approach used by the Northwest Atlantic Fisheries Organization (NAFO) in the Regulatory Area (NRA) on Flemish Cap and southeast Grand Banks. Kernel density analysis was used to identify high concentrations. These analyses were performed for each of the five biogeographic zones of eastern Canada. The largest sea pen fields were found in the Laurentian Channel as it cuts through the Gulf of St. Lawrence, while large gorgonian coral forests were found in the Eastern Arctic and on the northern Labrador continental slope. Large ball-shaped Geodia spp. sponges were located along the continental slopes north of the Grand Banks, while on the Scotian Shelf a unique population of the large barrel-shaped sponge Vazella pourtalesi was identified. The latitude and longitude marking the positions of all tows which form these and other dense aggregations are provided along with the positions of all tows which captured black coral, a non-aggregating taxon which is long-lived and vulnerable to fishing pressures.

This layer details Important Areas (IAs) relevant to coral, sponge, and reef-building species in the West Coast Vancouver Island (WCVI) ecoregion. This data was mapped to inform the selection of marine Ecologically and Biologically Significant Areas (EBSA). Experts have indicated that these areas are relevant based upon their high ranking in one or more of three criteria (Uniqueness, Aggregation, and Fitness Consequences).Canada’s Oceans Act provides the legislative framework for an integrated ecosystem approach to management in Canadian oceans, particularly in areas considered ecologically or biologically significant. DFO has developed general guidance for the identification of ecologically or biologically significant areas. The criteria for defining such areas include uniqueness, aggregation, fitness consequences, resilience, and naturalness. This science advisory process identifies proposed EBSAs in Canadian Pacific marine waters, specifically in the Strait of Georgia (SOG), along the west coast of Vancouver Island (WCVI, southern shelf ecoregion), and in the Pacific North Coast Integrated Management Area (PNCIMA, northern shelf ecoregion).Initial assessment of IA's in PNCIMA was carried out in September 2004 to March 2005 with spatial data collection coordinated by Cathryn Clarke. Subsequent efforts in WCVI and SOG were conducted in 2009, and may have used different scientific advisors, temporal extents, data, and assessment methods. WCVI and SOG IA assessment in some cases revisits data collected for PNCIMA, but should be treated as a separate effort.Though data collection is considered complete, the emergence of significant new data may merit revisiting of IA's on a case by case basis.Other datasets in this series detail IAs for birds, cetaceans, fish, geographic features, invertebrates, and other vertebrates.This package also includes project documentation and tech reports relevant to the IA process and its role within the selection of EBSAs.