Coordination of flux-related leaf and root traits impacts forest community assembly
Ma, Z.; Duan, M.; Sack, L.; Ma, C.; Li, L.; McCormack, M. L.; Lu, M.
Show abstract
Understanding the functions and coordination of plant traits is critical for predicting how diverse species respond to climate change. According to hydraulic and economic theories, leaves and roots--key organs for resource acquisition--are expected to function in coordination, such that species with faster resource utilization would possess leaf and root traits that facilitate rapid carbon, nutrient, and water uptake and fluxes. However, there has been limited evidence supporting leaf-root trait coordination and a role for that coordination on community structure. Here, we measured 13 leaf and root functional traits for 101 woody species from six tropical and subtropical forests, and assessed coordination and its association with community dominance. Hydraulic traits, such as leaf vein density and root vessel density, were coordinated between organs and showed compensation trade-offs between traits within organs, such as, leaf vein density and diameter. Economic traits relating to composition, such as nitrogen concentration, were coordinated between organs, whereas economic structural traits were decoupled, such as leaf mass per area and specific root length. Overall, hydraulic traits and economics traits were partially independent. The coordination of flux-related leaf and root traits was associated with ectomycorrhizal symbiosis and with dominance within the community. These findings indicate how trait organization within and across organs contributes to optimal whole plant function, with implications for performance in natural communities.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.