Trade-off among grain production, animal husbandry production, and habitat quality based on future scenario simulations in Xilinhot

The balance and optimization of ecosystem services (ESs) are the basis of spatial planning and ecological landscape design. Selecting suitable ESs and developing integrated, quantitative, and spatially explicit assessment models is the key to balance research. In Xilinhot in eastern Inner Mongolia, China, grain production, animal husbandry production, and habitat quality are key ESs that affect the livelihoods of local farmers and herders and the regional ecological balance. Based on GlobeLand30 data for 2000–2020, we designed six future land scenarios for the region and used the future land use simulation (FLUS) model to simulate the land use/cover scenarios in 2030. Then, we analyzed staple grain production (SGP), sustainable stocking capacity (SSC), and habitat quality (HQ) under each scenario, and constructed a multi-ES comprehensive trade-off method, using the comprehensive trade-off score (CTS) to measure their overall development quality. The results show the following. (1) Under various scenarios, the SGP is negatively correlated with SSC and HQ, and the SSC is positively correlated with HQ. (2) In the inertial development scenario, the economic development priority scenario, and the quality habitat protection scenario, the SGP will increase, the SSC and HQ will decrease; among these scenarios, the economic development priority scenario is the most significant; their CTSs are 0.97, 0.95, and 0.98, respectively. In the ecological comprehensive governance scenario, the SSC will increase, SGP and HQ will decrease, and CTS is 0.98. (3) Based on the comprehensive trade-off analysis, the economic and ecological coordination scenario is the most beneficial for regional sustainable development. It achieves the stability of the SGP; although the SSC decreases slightly, the negative impact can be offset by a larger improvement in HQ. This paper provides clear policy suggestions for regional development, and the methodological framework we have constructed provides a reference for the study of complex land scenario simulations and multi-ecosystem service comprehensive trade-offs.