Maximising Trait Evenness Promotes the Recovery of Plant Species Richness in Managed Grasslands

Land-use intensification threatens biodiversity, and restoring degraded ecosystems remains challenging due to the difficulty of identifying the rules governing community assembly and dynamics. Investigating the temporal dynamics of trait-abundance distributions (TADs) along long-term time series offers a promising approach to disentangle the influence of stochastic (e.g. climatic variability, ecological drift) and deterministic processes (e.g. biotic interactions, abiotic filtering) in shaping ecological communities and guiding biodiversity restoration. We used a long-term restoration experiment conducted in a species-poor, historically intensively managed grassland (Massif-central, France) to evaluate the relationships between land-use intensity, TADs dynamics, and the recovery of grassland plant species richness. TADs were quantified annually from 2004 to 2021 based on four traits related to plant architecture and leaf carbon economy. We analysed the temporal variability of TADs using the skewness-kurtosis relationship (SKR), a framework that explicitly accounts for stochasticity while revealing the imprint of deterministic processes on community assembly. TADs dynamics were not random, but were constrained according to trait- and land-use-specific SKR patterns. The cessation of fertilisation shifted TADs for all traits, from peaked distributions under fertilised management to more uniform distributions under unfertilised conditions. In the unfertilised treatment, TADs were also more stable than expected by chance and converged toward maximal trait evenness. Maximisation in trait evenness occurred during the early years of the experiment and preceded the long-term recovery of plant species richness. By explicitly accounting for stochastic community dynamics, our study reveals how plant communities reassemble during ecological restoration of grasslands historically degraded by intensive management and identifies the maximisation of trait evenness as a predictive benchmark linking early community reorganisation to long-term biodiversity recovery.