Understanding the joint impact of anthropologic and climatic changes on ecosystem function and dynamics is among the frontiers in global environmental change studies. Carbon and water balances are especially crucial to the sustainable ecosystem and functional returns in sensitive regions such as the Mongolian Plateau. In this study, the significance of non-climatic component (NCC) on carbon and water use efficiency (CUE and WUE) is quantified among the ecosystem types on the Mongolian Plateau. We mapped the spatial gradients of carbon/water balance and delineated the hotspots of NCC-driven CUE and WUE for 2000–2013 using gross and net primary production (GPP and NPP) and evapotranspiration (ET) products derived from the MODIS databases. Significantly higher CUE and WUE values were found in Mongolia (MG) than in Inner Mongolia (IM) due to both climatic forcing (CF) and NCC. NCC was found to dominate the changes in CUE and WUE in the steppes on the plateau by over 16% and 22%, respectively, but with spatially uneven distributions. NCC-driven WUE values were much higher than those driven by CF. The hotspots for NCC-driven CUE did not overlap with those of WUE, with CUE hotspots concentrated in the east of MG and northeast of IM; WUE hotspots were found in the central and Khangai regions of MG and eastern regions of IM. The NCC-driven CUE area in MG was from population growth and the industrial shares in gross domestic product, while the NCC-driven WUE area was due to livestock growth in MG but driven by the growth of cultivated lands in IM. In sum, we conclude that NCC provoked substantial spatiotemporal changes on carbon and water use. CF and NCC effects on carbon and water balance varied in space, by ecosystem type, and between the two political entities.

Climate change and anthropogenic replantation are supposed to greatly change vegetation coverage and ecosystem stability and functions, e.g., net primary productivity (NPP), evapotranspiration (ET) and water use efficiency (WUE). Our study compared WUE of nature- and human-induced forest cover increase on the Loess Plateau since 2000 using satellite-derived Vegetation Continuous Fields (VCF), NPP, ET. This study also applied over 30 years of model-based NPP and meteorological observations to compare the stability and changes brought up by the Grain for Green Project. The result showed that the average forest coverage fraction increased from 7.1% (~4.5 × 10⁴ km²) in 2000 to 11.2% (~7.3 × 10⁴ km²) in 2014. Artificial forest cover increase occupied 76.43% of the significantly increasing tree cover regions. The role of revegetation practice in NPP and ET became gradually more dominant than climate factors in artificial forests from the northern to the southern part of the Loess Plateau. For areas experiencing limited forest coverage increase, artificial forest areas showed higher WUE than natural forest areas under similar mean annual precipitation (MAP). The difference in stability was small between neighboring natural and artificial forest areas. The northwest of the Loess Plateau had an increasing resilience, whereas the south of the Plateau had an increased resistance to precipitation and temperature change. The higher dependency of the northern reforested areas on climate fluctuation indicates a growing threat of water scarcity to the sustainability of anthropogenic reforestation in semi-arid regions.

Integrating the dynamics and interconnections of natural and human system properties into a single measure would make it simpler to reliably and repeatedly assess and compare different social-environmental systems (SES). We propose a novel metric to assess the magnitudes and variations in SES dynamics by integrating longitudinal gross domestic product, population, and ecosystem net primary production. We use annual public data across the Asian Drylands Belt (ADB) from 1992 through 2016 for 18 political entities as our testbed for assessing the efficacy of the metric. We perform cross-comparisons with existing natural and social science metrics to demonstrate the validity of the proposed metric, including the Human Development Index and the Palmer Drought Severity Index. The new metric demonstrates notable and meaningful differences in trends among the political entities that reflect major social, economic and environmental events over the 25-year period. It provides unique perspectives about the three pillar components (social, economic and environmental systems) in each of the 18 political entities (PE) of the ADB. The metric also shows meaningful associations with key economic and environmental indicators and great potential for broader application and evaluation, given additional testing in other countries, regions, and biomes.

Land-use change contributes significantly to climate change mitigation through biophysical changes (albedo, α) and biogeochemical (greenhouse gases, GHG) emissions (here refers to methane, CH₄, and nitrous oxide, N₂O). While the impact of grassland–cropland conversion on global warming potential (GWP) is well-documented globally, research remains scarce in the saline-alkaline agropastoral transition zone (APTZ) of the western Songnen Plain, Northeast China, an ecotone uniquely characterized by soil-crusting and seasonal inundation. We conducted in situ bi-weekly measurements of N₂O and CH₄ fluxes (June–September) to acquire growing season ${\mathrm{GWP}}_{{\mathrm{N}}_2\mathrm{O}}$ and ${\mathrm{GWP}}_{{\mathrm{C}\mathrm{H}}_4}$, alongside α. The study compared an undisturbed fenced meadow (FMD) with three adjacent land-use types, clipped meadow (CMD), saline-alkaline meadow (SAL), and paddy rice field (PDY), converted from FMD from 2018 to 2022. Annual α-induced GWP (GWPΔα) was positive across all converted sites (CMD, SAL, and PDY), indicating a warming effect due to lower α compared to FMD. The PDY exhibited the highest CH₄ emission (5.04 kg CO₂ m⁻² yr⁻¹), exceeding other land uses by three orders of magnitude (p < 0.05). Conversely, N₂O emissions remained consistently minimal and stable across all sites. When integrating the net ecosystem exchange of CO₂ (NEE), the PDY functioned as a net warming source. In contrast, the warming effects of α and non-CO₂ GHGs were effectively offset by the NEE in other land uses. Machine learning identified soil water content (SWC) as the dominant predictor of α across all land uses in growing season. However, a mechanistic divergence was observed, i.e., α in low saline-alkali ecosystems (FMD, CMD and PDY) was shaped by coupled biotic and soil moisture controls, whereas in the degraded SAL ecosystem, α is almost exclusively abiotic-driven. These findings demonstrate that land-use conversion in the Songnen Plain governs complex land-surface feedbacks through distinct pathways. This study provides a quantitative framework for integrating biophysical and biogeochemical impacts to optimize land management for climate resilience in saline-alkaline agropastoral ecotones.