Modeling the current distribution of and predicting suitable habitats for threatened species support the species conservation and restoration planning process. Therefore, the purpose of this study was to model the actual distribution and predict environmentally suitable habitats for Carex alatauensis S.R.Zhang 2015, a locally threatened native grass species on the Qinghai–Tibet Plateau. To realize this objective, based on the geographical samples within the natural distribution of C. alatauensis, the dominant climatic factors in its potential distribution range were analyzed using the maximum entropy (MaxEnt) model. The results showed that the average values of the area under the receiver operating characteristic curve (AUC) of the training data were 0.833 ± 0.044, which indicated that the accuracy of the MaxEnt model was pretty high for modeling potential distribution regions of C. alatauensis. The combined results from the Jackknife test and the presented contribution of environmental variables revealed that the annual precipitation, the growth season precipitation, and the precipitation of the driest month were the key climatic factors that restricted the distribution of C. alatauensis on the Qinghai–Tibet Plateau. It is predicted that the potential distribution area of C. alatauensis on the Qinghai–Tibet Plateau is 1.96 × 10⁶ km², and the most suitable area is 3.7 × 10⁵ km², mainly located in the Qilian Mountains, the Himalayas, and the Qingtanggula Mountains.

In order to investigate the characteristics and driving factors of keystone species change in vegetation communities, we conducted a network analysis to analyze the complexity of grassland plant communities and keystone species. We conducted a study with six plots of degraded grassland, intact grassland, and various ages of artificial grassland. We systematically analyzed the characteristics of vegetation community and soil physical–chemical properties under different treatments. Our findings revealed that the 5-year-old artificial grassland exhibited lower biodiversity, as indicated by a Shannon–Weiner index of 1.70 and a Pielou’s evenness index of 0.72. In comparison to the degraded grassland, soil organic carbon and nitrate nitrogen levels in the 5-year-old artificial grassland increased by 22% and 13%, respectively, while soil density decreased by 9%. However, despite the relatively stable plant community in the 21-year-old artificial grassland, it had not fully recovered to the level of natural grassland due to the complexity of the plant community and the shift in keystone species. Therefore, it is crucial to consider the impact of soil bulk density and nutrient levels on the complexity of the plant community when restoring degraded alpine meadows through the establishment of artificial grassland.

Understanding how herbivores adjust their foraging strategies to cope with seasonal resource fluctuations has been central to the nutritional ecology. Optimal Foraging Theory (OFT) predicts that generalists should broaden their dietary niche when high-quality resources are scarce, but empirical evidence in extreme environments remains poorly understood. We used trnL-P6 metabarcoding of fecal samples (n = 10/season) and a local reference library of 120 plant species to quantify diet composition and niche metrics of free-ranging yaks (Bos grunniens) on the Qinghai–Tibetan Plateau in June (summer) and October (autumn) 2024. Yaks shifted from a diverse, forb-dominated diet (e.g., Polygonaceae, Rosaceae) in summer to a specialized diet dominated by grasses in autumn. Although dietary richness and total niche width (TNW) decreased in autumn, phylogenetic diversity remained stable, indicating a strategic shift to distinct evolutionary lineages to ensure functional redundancy. Furthermore, food network analyses demonstrated a transformation from a flexible, modular foraging pattern in summer to a highly integrated, synchronized network in autumn. These findings suggest that under the distinct quality–quantity trade-off of high-altitude ecosystems, yaks adopt an energy-maximization strategy by minimizing search costs, aligning with the opportunity cost constraints of OFT, rather than randomly expanding their niche. This insight into selective foraging dynamics is critical for developing sustainable grazing practices that accommodate the natural adaptive behaviors of alpine herbivores.

Soil fungi serve as key mediators of belowground ecological processes; however, the altitudinal distribution patterns and their driving mechanisms of soil fungal communities in alpine shrubland ecosystems remain poorly understood. In this study, soil samples were collected from Potentilla fruticosa shrubs at different altitudes, and their physical and chemical properties were determined. Illumina MiSeq sequencing technology was used to study the characteristics of soil fungal communities at different altitudes (3400, 3700, 4000, and 4300 m), and the driving factors affecting the composition of soil fungal communities were found through variance analysis and redundancy analysis. With the increase in altitude, species diversity decreased while total phosphorus and available phosphorus increased. Compared with 3400 m, the diversity index (Sobs, Chao1, and ACE index) of the soil fungal community at 4000 m is the highest, and that at 4300 m is the lowest. NMDS analysis showed that there were significant differences among soil fungal community structures at different altitudes. Redundancy analysis (RDA) indicated that available potassium, available phosphorus, and the Shannon–Wiener diversity index were the primary factors influencing the variation in soil fungal communities along the elevation gradient. Furthermore, the impact of soil physical and chemical properties on soil fungal communities was found to be more pronounced than that of plant characteristics. Network analysis shows that the network complexity is the highest at 4300 m above sea level. These studies provide a new perspective and basis for understanding the distribution pattern of soil fungi in the rhizosphere Potentilla fruticosa in the eastern Qinghai–Tibet Plateau.