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Jones, Matthew W. 
ORCID: https://orcid.org/0000-0003-3480-7980, Veraverbeke, Sander, Andela, Niels, Doerr, Stefan H., Kolden, Crystal, Mataveli, Guilherme, Pettinari, M. Lucrecia, Le Quéré, Corinne ORCID: https://orcid.org/0000-0003-2319-0452, Rosan, Thais M., van der Werf, Guido R., van Wees, Dave and Abatzoglou, John T.
(2024)
Global rise in forest fire emissions linked to climate change in the extratropics.
Science, 386 (6719).
ISSN 0036-8075
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Abstract
Climate change increases fire-favorable weather in forests, but fire trends are also affected by multiple other controlling factors that are difficult to untangle. We use machine learning to systematically group forest ecoregions into 12 global forest pyromes, with each showing distinct sensitivities to climatic, human, and vegetation controls. This delineation revealed that rapidly increasing forest fire emissions in extratropical pyromes, linked to climate change, offset declining emissions in tropical pyromes during 2001 to 2023. Annual emissions tripled in one extratropical pyrome due to increases in fire-favorable weather, compounded by increased forest cover and productivity. This contributed to a 60% increase in forest fire carbon emissions from forest ecoregions globally. Our results highlight the increasing vulnerability of forests and their carbon stocks to fire disturbance under climate change.
| Item Type: | Article |
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| Additional Information: | Data and materials availability: Pyromes are provided in three geospatial formats at Zenodo (131); shapefiles; 0.25° grids; and 0.05° grids. Gridded correlations for all variables are also available at Zenodo (131). The R code used for clustering forest ecoregions into pyromes is also archived at Zenodo (131). The raw data representing burned area, carbon emissions, and all predictor variables in our analysis are publicly available (49, 58, 59, 61, 62, 67–70, 132), except for the lightning flash data from the WWLLN (63), which are subject to a commercial agreement but can be provided in a gridded and coarsened form upon request. Funding: This work was funded by the following: UK Natural Environment Research Council (NERC) grant NE/V01417X/1 (M.W.J.); European Commission (E.C.) Horizon 2020 (H2020) project VERIFY grant 776810 (M.W.J.); São Paulo Research Foundation (FAPESP) grants 2019/25701-8, 2020/15230-5 and 2023/03206-0 (G.M.); EC H2020 project FirEURisk grant no. 101003890 (S.H.D., M.L.P.); NERC project UK-FDRS grant NE/T003553/1 (S.H.D.); European Space Agency (ESA) Climate Change Initiative (CCI) FireCCI project contract no. 4000126706/19/I-NB (MLP); Royal Society grant RP\R1\191063 (C.L.Q.); National Science Foundation grant OAI-2019762 (JTA). |
| Uncontrolled Keywords: | biochemistry, genetics and molecular biology(all),biomedical engineering,computer science applications,sdg 13 - climate action ,/dk/atira/pure/subjectarea/asjc/1300 |
| Faculty \ School: | Faculty of Science > School of Environmental Sciences University of East Anglia Research Groups/Centres > Theme - ClimateUEA |
| UEA Research Groups: | University of East Anglia Schools > Faculty of Science > Tyndall Centre for Climate Change Research Faculty of Science > Research Centres > Tyndall Centre for Climate Change Research Faculty of Science > Research Groups > Climatic Research Unit Faculty of Science > Research Groups > Centre for Ocean and Atmospheric Sciences |
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| Depositing User: | LivePure Connector |
| Date Deposited: | 07 Nov 2024 16:30 |
| Last Modified: | 16 Dec 2024 01:43 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/97571 |
| DOI: | 10.1126/science.adl5889 |
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