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Title: Soil microbial function and fungal community data along an ectomycorrhizal basal area gradient, Vermont, May 2019

Dataset ·
DOI:https://doi.org/10.15485/1659374· OSTI ID:1659374

Mycorrhizal fungi can affect soil organic matter cycling through several mechanisms including priming, nutrient competition, and direct enzyme production. Differences in nutrient foraging strategies between ectomycorrhizal (EcM) and arbuscular mycorrhizal (AM) fungi produce divergent belowground dynamics: where EcM can take up organic nitrogen and directly break down SOM by producing enzymes, AM fungi are limited to scavenging mineral N. EcM-associated tree species also have leaf litter with relatively higher ratios of carbon to nitrogen (C:N), and belowground saprotrophic communities more dominated by fungi. Consequently, free-living microbes in EcM-dominated soils should experience nitrogen limitation, with subsequent increases in enzyme production and decreased carbon use efficiency (CUE). However, the relative importance of the effects of substrate quality and fungal community composition on enzyme production and CUE are unclear. To assess this distinction, we sampled the organic horizon and 10 cm of the mineral horizon in northern temperate forest soils along a gradient of EcM dominance (see SCxTS_DBH.csv for full tree species information). We characterized fungal community composition by measuring EcM relative abundances from extracted fungal DNA (To run raw ASV data through R code, use SCxTS_ASV_taxonomy.csv, and R code ITS_processing.Rmd; to see processed data with EcM relative abundance, use file SCxTS_sum_afitch_Feb18.20.csv) and the fungal to bacterial ratios (see data file SCxTS_plfa.csv) from phospholipid fatty acid analysis. Soil microbial functions were measured as potential activities of five hydrolytic and two oxidative enzymes ( To run raw data through R code us SCxTS_metadata.csv, hydrolytic_oxidative_raw.csv, MUBraw.csv, Enzyme_soilweight.csv, and incubationtime.csv, and R code SCxTS_enzymes.Rmd; to use Enzyme data ready to run through statistics code, use file Enzyme.data.csv) and microbial carbon use efficiency (see file SCxTS_CUE.csv and for full calculations file 18O_CUEcalcs_SCxTS_2019.xlsx). We assessed soil substrate quality as the soil carbon:nitrogen ratio (See file Organic_CN.csv). Statistical analysis can be run using R code from file SCxTS_analysis.Rmd.

Research Organization:
Environmental System Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) (United States); Testing mechanisms of how mycorrhizal associations affect forest soil carbon and nitrogen cycling
Sponsoring Organization:
U.S. DOE > Office of Science > Biological and Environmental Research (BER)
OSTI ID:
1659374
Country of Publication:
United States
Language:
English