COS 5-2 - Linking community functional attributes with ecosystem carbon storage and soil resource availability in semi-arid grasslands

Monday, August 12, 2019: 1:50 PM
M111, Kentucky International Convention Center
Huoxing Zhu Sr., South China Botanical Garden, CAS, Scarborough, ON, Canada
Huoxing Zhu Sr., South China Botanical Garden, CAS

Background/Question/Methods

Disentangling the intertwined relationships between abiotic controls, biodiversity (especially its functional components), and ecosystem C storage is essential to advance the understanding of biodiversity-ecosystem functioning (BEF) relationships, and to predict the ecological consequences of changes in abiotic conditions caused by human activities.

We use a structural equation model to investigate community functional responses to changing soil conditions, and functional effects on ecosystem carbon storage. Community functional attributes was measured as community weighted mean trait values and functional dispersion of 4 functional traits (plant height, specific leaf area, leaf dry matter content and leaf nitrogen concentration). Ecosystem carbon storage was represented by aboveground biomass and soil carbon storage, while soil resource availability by soil water and nutrient levels.

Results/Conclusions

Community functional composition and diversity showed clear responses to changing soil resource availability, and had significant cascading effects on ecosystem C storage. Community weighted mean plant height and specific leaf area significantly increased with increasing soil resources while community functional dispersion decreased. Community functional dispersion showed a significant positive effect on aboveground biomass and a negative effect on surface soil C storage. Soil resource availability exerted the strongest direct control over both surface and deep soil C storage, while aboveground biomass was largely controlled by community weighted mean plant height, and to a lesser extent, soil nutrient availability. These findings provide great insight into the complex BEF relationship and improve our ability to predict and manage the ecological consequences of potential environmental change in a rapidly changing world.