AUTHOR=Su Yuqiao , Jia Xiaorong , Zhang Lu , Chen Hui TITLE=Size-dependent associations of woody plant structural diversity with soil C:N:P stoichiometry in a subtropical forest JOURNAL=Frontiers in Environmental Science VOLUME=10 YEAR=2022 URL=https://www.frontiersin.org/journals/environmental-science/articles/10.3389/fenvs.2022.990387 DOI=10.3389/fenvs.2022.990387 ISSN=2296-665X ABSTRACT=

Woody plant structural diversity and soil C:N:P stoichiometry have widely been examined for their spatial patterns and changes across environmental gradients, but the interactions and relationship of these biotic and abiotic variables have not been well understood. Here, we investigated the associations of woody plant structural diversity variables with soil total organic carbon (TOC), total nitrogen (TN), total phosphorus (TP), and their stoichiometry. We found only weak associations between soil C:N:P stoichiometry and species diversity variables, however, stronger significant associations were detected between C:N:P stoichiometry and species diversity variables for the adult trees and saplings when analyses were carried out with appropriate size stratification of woody plants. Most size diversity variables were significantly correlated with TOC, TN, TP, and their stoichiometric ratios, and the size diversity variables were greater in strength than species diversity in their associations with TOC, TN, TP, and C:N:P stoichiometric ratios. In most cases, C:N:P stoichiometric ratios were more sensitive than TOC, TN, or TP in predicting species diversity and size diversity. Our findings demonstrate that the associations of woody plant species diversity with TOC, TN, TP, C:N:P stoichiometry are size-dependent, and the size diversity is much more sensitive than species diversity in predicting the change of soil TOC, TN, TP, and C:N:P stoichiometric ratios. These findings also suggest that an appropriate size stratification will help demonstrate the linear relations between woody plant structural diversity and C:N:P stoichiometry and amplify the environmental signals from soil factors in predicting the biotic variables.