Abstract

AbstractFor remote communities in the discontinuous permafrost zone, access to permafrost distribution maps for hazard assessment is limited and more general products are often inadequate for use in local‐scale planning. In this study we apply established analytical methods to illustrate a time‐ and cost‐efficient method for conducting community‐scale permafrost mapping in the community of Whatì, Northwest Territories, Canada. We ran a binary logistic regression (BLR) using a combination of field data, digital surface model‐derived variables, and remotely sensed products. Independent variables included vegetation, topographic position index, and elevation bands. The dependent variable was sourced from 139 physical checks of near‐surface permafrost presence/absence sampled across the variable boreal–wetland environment. Vegetation is the strongest predictor of near‐surface permafrost in the regression. The regression predicts that 50.0% (minimum confidence: 36%) of the vegetated area is underlain by near‐surface permafrost with a spatial accuracy of 72.8%. Analysis of data recorded across various burnt and not‐burnt environments indicated that recent burn scenarios have significantly influenced the distribution of near‐surface permafrost in the community. A spatial burn analysis predicted up to an 18.3% reduction in near‐surface permafrost coverage, in a maximum burn scenario without factoring in the influence of climate change. The study highlights the potential that in an ecosystem with virtually homogeneous air temperature, ecosystem structure and disturbance history drive short‐term changes in permafrost distribution and evolution. Thus, at the community level these factors should be considered as seriously as changes to air temperature as climate changes.

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