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Assessment of fire effects based on Forest Inventory and Analysis data and a long-term fire mapping data setAuthor(s): John D. Shaw; Sara A. Goeking; James Menlove; Charles E. Werstak
Source: Journal of Forestry. 115(4): 258-269.
Publication Series: Scientific Journal (JRNL)
Station: Rocky Mountain Research Station
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DescriptionIntegration of Forest Inventory and Analysis (FIA) plot data with Monitoring Trends in Burn Severity (MTBS) data can provide new information about fire effects on forests. This integration allowed broad-scale assessment of the cover types burned in large fires, the relationship between prefire stand conditions and fire severity, and postfire stand conditions. Of the 42.5 million acres burned in eight Interior West states since 1984, 41.4% was forestland. Forest types with the most burned acreage were ponderosa pine, lodgepole pine, and Douglas-fir. Nearly 35% of plots had no live basal area of trees ≥5 in. diameter remaining postfire, but 32% of plots had greater than 40 ft2/ac of residual live basal area. Residual basal area appeared to decline slightly with time since fire, suggesting low mortality rates among survivor trees. Seedlings appeared to reach peak density 5-10 years postfire, and sapling density increased monotonically for at least 25 years postfire. Data from remeasured FIA plots indicate that the highest MTBS severity class is related to high prefire basal area. At a regional scale, MTBS severity classes represent significantly different levels of mean live basal area reductions, ranging from 4% for areas of very low fire severity to 89% for high-severity areas. Severity classes are less distinguishable for individual forest-type groups.
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CitationShaw, John D.; Goeking, Sara A.; Menlove, James; Werstak, Charles E., Jr. 2017. Assessment of fire effects based on Forest Inventory and Analysis data and a long-term fire mapping data set. Journal of Forestry. 115(4): 258-269.
Keywordsforest monitoring, wildfire, fire severity, Monitoring Trends in Burn Severity (MTBS), Forest Inventory and Analysis (FIA), regeneration
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