Why the world needs a wildfire risk prediction system based on plant functional traits and moisture—before fires ignite
This perspective proposes a new wildfire risk prediction system by integrating plant functional traits with microwave-derived vegetation optical depth to detect critical moisture thresholds before ignition. By shifting from reactive, thermal-based detection to proactive, ecology-driven forecasting, this approach could enhance preparedness, guide targeted mitigation, and improve resource allocation globally and would help reduce wildfire impacts on biodiversity, infrastructure, and communities in an era of intensifying climate-driven fire risk.
Authors
- Andrew R. Marshall (ORCID: https://orcid.org/0000-0002-3261-7326)
- Shawkat I. Sohel
Institutions
- University of the Sunshine Coast (AU)
Publication Details
- Journal
- npj natural hazards.
- Published
- 2025-10-21
- DOI
- https://doi.org/10.1038/s44304-025-00149-5
- Citations
- 1
- Primary Topic
- Fire effects on ecosystems
- Type
- article
- Field-Weighted Citation Impact
- 1.11