Abstract
In coupled human–environment systems, ignition heterogeneity and spatial non-stationarity are central to precision wildfire prevention. Using a DPS–CHANS framework and a spatially explicit Geo-XGBoost model, this study examines wildfire evolution and nonlinear interactions in Liangshan Prefecture (2004–2024). Human-caused ignitions accounted for 95.7% of identified fires, with agricultural burning (158 cases) and smoking (62 cases) being the dominant production and non-production sources, respectively. Wildfire occurrence showed strong spatio-temporal concentration, although high ignition-frequency zones did not always correspond to large burned areas. Agricultural burning generated the largest cumulative burned area (4440 ha), whereas powerline-related fires were less frequent but more severe per event. Elevationally, human-caused fires clustered at 1500–2500 m, while lightning-caused fires peaked at 2516.5 m. Nonlinear interaction analysis revealed ignition-specific and spatially non-stationary risk formation. Agricultural fire risk increased when VPD exceeded 1.02 kPa, with the strongest interaction observed for VPD × relative humidity (0.389). Lightning fires were concentrated in high-mountain canyons and primarily controlled by temperature and lightning frequency (VPD × vegetation interaction = 0.153). These findings demonstrate that wildfire risk in mountainous regions is an ignition-specific product of coupled meteorological, ecological, and human processes. Our results advocate for a transition toward process-based, ignition-specific, and regionally differentiated management strategies.
Similar content being viewed by others
Global lightning-ignited wildfires prediction and climate change projections based on explainable machine learning models
Human-ignited fires result in more extreme fire behavior and ecosystem impacts
Compounding effects of climate change and WUI expansion quadruple the likelihood of extreme-impact wildfires in California
Acknowledgements
This work was supported by the Natural Science Foundation of Sichuan Province (Grant Nos. 2025ZNSFSC1138 and 2025ZNSFSC0333), the National Natural Science Foundation of China (Grant No. 42205195), the Innovation and Development Special Project of the China Meteorological Administration (Grant No. CXFZ2026J024), and the Science and Technology Program of Sichuan Province (Grant No. 2024YFTX0016).
Author information
Authors and Affiliations
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
Supplementary Information (download PDF )
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Reprints and permissions
About this article
Cite this article
Liu, J., Wang, Y., Sun, Y. et al. Spatially non-stationary wildfire risk formation driven by nonlinear ignition–driver interactions in a mountainous socio-ecological system.
npj Nat. Hazards (2026). https://doi.org/10.1038/s44304-026-00226-3
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s44304-026-00226-3
Source: Ecology - nature.com
