Biological Sensitivity Mapping for Oil Spill Planning and Response, Quebec Region
The Planning for an Environmental Response (PIER) initiative falls under the umbrella of the Government of Canada's Oceans Protection Plan (OPP), whose goal is preserving marine ecosystems vulnerable to increased transportation and the development of the marine industry (https://pm.gc.ca/en/news/backgrounders/2016/11/07/canadas-oceans-protection-plan-preserving-and-restoring-canadas). The PIER was established in response to recommendations made in a 2013 report "A review of Canada's ship-source spill preparedness and response regime " by the Tanker Safety Expert Panel (https://tc.canada.ca/en/marine-transportation/marine-safety/tanker-safety-expert-panel). One of the recommendations calls on Fisheries and Oceans (DFO) to work with Environment and Climate Change Canada (ECCC) to collect and compile information on sensitive species and environments for each Canadian Coast Guard (CCG) response area and make it publicly available.
The PIERs’ main mandate is to acquire and update biological sensitivity data under its jurisdiction for preparation and response purposes in the event of an oil spill. With DFO-Science, PIER supports ECCC's National Environmental Emergencies Centre (NEEC) and the CCG in their preparations and responses through the sharing of data on biological sensitivities, the development of response tools and expert advice.
In this vein, DFO published an analysis in 2018 that aimed to identify the most vulnerable components of the St. Lawrence in order to prioritize them during data collection if gaps were identified (Desjardins et al. 2018). This exercise highlighted the vulnerability of several biological components and important data gaps, particularly in coastal areas. As a result of this finding, the Quebec region PIEI team embarked on a collaborative project with the Université du Québec à Rimouski (UQAR) to map eelgrass beds, tidal marshes and macroalgal beds. In consultation with other DFO-Science data producers, this team has also created datasets adapted for response purposes, notably regarding bivalves and marine mammals. These layers may be used for oil spill preparedness and response by DFO-Quebec Region's Environmental Incident Coordinator, NEEC and CCG. Several of them, deemed relevant in the first 72 hours following a spill, have been transmitted to the NEEC.
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Additional Info
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| Last Updated | October 20, 2025, 02:36 (UTC) |
| Created | October 20, 2025, 02:36 (UTC) |
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Domain / Topic
Domain or topic of the dataset being cataloged.
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Biota, Environment, Oceans |
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Title
Title for the Dataset.
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Biological Sensitivity Mapping for Oil Spill Planning and Response, Quebec Region |
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Description
A description of the dataset.
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The Planning for an Environmental Response (PIER) initiative falls under the umbrella of the Government of Canada's Oceans Protection Plan (OPP), whose goal is preserving marine ecosystems vulnerable to increased transportation and the development of the marine industry (https://pm.gc.ca/en/news/backgrounders/2016/11/07/canadas-oceans-protection-plan-preserving-and-restoring-canadas). The PIER was established in response to recommendations made in a 2013 report "A review of Canada's ship-source spill preparedness and response regime " by the Tanker Safety Expert Panel (https://tc.canada.ca/en/marine-transportation/marine-safety/tanker-safety-expert-panel). One of the recommendations calls on Fisheries and Oceans (DFO) to work with Environment and Climate Change Canada (ECCC) to collect and compile information on sensitive species and environments for each Canadian Coast Guard (CCG) response area and make it publicly available. The PIERs’ main mandate is to acquire and update biological sensitivity data under its jurisdiction for preparation and response purposes in the event of an oil spill. With DFO-Science, PIER supports ECCC's National Environmental Emergencies Centre (NEEC) and the CCG in their preparations and responses through the sharing of data on biological sensitivities, the development of response tools and expert advice. In this vein, DFO published an analysis in 2018 that aimed to identify the most vulnerable components of the St. Lawrence in order to prioritize them during data collection if gaps were identified (Desjardins et al. 2018). This exercise highlighted the vulnerability of several biological components and important data gaps, particularly in coastal areas. As a result of this finding, the Quebec region PIEI team embarked on a collaborative project with the Université du Québec à Rimouski (UQAR) to map eelgrass beds, tidal marshes and macroalgal beds. In consultation with other DFO-Science data producers, this team has also created datasets adapted for response purposes, notably regarding bivalves and marine mammals. These layers may be used for oil spill preparedness and response by DFO-Quebec Region's Environmental Incident Coordinator, NEEC and CCG. Several of them, deemed relevant in the first 72 hours following a spill, have been transmitted to the NEEC. |
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Format (CSV, XLS, TXT, PDF, etc)
File format of the dataset.
