This publication contains thirteen (13) maps of different biogeochemical and soil properties of forest ecosystems of Canada’s managed forest. A scientific article gives additional details on the methodology: Paré, D., Manka, F., Barrette, J., Augustin, F., Beguin, J. 2021. Indicators of site sensitivity to the removal of forest harvest residues at the sub-continental scale: mapping, comparisons, and challenges. Ecol. Indicators. https://dx.doi.org/10.1016/j.ecolind.2021.107516

This publication contains vector data (shapefile) of the post-harvest forest residues in Canada for the bioenergy/bioproducts sector in oven-dry tonnes per year (ODT/yr) over the next 20 years. The maps were produced using different remote sensing products. We used forest attribute data at 250 m MODIS for the years 2001 and 2011 (Beaudoin et al. 2014 and 2018) combined with forest cover changes for the years 1985 to 2015 contained in the CanLaD dataset at 30 m Landsat(Guindon et al. 2017 and 2018). Results of available biomass (in the form of harvest residues) were reported at the 10 km x 10 km scale, while the map of mature forests in Canada was prepared at the forest management unit (FMU) level. Briefly, our methodology consisted of three steps: 1- create a map of mature forests for the year 2011, based on 2001-2010 average cut volumes within FMUs; 2- develop an annual cut rate from the area harvested within FMUs from 1985 to 2015 and; 3- define the amount of biomass in the form of forest residues available for the bioenergy sector. The biomass of branches and leaves of forest attribute data was used as a proxy to define the biomass of forest residues available. Nationally, the average biomass of forest residues available after harvest is 26 ± 16 ODT/ha, while the total annual availability for all managed forests in Canada was 21 million ODT/yr. A scientific article gives additional details on the methodology: Barrette J, Paré D, Manka F, Guindon L, Bernier P, Titus B. 2018. Forecasting the spatial distribution of logging residues across the Canadian managed forest. Can. J. For. Res. 48: http://www.nrcresearchpress.com/doi/10.1139/cjfr-2018-0080 Reference for this dataset: Barrette J, Paré D, Manka F, Guindon L, Bernier P, Titus B. 2018. Maps forecasting the availability of logging residues in Canada. Natural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, Quebec, Canada. https://doi.org/10.23687/5072c495-240c-42a3-ad55-c942ab37c32a

BiologicEcologic ISO Feature Dataset symbolization and publication. September 5, 2017.

The Shorezone Biobanding Polygons are an area representation of the various types of biota (flora and fauna) and their distribution, or lack thereof, found in the shoreunit.

The Canadian Aquatic Biomonitoring Network (CABIN) is an aquatic biomonitoring program for assessing the health of fresh water ecosystems in Canada. Benthic macroinvertebrates are collected at a site location and their counts are used as an indicator of the health of that water body. CABIN is based on the network of networks approach that promotes inter-agency collaboration and data-sharing to achieve consistent and comparable reporting on fresh water quality and aquatic ecosystem conditions in Canada. The program is maintained by Environment and Climate Change Canada (ECCC) to support the collection, assessment, reporting and distribution of biological monitoring information. A set of nationally standardized CABIN protocols are used for field collection, laboratory work, and analysis of biological monitoring data. A training program is available to certify participants in the standard protocols. There are two types of sites in the CABIN database (reference and test). Reference sites represent habitats that are closest to “natural” before any human impact. The data from reference sites are used to create reference models that CABIN partners use to evaluate their test sites in an approach known as the Reference Condition Approach (RCA). Using the RCA models, CABIN partners match their test sites to groups of reference sites on similar habitats and compare the observed macroinvertebrate communities. The extent of the differences between the test site communities and the reference site communities allows CABIN partners to estimate the severity of the impacts at those locations. CABIN samples have been collected since 1987 and are organized in the database by study (partner project). The data is delineated by the 11 major drainage areas (MDA) found in Canada and each one has a corresponding study, habitat and benthic invertebrate data file. Links to auxiliary water quality data are provided when available. Visits may be conducted at the same location over time with repeat site visits being identified by identical study name / site code with different dates. All data collected by the federal government is available on Open Data and more partners are adding their data continually. The csv files are updated monthly. Contact the CABIN study authority to request permission to access non open data.

The Shorezone Biobanding Lines are a linear representation of the various types of biota (flora and fauna) and their distribution, or lack thereof, found in the shoreunit.

Forest Total Aboveground Biomass 2015Total aboveground biomass. Individual tree total aboveground biomass is calculated using species-specific equations. In the measured ground plots, aboveground biomass per hectare is calculated by summing the values of all trees within a plot and dividing by the area of the plot. Aboveground biomass may be separated into various biomass components (e.g. stem, bark, branches, foliage) (units = t/ha). Products relating the structure of Canada's forested ecosystems have been generated and made openly accessible. The shared products are based upon peer-reviewed science and relate aspects of forest structure including: (i) metrics calculated directly from the lidar point cloud with heights normalized to heights above the ground surface (e.g., canopy cover, height), and (ii) modelled inventory attributes, derived using an area-based approach generated by using co-located ground plot and ALS data (e.g., volume, biomass). Forest structure estimates were generated by combining information from lidar plots (Wulder et al. 2012) with Landsat pixel-based composites (White et al. 2014; Hermosilla et al. 2016) using a nearest neighbour imputation approach with a Random Forests-based distance metric. These products were generated for strategic-level forest monitoring information needs and are not intended to support operational-level forest management. All products have a spatial resolution of 30 m. For a detailed description of the data, methods applied, and accuracy assessment results see Matasci et al. (2018). When using this data, please cite as follows: Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Bolton, D.K., Tompalski, P., Bater, C.W., 2018b. Three decades of forest structural dynamics over Canada's forested ecosystems using Landsat time-series and lidar plots. Remote Sensing of Environment 216, 697-714. Matasci et al. 2018)Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011

