Return to CIG

Search

View All Publications

Go To Publication by Year:

View Publications by Topic:

Adaptation

Agriculture

Air Quality

Aquatic Ecosystems and Fisheries

Background Papers

Climate: Atmospheric Modeling

Climate: Coupled Atmosphere-Ocean Modeling

Climate: Diagnostics

Climate: Global Climate

Climate: Ocean Modeling

Climate: PNW Climate

Climate: Regional Climate Modeling

Coastal Ecosystems

Coastal Environments

Conservation Biology

Data Analysis and Sharing

Energy

Fact Sheets

Forecasts and Applications

Forest Ecosystems

Human Health

Hydrology and Water Resources

Infrastructure

Integrated Assessment

Ocean Acidification

Oceanography

Program Documents

Science Advisory Reports

Societal Dimensions

Special Reports

Theses and Dissertations

View Publications by Author:

Search the Publication Abstracts:


Other CSES Links:

About CSES

CSES Personnel

Data / Links

Publications

Welcome to the publications directory for the Climate Impacts Group and the Climate Dynamics Group. Please contact the web administrator for assistance with any of these publications.


View: Abstract

Space-time modeling of lightning-caused forest fires in the Blue Mountains, Oregon

Avalos, C.D., D.L. Peterson, E. Alvarado, and S.A. Ferguson. 2001. Space-time modeling of lightning-caused forest fires in the Blue Mountains, Oregon. Canadian Journal of Forest Research 31(9):1579-1593.

Abstract

Generalized linear mixed models (GLMM) were used to study the effect of vegetation cover, elevation, slope, and precipitation on the probability of ignition in the Blue Mountains, Oregon, and to estimate the probability of ignition occurrence at different locations in space and in time. Data on starting location of lightning-caused ignitions in the Blue Mountains between April 1986 and September 1993 constituted the base for the analysis. The study area was divided into a pixel-time array. For each pixel-time location we associated a value of 1 if at least one ignition occurred and 0 otherwise. Covariate information for each pixel was obtained using a geographic information system.

The GLMMs were fitted in a Bayesian framework. Higher ignition probabilities were associated with the following cover types: subalpine herbaceous, alpine tundra, lodgepole pine (Pinus contorta Dougl. ex Loud.), whitebark pine (Pinus albicaulis Engelm.), Engelmann spruce (Picea engelmannii Parry ex Engelm.), subalpine fir (Abies lasiocarpa (Hook.) Nutt.), and grand fir (Abies grandis (Dougl.) Lindl.). Within each vegetation type, higher ignition probabilities occurred at lower elevations. Additionally, ignition probabilities are lower in the northern and southern extremes of the Blue Mountains. The GLMM procedure used here is suitable for analysing ignition occurrence in other forested regions where probabilities of ignition are highly variable because of a spatially complex biophysical environment.