Xin He’s research while affiliated with Xinjiang University and other places

Land use/cover change (LUCC) significantly alters the carbon storage capacity of ecosystems with a profound impact on global climate change. The influence of land use changes on carbon storage capacity and the projection of future carbon stock changes under different scenarios are essential for achieving carbon peak and neutrality goals. This study applied the PLUS-InVEST model to predict the land use pattern in China’s arid Xinjiang Region in 2020–2050. The model assessed the carbon stock under four scenarios. Analysis of the historical LUCC data showed that the carbon storage in Xinjiang in 2000–2020 in five-year intervals was 85.69 × 10⁸, 85.79 × 10⁸, 85.87 × 10⁸, 86.01 × 10⁸, and 86.71 × 10⁸ t. The rise in carbon sequestration capacity in the study area, attributable to the expansion of cropland, water, and unused land areas, brought a concomitant increment in the regional carbon storage by 1.03 × 10⁸ t. However, prediction results for 2030–2050 showed that carbon storage capacity under the four scenarios would decrease by 0.11 × 10⁸ and increase by 1.2 × 10⁸, 0.98 × 10⁸ t, and 1.28 × 10⁸ t, respectively. The findings indicate that different land transfer modes will significantly affect Xinjiang’s carbon storage quantity, distribution, and trend. This research informs the past, present, and future of carbon storage in arid ecosystems of Xinjiang. It offers a reference for Xinjiang’s development planning and informs the efforts to achieve the carbon peak and neutrality goals.

With the rapid economic development of Xinjiang Uygur Autonomous Region (Xinjiang), energy consumption became the primary source of carbon emissions. The growth trend in energy consumption and coal-dominated energy structure are unlikely to change significantly in the short term, meaning that carbon emissions are expected to continue rising. To clarify the changes in energy-related carbon emissions in Xinjiang over the past 15 years, this paper integrates DMSP/OLS and NPP/VIIRS data to generate long-term nighttime light remote sensing data from 2005 to 2020. The data is used to analyze the distribution characteristics of carbon emissions, spatial autocorrelation, frequency of changes, and the standard deviation ellipse. The results show that: (1) From 2005 to 2020, the total carbon emissions in Xinjiang continued to grow, with noticeable urban additions although the growth rate fluctuated. In spatial distribution, non-carbon emission areas were mainly located in the northwest; low-carbon emission areas mostly small and medium-sized towns; and high-carbon emission areas were concentrated around the provincial capital and urban agglomerations. (2) There were significant regional differences in carbon emissions, with clear spatial clustering of energy consumption. The clustering stabilized, showing distinct "high-high" and "low-low" patterns. (3) Carbon emissions in central urban areas remained stable, while higher frequencies of change were seen in the peripheral areas of provincial capitals and key cities. The center of carbon emissions shifted towards southeast but later showed a trend of moving northwest. (4) Temporal and spatial variations in carbon emissions were closely linked to energy consumption intensity, population size, and economic growth. These findings provided a basis for formulating differentiated carbon emission targets and strategies, optimizing energy structures, and promoting industrial transformation to achieve low-carbon economic development in Xinjiang.

Xinjiang is an important arid region in the northwest of China and plays an important role in the field of ecological security protection in China. Because of its aridity, the identification of critical areas for ecological protection and the optimization of ecological space structure in Xinjiang are of great significance for promoting the harmonious development of the oasis economy, enhancing the ecological environment, and improving human well-being. This study applied an ecological security evaluation from the three dimensions of habitat quality, ecosystem service value, and soil-water conservation to identify the basic situation of the ecological security pattern. The core “source” area of ecological protection was extracted using the morphological spatial pattern analysis (MSPA) method, while the ecological corridor and important ecological nodes were identified using the minimum cumulative resistance model (MCR). The “point-line-plane” three-dimensional ecological network structure was then constructed, providing a case for the development of the ecological security and construction in the oasis. The results showed that in the arid regions of Xinjiang, the ecological land is extremely fragmented and is mainly distributed in the mountains and waters distant from human activities. Overall, there is a substantial geographical disparity with a low level of ecological security, particularly in the ecological marginal areas. The ecological network framework of Xinjiang is characterized by an uneven distribution of “sources”, broken corridor structure, and a low degree of networking. Therefore, this study proposed an ecological space layout system consisting of “7 ecological subsystems, 51 source areas, 87 ecological corridors, and 33 ecological nodes” by combining the regional physical and geographical characteristics with the overall development plan.

This study aims to understand the factors and mechanisms influencing the spatio-temporal changes of fractional vegetation cover (FVC) in the northern slopes of the Tianshan Mountains. The MOD13Q1 product data between June and September (peak of plants growing) during the 2001–2020 period was incorporated into the pixel dichotomy model to calculate the vegetation cover changes. Then, the principal component analysis method was used to identify the primary driving factors affecting the change in vegetation cover from the natural, human, and economic perspectives. Finally, the partial correlation coefficients of FVC with temperature and precipitation were further calculated based on the pixel scale. The findings indicate that (1) FVC in the northern slopes of the Tianshan Mountains ranged from 0.37 to 0.47 during the 2001–2020 period, with an obvious inter-annual variation and an overall upward trend of about 0.4484/10 a. Although the vegetation cover had some changes over time, it was generally stable, and the area of strong variation only accounted for 0.58% of the total. (2) The five grades of vegetation cover were distributed spatially similarly, but the area-weighted gravity center for each vegetation class shifted significantly. The FVC under different land use/land cover types and elevations was obviously different, and as elevation increased, vegetation coverage presented a trend of a “∩”-shape change. (3) According to the results of principal component analysis, human activities, economic growth, and natural climate were the main driving factors that caused the changes in vegetation cover, and the cumulative contribution of the three reached 89.278%. In addition, when it came to climatic factors, precipitation had a greater driving force on the vegetation cover change, followed by temperature and sunshine hours. (4) Overall, precipitation and temperature were correlated positively with FVC, with the average correlation coefficient values of 0.089 and 0.135, respectively. Locally, the correlations vary greatly under different LULC and altitudes. This research can provide some scientific basis and reference for the vegetation evolution pattern and ecological civilization construction in the region.

Under economic globalization, synergy among cities has been actively promoted. Establishing inter–city networks and joint regional development could catalyze economic growth. The mode and pace of urban growth could be gauged by construction land expansion and human–land coordination. This study adopted the dynamic change, the center of gravity, and coordination analyses to comprehensively portray spatial patterns and changes amongst 13 oasis town groups in Xinjiang, China, from 2000 to 2018. The results identified that 2010 was the turning point of acceleration in construction land expansion, demonstrating notable spatial differentiations among town groups. Northern Xinjiang experienced faster urban growth than southern Xinjiang. The Urumqi–Changji–Shihezi (UCS) town group on the northern slope of the Tianshan Mountains constituted the crucial urban core with the fastest construction land expansion. Although the towns in southern Xinjiang were small and beset by inherent limitations in the early period, some town groups acquired new impetus and vitality and became the fastest–developing areas in Xinjiang in recent years. The growth was driven by China’s western development program, economic assistance, and Silk Road Economic Belt. Eastern Xinjiang had convenient transportation, but its small urban entities needed population supplementation to invigorate urban expansion. In the far north, the Altay and Tacheng–Emin (TE) town groups were situated too far from development cores. They lacked the collateral benefits of nearby strong–growth loci, resulting in sluggish growth. A north–south dual–hub strategy was proposed to spearhead the dissemination of urban growth by fostering core–periphery linkages pump–primed by improved road connections.