Carbon neutrality is an important target in China’s efforts to combat the climate crisis. The implementation of carbon neutrality requires high crop yields in farmland ecosystems of arid regions. However, the responses of farmland ecosystems to environmental changes and their effects on the conversion and intensity of carbon sources/sinks within farmlands in arid regions remain unclear, which limits carbon sequestration. In this study, we used a set of eddy covariance systems to observe carbon and water fluxes in cotton and spring maize, two typical crops in arid regions of Northern Xinjiang in China. The carbon and water exchange and water use efficiency (WUE) of cotton and spring maize were evaluated over the entire growth cycle with respect to changes in the environment. Our results show that the carbon sequestration capacity of farmland ecosystems in arid regions is undeniable and is strongly influenced by the growth and development of plants. Spring maize, as a representative of C4 plants, exhibited a 58.4% higher carbon sequestration efficiency than cotton, a C3 plant, and they both reached their carbon sequestration efficiency peak in July. Throughout the growth period, temperature, net surface radiation, and saturated vapor pressure differences (VPD) significantly affected the carbon sequestration capacity and WUE of both crops. Optimal temperatures can maximize the carbon sequestration efficiency of cotton and spring maize; for cotton, they are 20–25 °C, and for spring maize, they are 22–27 °C, respectively. In addition, it is recommended that spring maize be harvested at the end of July when it meets the harvesting standards for silage feed and achieves the maximum carbon sequestration. Afterward, winter crops should be planted to maximize the yield and improve the carbon sequestration capacity of farmlands.

Precise regional crop yield estimates based on the high-spatiotemporal-resolution remote sensing data are essential for directing agronomic practices and policies to increase food security. This study used the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM), the flexible spatiotemporal data fusion (FSADF), and the spatial and temporal non-local filter based fusion model (STNLFFM) to calculate the normalized differential vegetation index (NDVI) of the summer maize planting area in the Southeast Loess Plateau based on the Sentinel-2 and MODIS data. The spatiotemporal resolution was 10 m and 1 d, respectively. Then, we evaluated the adaptability of the ESTARFM, FSADF, and STNLFFM fusion models in the field from the perspectives of spatial and textural characteristics of the data, summer maize NDVI growing curves, and yield estimation accuracy through qualitative visual discrimination and quantitative statistical analysis. The results showed that the fusion of ESTARFM–NDVI, FSDAF–NDVI, and STNLFFM–NDVI could precisely represent the variation tendency and local mutation information of NDVI during the growth period of summer maize, compared with MODIS–NDVI. The correlation between STNLFFM–NDVI and Sentinel-2–NDVI was favorable, with large correlation coefficients and a small root mean square error (RMSE). In the NDVI growing curve simulation of summer maize, STNLFFM introduced overall weights based on non-local mean filtering, which could significantly improve the poor fusion results at seedling and maturity stages caused by the long gap period of the high-resolution data in ESTARFM. Moreover, the accuracy of yield estimation was as follows (from high to low): STNLFFM (R = 0.742, mean absolute percentage error (MAPE) = 6.22%), ESTARFM (R = 0.703, MAPE = 6.80%), and FSDAF (R = 0.644, MAPE = 10.52%). The FADSF fusion model was affected by the spatial heterogeneity in the semi-humid areas, and the yield simulation accuracy was low. In the semi-arid areas, the FADSF fusion model had the advantages of less input data and a faster response.

