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.

Accurate, long time-series, high-resolution mapping of built-up land dynamics is essential for understanding urbanization and its environmental impacts. Despite advances in remote sensing and classification algorithms, built-up land mapping which only uses spectral data and derived indices remains prone to uncertainty. We mapped the extent of built-up land in the North China Plain, one of China’s most important agricultural regions, from 1990 to 2019 at three-yearly intervals and 30 m spatial resolution. We applied Discrete Fourier Transformation to dense time-stack Landsat data to create Fourier predictors to reduce mapping uncertainty. As a result, we improved the overall accuracy of built-up land mapping by 8% compared to using spectral data and derived indices. In addition, a temporal correction algorithm applied to remove misclassified pixels further improved mapping accuracy to a consistently high level (>94%) over the time periods. A cross-product comparison showed that our maps achieved the highest accuracies across all years. The built-up land area in the North China Plain increased from 37,941 km² in 1990–1992 to 131,578 km² in 2017–2019. Consistent, high-accuracy, long time-series built-up land mapping provides a reliable basis for formulating policy and planning in one of the most rapidly urbanizing regions on this planet.

Energy crops are a basic material in the bioenergy industry, and they can also mitigate carbon emissions and have environmental benefits when planted on marginal lands. The aim of this study was to evaluate the potential productivity of energy crops on marginal lands in China. A mechanistic model, combined with energy crop and land use characteristics, and meteorological and soil parameters, was used to simulate the potential productivity of energy crops. There were three main results. 1) The total marginal land in China was determined to be 104.78 × 10⁶ ha. The 400-mm precipitation boundary line, which is the dividing line between the semi-humid and semi-arid zones in China, also divided the marginal land into shrub land and sparse forest land in the southeast and bare land, bare rock land, and saline alkali land in the northeast. 2) The total area of the marginal land suitable for planting energy crops was determined to be 55.82 × 10⁶ ha, with Xanthoceras sorbifolia and Cerasus humilis mainly grown in the northern China, Jatropha curcas and Cornus wilsoniana mainly grown in the southwest and southeast, and Pistacia chinensis mainly grown in the central area, while also having a northeast-southwest zonal distribution. 3) Taking the highest yield in overlapping areas, the potential productivity of target energy crops was determined to be 32.63 × 10⁶ t/yr. Without considering the overlapping areas, the potential productivity was 6.81 × 10⁶ t/yr from X. sorbifolia, 8.86 × 10⁶ t/yr from C. humilis, 7.18 × 10⁶ t/yr from J. curcas, 9.55 × 10⁶ t/yr from P. chinensis, and 7.78 × 10⁶ t/yr from C. wilsoniana.

Australia is committed to achieving net-zero greenhouse gas (GHG) emissions by 2050 and nature-positive targets aligned with the Global Biodiversity Framework. Both commitments require extensive changes in land use and management (e.g., reforestation) which could compromise agricultural production and adversely impact water availability. This study assesses the potential of Australia’s land sector to simultaneously deliver on its commitments to national net-zero emissions and biodiversity goals, while meeting increasing domestic and export demand for agri-food production, without pushing catchments into water stress. Using the Land-Use Trade-Offs model version 2 (LUTO2), we simulated land-use and management pathways across the Australian continent which meet these environmental and agricultural objectives through to 2050 at high spatial and temporal resolution. Our results show that it is possible to achieve ambitious GHG emissions and biodiversity targets and simultaneously meet increasing agricultural demand. However, achieving these multiple objectives requires substantial changes in land use and management including the structural adjustment of major agricultural commodities and large-scale adoption of a suite of agricultural management practices, in addition to extensive conversion of land to non-agricultural uses. Notably, non-agricultural land uses such as Environmental plantings (mixed local native species) emerged as critical for simultaneously delivering biodiversity and GHG emissions targets. These findings offer actionable insights for policymakers, landholders, environmental planners, and industry stakeholders, informing strategic decisions about the type of changes in land-use and management required to support a sustainable, productive, and economically viable transition towards a nature positive net-zero and sustainable future for Australia.