Environmental managers and policymakers increasingly discuss trade-offs between ecosystem services (ESs). However, few studies have used nonlinear models to provide scenario-specific land-use planning. This study determined the effects of different future land use/land cover (LULC) scenarios on ESs in the Yili River Valley, China, and analyzed the trade-offs and synergistic response characteristics. We simulated land-use changes in the Yili River Valley during 2020–2030 under three different scenarios using a patch-generating land-use simulation (PLUS) model—business as usual (BAU), economic development (ED), and ecological conservation (EC). Subsequently, we evaluated the water yield (WY), carbon storage (CS), soil retention (SR), and nutrient export (NE) ESs by combining the PLUS and integrated valuation of ecosystem services and trade-offs (InVEST) models, thus exploring multiple trade-offs among these four ESs at a regional scale. For the BAU scenario, there are some synergistic effects between WY and SR in the Yili River Valley, in addition to significant trade-off effects between CS and NE. For the ED scenario, the rapid expansion of cropland and constructed land is at the expense of forested grassland, leading to a significant decline in ESs. For the EC scenario, the model predicted that the cumulative regional net future carbon storage, cumulative water retention, and cumulative soil conservation would all increase due to ecological engineering and the revegetation of riparian zones and that formerly steep agricultural land can be effective in improving ESs. Meanwhile, the trade-off effect would be significantly weakened between CS and NE. These results can inform decision makers on specific sites where ecological engineering is implemented. Our findings can enhance stakeholders’ understanding of the interactions between ESs indicators in different scenarios.

The survival and sustainability of regional species is constrained by habitat quality. In recent decades, the intensification of human activities on a global scale has had a profound impact on regional ecosystems and poses a serious threat to regional sustainable development. Scientific measurement of the drivers of habitat quality can provide important support for the development of effective biodiversity conservation and sustainable land-use policies. Taking the Hung River Valley as an example, the InVEST model was used to assess the habitat quality of the study area in 2000, 2005, 2010, 2015, and 2020 and to explore its spatial and temporal variation and distribution characteristics in combination with the spatial autocorrelation model, and the geographically weighted regression (GWR) model was used to explore the drivers of habitat quality change. The results show the following: (1) The overall habitat quality shows an increasing trend during 2000–2020, but the expansion of construction land in the central region plays a dominant role in the degradation of regional habitat quality. (2) The “Guide-Ledu” line is the dividing line of habitat quality in the Hung River Valley, with a general distribution of “south is good, north is bad” and “south is hot, north is cold”. (3) Natural factors such as slope and elevation basically shape the overall distribution pattern of habitat quality, while urbanisation factors such as population density, gross domestic product, and the night-time lighting index are generally negatively correlated with habitat quality. The results of the study can reveal the linkage between ecosystems and land-use change in the context of urbanisation.

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.

The purposes of this study are to reveal the spatial pattern and dynamic changes of NDVI in the northern slope of the Tianshan Mountains for an extended period and to explore whether the spatial and temporal evolution of NDVI in different spatial scales is consistent so as to provide a reasonable theoretical basis for the selection of appropriate remote sensing spatial resolution in the study area. The GIMMS NDVI remote sensing data set was used to resample the NDVI data with three spatial resolutions of 0.5 km × 0.5 km, 1 km × 1 km, and 8 km × 8 km. The Mann-Kendall method was used to analyze the spatial-temporal evolution characteristics of vegetation NDVI on the NTSM from 1981 to 2015. The results showed that the interannual variation trend and spatial distribution of vegetation NDVI were consistent at different spatial scales. The change of NDVI displayed an increasing trend with changes concentrated in the middle of the NTSM. Five distinct trends were observed: no significant change (35% of the area), significant positive change (26%), significant single peak change (15%), a significant U-shaped change relationship (12%), and significant negative change (11%). Remote sensing NDVI data with a spatial resolution of 8 km could be used to analyze the long-term interannual variation trend of vegetation NDVI on the NTSM.

Influenced by climate change, significant alterations in vegetation phenology have been observed globally. Grassland phenology is highly sensitive to climate change. However, research on the variations in grassland phenology and its responses to seasonal climatic changes in arid and semi-arid regions remains scarce. This study, utilizing Solar-Induced Chlorophyll Fluorescence (SIF) data, meteorological station data, and grassland type data, employs trend analysis and time series analysis to explore the trends of seasonal climatic variability and the sensitivity response of grassland phenology in Xinjiang to seasonal climates. The findings reveal the following: (1) The region experiences more pronounced warming in winter and spring than in summer and autumn, with ground temperature increments outpacing those of air temperatures. The summer season registers the peak in precipitation volume and rate of increase, where mountainous zones accrue more rainfall compared to basins and plains. The distribution of sunshine duration is characterized by higher values in eastern areas than in the west and more in the plains than in mountainous regions, potentially due to escalating cloudiness, which has contributed to a diminishing trend in sunshine hours across Xinjiang over the past 20 years. (2) Over the past two decades, the perennial greening phase of Xinjiang grasslands has predominantly occurred in early May, showing an overall trend of occurring earlier by approximately 5.47 days per decade, while the yellowing phase mainly occurs at the end of September and the beginning of October, demonstrating a delaying trend (6.61 days/decade). The average length of the growing season is 145 days, generally showing a slightly increasing trend (11.97 days/decade). (3) In spring, the rise in air and ground temperatures, along with increased sunshine duration, all promote grassland growth, leading to an earlier greening phase. Conversely, in autumn, increases in air temperature, ground temperature, and sunshine duration can inhibit grassland growth, resulting in an earlier yellowing phase. Increased precipitation in summer and autumn can delay the yellowing phase and extend the length of the grassland growing season. This research provides new insights into the factors influencing large-scale grassland phenology and offers references for grassland adaptation to future climate changes.