Alpine meadows are recognized as a core component of the ecological security barrier on the Qinghai-Tibet Plateau, whose patchy degradation is closely linked to the activities of the plateau pika (Ochotona curzoniae). To address the limitations of traditional monitoring methods, including low efficiency and oversimplified characterization of bare patches, a plateau pika disturbance index (PDI) is constructed by integrating bare patch area (PA), patch shape index (PSI), patch aggregation index (PAI), and Patrick’s richness index using UAV remote sensing and machine learning. The nonlinear response relationship between the PDI and bare patch coverage was subsequently analyzed. The results demonstrate these as follows. The random forest model achieves the highest accuracy in bare patch extraction, with an overall accuracy of 96.03% (Kappa = 0.920 7), significantly outperforming other classification methods. The PDI is effective in categorizing disturbance intensity levels and reveals distinct spatial heterogeneity: moderately disturbed areas are characterized by highly fragmented and locally aggregated bare patches, whereas severely disturbed areas exhibit a notable decline in aggregation due to patch merging. Furthermore, a marked reduction in disturbance intensity (R² = 0.759) is observed once the bare patch coverage reaches a threshold of 21.7%, suggesting that habitat deterioration may induce pika migration, thereby revealing a “self-limiting” mechanism in pika activity. These results indicate a “strengthening-weakening” nonlinear coupling between plateau pika activity and bare patch expansion, and this coupling feature and its spatial-pattern differences provide a quantitative basis for identifying degradation critical states and implementing level-specific management in alpine meadows. suggesting that habitat deterioration may induce pika migration, thereby revealing a “self-limiting” mechanism in pika activity. These results indicate a “strengthening-weakening” nonlinear coupling between plateau pika activity and bare patch expansion, and this coupling feature and its spatial-pattern differences provide a quantitative basis for identifying degradation critical states and implementing level-specific management in alpine meadows.