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We have found 57 datasets for the keyword " biotope". You can continue exploring the search results in the list below.
Datasets: 106,156
Contributors: 42
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57 Datasets, Page 1 of 6
Shorezone Biobanding Polygons
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.
Biologic and Ecologic
BiologicEcologic ISO Feature Dataset symbolization and publication. September 5, 2017.
Shorezone Biobanding Lines
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 Biomass (2022)
This dataset provides wall-to-wall maps of forest structure across Canada's 650 million hectare forested ecosystems for the year 2022, generated at a spatial resolution of 30 m. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Structure estimates include key attributes such as canopy height, canopy cover, and aboveground biomass, derived using a combination of airborne lidar and Landsat-based spectral composites. Structure models were trained using the - lidar-plot framework - (Wulder et al. 2012), which integrates co-located airborne lidar data and ground plot measurements with Landsat time-series composites (Hermosilla et al. 2016). A Nearest Neighbour imputation approach was applied to estimate structural attributes across the full extent of Canada's forested area. These nationally consistent products are intended to support strategic-level forest monitoring and assessment and are not designed for operational forest management.For further details on the methods, accuracy assessment, and source data, see Matasci et al. (2018).Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Bolton, D.K., Tompalski, P., Bater, C.W., 2018. 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. https://doi.org/10.1016/j.rse.2018.07.024 (Matasci et al. 2018)
Disease Investigations data
Table containing information relevant to animal disease investigations in Manitoba from 2012 to present.This table contains information relevant to animal disease investigations in Manitoba from 2012 to present, conducted by the Chief Veterinary Office (CVO). Information includes year, number of sites, number of linked sites, animal species, disease types and results. Updated on a weekly basis. It is important that users are aware of the following caveats when reviewing data presented in the Animal Disease Investigations Dashboard: 1. Each investigation can have one or more cases involved depending on the number of herds or animals exposed. Not all disease investigations are handled the same due to a partnership approach. Diseases can be detected via surveillance, ad hoc reporting, or through other programs. 2. Rabies is a separate program. Please see Manitoba's Provincial Rabies Management Program for data related to Rabies Surveillance.3. Certain zoonotic diseases, such as salmonella or influenza, are also captured in more detail through other means. The total occurrence of a zoonotic disease represented in this dashboard reflects occurrences where risks or exposures were deemed significant enough to warrant further investigation. 4. Historically, One Health Investigations that were predominantly focused on Public Health issues rather than Animal Health concerns were not captured in this system and will be underrepresented here. Fields included ( Alias (Field Name): Field description.) Year (Year): Year of the disease investigation Number of Sites (Number_of_Sites): Number of investigation sites Number of Linked Sites (Number_of_Linked_Sites): Number of sites linked to investigation sites Species/Class (Species__Class): Group of animal species Disease Type (Disease_Type): The type of disease that is being investigated Result (Result): The outcome (positive/negative) for the corresponding animal disease investigation
CABIN Canadian Aquatic Biomonitoring Network
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.
Georgia Basin Ecosystem Initiative Boundary - Polygon
The Georgia Basin Boundary dataset displays the extent of the Georgia Basin Ecosystem Initiative undertaken by the federal, provincial, and municipal governments. The objectives of the project are to support initiatives for clean air, clean water, habitat and species protection, and improved environmental decision-making in the Georgia Basin. The dataset consists of both a polygon layer and line layer
Bioterrain Mapping (TBT) Detailed Polygons with Short Attribute Table Spatial View
Bioterrain (TBT) contains polygons with key and amalgamated (concatenated) attributes derived from the RISC (Resource Inventory Standards Committee) standard attributes. TBT divides the landscape into units using the Terrain Classification System for British Columbia and ecological criteria. Polygon attributes include (but are not limited to) surficial material, surface expression, geomorphological processes, drainage class and aspect. TBT methods include manual air photo interpretation supported by selective field checking. Bioterrain mapping is integral to ecosystem mapping and its derivative products. This layer is derived from the STE_TEI_ATTRIBUTE_POLYS_SP layer by filtering on the PROJECT_TYPE attribute. Project types include: TEM, TEMNSS, TEMPRE, TEMSEI, TEMSET, TEMTSM, TBS, TBT, TEMWHR, TEMSDM, TEMPRW, and TEMSEW. Current version: v11 (published on 2024-10-03) Previous versions: v10 (published on 2023-11-14), v9 (published on 2023-03-01), v8 (published on 2016-09-01)
Zooplankton biomass at the Atlantic Zone Monitoring Program (AZMP)-Quebec’s stations
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.
Integrating Gut Microbiota and Population Genomics in White Hake (Urophycis tenuis): Supporting Data
PURPOSE:The purpose of this work was to determine (1) how the population genomic structure relates to gut microbiota composition of White Hake (Urophycis tenuis), and (2) whether microbiota community variation provides complementary insights into population structure of this species in eastern Canada.DESCRIPTION:Integrating host-associated microbiota with genomic approaches offers an opportunity to better understand the multiple biological dimensions shaping population structure in marine fishes. A clear understanding of population structure and dynamics is essential for informed fisheries management and conservation decisions; however, while genomic approaches have greatly improved our ability to delineate biological populations, they provide only a partial representation of biological structure, as patterns of differentiation reflect both historical divergence and contemporary ecological conditions. Host-associated microbiota can influence population-level ecological processes by contributing functional, potentially heritable variation that shapes host phenotype and fitness.In this study, we combined genotyping-by-sequencing with 16S rRNA gene amplicon sequencing to examine how population genomic structure relates to gut microbiota composition and to evaluate whether microbiota community variation provides complementary insights into population structure in White Hake (Urophycis tenuis) in eastern Canada. Genomic analyses identified two populations with greater spatial overlap than previously reported. Variation partitioning revealed that host genetics explained a negligible proportion of microbiota variation compared to environmental factors and fish length, suggesting that ontogenetic shifts in habitat use and resource acquisition influence gut microbiota composition. Several taxa were differentially abundant among fish length categories used as a proxy for diet, including taxa with chitin-degrading potential such as Photobacterium and Lachnospirales, which were enriched in smaller fish known to consume a crustacean-dominated diet. Together, these results indicate that gut microbiota composition in White Hake primarily reflects ecological and life-history processes rather than host population structure. PARAMETERS COLLECTED:Environmental parameters were also collected at most sampling sites, including depth, water temperature, oxygen and salinity levels.PHYSICAL SAMPLE DETAILS:Fin samples were collected to characterize the fish genotypes. Intestine (rectum) samples were collected to study fish gut microbiome.SAMPLING METHODS:In 2022 and 2023, White Hake were sampled during Fisheries and Oceans Canada (DFO) annual bottom trawl ecosystem monitoring surveys.USE LIMITATION:To ensure scientific integrity and appropriate use of the data, we would encourage you to contact the data custodian.
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