Litter chemical quality strongly affects forest floor microbial groups and ecoenzymatic stoichiometry in the subalpine forest
Litter chemical quality regulates the distinct composition of the main microbial groups and ecoenzymatic stoichiometry. Microbes in spruce ( Picea asperata Mast.) and fir ( Abies faxoniana Rehd.) rather than birch ( Betula platyphylla Suk.) and rhododendron ( Rhododendron lapponicum (L.) Wahl.) can more easily adjust their physiological metabolism to acclimate to low N resources.
Context Litter decomposition is the main pathway of nutrient cycling that bridges aboveground and underground material circulation and energy flow. Microorganisms are essential for the regulation of organic carbon decomposition and nutrient cycling.
Aims We sought to reveal whether litter chemical quality predominates forest floor microbial structure and function in different species and how their characteristics vary with litter decomposition stages.
Methods We measured litter substrate quality, microbial community structure, microbial biomass carbon (MBC) and nitrogen (MBN), extracellular enzyme activities and stoichiometric homeostasis of fresh litter (L), and fermentative (F) and humus (H) layers for these tree species.
Results Overall, the enzyme activities and microbial biomass of birch and rhododendron were greater than those of spruce and fir. The microbial abundances of birch and rhododendron decreased with decomposition. Forest floor microbial nutrient limitation is generally restricted by N in subalpine forests, and ecoenzymatic stoichiometry is affected mainly by dissolved C/N/P stoichiometry. Stronger microbial C:N homeostasis (H′) was observed for spruce (5.56) and fir (4.17) than that for birch (1.82) and rhododendron (1.33).
Conclusion We conclude that litter chemical quality led to the disparity in forest floor microbial groups and ecoenzymatic stoichiometry for different tree species.
Keywords
Tree species, Forest floor layers, Litter chemical quality, Microbial biomass, Ecoenzymatic stoichiometry
Publication
Liu, Y., Shen, X., Chen, Y. et al. Annals of Forest Science (2019) 76: 106. https://doi.org/10.1007/s13595-019-0890-3
For the read-only version of the full text: https://rdcu.be/bW3im
Data availability
The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.
