Using leaf traits to explain species co-existence and its consequences for primary productivity across a forest-steppe ecotone.

Trait-based approaches have been widely applied to uncover the mechanisms determining community assembly and biodiversity-ecosystem functioning relationships. However, they have rarely been used in forest-steppe ecotones. These ecosystems are extremely sensitive to disturbances due to their relatively complex ecosystem structures, functionings and processes. In this study, we selected seven sites along a transect from closed canopy forests (CF) to forest-steppe ecotones (FSE) and meadow steppes (MS) in northeast China. Six leaf functional traits (i.e. leaf nitrogen and phosphorus contents, leaf length and thickness, single leaf area and leaf mass per unit area, LMA) as well as the community composition and aboveground biomass at each site were measured. Both functional trait diversity indices (richness, evenness and divergence) and community-weighted mean trait values (CWMs) were calculated to quantify community trait distributions. We found that dominant species in the FSE communities showed acquisitive strategies with highest leaf nitrogen (Mean ± SE: 19.6 ± 0.5 mg g) and single leaf area (19.2 ± 1.3 cm), but the lowest LMA (59.6 ± 1.3 g cm) values compared to adjacent CF and MS communities. The ecotone communities also exhibited the largest functional trait richness (TOP), evenness (TED) and divergence (FDis) values (0.46, 0.92 and 0.67, respectively). Overall, niche differentiation emerges as the main mechanism influencing the coexistence of plant species in ecotone ecosystems. In addition, CWMs of leaf traits were the most important predictors for estimating variations in aboveground productivity across the transect, suggesting a major influence of dominant species. Our findings suggest that vegetation management practices in forest-steppe ecotones should increasingly focus on community functional trait diversity, and support the establishment and regeneration of plant species with rapid resource acquisition strategies.