Pepin et al. (2014) stated that three nested spatial scales were identified as relevant for the development of ecosystem summaries and management plans: Bioregion, Ecosystem Production Unit (EPU), and Ecoregion. A bioregion is composed by one or more EPUs, while an EPU consists of a combination of ecoregions, which represent elements with different physical and biological characteristics based on the analytical criteria applied. Pepin et al. (2014) reported on the consolidation of data and analyses of ecoregion structure for the continental shelf areas from the Labrador Sea to the mid-Atlantic Bight and provided recommendations on the definition of EPUs in the NAFO Convention Area. The results of two K-means clustering analyses (one geographically constrained and one un-constrained) and expert knowledge (including and considering location of ecoregions, knowledge of the distribution of major marine resources and fish stocks, and geographic proximity for delineation/definition of potential management units) served as guides for evaluation by NAFO’s (North Atlantic Fisheries Organization) working group on ecosystem science and assessments (WG-ESA). The final consensus from the discussions identified eight (8) major EPUs that can serve as practical candidate management units (from the 50 m isobaths, where research vessel data were available, seaward to the 1500 m isobaths) that consist of the Labrador Shelf (NAFO subareas 2GH), the northeast Newfoundland Shelf (subareas 2J3K), the Grand Banks (subareas 3LNO), Flemish Cap (subarea 3M), the Scotian Shelf (subareas 4VnsWX), Georges Bank (parts of subareas 5Ze and 5Zw), the Gulf of Maine (subarea 5Y and part of 5Ze) and the mid-Atlantic Bight (part of subarea 5Zw and subareas 6ABC). Southern Newfoundland (subarea 3Ps) was not included in the original analysis because fall survey data were unavailable. However, it was later added as an EPU after additional analysis of the fish community structure and trends using survey data from the spring, which indicated that this area is heavily influenced by the surrounding EPUs (NAFO 2015).The proposed candidate management units correspond to the EPUs that define major areas within the bioregions which contain a reasonably well defined food web/production system. The working group noted that the consensus solution represents a compromise that aims to define management units based on the boundaries of existing NAFO subareas that are appropriate for estimation of ecosystem and fishery production. References: NAFO. 2015. Report of the 8th Meeting of the NAFO Scientific Council (SC) Working Group on Ecosystem Science and Assessment (WGESA). 17-26 November 2015, Dartmouth, Canada. NAFO SCS Doc. 15/19.Pepin, P., Higdon, J., Koen-Alonso, M., Fogarty, M., and N. Ollerhead. 2014. Application of ecoregion analysis to the identification of Ecosystem Production Units (EPUs) in the NAFO Convention Area. NAFO SCR Doc. 14/069.

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.

Mean zooplankton biomass (g/m³) at the 46 stations grouped into Atlantic Zone Monitoring Program (AZMP) transects under Quebec region responsibility.Mean zooplankton wet weights of the last ten years are displayed as 4 layers in june (2013-2022, 2020 not sampled) and 4 layers in november (2013-2022). The 4 layers stand for total zooplankton, mesozooplankton, macrozooplankton and euphausiids. The attached files contain the biomass data: a .png file for each station, showing time series of biomass for the total zooplankton and the euphausiids, and a .csv file containing the data themselves (columns : Station,Date(UTC), Latitude, Longitude, Sounding(m), Depth_max/Profondeur_max(m), Depth_min/Profondeur_min(m), Mesozooplankton/Mésozooplancton(g/m³), Macrozooplankton/Macrozooplancton(g/m³), Zooplankton/Zooplancton(g/m³), Euphausiids/Euphausides(g/m³)).PurposeThe Atlantic Zone Monitoring Program (AZMP) was implemented in 1998 with the aim of increasing the Department of Fisheries and Oceans Canada’s (DFO) capacity to detect, track and predict changes in the state and productivity of the marine environment.The AZMP collects data from a network of stations composed of high-frequency monitoring sites and cross-shelf sections in each following DFO region: Québec, Gulf, Maritimes and Newfoundland. The sampling design provides basic information on the natural variability in physical, chemical, and biological properties of the Northwest Atlantic continental shelf. Cross-shelf sections sampling provides detailed geographic information but is limited in a seasonal coverage while critically placed high-frequency monitoring sites complement the geography-based sampling by providing more detailed information on temporal changes in ecosystem properties.In Quebec region, two surveys (46 stations grouped into transects) are conducted every year, one in June and the other in autumn in the Estuary and Gulf of St. Lawrence. Historically, 3 fixed stations were sampled more frequently. One of these is the Rimouski station that still takes part of the program and is sampled about weekly throughout the summer and occasionally in the winter period.Annual reports (physical, biological and a Zonal Scientific Advice) are available from the Canadian Science Advisory Secretariat (CSAS), (http://www.dfo-mpo.gc.ca/csas-sccs/index-eng.htm).Devine, L., Scarratt, M., Plourde, S., Galbraith, P.S., Michaud, S., and Lehoux, C. 2017. Chemical and Biological Oceanographic Conditions in the Estuary and Gulf of St. Lawrence during 2015. DFO Can. Sci. Advis. Sec. Res. Doc. 2017/034. v + 48 pp.Supplemental InformationZooplankton is sampled by bottom-surface vertical net tow with a conic 202 µm net and preserved in a 4% solution of buffered formaldehyde according to AZMP sampling protocol:Mitchell, M. R., Harrison, G., Pauley, K., Gagné, A., Maillet, G., and Strain, P. 2002. Atlantic Zonal Monitoring Program sampling protocol. Can. Tech. Rep. Hydrogr. Ocean Sci. 223: iv + 23 pp.