Document Type : Original Article
Authors
1
MSc. in Rangeland Science and Engineering, Faculty of Natural Resources and Earth Sciences, Shahrekord University, Shahrekord, Iran.
2
Associate Prof., Faculty of Natural Resources and Earth Sciences, Shahrekord University, Shahrekord, I.R. Iran.
3
Ph.D. of Rangeland Science and Engineering, Faculty of Natural Resources and Earth Sciences, Shahrekord University, Shahrekord, Iran.
Abstract
Wildfires significantly contribute to land degradation and threaten forest and rangeland ecosystems in arid and semi-arid areas. They reduce vegetation cover, speed up soil erosion, and weaken ecosystem stability. This research focused on modeling wildfire risk distribution and examining how climate change might shift fire-prone zones in the Central Zagros, using the Maximum Entropy (MaxEnt) model. The model was developed using 1,910 wildfire records from 2020 to 2024, along with 14 environmental variables, including bioclimatic factors, topography, land use, and the Normalized Difference Vegetation Index (NDVI). After removing multicollinearity among predictor variables, the MaxEnt model was applied. Climate change impacts were assessed using the HadGEM2-CC and MRI-ESM2-0 General Circulation Models (GCMs) under SSP2-4.5 and SSP5-8.5 scenarios for 2050 and 2070. The model showed strong predictive ability with an AUC of 0.82. Key predictors of wildfire risk included annual precipitation, land use, and slope, which together accounted for 67.9% of the model. About 27.9% of the area was classified as high risk, mainly in the western, northwestern, and central regions of the Central Zagros. Climate projections suggest that climate change may create new fire-prone zones across the region, affecting between 5.87% and 15.58% of the area depending on the climate model and emission scenario. This indicates a spatial shift in wildfire hotspots. The results offer crucial insights for prioritizing management areas, optimizing vegetation fuel control, establishing early warning systems, and planning proactive strategies to prevent land degradation and promote sustainable use of arid and semi-arid ecosystems.
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