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.

The Coastal Oceanography and Ecosystem Research section (DFO Science) reviewed the presence of Cod in the Population Ecology Division (DFO Science) Ecosystem Survey trawls to describe the likelihood of presence. The survey consists of a stratified random design using a bottom trawl. This layer was created for consideration in oil spill response planning.A version of this dataset was created for the National Environmental Emergency Center (NEEC) following their data model and is available for download in the Resources section.Cite this data as: Lazin, G., Hamer, A.,Corrigan, S., Bower, B., and Harvey, C. Data of: Likelihood of presence of Atlantic Cod in Area Response Planning pilot areas. Published: June 2018. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B. https://open.canada.ca/data/en/dataset/af2bf6c0-481d-4445-bbc6-7a785d2a9aa9

The Coastal Oceanography and Ecosystem Research section (DFO Science) reviewed the presence of Lobster in the Population Ecology Division (DFO Science) Ecosystem Survey trawls to describe the likelihood of presence. The survey consists of a stratified random design using a bottom trawl. Lobsters are found in few trawls in the Bay of Fundy and Port Hawkesbury Area Response Plan regions, however Lobsters are landed in nearshore areas. Therefore, lobsters are described as being likely present throughout the ARP. This layer was created for consideration in oil spill response planning.A version of this dataset was created for the National Environmental Emergency Center (NEEC) following their data model and is available for download in the Resources section.Cite this data as: Lazin, G., Hamer, A.,Corrigan, S., Bower, B., and Harvey, C. Data of: Likelihood of presence of American Lobster in Area Response Planning pilot areas. Published: June 2018. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B. https://open.canada.ca/data/en/dataset/47bf4555-ce3c-492f-a367-a6eab1862970

Appropriately responding to a marine pollution event, especially hydrocarbon spills, often requires detailed knowledge of local habitat and environmental features. Access to high resolution habitat profiles can support effective spill response plans, informing discussions on protection priorities or expediated remediation. However, marine habitat composition data for a given area is often lacking due to the high cost and effort of conducting such surveys across the vast shorelines of Canada. The purpose of this study was to develop methodologies for conducting rapid and affordable habitat compositions in the marine environment via drone aerial photography; an emerging technology for conducting high resolution surveys. We used the Musquash Marine Protected Area (MPA; Musquash, NB, Canada) as a model system as it contains a diverse range of habitat types, is a region of conservation concern in Atlantic Canada, and is in close proximity to oil and gas handling facilities and vessel traffic. The MPA consists of a tidal river that outflows into the Bay of Fundy. Using Geographic Information System (GIS) software, we subdivided the MPA into several transects (N =61) that were used to generate flight plans for a Remotely Piloted Aircraft System (RPAS; DJI Mavic 3 Enterprise, DJI ). The RPAS was flown (6 m s-1) at an altitude of 100m (Above ground level) taking images with side (70%) and front (80%) overlap. Resulting images were then compiled as an orthomosaic map using Pix4Dmatic software. These data will be used to inform marine spill response planning in the region, to support marine planning and conservation, and Marine Protected Area (MPA) monitoring efforts as well as develop further methodological approaches for conducting RPAS-based habitat surveys in other coastal systems within Atlantic Canada. Cite this data as: Lawrence MJ, Coates PJ, Matheson K, Hamer A. Characterisation of intertidal habitat types in the Musquash Marine Protected Area using aerial drone photography. Published November 2025. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B.

This dataset was designed for Environment and Climate Change Canada's (ECCC) National Environmental Emergencies Center (NEEC) for oil spill preparedness and response. The polygons from this layer come from the coastal ecosystems geodatabase as part of the Mapping of coastal ecosystems of the Estuary and Gulf of St. Lawrence project. This layer represents semi-vegetated (25-75%) and vegetated (75-100%) zones of which marsh vegetation is the dominant. The study area includes all of the estuarine and maritime coasts of Quebec, with the exception of certain sectors, including most of the Lower North Shore and Anticosti Island, with the exception of villages of Kegaska, la Romaine, Chevery, Blanc-Sablon and Port-Menier. Some islands off the estuary and gulf coasts are part of the region covered, such as Île d'Orléans, Isle-aux-Coudres, Île Verte and Île Bonaventure.The mapping of coastal ecosystems was carried out jointly by the Laboratory for Dynamics and Integrated Coastal Zone Management (LDGIZC) of the University of Quebec at Rimouski as part of the Coastal Resilience Project (https: //ldgizc.uqar.ca/Web/projets/projet-resilience-cotiere) funded by the MELCC; and by the Fisheries and Oceans Canada team, as part of its Integrated marine response planning (IMRP) component of the Oceans Protection Plan (OPP), with the objective of updating the Marine Oil Spill Preparedness and Response Regime of Canada. The master geodatabase of coastal ecosystems is hosted and distributed by UQAR on their SIGEC-Web mapping platform: https://ldgizc.uqar.ca/Web/sigecwebThe characterization of marshes was mainly carried out using photo-interpretation of RVBI aerial photos acquired by DFO (2015-2020) and oblique photos taken by helicopter acquired by UQAR in 2017. This dataset also includes the information from validation stations visited by UQAR (2018-2020), used to validate and refine the photo-interpretation.

