Author: Rodney A. NorumPublisher:
ISBN:
Category : Black spruce
Languages : en
Pages : 12
Book Description
Predicting Wildfire Behavior in Black Spruce Forests in Alaska
Author: Rodney A. NorumPublisher:
ISBN:
Category : Black spruce
Languages : en
Pages : 12
Book Description
Predicting Wildfire Behavior in Black Spruce Forests in Alaska
Author: Rodney A. NorumResearch Note PNW
Author: A Key for Predicting Postfire Successional Trajectories in Black Spruce Stands of Interior Alaska
Author: Jill Frances JohnstonePublisher:
ISBN:
Category : Black spruce
Languages : en
Pages : 46
Book Description
Black spruce (Picea mariana (Mill) B.S.P) is the dominant forest cover type in interior Alaska and is prone to frequent, stand-replacing wildfires. Through impacts on tree recruitment, the degree of fire consumption of soil organic layers can act as an important determinant of whether black spruce forests regenerate to a forest composition similar to the prefire forest, or to a new forest composition dominated by deciduous hardwoods. Here we present a simple, rule-based framework for predicting fire-initiated changes in forest cover within Alaska's black spruce forests. Four components are presented: (1) a key to classifying potential site moisture, (2) a summary of conditions that favor black spruce self-replacement, (3) a key to predicting postfire forest recovery in recently burned stands, and (4) an appendix of photos to be used as a visual reference tool. This report should be useful to managers in designing fire management actions and predicting the effects of recent and future fires on postfire forest cover in black spruce forests of interior Alaska.
A Key for Predicting Postfire Successional Trajectories in Black Spruce Stands of Interior Alaska
Author: United States Department of AgriculturePublisher: CreateSpace
ISBN: 9781508770886
Category :
Languages : en
Pages : 42
Book Description
Black spruce (Picea mariana (Mill) B.S.P) is the dominant forest cover type in interior Alaska and is prone to frequent, stand-replacing wildfires. Through impacts on tree recruitment, the degree of fire consumption of soil organic layers can act as an important determinant of whether black spruce forests regenerate to a forest composition similar to the prefire forest, or to a new forest composition dominated by deciduous hardwoods. Here we present a simple, rule-based framework for predicting fire-initiated changes in forest cover within Alaska's black spruce forests. Four components are presented: (1) a key to classifying potential site moisture, (2) a summary of conditions that favor black spruce self-replacement, (3) a key to predicting postfire forest recovery in recently burned stands, and (4) an appendix of photos to be used as a visual reference tool. This report should be useful to managers in designing fire management actions and predicting the effects of recent and future fires on postfire forest cover in black spruce forests of interior Alaska.
Research Note PNW
Author: Publisher:
ISBN:
Category : Forests and forestry
Languages : en
Pages : 374
Book Description
Preliminary Results of Experimental Fires in the Black Spruce Type of Interior Alaska
Author: Leslie A. ViereckPublisher:
ISBN:
Category : Black spruce
Languages : en
Pages : 28
Book Description
Research Note PNW.
Author: Pacific Northwest Forest and Range Experiment Station (Portland, Or.)Publisher:
ISBN:
Category : Forests and forestry
Languages : en
Pages : 48
Book Description
Quantifying Fire Severity and Carbon and Nitrogen Pools and Emissions in Alaska's Boreal Black Spruce Forest
Author: Leslie A. BobyPublisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
ABSTRACT: Fire severity can be defined as the amount of biomass combusted by wildfire. Stored carbon (C) and nitrogen (N) are emitted into the atmosphere as wildfires consume vegetation and soil organic layers, thus C and N emissions should be related to fire severity. Since boreal forests store 30% of the world's terrestrial C and are subject to high-intensity, stand-replacing wildfires, it is critical to be able to estimate C fluxes from wildfires. Furthermore, quantifying fire severity is important for predicting post-fire vegetation recovery and future C sequestration. We reconstructed pre-fire organic soil layers and quantified fire severity levels from the 2004 wildfires in Interior Alaska with the adventitious root height (ARH) method. We tested the ARH method in unburned stands and by comparing our reconstructed values in burned stands with actual prefire measurements. We found that ARH correlated to organic soil height in unburned stands (with a small offset of 3 cm). We measured organic soil (using the ARH method) and stand characteristics in boreal black spruce forest and estimated the amount of soil and canopy biomass consumed by fire. We compared these results to the composite burn index (CBI), a standardized visual method, which has not been widely used in the boreal forest. CBI assessments were significantly related to our ground and canopy fire severity estimates. We calculated C and N pools using C and N concentration and bulk density estimates from soils sampled in burned and unburned stands. We conclude that the ARH method can be used to reconstruct pre-fire organic soil depth, C and N pools and to assess fire severity. Furthermore, CBI shows promise as a way of estimating fire severity quickly and is a reasonably good predictor of biomass and soil C loss.
Field Procedures for Verification and Adjustment of Fire Behavior Predictions
Author: Richard C. RothermelPublisher:
ISBN:
Category : Forest fire forecasting
Languages : en
Pages : 28
Book Description
The problem of verifying predictions of fire behavior, primarily rate of spread, is discussed in terms of the fire situation for which predictions are made, and the type of fire where data are to be collected. Procedures for collecting data and performing analysis are presented for both readily accessible fires where data should be complete, and for inaccessible fires where data are likely to be incomplete. The material is prepared for use by field units, with no requirements for special equipment or computers. Procedures for selecting the most representative fuel model, for overall evaluation of prediction capability, and for developing calibration coefficients to improve future predictions are presented. Illustrated examples from several fires are included. The material is a companion publication to the fire prediction manual titled, 'INT-GTR-143: How to predict the spread and intensity of forest and range fire' by R. C. Rothermel.