Purpose This data set was developed for an M.Sc thesis that is attempting to explore the vegetation species composition along gradients of disturbances in relation to the potential Mackenzie Valley pipeline. It attempted to identify existing gradients of disturbance, species distributions of native and existing invasive alien species, and to document Tradition Ecological Knowledge about plant changes. This biological field sampling of the vegetation will be linked with geospatial mapping techniques, specifically a Geographical Information System (GIS). This will allow for environmental correlations to occur spatially, relating the location. GIS provides two advantages to the traditional methods of ecosystem comparative analysis, where researchers gain the ability to compare values across the entire data surface (landscape, ecosystem, bioregion, etc), rather than limiting it several points, and decrease the amount of bias found with selective point sampling.
Abstract As part of the International Polar Year (IPY) project 'The Impacts of Oil and Gas Activity on Peoples in the Arctic Using a Multiple Securities Perspective' this study focuses on the potential impacts that the future Mackenzie Valley Oil and Gas pipelines may have on plant community structures. Sampling occurred in Fort Simpson, Norman Wells, Fort Good Hope, and Inuvik, with each location being selected using different disturbance levels. The Norman Wells pipeline provided a reference site for comparison in sites with no pipeline activity and/or roads. Point-line transects using 1x1m quadrats (squares) were sampled along with community consultations. This attempted to identify existing gradients of disturbance, species distributions of native and existing invasive alien species, and to document Tradition Ecological Knowledge about plant changes. It was predicted that the pipelines will assist in a measurable amount of disturbance affecting baseline species composition and increasing the rate of invasive alien species movement. Preliminary analysis of plant communities suggests a change in vegetation along disturbances and an increased number of alien invasive species in disturbed areas. Results of the project are being developed into an integrated community monitoring program for invasive alien species with the Government of Northwest Territories, Environment and Natural Resources.
Monday, 04 May 2015 14:44
Unknown
Additional Info
- Project: Herbaceous vegetation data collected along gradient of disturbance in the Mackenzie Valley, NWT
- Dataset Title: Unknown
- Data Series: 2008
- Orginator: Milissa Elliott
- Institution Type: academic
- Author: Dr. Dawn Bazely, principalInvestigator Milissa Elliott, Originator Annika Trimble, Collaborator Ramona Menicoche, Collaborator
- Distributor: Canadian Cryospheric Information Network www.polardata.ca
- Data Type: spatial
- Délı̨nę District: no
- K’asho Got’ı̨nę District: yes
- Tulı́t’a District: yes
- Time Period: 2008
- Source Date: 2013
- Access Constraints: permission required
- Use Constraints: Use Constraints Terms of Use of the Polar Data Catalogue: https://www.polardata.ca/pdcinput/public/termsofuse.ccin
- Completion Status: ongoing
- Maintenance: unknown
- Maintenance Frequency: as needed
- Metadata Available: https://www.polardata.ca/pdcsearch/PDCSearchDOI.jsp?doi_id=1670
- Metadata Contact: Dawn Bazely York University Address 349 York Lanes, 4700 Keele Street Toronto Ontario M3J1P3 Canada Email This email address is being protected from spambots. You need JavaScript enabled to view it. Phone Number 416-736-2100 x33631 or x20109
- Spatial Extent: Mackenzie Valley, NWT
- Traditional Knowledge: yes
- Wildlife: no
- Habitat: yes
- Keywords: Fort Good Hope (Northern communities) Norman Wells (Northern communities) Inuvik (Northern communities) Plants (Natural sciences) Vegetation (Natural sciences) GIS (Natural sciences) Traditional Ecological Knowledge (TEK) (Social sciences, economics and policy)
- Format: unknown
- Feature Type: unknown
- Feature Count: unknown
- Dataset Descriptive Name: unknown
- File Name: unknown
- Scale: unknown
- Projection: Unknown
- Downloadable: no
Phone: 867-374-4040
Email: