China’s double carbon initiative faces huge challenges, and understanding the carbon sequestration service of terrestrial ecosystems under future interannual regional land use change is important to respond to China’s carbon policy effectively. Previous studies have recognized the important impact of land use/land cover (LULC) planning on carbon sequestration in terrestrial ecosystem services (ESs). However, exploring trends in carbon sequestration under sustainable development scenarios that combine economic and ecological development, particularly the mechanisms that balance the supply and demand of carbon sequestration, still requires in-depth exploration in different geographical contexts. In this study, we present the LULC simulation framework from 2000 to 2030 for four different development scenarios in the Xinjiang region, located in an important Belt and Road region, including business as usual (BAU), rapid economic development (RED), ecological land protection (ELP), and sustainable development with both economic and ecological development (SD). Our results suggest that both the supply and demand of carbon stock in Xinjiang will increase in 2025 and 2030, with the demand exceeding the supply. However, our scenario planning mitigates the supply and demand deficit situation for carbon sequestration in the context of future cropland expansion in different scenarios. In summary, our study’s findings will enrich the study of carbon sequestration under future scenarios in the Belt and Road region. Xinjiang should pay more attention to the dynamic changes in landscape type structure and its carbon storage supply and demand caused by cultivated land expansion. Among the four scenarios, the spatial difference between carbon storage supply and demand based on the SD scenario is the smallest, which is more in line with the high-quality development of regional ecological security in Xinjiang.

Drylands in northwest China have limited water resources, which negatively impacts economic development, ecological security, and the United Nations Sustainable Development Goals. However, few studies have examined water supply and demand under multiple future spatial patterns of land use, particularly under sustainable development scenarios. Further research is therefore needed to determine how affect water output services under various land use patterns. We used the GMOP-PLUS (Gray Multi-objective Optimization-Patch-generating Land Use Simulation) and the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) models to investigate future land use programs and the current and future trends in water yield services supply and demand in the typical dryland region of Xinjiang, China. The GMOP-PLUS model was used to project the spatial patterns of land use/land cover (LULC) change in Xinjiang in 2025 and 2030 under programs of business-as-usual, rapid economic development, ecological land protection and sustainable development. We then used the InVEST model to project the spatiotemporal evolution of water yield services supply and demand under the four different scenarios. Our results show that Our results show that water production in Xinjiang decreases to 911.30 × 10⁸ m³ in 2020–2030 under the business-as-usual scenario, with an expansion in arable land and a reduction in forested land being the main causes of this decrease. The decline in water production under the ecological land protection scenario is 913.88 × 10⁸ m³. The retention effect of vegetation slows the decline in water production, but the ecological land protection scenario is not effective in controlling the reduction in arable land. The rapid economic development scenario produces a significant increase in water yield of 915.09 × 10⁸ m³, mainly due to an increase in the area of impervious surfaces caused by the expansion of built-up land; however, the rapid economic development scenario leads to a decreasing trend in ecological land. The sustainable development scenario produces 914.15 × 10⁸ m³ of water. The sustainable development scenario increases water production while balancing the development of Constructed and the protection of ecological land, and the arable land also shows a slow growth trend. Between 2025 and 2030, the water security index fluctuates between –0.0225 and –0.0400, with a continued future deficit in water supply and demand in Xinjiang and a high degree of spatial heterogeneity. Programs for advancing sustainable development narrow the supply–demand gap for services that produce water.

Both climate change and human activities play critical roles in shaping the spatial distribution of cotton cultivation, particularly in arid and semi-arid environments. However, existing studies have not sufficiently quantified their synergistic effects, and regional-scale applications remain limited. This study selected key variables from 31 environmental factors—including climate, soil, topography, and human footprint—and employed an optimized MaxEnt model to project cotton distribution across three Shared Socioeconomic Pathways (SSP126, SSP245, and SSP585). We developed models based on (i) current climate conditions, (ii) an integrated model incorporating both current climate conditions and human footprint, and (iii) future climate projections for the 2030s, 2050s, and 2070s. The results indicate that human footprint, mean diurnal temperature range (bio2), mean temperature of the coldest quarter (bio11), precipitation of the coldest quarter (bio19), and solar radiation intensity are the primary factors influencing cotton distribution. Under prevailing climate conditions, suitable cotton habitats are mainly located in Aksu, Kashgar, Tacheng, Bayingolin Mongol Autonomous Prefecture, and Changji, where human activities have significantly expanded the cultivation range. Future climate projections indicate a decrease in the extent of suitable cotton habitats, with its distribution center shifting toward lower-altitude areas. This study offers key empirical evidence and conceptual understanding to address climate-induced risks to cotton farming, forming a basis for informed strategies in sustainable cultivation and habitat conservation.

Precision weeding in cotton fields requires joint plant detection and growth-point localization despite canopy overlap and limited embedded computing resources. We propose ADQ-PACR, a one-stage framework that combines quality-aware localization with auxiliary coordinate regularization. ADQ jointly predicts growth-point coordinates, keypoint validity, and scale-normalized localization quality. PACR maintains independent supervision of the primary candidate and supervises the auxiliary candidate with the lowest coordinate error. The auxiliary branches are removed before deployment, leaving a fixed primary path. Experiments used 3527 smartphone images collected in Shaya and Changji, Xinjiang, from April to July 2022, spanning cotton seedling to squaring stages and including weeds such as Amaranthus retroflexus, Chenopodium album, and Portulaca oleracea. Evaluation used 343 fixed test images and three training seeds, with a common evaluator for adapted YOLO pose baselines initialized from detection weights and two-stage systems using predicted boxes. The full ADQ-PACR framework increased mean keypoint mAP50–95 over the corresponding YOLOv8n, YOLO11n, and YOLO26n baselines by 3.29, 2.56, and 2.17 percentage points, respectively. The YOLO11n implementation achieved box mAP50–95 of 60.68 ± 0.11% and keypoint mAP50–95 of 43.50 ± 1.55%. TensorRT FP16 deployment on Jetson AGX Orin in MAXN mode yielded end-to-end latencies of 20.85–22.22 ms across the three backbones.

Analyzing the dominant drivers of the Food-Water-Land-Ecosystem (FWLE) nexus in the future is important for improving sustainable development in dryland ecosystems. However, the future trajectories of food–water–land–ecosystem interactions in typical drought-prone regions remain poorly understood. To address this gap, this study coupled the Gray Multi-Objective Programming with Patch-generating Land Use Simulation (GMOP-PLUS) model and applied spatial analysis methods (including longitudinal and zonal statistical analysis, trade-off synergy analysis, and redundancy analysis) to examine the spatiotemporal differentiation patterns of the FWLE nexus in Xinjiang under different development scenarios. Over the past two decades, water yield in Xinjiang’s agricultural landscapes has declined by 57.4%, primarily due to land-use and land-cover changes. Under the 2030 sustainable development scenario, a custom optimization developed via the GMOP model that balances economic and ecological objectives, crop production and habitat quality are projected to increase by 47.9% and 55.1%, respectively. Moreover, redundancy analysis results indicate that the driving contribution of precipitation on the FWLE nexus is expected to reach 76.9% by 2030. These findings provide a clear delineation of priority spatial units for improvement within Xinjiang agro-ecosystem and offer a strategic pathway for balancing ecological conservation and economic development.