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Various anthropogenic disturbances, such as urbanization, agricultural production, and infrastructure development, are contributing to global and regional ecosystem degradation. However, comprehensive quantitative assessment methods for evaluating regional-scale anthropogenic impacts remain insufficient. This study introduces a comprehensive assessment framework based on ecological integrity (EI) derived from the landscape condition model (LCM), combined with commonality analysis and other quantitative methods. This framework was applied to the Beijing–Tianjin–Hebei (BTH) region in North China to assess the spatio-temporal variations and spatial aggregation of EI, identify the major drivers of EI degradation, and determine the formation mechanisms of resultant EI patterns. The anthropogenic impacts, as measured by EI, exhibit significant spatial and aggregation heterogeneity across functional zones. This heterogeneity, along with the observed temporal variations (2000–2022), is attributed to diverse anthropogenic disturbances within intricate biophysical and socioeconomic contexts. This framework can indirectly improve the R2 of multiple linear regression models related to EI by identifying grassland and cropland as suppressor variables to enhance the predictive capacity of other variables. Consequently, this framework enables decision-makers to accurately identify major drivers of EI degradation, such as road construction and urbanization, and understand the combined effects of major drivers and suppressor variables on the resultant EI patterns. Lastly, within specific policy contexts, this framework offers several management implications for mitigating anthropogenic threats to EI, including effectively regulating urbanization and restoring forest landscapes. This framework provides fundamental support for anthropogenic impact assessment and management strategy design at a regional scale. |
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