A compendium of reports that provide information about aquatic and terrestrial animals and plants, soils, surface water, groundwater and their accompanying data files and maps

This data record contains four digitized maps recreated from an original report entitled An Ecological Sketch of Some Fundy Fisheries published by the Conservation Council of New Brunswick. The selected maps summaries information obtained from active and retired fishermen, combined with a survey of the scientific and historical information. They illustrate knowledge on spawning, migration, and nursery grounds for herring and other fisheries for Grand Manan, Bay of Fundy, and Gulf of Maine.Cite this data as: Coon, D. 1999. An Ecological Sketch of Some Fundy Fisheries. Conservation Council of New Brunswick, Fredericton, NB. 32 pp. Published: June 2026. Coastal Ecosystems Science Division, Maritimes Region, Fisheries and Oceans Canada, Dartmouth NShttps://open.canada.ca/data/en/dataset/d09eee14-4786-4787-a596-9ddec1ad9342

Identification of ecological and biological significant areas (EBSA) in the Estuary and the Gulf of St. Lawrence according to six groups of the food chain : primary production (Lavoie et al, 2007), secondary production (Plourde et McQuinn, 2010), meroplankton (Ouellet, 2007), benthic invertebrates (Chabot et al, 2007), demersal fishes (Castonguay et Valois, 2007) and pelagic fishes (McQuinn et al, 2012). The distribution area of each group has been evaluated using five criteria in order to determine the EBSA (DFO, 2004):1. Uniqueness: Ranked from areas whose characteristics are unique, rare, distinct, and for which alternatives do not exist to areas whose characteristics are widespread with many areas which are similar.2. Aggregation: Ranked from areas where most individuals of a species are aggregated to areas where individuals of the species are widespread3. Fitness consequence: Ranked from areas where the life history activity(ies) undertaken make a major contribution to the fitness of the population or species present to areas where the life history activity(ies) undertaken make only marginal contributions to fitness.4. Resilience: Ranked from areas where the habitat structures or species are highly sensitive, easily perturbed, and slow to recover to areas where the habitat structures or species are robust, resistant to perturbation, or readily return to the pre-perturbation state.5. Naturalness: Ranked from areas which are pristine and characterized by native species to areas which are highly perturbed by anthropogenic activities and/or with high abundances of introduced or cultured species.Castonguay, M. and Valois, S. 2007. Zones d’importance écologique et biologique pour les poissons démersaux dans le nord du Golfe du Saint-Laurent. DFO Can. Sci. Advis. Sec. Res. Doc. 2007/014. iii + 34 p.Chabot, D., Rondeau A., Sainte-Marie B., Savard L., Surette T. et Archambault P. 2007. Distribution des invertébrés benthiques dans l’estuaire et le golfe du Saint-Laurent. DFO Can. Sci. Advis. Sec. Res. Doc. 2007/018. iii + 118 p.DFO, 2004. Identification of Ecologically and Biologically Significant Areas. DFO Can. Sci. Advis. Sec. Ecosystem Status Rep. 2004/006. Lavoie, D., Starr, M., Zakardjian, B. and Larouche, P. 2007. Identification of ecologically and biologically significant areas (EBSA) in the Estuary and Gulf of St. Lawrence: Primary production. DFO Can. Sci. Advis. Sec. Res. Doc. 2007/079. iii + 29 p. McQuinn, I.H., Bourassa, M-N., Tournois, C., Grégoire, F., and Baril, D. 2012. Ecologically and biologically significant areas in the Estuary and Gulf of St. Lawrence: small pelagic fishes. DFO Can. Sci. Advis. Sec. Res. Doc. 2012/087. iii + 76 p.Ouellet P. 2007. Contribution à l’identification de zones d’importance écologique et biologique (ZIEB) pour l’estuaire et le golfe du Saint-Laurent : La couche des oeufs et des larves de poissons et de crustacés décapodes. DFO Can. Sci. Advis. Sec. Res. Doc. 2007/011. iii + 76 p. (Mise à jour novembre 2010)Plourde, S. et McQuinn, I.A. 2010. Zones d’importance écologique et biologique dans le golfe du Saint-Laurent : zooplancton et production secondaire. DFO Can. Sci. Advis. Sec. Res. Doc. 2009/104. iv + 27 p.

