The trade-off and synergy relationship of ecosystem services is an important topic in the current assessment. The value of each service provided by the ecosystem is substantially affected by human activities, and conversely, its changes will also affect the relevant human decisions. Due to varying trade-offs among ecosystem services and synergies between them that can either increase or decrease, it is difficult to optimize multiple ecosystem services simultaneously, making it a huge challenge for ecosystem management. This study firstly develops a global Gross Ecosystem Product (GEP) accounting framework. It uses remote sensing data with a spatial resolution of 1 km to estimate the ecosystem services of forests, wetlands, grasslands, deserts, and farmlands in 179 major countries in 2018. The results show that the range of global GEP values is USD 112–197 trillion, with an average value of USD 155 trillion (the constant price), and the ratio of GEP to gross domestic product (GDP) is 1.85. The trade-offs and the synergies among different ecosystem services in each continent and income group have been further explored. We found a correspondence between the income levels and the synergy among ecosystem services within each nation. Among specific ecosystem services, there are strong synergies between oxygen release, climate regulation, and carbon sequestration services. A trade-off relationship has been observed between flood regulation and other services, such as water conservation and soil retention services in low-income countries. The results will help clarify the roles and the feedback mechanisms between different stakeholders and provide a scientific basis for optimizing ecosystem management and implementing ecological compensation schemes to enhance human well-being.

The question of how to balance rapid economic growth with ecosystem pressures has become a key issue in recent years. Using the Tapio decoupling model, the spatial autocorrelation model, and the LMDI decomposition model, we analyzed the spatiotemporal variation in gross ecosystem product (GEP) in Hubei Province, studied the relationship between GEP and economic growth, and analyzed the driving factors of GEP variation. The results show that, during the period 2010–2019, the decoupling coefficient between GEP and economic growth in Hubei Province gradually decreased, while the decoupling relationship changed from weak decoupling to strong decoupling; this change is reflected not only in the decoupling index values of various cities but also in the number of changing cities, so this negative change should attract the attention of policy-makers. In addition, there is a significant local spatial autocorrelation in Hubei Province, mainly distributed in the northwest and southwest of the province, and the trend is becoming increasingly obvious. As the decoupling trend is negative, it is necessary to pay attention to local autocorrelation changes, especially in highly correlated cities, and take action to prevent the further exacerbation of such decoupling to maintain healthy economic and social development. Regarding the driving factors of GEP changes in Hubei Province, cities with strong decoupling and those with weak decoupling have certain differences, and different types of decoupling cities need to adopt different strategies to alleviate pressure on the ecological environment. Cities with a weak decoupling need to address the problem of pollutant emissions associated with industrial upgrading and the positive impact of scientific and technological innovation on the ecological environment. Cities with strong decoupling should not only address pollutant discharge but also improve the area of ecological land. From the perspective of urban development, the high-quality development trend of Wuhan, Yichang, Xiantao, Qianjiang, Xianning, and other cities shows a continuous trend of improvement. Ezhou, Jingzhou, Shennongjia, and other cities need to guard against the loss of ecosystems caused by economic growth.

Rural domestic sewage management is a crucial pathway for achieving Sustainable Development Goal (SDG) 6 targets. Addressing the crucial challenge of prioritizing administrative villages for rural domestic sewage treatment at the county scale requires dedicated planning. However, county-level comprehensive evaluation models designed specifically for this purpose are currently limited. To address this gap, we developed a model based on 13 evaluation indicators encompassing village distribution characteristics, villager demographics, rural economic levels, and sanitation facility conditions. To gauge the varying emphasis on these factors by different groups, a questionnaire survey was conducted among experts, enterprises, and government departments involved in the rural sewage sector in China. Two counties from distinct regions were then chosen to validate these models. The Analytic Hierarchy Process (AHP) coupled with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method was employed to rank the importance of the factors and determine the prioritization of rural domestic sewage management in each area. The model results indicated that priority should be given to the county government, township government, ecologically sensitive areas, and administrative villages near tourist attractions in the two selected empirical counties for governance. A sensitivity analysis showed that altitude consistently exhibited high sensitivity in influencing the ranking results across all scenarios (0.4–0.6). In addition, the empirical results obtained were largely consistent with the priorities of local governments. The proposed framework offers a practical application for decision-making systems in rural domestic sewage management at the county level, providing theoretical support and scientific strategies. This holds great significance for achieving SDG 6.