Publication
 

Aboveground carbon storage is driven by functional trait composition and stand structural attributes rather than biodiversity in temperate mixed forests recovering from disturbances

Key messageFunctional trait composition and stand structural complexity rather than biodiversity substantially enhance aboveground carbon storage in temperate mixed forests, while accounting for the effects of disturbance intensity. This study provides a strong support to the mass ratio effect in addition to the niche differentiation and facilitation effects.

Context: The underlying mechanisms for the relationships between biodiversity and ecosystem function remain hotly debated for the last four decades.

Aims: We tested how do biodiversity, functional trait composition, stand structural attributes, and topographic variables explain aboveground C storage under different disturbance regimes.

Methods: We used linear mixed effects and structural equation models to simultaneously evaluate the effects of biodiversity, stand structure attributes, functional trait composition, and topographic variables on aboveground C storage while considering for the effects of disturbance intensity. We used biophysical data from 260 plots within 11 permanent temperate mixed forests in Northeastern China.

Results: Aboveground C storage was driven by stand basal area, individual tree size inequality, community-weighted mean of maximum height and wood density, and diversity (functional evenness and mean nearest taxon distance). The structural equation model showed that aboveground C storage was positively affected by individual tree size inequality and trait composition (i.e., CWM of maximum height), after accounting for the strongest negative direct and indirect effects of disturbance intensity.

Conclusion: Conserving functional identity of species and maintaining complex stand structure would be the alternative choices for higher aboveground C storage in temperate mixed forests.

Authors: 
Z. Yuan, S. Wang, A. Ali, A. Gazol, P. Ruiz-Benito, X. Wang, F. Lin, J. Ye, Z. Hao, & M. Loreau
Journal: 
Annals of Forest Science
Year: 
2018
Volume: 
75
Issue: 
67
Pages: 
1-13
DOI: 
10.1007/s13595-018-0745-3
Site: 
Changbaishan