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We have found 176 datasets for the keyword "biodiversité". You can continue exploring the search results in the list below.
Datasets: 105,252
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176 Datasets, Page 1 of 18
Biodiversity Risk
The data represents an assessment of biodiversity risk for the agricultural area of Alberta in 2002. Biodiversity risk refers to the loss of biological diversity, or the variety of plant and animal life in agricultural landscapes. This map, created in ArcGIS, tries to show where biodiversity could be threatened, such as in areas with significant habitat that coincide with areas of greater agricultural economic activity. Biodiversity is believed to affect the overall health of the environment.
Biodiversity of the Stimpson's surfclam hydraulic dredge survey in the St. Lawrence Estuary (2017)
A research survey on Stimpson's surfclam (Mactromeris polynyma) was conducted from June 15 to June 26 2017 in the Estuary of the St. Lawrence River on the Forestville deposit (Fishing Area 1A). The primary objective of this survey was to investigate the spatial distribution of pre-commercial (< 80 mm) and commercial (≥ 80 mm) sizes of Stimpson's surfclams as well as to assess the abundance and diversity of benthic species associated with the sandy habitat of the Stimpson's surfclam. Only benthic species data associated with Stimpson's surfclam habitat are presented in this dataset.Data were collected according to a systematic sampling design consisting of 77 stations, between 7 and 45 m depth. Stations were spaced 200 m apart and dispersed along a total of 18 transects perpendicular to the bathymetry. Transects were parallel and spaced 500 m apart. Specimens were collected using a hydraulic dredge of the "New England" type with a total length of 2.29 meters and a total width of 1.68 meters, of which 1.35 meters was knife width. The dredge was lined with a 19 millimeter mesh Vexar™ to harvest small individuals. The hauls were made at a speed of 0.2-0.3 knots for a duration of 2 to 3 minutes. Start and end positions were recorded to calculate the distance traveled at each tow using the geosphere library in R. The average tow distance was approximately 25 m. The area covered at each stroke was the product of the width of the dredge blade and the distance.The three files provided (DarwinCore format) are complementary and are linked by the "eventID" key. The "event_information" file includes generic event information, including date and location. The "additional_information_event_and_occurrence" file includes sample size, sampling protocol and sampling effort, among others. The "taxon_occurrence" file includes the taxonomy of the species observed, identified to the species or lowest possible taxonomic level. For abundance and biomass estimates, contact Virginie Roy (virginie.roy@dfo-mpo.gc.ca).For quality controls, all taxonomic names were checked against the World Register of Marine Species (WoRMS) to match recognized standards. The WoRMS match was placed in the "scientificNameID" field of the occurrence file. Special cases were noted in "identificationRemarks" and selected specimens were confirmed using field photos. Data quality checks were performed using the R obistools and worrms libraries. All sampling locations were spatially validated.
Development of a coastal species characterization approach using environmental DNA (eDNA) using the marker COI
Species characterization by environmental DNA (eDNA) is a method that allows the use of DNA released into the environment by organisms from various sources (secretions, faeces, gametes, tissues, etc.). It is a complementary tool to standard sampling methods for the identification of biodiversity. This project provides a list of invertebrates species whose DNA has been detected in water samples collected at 2018 using the marker COI.The surveys were carried out in the summer of 2018 from August 11 to 14, between Forestville and Godbout (Haute-Côte-Nord). Sampling was carried out between 9-52 meters depth in 40 stations with one sample par station. Two liters of water were filtered through a 1.2 µm fiberglass filter. DNA extractions were performed with the DNeasy Blood and Tissue extraction kit (Qiagen). Negative field, extraction and PCR controls were added at the different stages of the protocol. Libraries at the COI locus were prepared by Genome Quebec and sequenced on an Illumina MiSeq PE250 system. The bioinformatics analysis of the sequences obtained was carried out using an in-house analysis pipeline as reported in Bourret et al. 2022. A first step made it possible to obtain a molecular operational taxonomic unit table (MOTU) using the cutadapt software for the removal of the adapters and the DADA2 R package for the filtration, fusion, chimera removal and data compilation. The MOTUs table was subsequently corrected by taking into account the negative controls, where the number of observations in the latter was removed from the linked samples. Singleton MOTUs have also been removed. Finally, the taxonomic assignments were carried out on the MOTUs using the IDTAXA classifier (present in the DECIPHIER R package) using a training set trained on the COI reference bank for Golf St-Laurent (GSL-rl v1.0, https://github.com/GenomicsMLI-DFO/MLI_GSL-rl) and a threshold of 40. Detections with an “Unreliable due to gaps” category were reported at the genus level only.The file provided includes generic activity information, including site, station name, date, marker type, assignment types used for taxa identification, and a list of taxa or species. The list of taxa has been verified by a biodiversity expert from the Maurice-Lamontagne Institute.This project was funded by Fisheries and Oceans Canada's Coastal Environmental Baseline Data Program under the Oceans Protection Plan. This initiative aims to acquire baseline environmental data that contributes to the characterization of significant coastal areas and supports evidence-based assessments and management decisions to preserve marine ecosystems.Data are also available on SLGO platform : https://doi.org/10.26071/ogsl-cd4c205b-f63b