Sand dune migration, as a typical dynamic process of aeolian geomorphology in arid regions, directly influences regional ecological security and infrastructure development. Focusing on the western edge of the Kumtag Desert, this study uses remote sensing imagery and field investigations, combined with multi-factor meteorological observations and CMIP6 climate scenarios, to quantitatively analyze the migration characteristics and influencing factors of representative dunes, and to construct a predictive model for future migration trends. The dominant migration direction is W–WNW–NW, which closely matches the composite resultant drift potential. The average annual migration speed is 12.86 m·a⁻¹, classifying these dunes as fast-moving; small to medium dunes migrate faster (13.84 m·a⁻¹) than large dunes (11.27 m·a⁻¹). Wind speed, sand-moving wind frequency, drift potential (DP), Vegetation Fractional Cover (FVC), and precipitation significantly affect migration speeds; wind speed is the primary driver (single-factor R² = 0.41), while precipitation (R² = 0.26) and FVC (R² = 0.27) exert a suppressing effect, particularly on small to medium dunes. Based on stepwise multiple regression analysis combined with CMIP6 multi-model predictions, under the SSP8.5 scenario, characterized by significant temperature increases, drastic fluctuations in precipitation patterns, and notable increases in wind speed, the average annual sand dune migration speed is projected to reach 18.59 m·a⁻¹ by the end of this century, an increase of 5.78 m·a⁻¹ compared to the current speeds; whereas under the SSP1–2.6 and SSP2–4.5 scenarios, changes are projected to be minor and overall relatively stable. The findings of this study provide a scientific basis for regional infrastructure and engineering planning, as well as for the renovation and protection of existing oil and power transmission lines.

The global carbon-cycle is crucial for climate change. Desert, which has long been neglected in the global carbon-cycle, may sequester enormous volumes of CO2 and play the role of a carbon-sink. As the world’s second-largest shifting desert, the Taklimakan Desert (TD) contributes substantially to desert carbon-sinks. However, the contributions of the internal processes of the TD to its carbon-sink and the long-term trend of the carbon-sink under climate change are still unclear. This study will address this important knowledge gap. Through field observations, we found that the expansion/contraction of soil air containing CO2 caused by heat fluctuation in shifting sand, in combination with salts/alkali chemistry dominates the release/absorption processes of CO2 in shifting sand. The mutual counteraction of these processes means that the TD shifting sand acts as a stable carbon-sink that had a CO2 annual uptake of 1.60×106 t•a-1 during 2004–2017. It suggests that global shifting deserts maybe uptake of ~2.125×108 t of CO2 per year. However, an increasing soil temperature-difference will stimulate soil air expansion of desert and release more CO2 into the atmosphere under climate change, causing the shifting sand carbon-sink decrease in the TD gradually in the future. These processes will be accelerated by positive feedback effect under climate change and enhance regional warming. These conclusions are very important for re-recognizing the status of deserts in the carbon-cycle, narrowing the gap in the missing carbon-sink and assessing the global carbon-cycle.

Saline–alkali soils in arid regions are increasingly recognized as critical yet underrepresented components of the global carbon cycle. However, their CO₂ flux dynamics under warming remain poorly understood. In this study, we conducted controlled growth-chamber experiments using typical saline–alkali soils from the Taklamakan Desert, where temperature, soil moisture, and atmospheric CO₂ concentrations were systematically manipulated. We quantified how warming reshaped moisture–temperature interactions regulating soil CO₂ fluxes. The results revealed a pronounced diurnal variation pattern, characterized by daytime CO₂ release and nighttime uptake. Temperature was identified as the dominant driver (R² > 0.93, p < 0.001), whereas soil moisture primarily modulated flux intensity; at 0.8 cm³ cm⁻³, fluxes declined by up to 61% compared with the baseline. Warming enhanced the temperature–moisture synergy (−43%, p < 0.01) and simultaneously reduced baseline fluxes (−56%, p < 0.01). These shifts fundamentally altered the regulation of CO₂ flux dynamics. Our findings highlight the necessity of integrating salt dynamics and carbonate equilibria into multiphase reactive transport models to improve regional carbon sink assessments. Ultimately, this study refines estimates of the contribution of saline–alkali soils to the global “missing carbon sink” (~1.7 Pg C a⁻¹) and emphasizes their overlooked role in the Earth’s carbon budget under a warming climate.