Background: Grazing disturbance plays an important role in the desert steppe ecosystem in Inner Mongolia, China. Previous studies found that grazing affected the spatial distribution of species in a community, and showed patchiness characteristics of species under different grazing treatments.Artemisia frigidais the dominant species and semi-shrub in desert steppe, and whether grazing interference will affect the spatial distribution ofA. frigidais studied. In this study, geo-statistical methods were mainly used to study the spatial distribution characteristics ofA. frigidapopulation in desert steppe of Inner Mongolia at two scales (quadrat size 2.5 m × 2.5 m, 5 m × 5 m) and four stocking rates (control, CK, 0 sheep·ha^–1·month^–1; light grazing, LG, 0.15 sheep·ha^–1·month^–1, moderate grazing, MG, 0.30 sheep·ha^–1·month^–1, heavy grazing, HG, 0.45 sheep·ha^–1·month^–1).Results: The results showed that the spatial distribution ofA. frigidatended to be simplified with the increase of stocking rate, and tended to be banded with increased spatial scale. The density and height ofA. frigidaincreased with increasing scale. With increased stocking rate, the density ofA. frigidapopulation decreased linearly, while its height decreased in a step-wise fashion. The spatial distribution ofA. frigidawas mainly affected by structural factors at different scales and stocking rate. The density ofA. frigidawas more sensitive to change in stocking rate, and the patchiness distribution ofA. frigidawas more obvious with increase in scale.Conclusions: Stocking rate has a strong regulatory effect on the spatial pattern ofA. frigidapopulation in the desert steppe. Heavy grazing reduced the spatial heterogeneity ofA. frigidain the desert steppe. The smaller dominant populations are unfavourable for its survival in heavy grazing condition, and affects the stability and productivity of the grassland ecosystem.

Cleistogenes songorica, as a clustered grass, is the main grassland flora of the Stipa breviflora desert grassland. Some studies have shown that the constructive species of S. breviflora (sparse cluster type) is prone to cluster fragmentation; however, research on C. songorica is relatively rare. Then will the C. songorica plant population (dense cluster type) also have cluster fragmentation under the influence of intense grazing? To answer this question, we used variance analysis and geo‐statistical methods. The spatial distribution of C. songorica in S. breviflora desert steppe in Inner Mongolia was measured under four grazing intensities (no grazing, CK, 0 sheep·ha⁻¹·half year⁻¹; light grazing, LG, 0.93 sheep·ha⁻¹·half year⁻¹; moderate grazing, MG, 1.82 sheep·ha⁻¹·half year⁻¹; and heavy grazing, HG, 2.71 sheep·ha⁻¹·half year⁻¹) and four scales (10 cm × 10 cm, 20 cm × 20 cm, 25 cm × 25 cm, 50 cm × 50 cm). We then analyzed C. songorica whether fragmentation was present. The results showed that increased grazing intensity is associated with increased density and decreased height, coverage, and standing crop of C. songorica. The spatial distribution of C. songorica was affected by structural factors, and spatial heterogeneity decreased with increased spatial scale. With increased grazing intensity and spatial scale, the patch area of C. songorica gradually increased and tended toward band distribution. In summary, increased grazing intensity and spatial scale led to weakened heterogeneity of C. songorica spatial distribution and increased consistency.

In agro-pastoral transitional zones, monitoring vegetation fraction coverage (FVC) and understanding its relationship with land use and climate change are crucial for comprehending how complex land-use/land-cover change (LUCC) improves ecological restoration and land management. This study focuses on the agro-pastoral transitional zone of Inner Mongolia, aiming to analyze vegetation cover changes from 2000 to 2020 using the Mann–Kendall (MK) significance test, Theil–Sen median trend analysis, and coefficient of variation (CV) analysis. Additionally, the study explores the impacts of LUCC, precipitation, and temperature on vegetation cover using methods such as geo-detector, pixel-based statistical analysis, and univariate linear regression. Based on the PLUS land-use prediction model and linear regression results, vegetation cover was simulated under different land-use scenarios for the future. The main findings are as follows: first, from 2000 to 2020, the spatial distribution of vegetation cover in the study area showed a distinct pattern of higher vegetation cover in the east compared to the west, with significant spatiotemporal heterogeneity. Although the overall vegetation cover slightly increased, there were notable differences in the trend across regions, with some areas experiencing a decrease in FVC. Second, LUCC is the most significant explanatory factor for vegetation cover changes, and the interactions between LUCC and other factors have a particularly notable impact on vegetation cover. Third, scenario simulations based on the PLUS model indicate that, by 2040, vegetation cover will perform optimally under the farmland protection and sustainable development scenarios. Particularly under the farmland protection scenario, the conversion of cropland, forestland, and grassland is notably suppressed. In contrast, the unmanaged natural development scenario will lead to a decline in vegetation cover. The results of this study show that vegetation cover in the agro-pastoral transitional zone of Inner Mongolia exhibits substantial fluctuations due to land-use change. Future ecological restoration policies should incorporate land-use optimization to promote vegetation recovery and address ecological degradation.

Ecological restoration has a positive impact on global climate change. How plant-soil stores carbon in degraded grassland ecological restoration requires long-term monitoring and support. To reveal the dynamics of plant-soil carbon storage in the succession process of ecological restoration, compare the effects of artificial interference and natural restoration, and determine the impact of climate change and biodiversity on vegetation soil carbon storage, we conducted a study in National Grassland Natural Park, which is located on the southern foot of the Yinshan Mountains in Hohhot, Inner Mongolia, China. Based on long restoration chronosequences (2012–2022), using a space-for-time substitution approach and one-way ANOVA tests, Pearson correlation and structural equation modeling were used to investigate the interactions among these various factors. The results indicated that the carbon storage of aboveground vegetation first increased, and then, decreased with time. The underground root carbon storage and soil carbon storage at 0–10 cm and 20–30 cm first increased, then decreased, and finally, stabilized. The highest soil carbon storage (0–30 cm) was 102.11 t/ha in 2013, which accounted for 96.61% of the total organic carbon storage. The Shannon–Wiener index, individual number of species, and surface root carbon storage (0–10 cm) significantly increased the carbon storage of surface soil (0–10 cm) (p < 0.05). Compared to natural restoration, artificial restoration over seven years decreased soil carbon storage at 0–30 cm and underground root carbon storage at 0–10 cm (p < 0.05). Consequently, combining artificial restoration with natural restoration can help in establishing a more stable ecosystem faster and in increasing the carbon storage of the ecosystem. It is an effective management measure to promote grassland restoration in arid areas. Also, climate (MAT, MAP) change was closely correlated with plant-soil carbon storage.

Due to climate change and global warming, the frequency of sandstorms in northern China is increasing. Stipa breviflora, a dominant species in Eurasian grasslands, can help prevent desertification from becoming more serious. Studies on S. breviflora cover a wide range of fields. To the best of our knowledge, the present study is the first to sequence, assemble, and annotate the S. breviflora genome. In total, 2,781,544 contigs were assembled, and 2,600,873 scaffolds were obtained, resulting in a total length of 649,849,683 bp. The number of scaffolds greater than 1 kb was 70,770. We annotated the assembled genome (>121 kb), conducted a selective sweep analysis, and ultimately succeeded in assembling the Matk gene of S. breviflora. More importantly, our research identified 26 scaffolds that may be responsible for the drought tolerance of S. breviflora Griseb. In summary, the data obtained regarding S. breviflora will be of great significance for future research.