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Forest fragmentation susceptibility assessment using the weight of evidence model in Mizoram, India

Year: 2026
Type: article
Abstract: Forest fragmentation represents one of the major threats to biodiversity and ecosystem sustainability. Despite having the highest proportion of forest cover percentage to total geographical area among Indian states, forest fragmentation susceptibility in Mizoram remains a serious concern. The present study assesses forest fragmentation susceptibility in the state of Mizoram using RS-GIS based Weight of Evidence model (WOE). LULC maps for 2005 and 2025 were generated using Landsat-5 and Landsat-9 imageries, and the Landscape Fragmentation Tool (LFT v2.0) was used to delineate the fragmentation classes. Seven causative factors, viz. altitude, slope, aspect, distance to roads, distance to streams, distance to agricultural land, and distance to built-up areas were incorporated into the WOE Model. A multicollinearity analysis was conducted which confirmed the suitability of the selected variables (VIF < 5). The results reveal that nearly 41.06% of the study area falls under moderate to very high forest fragmentation susceptibility categories. Areas located close to built-up and agricultural land, and lying on gentle slopes at elevations between 1000 and 2000 m are more prone to fragmentation. Areas near roads (< 1000 m) and streams (< 500 m) were found to be susceptible to fragmentation indicating the influence of anthropogenic activities and landscape accessibility on forest fragmentation patterns. The model was validated using the Receiver Operating Characteristic (ROC) curve and achieved a good predictive accuracy, with an Area Under Curve (AUC) value of 0.831. The findings bring into light the need for targeted conservation and management interventions, particularly in areas experiencing increasing anthropogenic pressure from agricultural and built-up expansion. The generated susceptibility provides a valuable decision-support framework for policymakers and planners to mitigate future fragmentation and ensure long-term sustainability of Mizoram’s forest ecosystems.
Institution: Gauhati University
Language: English
Subfield: Ecology
Open Access status: diamond
OpenAlex ID: W7224922756
FWCI:
Cites: 52
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Related to: 10