Coarse Filter - Terrestrial
To help sustain the NWT’s biodiversity and cultural landscapes, the NWT Protected Areas Strategy (PAS) aims to protect special natural and cultural areas, and core representative areas within each of the territory’s 42 ecoregions. The PAS Science Team has developed a methodology to identify options for core representative areas in the NWT, mainly through a coarse filter ecological representation analysis.
Ecological Representation Analysis
This method is based on best practices in conservation planning, adapted to fit the context of the NWT. A coarse filter analysis seeks to protect biodiversity by using relatively coarse-scale data that are thought to be good surrogates for biodiversity (e.g. physical features such as soils, elevation, climate, vegetation). The underlying assumption with this approach is that species distribution is determined largely by environmental factors, such as climate and substrate, and that vegetation and other species assemblages respond to gradients of these factors across the landscape. Protecting examples of all types of landscape features should capture the majority of species without having to consider those species individually. Complete details and theory behind the method can be found in a technical report prepared by the PAS Science Team.
The results of the coarse filter analyses are provided to communities, land use planning boards/agencies and protected area working groups. This information can be used together with traditional knowledge and other ecological, social and economic information to make decisions about which areas to propose for protection and/or to make decisions about final boundary options. The analyses are also used to assess how well the protected area network achieves ecological representation (also called “gap analysis”).
What method is used to identify representative areas?
To identify options for representative terrestrial areas, the PAS Science Team uses a computerized site selection program called “Marxan". This program selects areas which represent many different landscape features using the smallest amount of land possible. The model uses three types of landscape features that are assumed to be good surrogates for biodiversity (see map here):
- physiographic units: a combination of elevation, regional climate, topography and latitude, which influence species habitats
- landscape units: a combination of surficial geology, soil and terrain, which have an influence on what the landscape and biological community look like
- vegetation types: plant types (e.g. spruce, tall shrubs, emergent (wetland) vegetation), which are an important part of species habitats
Because smaller features are more vulnerable to natural and human disturbances, representation objectives are set such that proportionately more of the smaller landscape features and less of the larger landscape features are represented. Overall representation objectives total approximately 30% of the land area. It is recognized that 30% land protection alone is not sufficient to protect biodiversity and that core representative areas must work in combination with functioning habitat outside of protected areas.
There are multiple options for meeting the ecological representation objectives and Marxan can be used to explore these options through different scenarios. The results of the Marxan terrestrial coarse filter representation analysis scenarios are used as only one part of the conservation planning process. Other methods being used or developed include coarse level representation of freshwater habitats, fine filter analyses to ensure that special features are also represented, focal species analyses, and consideration of larger ecosystem processes. Additional information, including traditional knowledge, development interests, and other scientific information also contributes to identifying the best areas for protection and helps refine the boundaries of proposed protected areas.
How does the PAS evaluate ecological representation of ecoregions?
To ensure that the goals of the PAS are met, the PAS Science Team assesses:
- how much of each ecoregion must be protected to fully represent the biodiversity of each ecoregion in the NWT;
- how much of each ecoregion is already protected by existing protected areas and how much the currently proposed protected areas would contribute to representing the biodiversity of NWT ecoregions (see map here);
- where the gaps in protection are; and
- options for protection other than permanent protected areas.
Related Links
- A National Ecological Framework for Canada. 1996.
- Protected Areas in Northern Canada: Designing for Ecological Integrity Phase 1 (CCEA Publication). 2005. (pdf)
- Conservation Beyond Crisis Management: A Reverse-Matrix Model - A Discussion Paper for the Canadian BEACONs Project. 2006. (pdf)
A document that explores an alternative approach to conservation planning in relatively intact systems such as the boreal regions of Canada. - Ecological Regions of the Northwest Territories:
Taiga Plains.
2007.
A re-assessment of the national ecosystem classification system (A National Ecological Framework for Canada 1996) for the Taiga Plains ecozone. - Ecological Regions of the Northwest Territories:
Taiga Shield.
2008.
A re-assessment of the national ecosystem classification system (A National Ecological Framework for Canada 1996) for the Taiga Shield. - Ecological Regions of the Northwest Territories:
Cordillera. 2010.
A re-assessment of the national ecosystem classification system (A National Ecological Framework for Canada 1996) for the Cordillera. - Natural Resources Canada's Earth Observation for Sustainable Development of Forests
(EOSD) land cover mapping (Wulder et al., 2004; Natural Resources Canada, 2006).
This vegetation information was used in our analyses, and is based on Landsat satellite imagery at 25-metre resolution. - Methods for Identifying Potential Core Representative Areas for the Northwest Territories Protected Areas Strategy (pdf)
A technical document explaining the methodology for coarse filter ecological representation analyses.
