A trait‐based approach reveals the importance of biotic filter for elevational herb richness pattern

Abstract

AbstractAimTo evaluate how a biotic filter (overstorey cover [OC]) shapes an elevational herb richness pattern and to test whether intermediate elevations represent more suitable habitats for herb species due to the minimal biotic and moderate abiotic filtering that occured there.LocationDongling Mountain, China.TaxonHerbs.MethodsWe sampled herb richness along a 1,000‐m vertical transect (OC and elevation covary) and four horizontal transects (across the OC gradient with no change in elevation). Functional traits related to shade (leaf mass per area [LMA] and leaf stem ratio [LSR]) and freezing tolerance (leaf thickness [LT] and hair density [HD]) were collected based on vegetation sampling plots. We divided the richness data into below‐ and above‐timberline groups and then assessed the most important driver for each group. By estimating the variations in species richness and functional diversity along horizontal transects, we examined how these parameters responded to OC while controlling for associated differences in elevation.ResultsHerb richness showed a unimodal relationship with elevation, with a peak around the timberline. Below the timberline, herb richness was better predicted by OC and showed a positive relationship with the functional diversity of LMA and LSR. The frost period performed better in predicting herb richness above the timberline, and herb richness was positively related to the functional diversity of HD.Main conclusionsThe results support our hypothesis and highlight the importance of OC in shaping herb richness patterns. Below the timberline, OC acts as a filter, sorting species based on their ability to tolerate shade, whereas the frost period limits richness above the timberline and favours species that can tolerate low temperatures. Therefore, we suggest that biotic interactions, as well as environmental and geographical factors, should be considered the main drivers of elevational plant richness patterns.