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Increasing severity of large-scale fires prolongs recovery time of forests globally since 2001

Nature Ecology & Evolution volume 9, pages 980–992 (2025)Cite this article

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A Publisher Correction to this article was published on 06 May 2025

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Abstract

Ongoing and sharply increased global forest fires, especially extreme large-scale fires (LFs) with their greater destructiveness, have significantly altered forest structures and functions. However, long-term variations in the severity of LFs and corresponding effects on the natural post-LF recovery time of global forests remain unclear. Here, we rigorously identified 3,281 global large-scale (>10 km2) single-time fire events (LSFs) from 2001 to 2021, and used multiple indicators to understand the post-LSF recovery dynamics from different perspectives and comprehensively reveal major driving factors across regions and forests types based on multiple models. Compared with pre-2010, LSFs after 2010 caused greater forest damage, with the fire severity expanding further from low to high latitudes and from humid to arid regions, particularly affecting evergreen needleleaf forests. Fewer than one-third of the forests recovered successfully within 7 years, and most of these were tropical, moisture-rich broadleaf forests. The average time required for three indicators to recover to pre-fire conditions increased by 7.5% (vegetation density), 11.1% (canopy structure) and 27.3% (gross primary productivity). Moreover, the positive sensitivity of recovery time to increased fire severity was significantly intensified. Notably, more forests experienced recovery stagnation with increased severity, especially in boreal forests, further extending recovery time. The negative impact of the severity of LSFs on forest recovery was much stronger than that of post-LSF climate conditions. Soil moisture after LSFs was identified as the primary facilitating factor. Temperature generally had a positive role before 2010, but a strong negative influence on post-LSF forest recovery after 2010. These findings provide a useful reference for better understanding global forest recovery mechanisms, estimating forest carbon sinks and implementing post-LSF management accordingly.

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Fig. 1: Differences in severity of global LSFs before and after 2010.
Fig. 2: The recovery process of NDVI, LAI and GPP after LSFs.
Fig. 3: The recovery time of successfully recovered forests after LSFs.
Fig. 4: The response of forest NDVI, LAI and GPP recovery time to variations in fire severity of LSFs.
Fig. 5: Driving factors on forest recovery after LSFs.

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Data availability

Fire Events Delineation (FIRED) dataset (2001–2021) is available on the University of Colorado Boulder portal (https://scholar.colorado.edu/collections/pz50gx05h)67. NDVI, LAI, GPP and land-cover data are acquired from MODIS products (MCD12Q1.061, MOD13A1.061, MOD15A2H.061 and MOD17A2H.061) at https://www.earthdata.nasa.gov/data/instruments/modis. The Landsat imagery (Landsat 7 and 8) is from https://landsat.gsfc.nasa.gov/data/. ERA5-Land data are derived from https://cds.climate.copernicus.eu/datasets. TerraClimate dataset is derived from https://www.climatologylab.org/terraclimate.html. The Köppen–Geiger climate is available on GloH20 (https://www.gloh2o.org/)76. The aridity index data are available via Figshare at https://doi.org/10.6084/m9.figshare.7504448.v5 (ref. 77).

Code availability

All the code used for data analysis and figure generation is available via GitHub at https://github.com/laura-wq/Fire-recovery-time.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (grant no. 42192580 to Q.W., grant no. 42171399 to Z.C. and grant no. 42125101 to C.W.).

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Authors and Affiliations

  1. State Key Laboratory of Remote Sensing and Digital Earth, Faculty of Geographical Science, Beijing Normal University, Beijing, China

    Qiancheng Lv, Ziyue Chen, Zeyu Yang, Jianqiang Hu, Chaoqun Zhang, Yuheng Fu & Qiao Wang

  2. The Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China

    Chaoyang Wu

  3. CSIC, Global Ecology Unit CREAF-CSIC-UAB, Barcelona, Spain

    Josep Peñuelas

  4. School of Geographical Sciences, Southwest University, Chongqing, China

    Lei Fan

  5. State Key Laboratory for Ecological Security of Regions and Cities, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China

    Yongxian Su

  6. School of Geography and Ocean Science, Nanjing University, Nanjing, China

    Manchun Li

  7. College of Land Science and Technology, China Agricultural University, Beijing, China

    Bingbo Gao

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  1. Qiancheng Lv
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Contributions

Conceptualization: Q.L. Investigation: Q.L., Z.C., J.P., L.F., Y.S., C.W. and Z.Y. Methodology: Q.L. Writing—original draft: Q.L. Writing—review and editing: Q.L., Z.C., J.P., L.F., Y.S., C.W., Z.Y., Y.F., Q.W., M.L., B.G., C.Z. and J.H.

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Correspondence to Ziyue Chen or Chaoyang Wu.

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Extended data

Extended Data Fig. 1 Three specific patterns of forest recovery after LSFs.

All cases occurred in North America after 2010. a. The forest successfully recovered within seven years after LSFs. b. The forest did not successfully recover within seven years after LSFs, but maintained ongoing recovery. c. The forest did not successfully recover within seven years after LSFs, and presented a stagnation in the recovery process.

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Lv, Q., Chen, Z., Wu, C. et al. Increasing severity of large-scale fires prolongs recovery time of forests globally since 2001. Nat Ecol Evol 9, 980–992 (2025). https://doi.org/10.1038/s41559-025-02683-x

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