Global warming is expected to enhance the severity and frequency of drought in subtropical areas; thus, understanding how vegetation growth responds to precipitation is crucial to comprehending the impact of these changes on ecosystem services, such as carbon storage. However, vegetation activity in subtropical karst regions in Southwest China is hard to explain when we merely consider the influence of climate and soil factors. In this study, we extended traditional research by combining bedrock data we aim to investigate the role of bedrock and its interaction with precipitation on plant growth in the Guizhou Province of China. We analyzed the differences in the precipitation–vegetation growth relationship in noncarbonate and carbonate rock regions, assessing the sensitivity of vegetation from two lithological types to drought. The results reveal that although there are no significant differences in climate and soil parameters between carbonate and noncarbonate regions, the normalized difference vegetation index (NDVI) in carbonate regions is more strongly related to precipitation (carbonate region: R² = 0.67; noncarbonate region: R² = 0.37), while the spring greenness–precipitation relationship show is more stable in the carbonate region. Our results show that the vegetation activity in the carbonate region is more vulnerable during the drought period, highlighting that the vegetation dynamic was not only regulated by climatic factors, and bedrock-caused water stress should be taken into account.

Many hypotheses have been proposed to explain elevational species richness patterns; however, evaluating their importance remains a challenge, as mountains that are nested within different biogeographic regions have different environmental attributes. Here, we conducted a comparative study for trees, shrubs, herbs, and ferns along the same elevational gradient for 22 mountains worldwide, examining the performance of hypotheses of energy, tolerance, climatic variability, and spatial area to explain the elevational species richness patterns for each plant group. Results show that for trees and shrubs, energy-related factors exhibit greater explanatory power than other factors, whereas the factors that are associated with climatic variability performed better in explaining the elevational species richness patterns of herbs and ferns. For colder mountains, energy-related factors emerged as the main drivers of woody species diversity, whereas in hotter and wetter ecosystems, temperature and precipitation were the most important predictors of species richness along elevational gradients. For herbs and ferns, the variation in species richness was less than that of woody species. These findings provide important evidence concerning the generality of the energy theory for explaining the elevational species richness pattern of plants, highlighting that the underlying mechanisms may change among different growth form groups and regions within which mountains are nested.

China’s southwest mountainous region is one of the hotspots of biodiversity in the world. However, the study on the pattern of species richness distribution of endemic plants in this region and its influencing factors is still in the exploration stage. A clear regional spatial distribution pattern of plants and its influencing factors are very important for the protection and management of plant diversity in southwest China. In this study, 511 county-level regions in the southwest mountainous region were taken as examples to establish a plant species resource bank in the southwest mountainous region, and the distribution pattern of the proportion and abundance of endemic plant families and genera was analyzed based on 19 climate and environmental factors and 8 human disturbance factors in the southwest mountainous region. The geographical weighted regression model (GWR) was used to reveal the main factors affecting the spatial distribution of species. The results showed that: (1) A total of 4688 species investigated in the southwest mountain belong to 19 families and 32 genera. (2) The endemic species richness in the southwest mountainous region showed a significant uneven spatial pattern, mainly concentrated in the Heng Duan Mountain area, southwest Sichuan and northern Yunnan area, and the Ruoergai-Hongyuan area of West Sichuan Plateau. (3) The results of the GWR model showed that the diurnal mean temperature range, precipitation seasonality and distance from the main road had significant effects on species richness. The study on the distribution of endemic genera and their influencing factors in the southwest mountainous region has important implications for the exploration of the evolutionary history and species conservation of the mountain flora.

Numerous studies have demonstrated that sampling intensity can significantly influence the detection of richness patterns and the assessment of the importance of driving factors. However, existing research has primarily focused on comparing the influence of sampling intensity across different locations or community types, with less attention paid to its influence across growth forms. Through field surveys on Baima Snow Mountain and bootstrap resampling analyses, we quantified the influence of sampling intensity on plant elevational richness patterns across growth forms (trees, shrubs, and herbs). Our results revealed that with increasing sampling intensity, the error in assessing elevational richness patterns decreased rapidly then stabilized for all growth forms. A similar trend was observed in the estimation of climatic drivers. However, significant variations emerged across different growth forms. The suitable sampling intensity was higher for trees and shrubs than for herbaceous plants. Furthermore, estimation errors for tree richness patterns declined significantly faster with increasing sampling intensity than those for shrubs and herbs. Similarly, the relationship between sampling intensity and error in estimating richness-climate relationships showed significant differences across growth forms. However, these differences were subject to the climate drivers selected. These findings demonstrate that growth-form differences must be considered in elevation-richness surveys. However, our meta-analysis revealed that no current study accounted for this factor in their protocols. Our findings provide empirical evidence for developing growth form-specific sampling protocols, offering practical solutions to improve the accuracy of mountain richness studies and enhance cross-study comparability in elevational gradient research.

Droughts pose a significant global threat to ecosystem stability and plant diversity. The sensitivity of vegetation to drought is highly variable, influenced by both vegetation types and landscape properties. However, little is known about whether bedrock type influences vegetation drought sensitivity, especially in karst regions, where unique hydrogeology creates severe water stress for surface vegetation. In this study, we quantify the effect of bedrock types (i.e., limestone, dolomite, and clastic rocks) on vegetation drought sensitivity karst regions across Guizhou Province (China). We found that during the early growing season, vegetation sensitivity to drought was 1.3–1.8 times higher in limestone areas than in dolomite and clastic areas. We also determined that the duration of dry spells is a critical temporal factor that amplifies drought stress. Hierarchical modeling indicated that models jointly incorporating bedrock type and dry spell duration significantly improve predictions of vegetation activity. These findings highlight the crucial role bedrock’s in shaping vegetation growth under drought conditions, supporting the integration of bedrock data into hydrologic and climate models to improve their predictive accuracy under drought stress.