Research Database
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Mortality predictions of fire-injured large Douglas-fir and ponderosa pine in Oregon and Washington, USA
Year: 2017
Wild and prescribed fire-induced injury to forest trees can produce immediate or delayed tree mortality but fire-injured trees can also survive. Land managers use logistic regression models that incorporate tree-injury variables to discriminate between fatally injured trees and those that will survive. We used data from 4024 ponderosa pine (Pinus ponderosa Dougl. ex Laws.) and 3804 Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) trees from 23 fires across Oregon and Washington to assess the discriminatory ability of 21 existing logistic regression models and a polychotomous key (Scott…
Publication Type: Journal Article
Predicting post-fire tree mortality for 14 conifers in the Pacific Northwest, USA: Model evaluation, development, and thresholds
Year: 2017
Fire is a driving force in the North American landscape and predicting post-fire tree mortality is vital to land management. Post-fire tree mortality can have substantial economic and social impacts, and natural resource managers need reliable predictive methods to anticipate potential mortality following fire events. Current fire mortality models are limited to a few species and regions, notably Pinus ponderosa and Pseudotsuga menziesii in the western United States. The efficacy of existing mortality models to predict fire-induced tree mortality is central to effective forest management.…
Publication Type: Journal Article