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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Total article views: 3,018 (including HTML, PDF, and XML)
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2,179
718
121
3,018
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195
HTML: 2,179
PDF: 718
XML: 121
Total: 3,018
Supplement: 278
BibTeX: 123
EndNote: 195
Views and downloads (calculated since 21 Feb 2023)
Cumulative views and downloads
(calculated since 21 Feb 2023)
Total article views: 1,815 (including HTML, PDF, and XML)
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EndNote
1,412
331
72
1,815
125
95
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HTML: 1,412
PDF: 331
XML: 72
Total: 1,815
Supplement: 125
BibTeX: 95
EndNote: 169
Views and downloads (calculated since 21 Feb 2024)
Cumulative views and downloads
(calculated since 21 Feb 2024)
Total article views: 1,203 (including HTML, PDF, and XML)
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767
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49
1,203
153
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26
HTML: 767
PDF: 387
XML: 49
Total: 1,203
Supplement: 153
BibTeX: 28
EndNote: 26
Views and downloads (calculated since 21 Feb 2023)
Cumulative views and downloads
(calculated since 21 Feb 2023)
Viewed (geographical distribution)
Total article views: 3,018 (including HTML, PDF, and XML)
Thereof 2,901 with geography defined
and 117 with unknown origin.
Total article views: 1,815 (including HTML, PDF, and XML)
Thereof 1,731 with geography defined
and 84 with unknown origin.
Total article views: 1,203 (including HTML, PDF, and XML)
Thereof 1,170 with geography defined
and 33 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...
