Grazing-Mediated State Transition in Grassland Plant Communities: A Mean-Field Analysis

: To elucidate the driving mechanisms behind plant community state transitions in desert steppe under grazing disturbance, this study established a long-term monitoring platform (initiated in 2004) in Stipa breviflora desert steppe in Inner Mongolia. Four stocking rate gradients were implemented: no grazing (CK), light grazing (LG), moderate grazing (MG), and heavy grazing (HG), ranging from 0 to 2.71 sheep units·hm⁻²·half-year⁻¹. Plant population characteristics were surveyed across 145 quadrats. Using mean occurrence probability combined with transition probability models, this research quantifies the patterns and characteristics of mutual transitions at three levels—species, functional groups, and plant families—during state shifts induced by varying stocking rates. Results demonstrated that: As stocking rate increased, the species network shifted from a single-core hierarchy (dominated by Stipa breviflora) to a multi-core complex network, eventually simplifying into a sparse network governed by grazing-tolerant species under heavy grazing. Perennial grasses (PG) exhibited the highest grazing tolerance, receiving up to 43% of transition probability from other functional groups. Shrubs and semi-shrubs (SS) maintained system functionality through self-sacrifice (27% transition probability to PG during the MG stage), while annual-biennial plants (AB) acted as ecological bridges during state transitions. Poaceae (POA) consistently received resources (probability of OTH→POA increased to 52%), reinforcing its dominance, whereas resource transfer from Fabaceae (FAB) to POA (24%) intensified nitrogen limitation and triggered system state transition. In summary, a stocking rate≤1.82 sheep units·hm⁻²·half-year⁻¹ maintains multistability in S. breviflora desert steppe. Species, functional groups, and plant families revealed distinct response strategies during state transitions, whose salient manifestations and synergistic interactions provide a theoretical basis for adaptive management in desert steppes.