Mountain Pine Beetles, Salvage Logging, and Hydrologic Change: Predicting Wet Ground Areas
AbstractThe mountain pine beetle epidemic in British Columbia has covered 18.1 million hectares of forest land showing the potential for exceptionally large-scale disturbance to influence watershed hydrology. Pine stands killed by the epidemic can experience reduced levels of evapotranspiration and precipitation interception, which can translate into an increase in soil moisture as observed by some forest practitioners during salvage logging in the epicenter of the outbreak. They reported the replacement of summer ground, dry firm soil areas, with winter ground areas identified by having wetter, less firm soils upon which forestry equipment operation is difficult or impossible before winter freeze-up. To decrease the likelihood of soil disturbance from harvesting, a set of hazard indicators was developed to predict wet ground areas in areas heavily infested by the mountain pine beetle. Hazard indicators were based on available GIS data, aerial photographs, and local knowledge. Indicators were selected by an iterative process that began with office-based selection of potential indicators, model development and prediction, field verification, and model refinement to select those indicators that explained most field data variability. Findings indicate that the most effective indicators were lodgepole pine content, understory, drainage density, soil texture, and the topographic index. View Full-Text
The authors wish to acknowledge a funding agency in their recently published paper  and make the following correction.
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Rex, J.; Dubé, S.; Foord, V. Mountain Pine Beetles, Salvage Logging, and Hydrologic Change: Predicting Wet Ground Areas. Water 2013, 5, 443-461.
Rex J, Dubé S, Foord V. Mountain Pine Beetles, Salvage Logging, and Hydrologic Change: Predicting Wet Ground Areas. Water. 2013; 5(2):443-461.Chicago/Turabian Style
Rex, John; Dubé, Stéphane; Foord, Vanessa. 2013. "Mountain Pine Beetles, Salvage Logging, and Hydrologic Change: Predicting Wet Ground Areas." Water 5, no. 2: 443-461.