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

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.

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.

The B.C. Conservation Data Centre’s spatial view of publicly available, known locations of species and ecological communities at risk. This spatial view is split into the "Publicly Available Occurrences" layer and "(Extirpated and Historical) Publicly Available Occurrences" layer. The Extirpated and Historical layer includes element occurrences that have a last observation date greater than 40 years ago and element occurrences that are extirpated due to general habitat loss or degradation of the environment in the area. Use the field ‘Rank Description’ to differentiate between Historical and Extirpated element occurrences in this layer. All element occurrences are polygons: the size of the polygon usually reflects the locational uncertainty associated with the source data, represented with varying sized circles. Some polygons may be larger to reflect the actual area covered by the element occurrence. The field "Representational Accuracy" is used to communicate how accurately the polygon reflects the actual area covered by the element. If you do not find an element occurrence in your area of interest, this means there are none currently mapped in the CDC database. The best way to verify whether an area contains a species or ecosystem at risk is to have do a detailed assessment of the property during the appropriate season.

Territories of ecological interest in the City of Trois-Rivières**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Ecologically and Biologically Significant Areas (EBSAs) are areas within Canada's oceans that have been identified through formal scientific assessments as having special biological or ecological significance when compared with the surrounding marine ecosystem.Failure to define an area as an EBSA does not mean that it is unimportant ecologically. All areas serve ecological functions to some extent and require sustainable management. Rather, areas identified as EBSAs should be viewed as the most important areas where, with existing knowledge, regulators and marine users should be particularly risk averse to ensure ecosystems remain healthy and productive.Why are EBSAs identified?EBSA information is used to inform marine planning, including environmental assessment and the siting of marine-based activities, by:- Informing and guiding project-specific or regional environmental assessments;- Informing and guiding industries and regulators in their planning and operations, for example: EBSAs have been acknowledged and referred to (often as "Special Areas" or "Potentially Sensitive Areas") in oil and gas related assessments;- EBSA information has been provided to proponents of submarine cable projects to be used for route planning purposes;- Informing and guiding Integrated Oceans Management (IOM) process within five Large Ocean Management Areas (LOMAs) and twelve marine bioregions;- Serving as a basis for the identification of Areas of Interest (AOIs) and of Marine Protected Areas (MPAs) (individually and in the context of planning bioregional networks of MPAs).How are EBSAs identified?The process used to identify EBSAs is generally comprised of two phases. The first phase involves compiling scientific data and knowledge of a marine area's ecosystems - notably fish species, marine mammals, sea birds, marine flora, marine productivity, physical and chemical conditions and geology. "Knowledge" includes experiential knowledge of long-time uses of the areas. In some cases (e.g., in the Arctic), substantial efforts are taken to collect traditional knowledge on ecosystems and environmental conditions from community members, fish harvests, hunters and individuals whose knowledge of the study area complement often helps fill scientific data gaps.In the second phase, the available information for a marine area (e.g. a bioregion) is assessed against five nationally-established science-based criteria including:- Uniqueness: How distinct is the ecosystem of an area compared to surrounding ones?- Aggregation: Whether or not species populate or convene to the study area?- Fitness consequence: How critical the area is to the life history of the species that use it (e.g. is it a spawning or feeding ground)?- Naturalness: How pristine or disturbed by human activities is the study area?- Resilience: What is the ability of the ecosystem to bounce back if it is disturbed?Progress to date and next stepsEBSAs have been identified for large portions of Canada's Atlantic and Pacific Oceans as well as most of the Arctic oceans. EBSAs will continue to be identified in priority areas as resources become available to carry out the process. The boundaries or locations of existing EBSAs may be modified to reflect both new knowledge and changing environmental conditions.

For most recent Ecological Land Classification data, see: https://data.novascotia.ca/d/q6zd-39t3 The Ecological Land Classification (ELC) for Nova Scotia provides a hierarchical mapping of the province's forest ecosystems into ecosections, ecodistricts and ecoregions. It includes interpretation of the dominant natural disturbance regimes and potential climax forests at the ecosection level.