Detecting Spatiotemporal Dynamics and Driving Patterns in Forest Fragmentation with a Forest Fragmentation Comprehensive Index (FFCI): Taking an Area with Active Forest Cover Change as a Case Study

Forests play an irreplaceable role in preserving soil and water, as well realizing carbon neutrality. However, logging urban expansion have caused widespread forest fragmentation globally, resulting biodiversity loss emissions. Therefore, it is a prerequisite to develop comprehensive index for evaluating the degree of propose effective policies protection restoration. In this study, (FFCI) was constructed through principal component analysis (PCA) based on land-use data from 2000 2020 Fujian Province, composed five commonly used landscape metrics: patch density (PD), largest (LPI), mean area (MPA), aggregation (AI), division. Then, semivariogram function moving windows method were employed explore scale effect spatiotemporal variations FFCI. The spatial autocorrelation distinguish relationship fragmentation, while driving mechanisms explored using geographic detector (GD). results show that optimal reflect window 3500 m. proposed FFCI could explain more than 85% information all metrics, effectivity validated by urban–rural gradient transect analysis. We also found that, despite having highest coverage China, Province has experienced severe fragmentation. High medium accounted over 50% types with decreasing trends low very increasing high time, indicating study aggravated time. Moreover, distribution pattern mainly high–high clusters low–low clusters, showing trend year year. areas distributed center coastal cities, internal cities western central regions had relatively Additionally, differentiation variation influenced elevation, slope, nighttime light intensity. superimposed impact two factors greater individual factors. These provide approach assessing offer scientific support mitigating