Optimization of ecosystem services trade-offs based on NSGA-III and TOPSIS: A case study of the Lower Yellow River Region, China

Abstract

Understanding and managing the complex trade-offs among multiple ecosystem services (ESs) against the backdrop of rapid urbanization is critical for achieving sustainable ecological and socio-economic development in urbanized areas. Taking the rapidly urbanizing Lower Yellow River Region (LYRR) as a typical case area, this study investigated the spatiotemporal evolution characteristics of five ESs including water yield (WY), carbon storage (CS), soil conservation (SC), food production (FP), and habitat quality (HQ) from 1990 to 2020, utilizing multi-source spatiotemporal data and ecological process modeling. Next, correlation analysis was applied to assess their trade-offs and synergies. On this basis, a multi-objective land use spatial optimization model was constructed by integrating the non-dominated sorting genetic algorithm III (NSGA-III) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), aiming to identify optimal land use configuration scheme for balancing competing ESs under diverse policy scenarios. The results indicate that ESs exhibit diverse evolutionary trends and significant spatial heterogeneity from 1990 to 2020, with most being significantly negatively impacted by urban expansion. In addition, a strong trade-off relationship was observed between WY and CS, HQ, and SC, which intensified over time alongside urbanization. Importantly, optimizing land use spatial patterns can mitigate these trade-offs. For instance, converting 1.3 % of cropland into ecological land under the ecological conservation priority scenario increased CS by 0.26 % and improved HQ by 0.49 %, while maintaining stable FP and WY levels. The carbon sequestration priority scenario was realized by increasing woodland and cropland area, a strategy that not only enhanced HQ by 0.31 % and CS by 0.29 %, but also increased FP by 3.4 × 10⁴ tons. Our findings advance the understanding of ESs trade-offs in rapidly urbanizing areas and provide a scientific foundation for land use optimization and ecosystem management in the Yellow River Basin.