Home /Search
Search datasets
We have found 228 datasets for the keyword "cumulative impacts". You can continue exploring the search results in the list below.
Datasets: 104,589
Contributors: 42
Results
228 Datasets, Page 1 of 23
Cumulative impacts from anthropogenic activities and stressors on marine ecosystems in Pacific Canada
Fisheries and Oceans Canada has conducted a cumulative human impact mapping analysis for Pacific Canada to support ongoing Marine Spatial Planning. Cumulative impact mapping (CIM) combines spatial information on human activities, habitats, and a matrix of vulnerability weights into an intuitive relative ‘cumulative impact score’ that shows where cumulative human impacts are greatest and least. To map cumulative impacts, a recently developed ecosystem vulnerability assessment for Pacific Canadian waters (Murray et al. 2022) was combined with spatial information on thirty-eight (38) different habitat types and forty-five (45) human activities following the methodology from Halpern et al.(2008) and Murray et al. (2015). The cumulative impact map is provided in a 1x1 km grid used for oceans management by Fisheries and Oceans Canada. For further information, please contact the data provider.
Cumulative human impact maps for the Bay of Fundy and Scotian Shelf
DFO Maritimes Region has conducted a cumulative human impact mapping analysis for the Scotian Shelf-Bay of Fundy management area to support ongoing Marine Spatial Planning initiatives (Murphy et al. 2024). Cumulative human impact mapping (CIM) combines spatial information on human activities and habitats with a matrix of vulnerability weights, into an intuitive relative ‘cumulative impact score’ that shows where cumulative human impacts are greatest and least. To map cumulative impacts in DFO’s Maritimes Region, a recently developed ecosystem vulnerability assessment for Atlantic Canadian waters (Murray et al. 2022) was combined with spatial information on 21 different habitat types and 45 human activities across five different sectors (climate change, land-based, marine-based, coastal, commercial fishing) following the methodology from Halpern et al. (2008). An uncertainty analysis of the cumulative impact map was conducted to assess the robustness of results and identify hot and cold spots of cumulative impacts. This dataset provides: 1) cumulative impact maps for the DFO Maritimes Region at 1 km2 resolution: a total cumulative impact map (i.e. including all 45 human activities), as well as cumulative impact maps for each of the five sectors, 2) a layer that identifies which grid cells are considered hot and cold spots of cumulative human impacts, and 3) the habitat layers included in the CIM.For further information concerning specifics of the maps and methods see Murphy et al. (2024) or contact the data provider. References:Halpern, B.S., Walbridge, S., Selkoe, K.A., Kappel, C.V., Micheli, F., D'Agrosa, C., Bruno, J.F., Casey, K.S., Ebert, C., Fox, H.E., Fujita, R., Heinemann, D., Lenihan, H.S., Madin, E.M.P., Perry, M.T., Selig, E.R., Spalding, M., Steneck, R., and Watson, R. 2008. A Global Map of Human Impact on Marine Ecosystems. Science. 319(5865): 948-952. doi:10.1126/science.1149345.Murray, C.C., Kelly, N.E., Nelson, J.C., Murphy, G.E.P., and Agbayani, S. 2022. Cumulative impact mapping and vulnerability of Canadian marine ecosystems to anthropogenic activities and stressors. DFO Can. Sci. Advis. Sec. Res. Doc. 2022/XXX. vi. + 52 p.Murphy, G.E.P., Stock, A., and Kelly, N.E. 2024 (in press). From land to deep sea: A continuum of cumulative human impacts on marine habitats in Atlantic Canada. Ecosphere.Cite this data as: Murphy, Grace; Kelly, Noreen (2023) Cumulative human impact maps for the Bay of Fundy and Scotian Shelf. Published September 2023. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/37b59b8b-1c1c-4869-802f-c09571cc984b
Cumulative Effects of Marine Shipping - Pilot areas
Launched in 2017, the Cumulative Effects of Marine Shipping (CEMS) initiative is part of Canada’s $1.5 billion Oceans Protection Plan, which is providing economic opportunities to Canadians today, while protecting our coasts and waterways for future generations. The Cumulative Effects of Marine Shipping initiative is another way that the Government of Canada is protecting our coasts and waterways.https://tc.canada.ca/en/marine-transportation/marine-pollution-environmental-response/cumulative-effects-marine-shippingAs part of this initiative, Transport Canada is working with Indigenous partners and stakeholders in six pilot areas across Canada. Together, we are trying to understand the effects of marine shipping in various coastal areas. These pilot areas include:- North Coast British Columbia- South Coast British Columbia- St. Lawrence and Saguenay Rivers, Quebec- Bay of Fundy, New Brunswick and Nova Scotia- Placentia Bay, Newfoundland- Cambridge Bay, Nunavut
