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キーワード:
Fagus sylvatica; Forest management; Fungal metabarcoding; Litter decomposition; Metabolomics; Metatranscriptomics
要旨:
In forest ecosystems, decomposition is essential for carbon and nutrient cycling and therefore a key process for ecosystem functioning. During the decomposition process, litter chemistry, involved decomposer organisms, and enzymatic activity change interdependently. Chemical composition of the litter is the most complex and dynamic component in the decomposition process and therefore challenging to assess holistically. In this study, we aimed to characterize chemical shifts during decomposition and link them to changes in decomposer fungal activity. We characterized the chemical composition of freshly fallen autumn leaves of European beech (Fagus sylvatica) and the corresponding leaf litter after 1 year of decomposition by proton nuclear magnetic resonance spectroscopy. We further tested the applicability of spiking experiments for qualitative and quantitative characterization of leaves and litter chemistry. The composition and transcriptional activity of fungal communities was assessed by high-throughput Illumina sequencing in the same litter samples. We were able to distinguish freshly fallen leaves from 1-year-old litter based on their chemical composition. Chemical composition of leaves converged among regions with progressing decomposition. Fungal litter communities differed in composition among regions, but they were functionally redundant according to the expression of genes encoding litter degrading enzymes (CAZymes). Fungi of the saprotrophic genera Mycena and Chalara correlated with transcription of litter-degrading CAZymes in 1-year-old litter. Forestry measures influenced the diversity and transcription rate of the detected CAZymes transcripts in litter. Their expression was primarily predicted by composition of the soluble chemical fraction of the litter. Environmental NMR fingerprints thus proved valuable for inferring ecological contexts. We propose and discuss a holistic framework to link fungal activity, enzyme expression, and chemical composition. © 2023, The Author(s).
