Exploring spatial correlations between ecosystem services and sustainable development goals: a regional-scale study from China

Context Ecosystem services (ESs) are the bridge connecting natural capital and social development. Incorporating ESs into social-ecological management strategy helps to achieve the Sustainable Development Goals (SDGs). However, there is currently a lack of quantitative exploration of the correlations between ES and SDGs, especially from a spatial zoning perspective. Objectives This study attempted to explore spatial correlations between ESs and SDGs to support sustainable landscape planning in Guangdong Province, China. Methods The self-organizing feature map neural network analysis was used to characterize the spatial clustering of eight types of ESs and three types of SDGs, and the spatial explanatory power of ESs for SDGs in different zones was analyzed with the application of geographical detector. Results Guangdong Province was divided into four zones based on spatial clustering: ecological regulation dominant zone (Zone 1), production-ecology transition zone (Zone 2), key grain production zone (Zone 3), and high well-being zone (Zone 4). The high ESs values were concentrated in the Zone 1, and the high SDGs values were concentrated in the Zone 4. In the Zone 1, habitat quality and soil conservation had high explanatory power for no poverty, while water yield and soil conservation had high explanatory power for zero hunger. In the Zone 2, water yield and habitat quality had high explanatory power for no poverty. In the Zone 3, grain production and tropical cyclone impact mitigation had high explanatory power for no poverty, while soil conservation had high explanatory power for zero hunger. In the Zone 4, grain production had high explanatory power for no poverty, while landscape recreation had high explanatory power for good health. Conclusions The spatial correlations between ESs and SDGs were obviously different among regions with different social-ecological backgrounds. When implementing SDGs-oriented sustainable landscape planning, targeted strategies are needed based on the correlations between ESs and SDGs in different regions.