Assessment of forest fire vulnerability in Chir pine forest of Pallandri, Azad Jammu and Kashmir (AJK) Pakistan

Abstract

This study assesses the vulnerability of Chir Pine (Pinus roxburghii) forests to wildfires in Pallandri, Azad Jammu and Kashmir (AJK), Pakistan, using spatial modeling and bioclimatic data. The MaxEnt (Maximum Entropy) model was employed to predict fire-prone zones by analyzing environmental variables and field-based presence data. A total of 63 sampling plots were established to collect data on tree height, diameter, stocking density, and spatial coordinates, alongside 19 bioclimatic variables. Key factors influencing fire vulnerability included forest density, fuel load from dry pine needles, and topographical aspects, particularly in north- and east-facing slopes. The model exhibited high accuracy, validated by area under the curve (AUC) metrics and jackknife tests, highlighting NDVI and land cover type (GLC2000) as major contributors. Results indicated that high-density stands with reduced tree spacing and smaller diameters were more prone to fire, especially during the peak fire season from May to July. The results highlight the critical importance of implementing effective forest management strategies, enhancing fire prevention efforts, and promoting community education initiatives to reduce the risk of wildfires in the area. This study provides critical insights for conservation planning, habitat suitability mapping, and resource allocation in the face of escalating climate-induced wildfire threats.