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Abstract: Quantifying the Controls on Boreal Forest Reburning with Interpretable Machine Learning (AGU25)

Quantifying the Controls on Boreal Forest Reburning with Interpretable Machine Learning

Jeremy Forsythe1, Logan T. Berner2, Scott J. Goetz3, Winslow Hansen4, Jill F Johnstone5, Michelle C Mack6, Stefano Potter7, Brendan Rogers8, Anna Talucci8, Jonathan A Wang9 and Xanthe J Walker6, (1)Northern Arizona University, Center for Ecosystem Science and Society, Flagstaff, United States, (2)Northern Arizona University, SICCS, Flagstaff, United States, (3)Northern Arizona University, SICCS, Flagstaff, AZ, United States, (4)Cary Institute of Ecosystem Studies, Millbrook, NY, United States, (5)University of Alaska Fairbanks, Fairbanks, United States, (6)Northern Arizona University, Center for Ecosystem Science and Society, Flagstaff, AZ, United States, (7)Woods Hole Research Center, Falmouth, United States, (8)Woodwell Climate Research Center, Falmouth, United States, (9)University of Utah, School of Biological Sciences, Salt Lake City, UT, United States
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