Space–time modelling of lightning-caused ignitions in the Blue Mountains, Oregon

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 star...

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Published in:Canadian Journal of Forest Research
Main Authors: Díaz-Avalos, Carlos, Peterson, David L, Alvarado, Ernesto, Ferguson, Sue A, Besag, Julian E
Format: Article in Journal/Newspaper
Language:English
Published: Canadian Science Publishing 2001
Subjects:
Online Access:http://dx.doi.org/10.1139/x01-089
http://www.nrcresearchpress.com/doi/pdf/10.1139/x01-089
id crcansciencepubl:10.1139/x01-089
record_format openpolar
spelling crcansciencepubl:10.1139/x01-089 2024-04-28T08:40:54+00:00 Space–time modelling of lightning-caused ignitions in the Blue Mountains, Oregon Díaz-Avalos, Carlos Peterson, David L Alvarado, Ernesto Ferguson, Sue A Besag, Julian E 2001 http://dx.doi.org/10.1139/x01-089 http://www.nrcresearchpress.com/doi/pdf/10.1139/x01-089 en eng Canadian Science Publishing http://www.nrcresearchpress.com/page/about/CorporateTextAndDataMining Canadian Journal of Forest Research volume 31, issue 9, page 1579-1593 ISSN 0045-5067 1208-6037 Ecology Forestry Global and Planetary Change journal-article 2001 crcansciencepubl https://doi.org/10.1139/x01-089 2024-04-09T06:56:30Z 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. Article in Journal/Newspaper Tundra Canadian Science Publishing Canadian Journal of Forest Research 31 9 1579 1593
institution Open Polar
collection Canadian Science Publishing
op_collection_id crcansciencepubl
language English
topic Ecology
Forestry
Global and Planetary Change
spellingShingle Ecology
Forestry
Global and Planetary Change
Díaz-Avalos, Carlos
Peterson, David L
Alvarado, Ernesto
Ferguson, Sue A
Besag, Julian E
Space–time modelling of lightning-caused ignitions in the Blue Mountains, Oregon
topic_facet Ecology
Forestry
Global and Planetary Change
description 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.
format Article in Journal/Newspaper
author Díaz-Avalos, Carlos
Peterson, David L
Alvarado, Ernesto
Ferguson, Sue A
Besag, Julian E
author_facet Díaz-Avalos, Carlos
Peterson, David L
Alvarado, Ernesto
Ferguson, Sue A
Besag, Julian E
author_sort Díaz-Avalos, Carlos
title Space–time modelling of lightning-caused ignitions in the Blue Mountains, Oregon
title_short Space–time modelling of lightning-caused ignitions in the Blue Mountains, Oregon
title_full Space–time modelling of lightning-caused ignitions in the Blue Mountains, Oregon
title_fullStr Space–time modelling of lightning-caused ignitions in the Blue Mountains, Oregon
title_full_unstemmed Space–time modelling of lightning-caused ignitions in the Blue Mountains, Oregon
title_sort space–time modelling of lightning-caused ignitions in the blue mountains, oregon
publisher Canadian Science Publishing
publishDate 2001
url http://dx.doi.org/10.1139/x01-089
http://www.nrcresearchpress.com/doi/pdf/10.1139/x01-089
genre Tundra
genre_facet Tundra
op_source Canadian Journal of Forest Research
volume 31, issue 9, page 1579-1593
ISSN 0045-5067 1208-6037
op_rights http://www.nrcresearchpress.com/page/about/CorporateTextAndDataMining
op_doi https://doi.org/10.1139/x01-089
container_title Canadian Journal of Forest Research
container_volume 31
container_issue 9
container_start_page 1579
op_container_end_page 1593
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