Synergies and trade-offs among ecosystem services (ESs) are central to sustainable regional management, yet their interactions often display nonlinear behavior under the combined influences of climate variability and human activities. These relationships are not static but may shift abruptly when critical thresholds are crossed, leading to reorganized patterns of synergy and trade-off. Although previous studies have explored long-term or static ESs trends, abrupt transitions and their underlying drivers remain insufficiently understood. To address this gap, we developed an integrated framework that couples breakpoint detection with machine learning to examine the spatiotemporal dynamics, interaction patterns, and driving mechanisms of ESs on the Loess Plateau from 1990 to 2022. The results show that (1) net primary productivity (NPP), soil conservation (SC), and water yield (WY) increase from northwest to southeast, while habitat quality (HQ) exhibits strong spatial heterogeneity driven by land-use intensity and habitat fragmentation. (2)Strong synergies were observed among NPP, SC, and WY, reflecting the ecological benefits of afforestation and reforestation, whereas HQ maintained weak and unstable correlations with other services. (3)ESs relationships underwent three major transitions in 1999, 2004, and 2011, corresponding to strengthened HQ–NPP synergy, a sharp rise in SC–NPP interaction, and further enhancement of HQ–SC. These transitions were associated with changing contributions from climatic and socioeconomic drivers, reflecting the dynamic influence of climate variability and human activities. This study advances understanding of ES dynamics in fragile ecosystems and provides guidance for restoration and adaptive management in semi-arid regions. • Developed an integrated framework to detect abrupt shifts in ecosystem service interactions. • Identified three critical breakpoints (1999, 2004, 2011), revealing enhanced ES synergies. • Revealed shifting contributions of climate and socioeconomic drivers over time.
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董彭蓓 et al. (Sun,) studied this question.
www.synapsesocial.com/papers/69e7138bcb99343efc98d00d — DOI: https://doi.org/10.1016/j.ecolind.2026.114887
董彭蓓
Zongping Ren
Guoce Xu
Ecological Indicators
Institute of Earth Environment
Xi'an University of Technology
Shaanxi Institute of Zoology
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