Quantifying and mapping trans‐boundary ecosystem service (ES) flows can help identify dependencies and responsibilities for promoting economic development and environmental sustainability between nations, but few studies have focused on ES flows beyond national boundaries. Our case‐study region—Central Asia—hosts one of the largest dryland areas in the world, and this ecosystem is vulnerable to climate variability and anthropogenic impacts. Understanding ES supply, demand and flows is essential for supporting human wellbeing, livelihoods and economic development. In this study, we mapped the supply, demand and flows of four ES including freshwater provision, food provision, carbon sequestration and cultural (recreation) services between the five Central Asian nations of Kazakhstan, Kyrgyzstan, Uzbekistan, Tajikistan and Turkmenistan for the year 2016. We quantified the spatial patterns in ES supply and demand at local and regional scales, driven by environmental heterogeneity and socio‐economic development, and revealed complex telecoupling of ES flows between nations. Kazakhstan provided the greatest amount of ES to other countries, especially food provision and carbon sequestration, while Uzbekistan was the biggest ES beneficiary, especially from freshwater and food provision services. Our analysis of trans‐boundary ES flows helps to understand the complex telecoupling and rich interdependencies between people and nature between different countries. This information is essential for policy making to balance human and ecological needs, enhance the management of natural capital, and sustain ES provision in our metacoupled world. A free Plain Language Summary can be found within the Supporting Information of this article.

Water quality data represent a critical resource for evaluation of the well-being of aquatic ecosystems and assurance of clean water sources for human populations. While the availability of water quality datasets is growing, the absence of a publicly accessible national water quality dataset for both inland and the ocean in China has been notable. To address this issue, we utilized R and Python programming languages to collect, tidy, reorganize, curate, and compile three publicly available datasets, thereby creating an extensive spatiotemporal repository of surface water quality data for China. Distinguished as the most expansive, clean, and easily accessible water quality dataset in China to date, this repository comprised over 330 000 observations encompassing daily (3588), weekly (217 751), and monthly (114 954) records of surface water quality covering the period from 1980 to 2022. It spanned 18 distinct indicators, meticulously gathered at 2384 monitoring sites, which were further categorized as daily (244 sites), weekly (149 sites), and monthly (1991 sites), ranging from inland locations to coastal and oceanic areas. This dataset will support studies relevant to the assessment, modeling, and projection of water quality, ocean biomass, and biodiversity in China, and therefore make substantial contributions to both national and global water resources management. This water quality dataset and supplementary metadata are available for download from the figshare repository at https://doi.org/10.6084/m9.figshare.22584742 (Lin et al., 2023b).

Identifying relationships among multiple ecosystem services (ESs) at different scales and the factors affecting such relationships is the foundation for sustainable ecosystem management. A case study was conducted in the Sihu Lake Basin, an agricultural basin in Central China, to examine the interactions among ESs across different scales and the responses to landscape pattern changes (2000–2020). The results indicate that (1) agricultural land and wetlands were converted into construction land and gradually decreased in size; forestland and artificial channels gradually increased in size. (2) ESs had spatial heterogeneity in their strength at the grid and county scales. (3) Most relationships between ESs were synergistic at the grid and county scales, and most correlations increased as the scale increased due to landscape consistency. (4) The landscape metrics explained approximately 45.56–61.06% of the variations in ESs, and the main influencing factor was agricultural land. Our results demonstrated that the construction of rivers and channels, dense and widely distributed agricultural land and construction land were more positively correlated with increasing crop production and nitrogen export, whereas forestland exhibited a stronger contribution to increasing carbon storage and water yield. These findings explore appropriate management methods for agricultural development and ecological conservation in agricultural basins.