The main objective of this sampling program was to assess the effects of the spill on the toxicity of surface water collected during the spill by comparing them with the results of water collected prior to the discharge.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

With the changing climate conditions, marine traffic along Canada’s coastal regions has increased over the past few decades and the need to improve our state of preparedness for oil-spill-related emergencies is critical. Baseline coastal information, such as shoreline form, substrate, and vegetation type, is required for prioritizing operations, coordinating onsite spill response activities (i.e., Shoreline Cleanup Assessment Technique [SCAT]), and providing information for wildlife and ecosystem management. Between 2011 and 2016, georeferenced high-definition videography and photos were collected for various study sites along the east coast. The study areas include Labrador, Bay of Fundy and Chedabucto Bay in Atlantic Canada.Data was collected during ice-free and low tide conditions (where applicable) between July and September. Low-altitude helicopter surveys were conducted at each study site to capture video of the shoreline characteristics. In addition to acquiring videography, ground-based observations were recorded in several locations for validation.Shoreline segmentation was then carried out by manual interpretation of the oblique videography and the photos aided by ancillary data. This involved splitting and classifying the shoreline vectors based on homogeneity of the upper intertidal zone. Detailed geomorphological information (i.e., shoreline type, substrate, slope, height, accessibility etc.) describing the upper intertidal, lower intertidal, supratidal and backshore zones was extracted from the video and entered into a geospatial database using a customized data collection form. In addition, biological characteristics like biobands, water features, fauna, human use etc. observed along the coast were recorded.The data was also validated through ground observations (when available) and a second interpreter QA (quality analysis) was performed on each dataset to ensure high quality and consistency. The final dataset contains segments ranging in length from 150 metres to 2500 metres. In total, from 2011 to 2016, within the 3 study sites, about 1,850 km of shoreline were mapped.

Macroalgae dominated areas with a vegetated cover above 25%, located in the coastal zone of the Estuary and the Gulf of St. Lawrence (Quebec)This dataset was designed for Environment and Climate Change Canada's (ECCC) National Environmental Emergencies Center (NEEC) for oil spill preparedness and response. The polygons of this layer were selected from the surface geodatabase of coastal ecosystems from the UQAR-MPO project Mapping coastal ecosystems of the Estuary and Gulf of St. Lawrence. Are represented in this dataset exclusively the polygons whose plant dominance corresponds to a class of macroalgae and presenting a semi-vegetated (25-75%) or vegetated (75-100%) cover. The study area includes all of the estuarine and maritime coasts of Quebec, with the exception of certain sectors, including most of the Lower North Shore and Anticosti Island, with the exception of villages of Kegaska, la Romaine, Chevery, Blanc-Sablon and Port-Menier. Some islands off the estuary and gulf coasts are part of the region covered, such as Île d'Orléans, Isle-aux-Coudres, Île Verte and Île Bonaventure.The mapping of coastal ecosystems was carried out jointly by the Laboratory for Dynamics and Integrated Coastal Zone Management (LDGIZC) of the University of Quebec at Rimouski as part of the Coastal Resilience Project (https: //ldgizc.uqar.ca/Web/projets/projet-resilience-cotiere) funded by the MELCC; and by the Fisheries and Oceans Canada team, as part of its Integrated marine response planning (IMRP) component of the Oceans Protection Plan (OPP),with the objective of updating the Marine Oil Spill Preparedness and Response Regime of Canada. The master geodatabase of coastal ecosystems is hosted and distributed by UQAR on their SIGEC-Web mapping platform: https://ldgizc.uqar.ca/Web/sigecwebThe macroalgae characterization was mainly carried out from the photo-interpretation of RGBI aerial photos acquired by the DFO (2015-2022) and oblique helicopter photos acquired by UQAR in 2017. Data from 3155 sampling stations, conducted aboard small boats during DFO field campaigns (2017-2023) were used to detail the nature of algal communities and validate the photo-interpretation.Credits © UQAR-MPO (2025, Laboratoire de dynamique et de gestion intégrée des zones côtières, Pêches et Océans Canada)RéférenceProvencher-Nolet, L., Paquette, L., Pitre, L.D., Grégoire, B. and Desjardins, C. 2024. Cartographie des macrophytes estuariens et marins du Québec. Rapp. Tech. Can. Sci. halieut. Aquat. 0000 : v + 99 p.Grégoire, B., Pitre, L.D., Provencher-Nolet, L., Paquette, L. and Desjardins, C. 2024. Distribution d’organismes marins de la zone côtière peu profonde du Québec recensés par imagerie sous-marine de 2017 à 2021. Rapp. tech. can. sci. halieut. aquat. 0000 : v + 78 p.Grégoire, B. 2022. Biodiversité du relevé côtier Planification pour une intervention environnementale intégrée dans l’estuaire et le golfe du Saint-Laurent (2017–2021). Observatoire global du Saint-Laurent. [Jeu de données]Jobin, A., Marquis, G., Provencher-Nolet, L., Gabaj Castrillo. M. J., Trubiano C., Drouet, M., Eustache-Létourneau, D., Drejza, S. Fraser, C. Marie, G. et P. Bernatchez (2021) Cartographie des écosystèmes côtiers du Québec maritime — Rapport méthodologique. Chaire de recherche en géoscience côtière, Laboratoire de dynamique et de gestion intégrée des zones côtières, Université du Québec à Rimouski. Rapport remis au ministère de l’Environnement et de la Lutte contre les changements climatiques, septembre 2021, 98 p.

