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dc.contributor.authorSchmidt, Jennifer, I.
dc.date.accessioned2024-08-13T23:21:49Z
dc.date.available2024-08-13T23:21:49Z
dc.date.issued2023
dc.identifier.citationCalef, MP, Schmidt, JI, Varvak, A, Ziel, R (2023) Predicting the Unpredictable: Predicting Landcover in Boreal Alaska and the Yukon Including Succession and Wildfire Potential. Forests 14, 1577.en_US
dc.identifier.otherhttps://doi.org/10.3390/f14081577
dc.identifier.urihttp://hdl.handle.net/11122/15273
dc.description.abstracthe boreal forest of northwestern North America covers an extensive area, contains vast amounts of carbon in its vegetation and soil, and is characterized by extensive wildfires. Catastrophic crown fires in these forests are fueled predominantly by only two evergreen needle-leaf tree species, black spruce (Picea mariana (Mill.) B.S.P.) and lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.). Identifying where these flammable species grow through time in the landscape is critical for understanding wildfire risk, damages, and human exposure. Because medium resolution landcover data that include species detail are lacking, we developed a compound modeling approach that enabled us to refine the available evergreen forest category into highly flammable species and less flammable species. We then expanded our refined landcover at decadal time steps from 1984 to 2014. With the aid of an existing burn model, FlamMap, and simple succession rules, we were able to predict future landcover at decadal steps until 2054. Our resulting land covers provide important information to communities in our study area on current and future wildfire risk and vegetation changes and could be developed in a similar fashion for other areas.en_US
dc.subjectboreal forest; wildfire; interior Alaska; Yukon; machine learning modelen_US
dc.titlePredicting the Unpredictable: Predicting Landcover in Boreal Alaska and the Yukon Including Succession and Wildfire Potentialen_US
dc.typeArticleen_US
dc.description.peerreviewYesen_US
refterms.dateFOA2024-08-13T23:21:51Z
dc.identifier.journalForestsen_US


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