Community Trait Distributions Drive Biomass Stand Allocation Trade‐Offs in Karst Forests

Community biomass allocation is jointly determined by habitat conditions and plant functional traits. Studies of biomass allocation patterns in topographic-soil climax communities of karst ecosystems remain scarce. According to the trait-driven paradigm, topographic gradients and soil properties indirectly influence karst forest biomass, via their control over community-level functional structure. In the 25-ha Maolan Dynamic Plot of the Karst Forest Ecosystem in South China, we compiled 1255 high-quality trait records for six key plant functional traits related to biomass from 48 dominant species, individual biomass data for 12,354 stems, and fine-scale environmental variables. Partial least-squares structural equation modeling (PLS-SEM) was used to quantify the direct and indirect factors affecting biomass allocation in this climax karst forest community. We observed that the trade-offs in biomass among different forest layers were more effective in predicting the biomass status of natural communities (<i>R</i> ² = 0.69). Topographic heterogeneity acted as an environmental filter, driving the assembly of distinct karst climax communities. Community-level trait distributions and abiotic variables significantly influenced both community biomass and its trade-offs, although trait patterns explained biomass trade-offs more effectively than environmental factors. PLS-SEM identified slope position as the primary driver of biomass trade-offs in the karst climax communities, with community-level variation in specific leaf area (SLA) mediating biomass allocation. Slope position decline reduced the community-weighted mean of functional traits (SLA, Wood density, Leaf nitrogen content) and concurrently increased biomass of the stable layer. In parallel, lower community-weighted variance of traits (SLA) attenuated biomass loss in the regeneration layer. These results underscore the pivotal role of trait composition in mediating biomass partitioning at the community scale.