With the changing climate conditions, marine traffic along Canada’s coastal regions has increased over the past couple of decades and the need to improve our state of preparedness for oil-spill-related emergencies is critical. Baseline coastal information, such as shoreline form, substrate, and vegetation type, is required for prioritizing operations, coordinating onsite spill response activities (i.e. Shoreline Cleanup Assessment Technique [SCAT]), and providing information for wildlife and ecosystem management. Between 2013 and 2019, georeferenced high-definition videography and photos were collected for various study sites along the west coast. The study areas include the mainland, inlets, channels and islands along the BC coast starting from Kitimat in the north to Quadra Island in the south, including Haida Gwaii and North Vancouver Island in the west and Burrard Inlet in the extreme south.Data was collected during low tide conditions (where applicable) between July and September. Low-altitude helicopter surveys were conducted at each of the study site to capture video of the shoreline characteristics. In addition to acquiring videography, ground-based observations were recorded in several locations for validation.Shoreline segmentation was then carried out by manual interpretation of the oblique videography and the photos aided by ancillary data. This involved splitting and classifying the shoreline vectors based on homogeneity of the upper intertidal zone. Detailed geomorphological information (i.e. shoreline type, substrate, slope, height, accessibility etc.) describing the upper intertidal, lower intertidal, supratidal and backshore zones was extracted from the video and entered into a geospatial database using a customized data collection form. In addition, biological characteristics like biobands, water features, fauna, human use etc. observed along the coast were recorded.The data was also validated through ground samples (when available) and a second interpreter QA (quality analysis) was performed on the dataset to ensure high quality and consistency. The final dataset contains segments ranging in length from 150 metres (45 metres for study areas surveyed in 2018-19) to 2500 metres. In total, from 2013 to 2019, about 15,000 km of shoreline were segmented.

With the changing climate conditions, marine traffic along Canada’s coastal regions has increased over the past couple of decades and the need to improve our state of preparedness for oil-spill-related emergencies is critical. Baseline coastal information, such as shoreline form, substrate, and vegetation type, is required for prioritizing operations, coordinating onsite spill response activities (i.e. Shoreline Cleanup Assessment Technique [SCAT]), and providing information for wildlife and ecosystem management. Between 2010 and 2016, georeferenced high-definition videography and photos were collected for various study sites along the north coast of Canada. The study areas include Beaufort Sea, Mackenzie Delta channels and Banks Island in the western Canadian Arctic and James Bay, Hudson Bay, Nunavik, Resolute Bay, Victoria Strait, Baffin Island and Coronation Gulf in the eastern Canadian Arctic.Data was collected during ice-free and low tide conditions (where applicable) between July and September. Low-altitude helicopter surveys were conducted at each study site to capture video of the shoreline characteristics. In addition to acquiring videography, ground-based observations were recorded in several locations for validation.Shoreline segmentation was then carried out by manual interpretation of the oblique videography and the photos aided by ancillary data. This involved splitting and classifying the shoreline vectors based on homogeneity of the upper intertidal zone. Detailed geomorphological information (i.e. shoreline type, substrate, slope, height, accessibility etc.) describing the upper intertidal, lower intertidal, supratidal and backshore zones was extracted from the video and entered into a geospatial database using a customized data collection form. In addition, biological characteristics like biobands, water features, fauna, human use etc. observed along the coast were recorded.The data was also validated through ground observations (when available) and a second interpreter QA (quality analysis) was performed on each dataset (excluding Nunavik) to ensure high quality and consistency. The final dataset contains segments ranging in length from 150 metres to 2500 metres. In total, from 2010 to 2016, within the 8 study sites, about 16,800 km of shoreline were segmented.