Influence of land use change on the ecosystem service trade-offs in the ecological restoration area: Dynamics and scenarios in the Yanhe watershed, China

Land use change can result in variations in ecosystem services (ESs) and their relationships. Studying the temporal dynamics of ESs and their relationships can support scenario analyses that provide the theoretical basis for policy decisions and regional ecosystem management. Previous studies have revealed the trade-offs between two ESs on multiple scales, while the trade-offs between multiple ESs require further analysis. Furthermore, trade-offs are rarely considered in scenario constructions, which weakens the ability of scenarios to inform land use policy. In this study, the InVEST model was applied to assess carbon sequestration, habitat quality, nutrient retention, sediment retention and seasonal water yield at five-year intervals from 1990 to 2015 and to construct five simulated scenarios that represented different ecological restoration and land reclamation policies. The results indicated that the Grain for Green Project (GFGP) increased all ESs, with seasonal water yield increasing by approximately 1.29 times above the initial stage. However, decreasing cropland area reduced the correlations between ESs both in trade-offs and synergies. Among all scenarios studied, the Returning Cropland to Grassland trade-off scenario had the maximum effect, while the natural succession to shrubland scenario had a minimum effect at the pixel level. Except for the land reclamation scenario, the overall ES benefits in the other scenarios exceeded the benefits received in 2015. Given the extent of watershed areas impacted by different overall ES benefit and trade-off situations, the Returning Cropland to Grassland scenario appears to best reduce the impacts of the worst situation compared to 2015, reducing the negative impacts by 22.6%. We suggest that scenarios that combine both overall ESs values and their trade-offs can support more effective and efficient land use decisions. (C) 2018 Elsevier B.V. All rights reserved.