Snow survey administrative basin areas, which are components of the BC snow survey network. Basin codes are used as basis of snow survey station names, and for some reporting purposes.

An administrative unit of forest land designated by the Minister, as authorized under Section 14(1) of the Forests Act.

The spatial representation for an Inventory Region or Compartment. Established by the Resource Inventory Branch, Inventory Regions are large drainages encompassing groups of small drainages also known as compartments. These were once used for planning purposes, similar to the current Planning Cells. They are now maintained in the files as reference for many administration boundaries

This spatial data represents the boundaries of Manitoba's forest sections. Forest sections are administrative areas comprised of Forest Management Units (FMU's). There are 14 uniquely named forest sections in Manitoba, 9 of which are capable of growing commercial forests.Manitoba's f orest sections are administrative areas comprised of Forest Management Units (FMU's). There are 14 uniquely named forest sections in Manitoba, 9 of which are capable of growing commercial forests. The Aspen Parkland forest section in the south along with the northern forest sections of Boreal Shield, Taiga Shield, Hudson Plains and Southern Arctic are incapable of growing commercial forests. The four northern forest sections were previously called the 'white zone' and all have retained the previous white zone forest section number of 10. The northern forest section boundaries are based on the following ecozones:Hudson Plains: A subarctic area encompassing the coastal areas of Hudson Bay. The area is formed into a wide, level plain, characterised by poor drainage that has resulted in large and numerous peatlands, lakes, coastal marshes, and tidal flats. Alder, willow, black spruce, and tamarack are the most common tree species.Taiga Shield: Terrain is typically flat or with rolling hills caused by glacial retreat; long eskers and uplands are common. Shallow soils remain damp year-round and regularly freeze and thaw; this leads to tilted growing trees, sometimes called ‘drunken forests’. The northern edge of the forest section is delineated by the tree line. Black spruce, jack pine, birch, tamarack, white spruce, balsam fir, trembling aspen, and balsam poplar are common tree species.Southern Arctic: The southern boundary designated the tree line. Moraines, eskers, kettle lakes, and ponds are common. Permafrost occurs in a continuous sheet throughout the section; polygonal hummocks often result from the freeze and thaw of the soils.Boreal Shield : This forest section represents the upper boundary of the boreal shield ecozone, characterised by long, cold winters and warm summers. Permafrost is widespread. Uplands and lowland tree species are common. Soil varies from poorly drained muskeg to glacially-deposited sand. Coniferous trees include white and black spruce, balsam fir, jack pine, and tamarack; hardwood tree species include birch, trembling aspen, and balsam poplar. Forest fires and insect outbreaks are the natural drivers of forest succession. The ten forest sections south of forest section 10 are sometimes referred to as the 'green zone' and include the following: Pineland, Aspen Parkland, Mountain, Interlake, Lake Winnipeg East, Churchill, Nelson River, Hayes River, Saskatchewan River and Highrock. Fields Included: S ECTION : Forest section number . SECTION_NAME : Forest section name .

An exploratory project on the taxonomic and genetic diversity of decapods in three ocean subregions (Northeast Pacific, Canadian Arctic, and Northwest Atlantic), which were sampled in 2022, was undertaken by the Arctic Working Group under the Canada-U.S. Fisheries and Climate Collaboration between Fisheries and Oceans Canada (DFO) and the National Marine Fisheries Service (NMFS) of the National Oceanic and Atmospheric Administration (NOAA). This collaboration framework aims to pool Canadian and U.S. data to explore the impacts of broad-scale climate change on marine biodiversity. In early summer 2022, a sampling protocol with the selection of targeted decapods was provided to DFO and NOAA collaborators. Targeted genera were collected from a total of 10 research programs across three ocean subregions and four marine regions. The Northeast Pacific samples were collected in the Bering Sea during the Northern Bering Sea Ecosystem and Surface Trawl Survey, and the Eastern and Northern Bering Sea Continental Shelf Bottom Trawl Survey of Groundfish and Invertebrate Fauna onboard the F/V Northwest Explorer, F/V Alaska Knight and F/V Vesteraalen. In the Western Canadian Arctic (mainly from Beaufort Sea and Amundsen Gulf), specimens were collected during DFO’s Canadian Beaufort Sea – Marine Ecosystem Assessment (CBS-MEA) survey onboard the F/V Frosti. In Eastern Canadian Arctic (mainly from Baffin Bay and Davis Strait), specimens were collected during DFO’s Knowledge and Ecosystem-Based Approach in Baffin Bay (KEBABB) survey onboard the CCGS Amundsen and DFO’s North Atlantic Fisheries Organization (NAFO) Subarea 0B survey onboard the R/V Tarajoq. In the Estuary and Gulf of St. Lawrence (EGSL), specimens were collected from coastal surveys (scallops, sea cucumber, snow crab, and whelk surveys) onboard the CCGS Leim and offshore during the Ecosystemic Survey onboard the CCGS Teleost. Decapods were collected from various sampling gears (benthic beam trawl, modified Atlantic Western IIA otter trawl, Bacalao trawl, shrimp trawl, Digby scallop dredge, or modified sea cucumber dredge) and identified to the lowest possible taxonomic level and photographed, when possible. All specimens were frozen at sea (n = 995). In the lab, the identifications were validated or refined with the photos and the frozen specimens. DNA was extracted for 87 specimens and a section of COI gene was amplified in order to be sequenced using Sanger method. Sequences were compared with existing data using The Basic Local Alignment Search Tool (BLAST) in the National Center for Bio-technology Information Nucleotide database (NCBI-nt, including the GenBank database) to compare scientific names, where available.The present dataset includes 391 decapod species occurrences. DNA was extracted for a subset of 87 specimens (COI gene); sequences are publicly available on BOLD data portal under project code DDAO (see supporting document "citations_references.csv" for more information).The data are presented in Darwin Core format and are separated in three files:The "Activité_décapodes_DDAO_decapods_event_en" file contains information about missions, stations and deployments, which are presented under a hierarchical activity structure.The "Occurrence_décapodes_DDAO_decapods_en" file contains the taxonomic occurrences.The "ADN_décapodes_DDAO_decapods_DNA_en" file contains the DNA derived data.For further details, please refer to the technical report available in the supporting document named "citations_references.csv". USE LIMITATION:To ensure scientific integrity and appropriate use of the data, we would encourage you to contact the data custodian.