MBON Pole to Pole: Sandy beach biodiversity of southwest New Brunswick, Canada
The Marine Biodiversity Observation Network Pole to Pole (MBON P2P) effort seeks to develop a framework for the collection, use and sharing of marine biodiversity data in a coordinated, standardized manner leveraging on existing infrastructure managed by the Global Ocean Observing System (GOOS; IOC-UNESCO), the GEO Biodiversity Observation Network (GEO BON), and the Ocean Biogeographic Information System (OBIS). The MBON Pole to Pole aims to become a key resource for decision-making and management of living resource across countries in the Americas for reporting requirements under the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), Aichi Targets of the Convention of Biological Diversity (CBD), and the UN 2030 Agenda for Sustainable Development Goals (SDGs).This collection corresponds to the species registered on sandy beaches of the Musquash Harbour, Mispec Bay, and New River Beach, New Brunswick, Canada, using the MBON P2P sampling protocol for sandy beaches, with funding from the Government of Canada's Coastal Environmental Baseline Program.Citation: Reinhart B, Jonah L (2025). MBON POLE TO POLE: SANDY BEACH BIODIVERSITY OF SOUTHWEST NEW BRUNSWICK, CANADA. Version 1.7. Caribbean OBIS Node. Samplingevent dataset. https://ipt.iobis.org/mbon/resource?r=sandybeachesbayoffundynb&v=1.7
Old Growth Management Areas - Non Legal - Current
This 'Current' spatial data layer is publicly accessible, contains the most current Non-Legal Old Growth Management Area (OGMA) polygons and excludes any sensitive information. This data represents spatially defined areas of old growth forest that are identified during landscape unit planning or an operational planning process. Forest licensees are not required to follow direction provided by non-legal OGMAs when preparing FSPs, and may choose to manage required old growth biodiversity targets in other ways. OGMAs, in combination with other areas where forestry development is prevented or constrained, are used to achieve biodiversity targets. Please see the Additional Information and Object Description Comments below.
MBON Pole to Pole: Rocky shore biodiversity of Musquash Harbour, Passamaquoddy Bay and Mispec Bay
The Marine Biodiversity Observation Network Pole to Pole (MBON P2P) effort seeks to develop a framework for the collection, use and sharing of marine biodiversity data in a coordinated, standardized manner leveraging on existing infrastructure managed by the Global Ocean Observing System (GOOS; IOC-UNESCO), the GEO Biodiversity Observation Network (GEO BON), and the Ocean Biogeographic Information System (OBIS). The MBON Pole to Pole aims to become a key resource for decision-making and management of living resource across countries in the Americas for reporting requirements under the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), Aichi Targets of the Convention of Biological Diversity (CBD), and the UN 2030 Agenda for Sustainable Development Goals (SDGs).This collection corresponds to the species registered on rocky shores of the Musquash Harbour, Passamaquoddy Bay and Mispec Bay, New Brunswick, Canada, using the MBON P2P sampling protocol for rocky shores, with funding from the Government of Canada's Coastal Environmental Baseline Program.Citation: Reinhart B, Cooper A, Nason R, Jonah L (2025). MBON POLE TO POLE: ROCKY SHORE BIODIVERSITY OF MUSQUASH HARBOUR, PASSAMAQUODDY BAY AND MISPEC BAY. Version 1.7. Caribbean OBIS Node. Samplingevent dataset. https://ipt.iobis.org/mbon/resource?r=rockyshoresbayoffundynb&v=1.7
Landscape Units of British Columbia - Current
Landscape Units are spatially identified areas of land and/or water used for long-term planning of resource management activities. Landscape units are important for designing strategies and objectives to maintain landscape level biodiversity and for managing other forest resources. Landscape units are also used to initiate landscape unit plans, which provide direction on biodiversity, old growth forest retention, wildlife habitat maintenance and timber harvesting. LUs may also be used as planning zones for other stakeholders in addition to forest licensees and MOFR. This spatial view was created based on the selection from the layer LANDSCAPE UNIT SP, where the DATE OF RETIREMENT is null. Therefore, only current LU shapes are included in this layer
Land cover mapping of the St. Lawrence Lowlands, circa 2014
Since 1988, the governments of Canada and Quebec have been working together to conserve, restore, protect and develop the St. Lawrence River under the St. Lawrence Action Plan (SLAP). One of the projects identified under the theme of biodiversity conservation is the development of an integrated plan for the conservation of the natural environments and biodiversity of the St. Lawrence River.The identification of priority sites for conservation has been the first step of this planning exercise. Conservation planning of natural environments requires a reliable, accurate and up-to-date image of the spatial distribution of ecosystems in the study area. In order to produce an Atlas of Priority Sites for Conservation in the St. Lawrence Lowlands, an updated cartography of the land cover of this vast territory was undertaken.This project required obtaining reliable information on the natural environments of the St. Lawrence Lowlands. Although several land cover mapping projects have been conducted for specific types of habitats, it was particularly important to obtain a homogeneous product that would cover the entire territory and that would provide the most detailed information on its various thematic components: agricultural, aquatic, human-modified and forest environments, wetlands as well as old fields and bare ground. The methodology used to produce the land cover mapping of the St. Lawrence Lowlands thus relied mainly on combining and enhancing the best existing products for each theme. This project was made in collaboration with MDDELCC as part of the St. Lawrence Action Plan (SLAP).
