Assessing forest cover changes and fragmentation in the Himalayan temperate region: implications for forest conservation and management

This study comprehensively assessed long-term vegetation changes and forest fragmentation dynamics in the Himalayan temperate region of Pakistan from 1989 to 2019. Four satellite images, including Landsat-5 TM and Landsat-8 Operational Land Imager (OLI), were chosen for subsequent assessments in October 1989, 2001, 2011 and 2019. The classified maps of 1989, 2001, 2011 and 2019 were created using the maximum likelihood classifier. Post-classification comparison showed an overall accuracy of 82.5% and a Kappa coefficient of 0.79 for the 2019 map. Results revealed a drastic decrease in closed-canopy and open-canopy forests by 117.4 and 271.6 km², respectively, and an increase in agriculture/farm cultivation by 1512.8 km². The two-way ANOVA test showed statistically significant differences in the area of various cover classes. Forest fragmentation was evaluated using the Landscape Fragmentation Tool (LFT v2.0) between 1989 and 2019. The large forest core (> 2.00 km²) decreased from 149.4 to 296.7 km², and a similar pattern was observed in medium forest core (1.00–2.00 km²) forests. On the contrary, the small core (< 1.00 km²) forest increased from 124.8 to 145.3 km² in 2019. The perforation area increased by 296.9 km², and the edge effect decreased from 458.9 to 431.7 km². The frequency of patches also increased by 119.1 km². The closed and open canopy classes showed a decreasing trend with an annual rate of 0.58% and 1.35%, respectively. The broad implications of these findings can be seen in the studied region as well as other global ecological areas. They serve as an imperative baseline for afforestation and reforestation operations, highlighting the urgent need for efficient management, conservation, and restoration efforts. Based on these findings, sustainable land-use policies may be put into place that support local livelihoods, protect ecosystem services, and conserve biodiversity.