Decoding Climatic Variability: A Data-Driven Approach to Assess Drought Impacts on Plant Communities in Hulunbuir

This research delves into the resilience of plant communities, with a focal emphasis on their adaptation mechanisms towards drought, with an overarching objective to broaden our comprehension of ecosystem dynamics and bolster environmental sustainability. We executed multiple regression analyses encompassing variables such as temperature, precipitation, and species richness within the Hulun-beier Baikal grassland situated in Inner Mongolia. The Standardized Precipitation Evapotranspiration Index (SPEI) was incorporated as a salient indicator of drought conditions. In parallel, a differential equation model was utilized to approximate aboveground biomass, coupled with the application of a particle swarm optimization algorithm aimed at accurately determining maximum biomass and optimal species count. A sensitivity anal-ysis further elucidated a linear correlation between monthly SPEI values and species numbers within the studied region. Key discoveries encompass: 1. Extreme climatic perturbations such as droughts or heavy rainfalls significantly undermine the sta-bility of plant communities, with particularly pro-nounced effects on those already encumbered by additional stressors such as pollution or habitat loss. 2. Rampant intraspecific competition within plant communities precipitates a decline in their numbers, a process that is further exacerbated by prevailing environmental stressors. 3. For a cogent prediction of the impacts of future drought events on ecosystems, it is paramount to integrate comprehensive models that account for an array of factors such as soil quality, nutrient cycling, biological interactions, and anthropogenic activities. This research presents critical insights pertinent to the conservation of plant biodiversity, the promotion of environmental sustainability, and the augmentation of our understanding of natural systems.