eDNA metabarcoding enriches traditional trawl survey data for monitoring biodiversity in the marine environment
Marine Protected Areas require comprehensive monitoring to ensure objectives are achieved; however, monitoring natural ecosystems at scale is challenged by the biodiversity it aims to measure. Environmental DNA (eDNA) metabarcoding holds promise to address this monitoring challenge. We conducted paired sampling at 54 sites for fish and invertebrate assemblages in the Northwest Atlantic using groundfish trawls and eDNA metabarcoding of benthic seawater using four genetic markers (12S rRNA, 16S rRNA, 18S rRNA, and CO1). Compared to trawling, eDNA detected similar patterns of species turnover, larger estimates of gamma diversity, and smaller estimates of alpha diversity. A total of 63.6% (42/66) of fish species captured by trawling were detected by eDNA, along with an additional 26 species. Of the 24 missed detections by eDNA, 12 were inevitable as they lacked reference sequences. Excluding taxa assigned to higher than species level and those without a species name, 23.6% (17/72) of invertebrate species captured by trawling were detected by CO1, which detected an additional 98 species. We demonstrate that eDNA is capable of detecting patterns of community assemblage and species turnover in an offshore environment, emphasizing its strong potential for a non-invasive, comprehensive, and scalable tool for biodiversity monitoring supporting marine conservation programmes.Cite this data as: Jeffery, N., Rubidge, E., Abbott, C., Westfall, K., Stanley, R. (2024): Data of: eDNA metabarcoding enriches traditional trawl survey data for monitoring biodiversity in the marine environment.Published: August 2024. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/43a91ba7-8025-4330-88db-db14022d729d
Maritimes Coastal Biodiversity Monitoring Program – Beach Seining
Monitoring programs are an important component of Marine Protected Area (MPA) management, providing requisite information on the state of, and changes in, protected ecosystems. Monitoring is required to gauge the efficacy of MPAs towards their conservation objectives and provides information needed to evaluate the benefits provided to biodiversity from restricted access. However, in Nova Scotia’s coastal zone, there is a lack of baseline data, including fish diversity and community structure in macrophyte beds, which makes monitoring intractable. In 2017, the Eastern Shore Islands was identified as a coastal Area of Interest (AOI) for the potential establishment of an MPA. In 2018 an overview was conducted, detailing the spatial and temporal ecological attributes of the AOI. This information revealed a unique coastal ecosystem associated with a dense archipelago and relatively natural seascape. The abundance of plant and algal biogenic habitats within the area was assumed to host a diversity of juvenile fish species. The primary objective of this project is to begin development of a long-term biodiversity monitoring program in the Eastern Shore Islands and other coastal Areas of Interest for conservation planning. We propose implementing this program with the use of direct (beach seines, scuba diving, and stable isotope sampling) and indirect (environmental DNA - eDNA) sampling. Environmental DNA (eDNA) is a useful tool to examine marine biodiversity in a non-invasive way, on a small spatial scale. eDNA can be easily collected and filtered and is becoming increasingly cost efficient to sequence and may be a useful marine protected area monitoring tool. While eDNA generally yields comparable results to traditional sampling techniques in terms of biodiversity captured, little is known on how eDNA signals fluctuate across years (or even days to weeks). We will compare species detections using eDNA metabarcoding to visual surveys (scuba and seine nets) to census eelgrass beds across the coastal zone, providing a baseline and time series of species diversity on which to base long-term monitoring. This project will generate inventories of eelgrass bed locations, and fish and invertebrate diversity within eelgrass beds. We additionally collect fish length distribution data to examine seasonal and inter-annual trends in size structure over time. The data generated from direct and indirect sampling will provide a comprehensive and ongoing catalog of species diversity and community structure in coastal eelgrass beds, as well as best-practices for sampling eDNA in the coastal environment.Cite this data as: Jeffery, N.W., Pettitt-Wade, H., Van Wyngaarden, M., and Stanley, R.R.E. Maritimes Coastal Biodiversity Monitoring Program – Beach Seining.Published: December 2023. Coastal Ecosystems Science Division, Maritimes region, Fisheries and Oceans Canada, Dartmouth NS. https://open.canada.ca/data/en/dataset/dbbcb23a-d018-4b70-b8ec-89997aded770
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