Ontario's Crown forest is divided into geographic planning areas, known as forest management units. Most of these units are managed by individual forest companies under a Sustainable Forest License. A forest management unit is identified by an assigned official name (e.g., Black Spruce Forest) and a unique numeric code. Before any forestry activities can take place in a management unit, there must be an approved forest management plan in place for each management unit. Instructions for downloading this dataset: This product requires the use of geographic information system (GIS) software.

####Leading Group for the Cariboo Region (pinegroup or firgroup). #### 1. IDF - Fir Group: includes all forest polygons in NDT 4 (IDF and BG biogeoclimatic zones) that meet any of the following criteria: *a) Douglas-fir ( Fd or Fdi) leading or ponderosa pine leading; *b) Lodgepole pine leading, and Douglas-fir ( Fd or Fdi) or ponderosa pine greater than 15% in any inventory layer; *c) Trembling aspen leading, and Douglas-fir ( Fd or Fdi) or Ponderosa pine greater than 15% in any inventory layer, and spruce, red-cedar, cottonwood and birch less than 6% in any inventory layer; *d) No species information in inventory data (usually NSR stands), and inventory type group for pre-harvest stand or the current stand = 1, 2, 3, 4, 5, 6, 7, 8, 29, or 32 These inventory type groups correspond to the following species compositions F, FC, FCy, FH, FS, FPl, Fpy, FL, FDEcid, PlF and Py. If inventory type group=0 and pre-harvest inventory type is not available, classify the polygon as Pine Group. 2. IDF-Pl Group: includes all forest polygons in NDT 4 (IDF and BG biogeoclimatic zones) that do not meet the above definition for IDF-Fir Group.

The blue whale (Balaenopterus musculus) is a wide-ranging cetacean that can be found in all oceans, inhabiting coastal and oceanic habitats. In the North Atlantic, little is known about blue whale distribution and genetic structure, and if whether animals found in Icelandic waters, the Azores, or Northwest Africa are part of the same population as those from the Northwest Atlantic. In the Northwest Atlantic, seasonal movements of blue whales and habitat use, including the location of breeding and wintering areas, are poorly understood.The behaviour of remotely-monitored animals can be inferred from a time series of location data. This is because animals tend to demonstrate stochasticity in their movement paths as a result of spatial variation in environmental characteristics, such as topography or prey density (Curio 1976; Gardner et al. 1989; Turchin 1991; Wiens et al. 1993). Predators are expected to decrease travel speed and/or increase turning frequency and turning angle when a suitable resource, e.g., food patch, is encountered (Turchin 1991), otherwise known as area-restricted search (ARS). In contrast, animals in transit or travelling tend to move at faster and more regular speeds, with infrequent and smaller turning angles (Kareiva and Odell 1987; Turchin 1998).Based on satellite telemetry to track the seasonal movements of 24 blue whales from eastern Canada in 2002 and from 2010 to 2015, it was possible to estimate trajectories and locations where ARS behaviour of blue whales was inferred at a 4h time interval.To assess blue whale movements and behavior, a Bayesian switching statespace model (SSSM) was applied to Argos-derived telemetry data (Jonsen et al. 2005; Jonsen et al. 2013). An SSSM essentially estimates animal location at fixed time intervals, movement parameters and behavioral patterns.Two important sources of uncertainty can be measured separately: estimation error resulting from inaccurate observations (Argos location error) and process variability linked to the stochasticity of the movement process (behavior mode estimation) (Jonsen et al. 2003; Patterson et al. 2008).The points visible on land are the result of errors in the Argos geographic position calculation. They have been deliberately left unchanged to assess the performance of the model, which was able to clean up some positions, but not all.Lesage, V., Gavrilchuk, K., Andrews, R.D., and Sears, R. 2016. Wintering areas, fall movements and foraging sites of blue whales satellite-tracked in the Western North Atlantic. DFO Can. Sci. Advis. Sec. Res. Doc. 2016/078. v + 38 p.

The spatial representation of a Forest Stewardship Plan and Forest Development Units. A Forest Stewardship Plan is a plan submitted by a forest industry licensee stating how the BC Government's objectives for managing the province's forest resources will be met. It identifies the plan-holder's obligations for a five-year period. The Forest Development Unit is the spatially-mapped area of land within a Forest Stewardship Plan where specific forest practices obligations apply to specific forest licensees.

Historical finds of Coleophora serratella