Influence of divergent sampling intensity across plant growth forms on estimating elevational richness patterns and their drivers.

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.