henhaobio
Sign in

EcosphereEcologyPeer-reviewed journal article

Microbial functional guilds and genes are key to explaining soil nutrient cycling alongside soil and plant variables

Corinne R. VietorisziD, Nahuel PolicelliiD, Abigail Li, Lindsey A. Adams, Kathryn F. AthertoniD, Jennifer M. BhatnagariD

PDFDOIPreprint

Abstract

Microbes play central roles in soil nutrient cycling, yet a limited range of microbial community characteristics have been used to explain ecosystem nutrient cycling rates and their importance relative to plant and abiotic factors remains unclear. In this study, we assessed which of 126 commonly measured soil fungal and bacterial community characteristics best explained soil nitrogen (N) and phosphorus (P) cycling rates in temperate forests in the Northeastern U.S., as well as the relative contributions of microbial, plant, and abiotic factors. Using boosted regression tree modeling, we identified the microbial variables with the highest contributions to models explaining nutrient cycling rates: the relative abundances of ectomycorrhizal fungi and N-decomposition genes from oligotrophic bacteria were the most important for net ammonification, the relative abundances of indicator taxa in bacterial networks, nitrifying bacteria, and copiotrophic bacteria were the most important for net nitrification, and the relative abundance of fungal P-cycling oxidoreductase genes was the most important for net soil phosphate change. Microbial variables explained more variation than plant and abiotic variables in multivariate linear models of net nitrification and net phosphate release rates, but not net ammonification rates, which were largely explained by soil edaphic factors. Leaf litter traits were also important in explaining variation in net nitrification rates, and soil temperature was important in explaining rates of net phosphate release in soil. Collectively, our findings suggest that the N-cycling capacity of microbial functional guilds and fungal community P-cycling capacity should be incorporated into ecosystem biogeochemical models to improve our predictions and understanding of nutrient cycling and related ecological processes.

Citations
13
FWCI
5.66
Field percentile
top 3%

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.