Institute for a Secure and Sustainable Environment and Department of Industrial and Systems Engineering, University of Tennessee, Knoxville, TN 37996, USA
Department of Biological & Agricultural Engineering, University of Arkansas, Fayetteville, AR 72701, USA
Institute for a Secure and Sustainable Environment and Department of Industrial and Systems Engineering, University of Tennessee, Knoxville, TN 37996, USA
Department of Biology and Graduate Degree Program in Ecology, Colorado State University, Fort Collins, CO 80523, USA
Yulong Zhang
Institute for a Secure and Sustainable Environment and Department of Industrial and Systems Engineering, University of Tennessee, Knoxville, TN 37996, USA
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1,768
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2,462
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PDF: 594
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Total: 2,462
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Cumulative views and downloads
(calculated since 21 Feb 2023)
Total article views: 1,309 (including HTML, PDF, and XML)
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1,021
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1,309
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PDF: 237
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Supplement: 90
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EndNote: 138
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Cumulative views and downloads
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Total article views: 1,153 (including HTML, PDF, and XML)
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747
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1,153
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PDF: 357
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Total: 1,153
Supplement: 129
BibTeX: 28
EndNote: 26
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Cumulative views and downloads
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Viewed (geographical distribution)
Total article views: 2,462 (including HTML, PDF, and XML)
Thereof 2,408 with geography defined
and 54 with unknown origin.
Total article views: 1,309 (including HTML, PDF, and XML)
Thereof 1,286 with geography defined
and 23 with unknown origin.
Total article views: 1,153 (including HTML, PDF, and XML)
Thereof 1,122 with geography defined
and 31 with unknown origin.
Carbon-rich boreal peatlands are at risk of burning. The reproducibility and predictability of rare peatland fire events are investigated by constructing a two-step error-correcting machine learning framework to tackle such complex systems. Fire occurrence and impacts are highly predictable with our approach. Factor-controlling simulations revealed that temperature, moisture, and freeze–thaw cycles control boreal peatland fires, indicating thermal impacts on causing peat fires.
Carbon-rich boreal peatlands are at risk of burning. The reproducibility and predictability of...