Government of Canada Cumulative Effects Initiatives
The Government of Canada leads or supports a variety of initiatives that involve monitoring, assessing or managing cumulative effects. This record contains information about cumulative effects initiatives that are taking place across Canada. 16 federal departments and agencies that are involved in cumulative effects and related work were surveyed and 388 initiatives were collected. Each entry includes:• a description of the initiative• information about its location, partners involved, relevant industries, and overarching or related initiatives• links to further information or related Open Data sources
High resolution forest change for Canada (Change Year) 1985-2011
High resolution forest change for Canada (Change Year) 1985-2011The forest change data included in this product is national in scope (entire forested ecosystem) and represents the first wall-to-wall characterization of wildfire and harvest in Canada at a spatial resolution commensurate with human impacts. The information outcomes represent 27 years of stand replacing change in Canada’s forests, derived from a single, consistent spatially-explicit data source, derived in a fully automated manner. This demonstrated capacity to characterize forests at a resolution that captures human impacts is key to establishing a baseline for detailed monitoring of forested ecosystems from management and science perspectives. Time series of Landsat data were used to characterize national trends in stand replacing forest disturbances caused by wildfire and harvest for the period 1985–2011 for Canada's 650 million hectare forested ecosystems (https://authors.elsevier.com/sd/article/S0034425717301360 ). Landsat data has a 30m spatial resolution, so the change information is highly detailed and is commensurate with that of human impacts. These data represent annual stand replacing forest changes. The stand replacing disturbances types labeled are wildfire and harvest, with lower confidence wildfire and harvest, also shared. The distinction and sharing of lower class membership likelihoods is to indicate to users that some change events were more difficult to allocate to a change type, but are generally found to be in the correct category. For an overview on the data, image processing, and time series change detection methods applied, as well as information on independent accuracy assessment of the data, see Hermosilla et al. (2016; http://www.tandfonline.com/doi/full/10.1080/17538947.2016.1187673).The data available is, 1. a binary change/no-change; 2. Change year; and, 3. Change type. When using this data, please cite as: White, J.C., M.A. Wulder, T. Hermosilla, N.C. Coops, and G. Hobart. (2017). A nationwide annual characterization of 25 years of forest disturbance and recovery for Canada using Landsat time series. Remote Sensing of Environment. 192: 303-321. DOI: 10.1016/j.rse.2017.03.035. https://authors.elsevier.com/sd/article/S0034425717301360Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011
High resolution forest change for Canada (Change Type) 1985-2011
High resolution forest change for Canada (Change Type) 1985-2011The forest change data included in this product is national in scope (entire forested ecosystem) and represents the first wall-to-wall characterization of wildfire and harvest in Canada at a spatial resolution commensurate with human impacts. The information outcomes represent 27 years of stand replacing change in Canada’s forests, derived from a single, consistent spatially-explicit data source, derived in a fully automated manner. This demonstrated capacity to characterize forests at a resolution that captures human impacts is key to establishing a baseline for detailed monitoring of forested ecosystems from management and science perspectives. Time series of Landsat data were used to characterize national trends in stand replacing forest disturbances caused by wildfire and harvest for the period 1985–2011 for Canada's 650 million hectare forested ecosystems (https://authors.elsevier.com/sd/article/S0034425717301360 ). Landsat data has a 30m spatial resolution, so the change information is highly detailed and is commensurate with that of human impacts. These data represent annual stand replacing forest changes. The stand replacing disturbances types labeled are wildfire and harvest, with lower confidence wildfire and harvest, also shared. The distinction and sharing of lower class membership likelihoods is to indicate to users that some change events were more difficult to allocate to a change type, but are generally found to be in the correct category. For an overview on the data, image processing, and time series change detection methods applied, as well as information on independent accuracy assessment of the data, see Hermosilla et al. (2016; http://www.tandfonline.com/doi/full/10.1080/17538947.2016.1187673).The data available is, 1. a binary change/no-change; 2. Change year; and, 3. Change type. When using this data, please cite as: White, J.C., M.A. Wulder, T. Hermosilla, N.C. Coops, and G. Hobart. (2017). A nationwide annual characterization of 25 years of forest disturbance and recovery for Canada using Landsat time series. Remote Sensing of Environment. 