Abstract
In most of the world, conditions conducive to wildfires are becoming more prevalent. Net carbon emissions from wildfires contribute to a positive climate feedback that needs to be monitored, quantified, and predicted. Here we use a causal inference approach to evaluate the influence of top-down weather and bottom-up fuel precursors on wildfires. The top-down dominance on wildfires is more widespread than bottom-up dominance, accounting for 73.3% and 26.7% of regions, respectively. The top-down precursors dominate in the tropical rainforests, mid-latitudes, and eastern Siberian boreal forests. The bottom-up precursors dominate in North American and European boreal forests, and African and Australian savannahs. Our study identifies areas where wildfires are governed by fuel conditions and hence where fuel management practices may be more effective. Moreover, our study also highlights that top-down and bottom-up precursors show complementary wildfire predictability across timescales. Seasonal or interannual predictions are feasible in regions where bottom-up precursors dominate.
| Original language | English |
|---|---|
| Article number | 6829 |
| Pages (from-to) | 1-9 |
| Number of pages | 9 |
| Journal | Nature Communications |
| Volume | 14 |
| DOIs | |
| Publication status | Published - 26 Oct 2023 |
Bibliographical note
Funding Information:This study is supported by the China Scholarship Council (CSC) under grant number 201906040220 (Y.Q.), the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – SFB 1502/1-2022 – project number 450058266 (Y.Q., C.M., and H.V.), the Dutch Research Council through Vidi grant 016.Vidi.189.070 and the European Research Council through a Consolidator grant under the European Union’s Horizon 2020 research and innovation program under grant agreement No. 101000987 (S.V.), and the European Research Council under grant agreement 101088405 (HEAT, D.G.M.).
Publisher Copyright:
© 2023, The Author(s).
Funding
This study is supported by the China Scholarship Council (CSC) under grant number 201906040220 (Y.Q.), the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – SFB 1502/1-2022 – project number 450058266 (Y.Q., C.M., and H.V.), the Dutch Research Council through Vidi grant 016.Vidi.189.070 and the European Research Council through a Consolidator grant under the European Union’s Horizon 2020 research and innovation program under grant agreement No. 101000987 (S.V.), and the European Research Council under grant agreement 101088405 (HEAT, D.G.M.).