Vegetation net primary productivity (NPP) reflects available biomass and land carrying capacity, serving as a critical biophysical variable coupling climate fluctuations, resources, and prehistoric subsistence strategies. The farming-pastoral ecotone of northern China, located at the East Asian summer monsoon margin, is a pivotal region for early agriculture expansion and settlement evolution. However, quantitative Holocene NPP dynamics and their socio-ecological impacts remain limited. Utilizing the modern pollen dataset of Asia and MODIS data, we developed a random forest-based pollen-NPP transfer function and applied it to multiple Holocene sequences across the farming-pastoral ecotone. Combining this reconstruction with Haminmangha site multi-proxy records (pollen and phytoliths), TraCE-21ka precipitation simulations, and bioarchaeological data, we analyzed how NPP variations influenced prehistoric subsistence and settlement vulnerability. Results show that regional NPP underwent three stages: an early Holocene rapid rise, a mid-Holocene high plateau (8000–5500 cal yr BP), and a fluctuating decline since 5500 cal yr BP. The mid-Holocene high NPP sustained millet agriculture expansion, population growth, and settlement development. Post-5500 cal yr BP, declining NPP destabilized rainfed cultivation, prompting populations to diversify subsistence by intensifying hunting, gathering, fishing, and herding within agriculture-dominated frameworks. Locally, Haminmangha records reveal a forest-steppe to open steppe transition after ∼5250 cal yr BP under a cooling-drying trend, with an NPP drop around 5000 cal yr BP coinciding with the anomalous abandonment of the Haminmangha and Miaozigou sites. This abnormal abandonment likely stemmed from the combined effects of diminished agricultural capacity, subsistence diversification, heightened steppe epidemic risks, and cumulative social vulnerability triggered by declining NPP. Consequently, NPP acts not only as an ecological indicator of climate change but also as a key mediating variable unraveling climate-resource-society coupling mechanisms.
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Yan et al. (2026) studied this question.
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