192: 303-321. DOI: 10.1016/j.rse.2017.03.035. https://authors.elsevier.com/sd/article/S0034425717301360Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011
British Columbia Coastal Anchor Marks
The marks left in the seabed by the commercial anchoring process can be seen as linear features in high-resolution multibeam bathymetry data. These features have been digitized to polylines for individual marks and polygons for anchor scour zones for British Columbia's (BC) commercial anchorages. They are made available via the Federal Geospatial Platform (FGP) for use in a Geographical Information System (GIS). This feature dataset is complete for published BC commercial anchorages and the multibeam bathymetry data available in 2021. It does not represent features produced since the collection of each multibeam bathymetry survey nor any features infilled since. The data are intended to be used for scientific research to better understand the cumulative impacts to the seabed from commercial anchoring at a 1:5000 scale or greater.
Great Lakes Nearshore Waters Assessment
Water quality and ecosystem health data used to conduct a cumulative effects assessment of Canadian Great Lakes nearshore waters in support of the Great Lakes Water Quality Agreement are included in this dataset. The data was collected by various government and non-government agencies and organizations and integrated into this dataset to allow the assessment to be conducted. By conducting a regular, systematic assessment of cumulative effects in the nearshore waters of the Great Lakes Environment and Climate Change Canada (ECCC) is able to identify areas of high quality and areas under stress. Knowledge of ecological thresholds, other Great Lakes assessments, stressor information, indicators and local and traditional ecological knowledge will be used to aid in: 1) the identification and mapping of high quality nearshore areas and areas that are or may become subject to high stress and; 2) the determination of factors and cumulative effects that are causing stress or threats. Cumulative effects impacting the nearshore and future threats to areas of high ecological value will be better understood and the knowledge shared will assist in priority setting for science and management at a meaningful and practical spatial scale within each Great Lake and connecting channel.
Drought Impact Type
The Drought Impact Label dataset is used on all drought polygons from D1 to D4 to specify the longitude and magnitude of impacts. Impact labels are often used in association with the Drought Impact Line dataset.The impact labels are classified as follows:S – Short-Term, typically less than 6 months.L – Long-Term, typically more than 6 months.SL – A combination of Short and Long-Term impacts.
Canadian Index of Multiple Deprivation 2021
The Canadian Index of Multiple Deprivation (CIMD) is an area-based index which used 2021 Census of Population microdata to measure four key dimensions of deprivation at the dissemination area (DA)-level: residential instability, economic dependency, situational vulnerability and ethno-cultural composition.Using factor analysis, DA-level factor scores were calculated for each dimension. Within a dimension, ordered scores were assigned a quintile value, 1 through 5, where 1 represents the least deprived and 5 represents the most deprived.The CIMD allows for an understanding of inequalities in various measures of health and social well-being. While it is a geographically-based index of deprivation and marginalization, it can also be used as a proxy for an individual. The CIMD has the potential to be widely used by researchers on a variety of topics related to socio-economic research. Other uses for the index may include: policy planning and evaluation, or resource allocation.*** Correction October 22, 2024 ***A correction has been made to the variables in the following downloadable 2021 CIMD index datasets : Canada, Atlantic, Quebec, Ontario, Prairies, and British-Columbia. This correction impacts all the data in these datasets.
Tell us what you think!
GEO.ca is committed to open dialogue and community building around location-based issues and
topics that matter to you.
Please send us your feedback