期刊
LANDSCAPE ECOLOGY
卷 32, 期 6, 页码 1181-1199出版社
SPRINGER
DOI: 10.1007/s10980-017-0527-6
关键词
Multiple ecosystem services; Trade-off; Synergy; Temporal dynamics; Spatial heterogeneity; Partial correlation; LULC change; Loess Plateau
资金
- National Natural Science Foundation of China [41601182]
- National Key Research and Development Plan of China [2016YFC0501601]
- Key Project of Chinese Ministry of Education [15JJD790022]
- National Social Science Foundation of China [14AZD094]
- Fundamental Research Funds for the Central Universities [GK201603078]
- China Postdoctoral Science Foundation [2016M592743]
Human demands for ecosystem services (ES) have tremendously changed the landscape and led to degradation of ecosystems and associated services. The resolving of current eco-environmental problems calls for better understanding of the spatially explicit ES interactions to guide targeted land-use policy-making. We propose a framework to map ES in continuous time-series, based on which we further quantify interactions among multiple ES. The supply of three key ES-soil conservation (SC), net primary production (NPP) and water yield (WY)-were quantified and mapped at fine-resolution from 2000 to 2013 using easily-accessible spatial data. Pairwise ES interactions were quantified using a spatio-temporal statistical method. Spatio-temporal analyses of ES dynamics illustrated that the supply of the three ES increased over the past 14 years in northern Shaanxi, where land cover dramatically changed owing to the wide-range ecological restoration projects. Our results also revealed that ES interactions varied across locations due to landscape heterogeneity and climate difference. In the arid and semi-arid area, synergies among ES (e.g., SC vs. WY) tended to dominate in grassland, while in artificial lands ES were prone to show trade-offs. In the semi-humid area, pairwise ES (e.g., NPP vs. WY) in woodland tended to present synergies. The spatio-temporal variation of ES and their interactions resulted from coupling effect of human-induced climate and land-use change. In the long-term, spatially explicit quantification of ES interactions can help identify spatial heterogeneity in ES trade-offs and synergies, and inform regional targeted land-use policy adjustment and sustainable ecosystem management.
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