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• W2896676932 abstract "Land change, especially urban land expansion, is increasingly triggered by remote demands for goods and services rather than by purely local drivers, exerting pressure on ecosystem services beyond local boundaries. This effect has been termed as ‘tele-connections’. China has become the world's second largest economy. Understanding the tele-connections between China's future urban growth and its impacts on ecosystem services is essential to reconcile the conflict between socioeconomic developments and ecological protection. To this end, we propose to integrate an urban growth simulation model with the multi-region input-output (MRIO) model, thereby illustrating how urban land consumption in one region can cause ecosystem services' degradation in another. We explore the decline in ecosystem services due to urban land tele-connections under five shared socioeconomic pathway (SSP) scenarios. The results yield the direct loss of ecosystem services by 1.14–5.42% in food production, 0.06–0.44% in carbon sequestration, 0.09–0.59% in soil retention, 0.05–0.29% in sandstorm prevention, 0.12–0.80% in water retention and 0.19–1.04% in habitat provision. Uneven ecological consequences caused by domestic urban land displacement are witnessed not only in China's peripheral regions but also in developed regions. Shanghai, as the largest city in China, is expected to exert great impacts in terms of the quantity of ecosystem services decline and its spatial extent as well. Overall, the presented scenario simulations can support the establishment of effective compensation strategies toward balancing the responsibility and rights of stakeholders associated with ecological services protection." @default.
• W2896676932 created "2018-10-26" @default.
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• W2896676932 date "2019-02-01" @default.
• W2896676932 modified "2023-10-15" @default.
• W2896676932 title "Tele-connecting China's future urban growth to impacts on ecosystem services under the shared socioeconomic pathways" @default.
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• W2896676932 doi "https://doi.org/10.1016/j.scitotenv.2018.10.283" @default.
• W2896676932 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30380484" @default.
• W2896676932 hasPublicationYear "2019" @default.
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