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

## TL;DR

This study explores how plant traits and environmental factors influence biomass distribution in karst forests, revealing that trait patterns better predict biomass trade-offs than environmental variables.

## Contribution

The study reveals for the first time how trait distributions and topographic-soil factors jointly shape biomass allocation in karst climax communities.

## Key findings

- Community-level trait distributions explain biomass trade-offs more effectively than abiotic factors.
- Slope position is the primary driver of biomass trade-offs, mediated by specific leaf area (SLA) variation.
- Lower trait variance in regeneration layers reduces biomass loss, while stable layer biomass increases with slope decline.

## Abstract

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 (R
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.

In this study, multi‐source data (functional traits of dominant species, topography‐soil parameters, and biomass) of the dynamic monitoring plot of Maolan Dynamic Plot of Karst Forest Ecosystem in South China were collected. The partial least squares structural equation model (PLS‐SEM) was adopted to study the biomass trade‐off strategy of the karst forest community at the “topography‐soil” extremum. It is revealed for the first time that: (1) The forest layer distribution model of community biomass has the advantage of biomass trade‐off in the karst polar community. (2) The karst climax community is jointly influenced by the “topographic – soil” environment, and the community functional structure shows obvious differences. (3) Based on the theory of trait drive, break through the cognitive framework of the functional structure of the community affected by environmental factors from the weighted moments of functional trait communities. This research aims to deepen the understanding of the construction mechanism of non‐zonal vegetation communities in the study of subtropical karst forest ecosystems.