Exploring the Impact of Grain-for-Green Program on Trade-Offs and Synergies among Ecosystem Services in West Liao River Basin, China.

Remote. Sens.(2023)

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Abstract
Natural ecosystems of the West Liao River basin (WLRB) in northeast China have been damaged by both natural and human factors from the 1990s. Since 2000, China's Grain-for-Green Program (GFGP) has been widely adopted with the aim of improving ecosystem services. An accurate evaluation of the eco-hydrological effects for policy implementation is essential to provide references for further restoration of ecosystem services. This study quantified and characterized the ecosystem services and their trade-offs/synergies using models and statistical methods in the WLRB from 1990 to 2020. Moreover, the impact of key drivers on ecosystem services was evaluated by the difference-in-differences model. Among them, the study mainly investigated how GFGP affects ecosystem services. The results confirmed that the water yield, carbon sequestration, habitat quality, and total ecosystem service of the WLRB decreased in the pre-GFGP period (1990-2000). However, this tendency was reversed in the regions where the GFGP was implemented during the period of 2001-2020. Furthermore, a synergistic relationship was shown among carbon sequestration, soil conservation, and habitat quality. Additionally, there were tradeoffs between water yield and the other three ecosystem services, especially in mountain areas. The GFGP could restore carbon sequestration, habitat quality, and total ecosystem services by 1.3%, 2.1%, and 0.6%, respectively. Nevertheless, GFCP may enlarge the tradeoff and imbalance between water yield and habitat quality. Results highlight the need for the governance of ecosystem protection and suggest natural restoration in the mountain area for maintaining water yield and helping ecosystem restoration. Timely adjustment of the policy implementation areas is the key to improving and balancing multiple ecosystem services in the future.
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Key words
ecosystem services, driving factor, land use and climate change, tradeoff, difference-in-differences model
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