Forest fire and its key drivers in the tropical forests of northern Vietnam
P. T. Trang A B , M. E. Andrew A , T. Chu C D and N. J. Enright A *
+ Author Affiliations
- Author Affiliations
A Environmental and Conservation Sciences, Murdoch University, Murdoch, WA, 6150, Australia.
B Faculty of Forest Resource and Environmental Management, Vietnam National University of Forestry, Xuan Mai, Chuong My, Hanoi, 10000, Vietnam.
C Department of Geography and Planning, University of Saskatchewan, Saskatoon, SK S7N5C8, Canada.
D Faculty of Forestry, Vietnam National University of Forestry, Xuan Mai, Chuong My, Hanoi, 10000, Vietnam.
* Correspondence to: n.enright@murdoch.edu.au
International Journal of Wildland Fire 31(3) 213-229 https://doi.org/10.1071/WF21078
Submitted: 15 June 2021 Accepted: 16 December 2021 Published: 17 February 2022
© 2022 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of IAWF. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)
Abstract
Fire increasingly threatens tropical forests in northern Vietnam as climate changes and human population grows. Understanding fire occurrence patterns may support more effective forest management and reduce fire risk. We investigated spatiotemporal patterns and drivers of wildfire across three provinces in northern Vietnam and assessed the effectiveness of the Modified Nesterov index (MNI) fire danger rating system. We explored fire occurrence and size within and between years and forest types using descriptive analyses and developed spatiotemporal Maximum Entropy (Maxent) models incorporating variables representing potential drivers of fire, including weather, fuel, topography and human activity. Most fires occurred late in the dry season and fires were most common in natural forest. Maxent models successfully predicted fire occurrence (area under the receiver operating characteristic curve (AUC) values 0.67–0.79). While the contributions of drivers varied among provinces, MNI, temperature, elevation and distance to road were consistently important. The model for combined provinces showed that fire probability was greater under higher temperature and MNI, in areas with lower population, farther from roads, at higher elevations and in natural forests. This study suggests that an assessment integrating multiple drivers better predicts fire occurrence than a system based on weather alone and may support improved fire management and education in northern Vietnam.
Keywords: forest fire occurrence, human activity, Maxent, Modified Nesterov index, plantation forest, rainforest, topography, weather conditions.
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