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Dataset size in megabytes.
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Metadata Identifier
Metadata identifier – can be used as the unique identifier for catalogue entry
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Published Date
Published date of the dataset.
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2022-01-01 |
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Start date of the data in the dataset.
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Time Period Data Span (end date)
End date of time data in the dataset.
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GeoSpatial Area Data Span
A spatial region or named place the dataset covers.
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Access category
Type of access granted for the dataset (open, closed, service, etc).
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License
License used to access the dataset.
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Open Government Licence - Canada |
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Limits on use
Limits on use of data.
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Location
Location of the dataset.
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https://open.canada.ca/data/en/dataset/d8a6c6fd-76cc-4d68-a949-c4d80eb2f296 |
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Data Service
Data service for accessing a dataset.
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Owner
Owner of the dataset.
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Fisheries and Oceans Canada | Pêches et Océans Canada |
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Contact Point
Who to contact regarding access?
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Government of Canada; Fisheries and Oceans Canada; Sciences/Scientific Advice, Information and Support Branch, [email protected] |
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Contact Point Email
The email to contact regarding access?
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Publisher
Publisher of the dataset.
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Publisher Email
Email of the publisher.
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[email protected] |
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Author
Author of the dataset.
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Author Email
Email of the author.
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Accessed At
Date the data and metadata was accessed.
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Identifier
Unique identifier for the dataset.
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Language
Language(s) of the dataset
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Link to dataset description
A URL to an external document describing the dataset.
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Persistent Identifier
Data is identified by a persistent identifier.
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Globally Unique Identifier
Data is identified by a persistent and globally unique identifier.
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Contains data about individuals
Does the data hold data about individuals?
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Contains data about identifiable individuals
Does the data hold identifiable data about individual?
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Contains Indigenous Data
Does the data hold data about Indigenous communities?
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Portal Type
Platform type of the source portal.
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Version
Version of the datatset
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None |
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Source
Source of the dataset.
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None |
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Version notes
Version notes about the dataset.
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Is version of another dataset
Link to dataset that it is a version of.
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Other versions
Link to datasets that are versions of it.
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Provenance Text
Provenance Text of the data.
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Provenance URL
Provenance URL of the data.
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Temporal resolution
Describes how granular the date/time data in the dataset is.
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GeoSpatial resolution in meters
Describes how granular (in meters) geospatial data is in the dataset.
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GeoSpatial resolution (in regions)
Describes how granular (in regions) geospatial data is in the dataset.
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Indigenous Community Permission
Who holds the Indigenous Community Permission. Who to contact regarding access to a dataset that has data about Indigenous communities.
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Community Permission
Community permission (who gave permission).
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The Indigenous communities the dataset is about
Indigenous communities from which data is derived.
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Number of data rows
If tabular dataset, total number of rows.
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Number of data columns
If tabular dataset, total number of unique columns.
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Number of data cells
If tabular dataset, total number of cells with data.
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Number of data relations
If RDF dataset, total number of triples.
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Number of entities
If RDF dataset, total number of entities.
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Number of data properties
If RDF dataset, total number of unique properties used by the triples.
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Data quality
Describes the quality of the data in the dataset.
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Metric for data quality
A metric used to measure the quality of the data, such as missing values or invalid formats.
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