Conant, R. T. et al. Temperature and soil organic matter decomposition rates—synthesis of current knowledge and a way forward. Glob. Change Biol. 17, 3392–3404 (2011).
Google Scholar
Yost, J. L. & Hartemink, A. E. How deep is the soil studied—an analysis of four soil science journals. Plant Soil 452, 5–18 (2020).
Google Scholar
Jobbágy, E. G. & Jackson, R. B. The vertical distribution of soil organic carbon and its relation to climate and vegetation. Ecol. Appl. 10, 423–436 (2000).
Google Scholar
Dove, N. C. et al. Continental-scale patterns of extracellular enzyme activity in the subsoil: an overlooked reservoir of microbial activity. Environ. Res. Lett. 15, 1040a1 (2020).
Google Scholar
Hicks Pries, C. E., Castanha, C., Porras, R. C. & Torn, M. S. The whole-soil carbon flux in response to warming. Science 355, 1420–1423 (2017).
Google Scholar
Taş, N. et al. Impact of fire on active layer and permafrost microbial communities and metagenomes in an upland Alaskan boreal forest. ISME J. 8, 1904–1919 (2014).
Google Scholar
Brewer, T. E. et al. Ecological and genomic attributes of novel bacterial taxa that thrive in subsurface soil horizons. mBio 10, e01318–e01319 (2019).
Google Scholar
Sulman, B. N. et al. Multiple models and experiments underscore large uncertainty in soil carbon dynamics. Biogeochemistry 141, 109–123 (2018).
Google Scholar
Romero-Olivares, A. L., Allison, S. D. & Treseder, K. K. Soil microbes and their response to experimental warming over time: a meta-analysis of field studies. Soil Biol. Biochem. 107, 32–40 (2017).
Google Scholar
Melillo, J. M. et al. Long-term pattern and magnitude of soil carbon feedback to the climate system in a warming world. Science 358, 101–105 (2017).
Google Scholar
Melillo, J. M. et al. Soil warming, carbon–nitrogen interactions, and forest carbon budgets. Proc. Natl Acad. Sci. USA 108, 9508–9512 (2011).
Google Scholar
Crowther, T. W. et al. Quantifying global soil carbon losses in response to warming. Nature 540, 104–108 (2016).
Google Scholar
Feng, X., Simpson, A. J., Wilson, K. P., Dudley Williams, D. & Simpson, M. J. Increased cuticular carbon sequestration and lignin oxidation in response to soil warming. Nat. Geosci. 1, 836–839 (2008).
Google Scholar
Dove, N. C., Stark, J. M., Newman, G. S. & Hart, S. C. Carbon control on terrestrial ecosystem function across contrasting site productivities: the carbon connection revisited. Ecology 100, e02695 (2019).
Google Scholar
Frey, S. D., Lee, J., Melillo, J. M. & Six, J. The temperature response of soil microbial efficiency and its feedback to climate. Nat. Clim. Change 3, nclimate1796 (2013).
Google Scholar
Olander, L. P. & Vitousek, P. M. Regulation of soil phosphatase and chitinase activity by N and P availability. Biogeochemistry 49, 175–190 (2000).
Google Scholar
DeAngelis, K. M. et al. Long-term forest soil warming alters microbial communities in temperate forest soils. Front. Microbiol. 6, 104–115 (2015).
Cheng, L. et al. Warming enhances old organic carbon decomposition through altering functional microbial communities. ISME J. 11, 1825–1835 (2017).
Google Scholar
Billings, S. A. & Ballantyne, F. How interactions between microbial resource demands, soil organic matter stoichiometry, and substrate reactivity determine the direction and magnitude of soil respiratory responses to warming. Glob. Change Biol. 19, 90–102 (2013).
Google Scholar
Rasmussen, C., Torn, M. S. & Southard, R. J. Mineral assemblage and aggregates control carbon dynamics in a California conifer forest. Soil Sci. Soc. Am. J. 69, 1711–1721 (2005).
Google Scholar
Jones, D. L. et al. Microbial competition for nitrogen and carbon is as intense in the subsoil as in the topsoil. Soil Biol. Biochem. 117, 72–82 (2018).
Google Scholar
Pold, G. et al. Carbon use efficiency and its temperature sensitivity covary in soil bacteria. mBio 11, e02293–19 (2020).
Google Scholar
Geyer, K. M., Dijkstra, P., Sinsabaugh, R. & Frey, S. D. Clarifying the interpretation of carbon use efficiency in soil through methods comparison. Soil Biol. Biochem. 128, 79–88 (2018).
Schmidt, M. W. I. et al. Persistence of soil organic matter as an ecosystem property. Nature 478, 49–56 (2011).
Google Scholar
Vitousek, P. M., Porder, S., Houlton, B. Z. & Chadwick, O. A. Terrestrial phosphorus limitation: mechanisms, implications, and nitrogen–phosphorus interactions. Ecol. Appl. 20, 5–15 (2010).
Google Scholar
Sullivan, B. W. et al. Assessing nutrient limitation in complex forested ecosystems: alternatives to large‐scale fertilization experiments. Ecology 95, 668–681 (2014).
Google Scholar
Hart, S. C., Firestone, M. K. & Paul, E. A. Decomposition and nutrient dynamics of ponderosa pine needles in a Mediterranean-type climate. Can. J. Forest Res. 22, 306–314 (1992).
Google Scholar
Dijkstra, P. et al. Effect of temperature on metabolic activity of intact microbial communities: evidence for altered metabolic pathway activity but not for increased maintenance respiration and reduced carbon use efficiency. Soil Biol. Biochem. 43, 2023–2031 (2011).
Google Scholar
Don, A., Rödenbeck, C. & Gleixner, G. Unexpected control of soil carbon turnover by soil carbon concentration. Environ. Chem. Lett. 11, 407–413 (2013).
Google Scholar
Rodriguez-R, L. M. & Konstantinidis, K. T. Nonpareil: a redundancy-based approach to assess the level of coverage in metagenomic datasets. Bioinformatics 30, 629–635 (2014).
Google Scholar
Rodriguez-R, L. M. & Konstantinidis, K. T. Estimating coverage in metagenomic data sets and why it matters. ISME J. 8, 2349–2351 (2014).
Google Scholar
Lombard, V., Golaconda Ramulu, H., Drula, E., Coutinho, P. M. & Henrissat, B. The carbohydrate-active enzymes database (CAZy) in 2013. Nucleic Acids Res. 42, D490–D495 (2014).
Google Scholar
Levasseur, A., Drula, E., Lombard, V., Coutinho, P. M. & Henrissat, B. Expansion of the enzymatic repertoire of the CAZy database to integrate auxiliary redox enzymes. Biotechnol. Biofuels 6, 41 (2013).
Google Scholar
Benoit, I. et al. Degradation of different pectins by fungi: correlations and contrasts between the pectinolytic enzyme sets identified in genomes and the growth on pectins of different origin. BMC Genomics 13, 321 (2012).
Google Scholar
Tveit, A. T., Urich, T. & Svenning, M. M. Metatranscriptomic analysis of arctic peat soil microbiota. Appl. Environ. Microbiol. 80, 5761–5772 (2014).
Google Scholar
Huergo, L. F. & Dixon, R. The emergence of 2-Oxoglutarate as a master regulator metabolite. Microbiol. Mol. Biol. Rev. 79, 419–435 (2015).
Google Scholar
Bai, X. et al. Expression of a β-mannosidase from Paenibacillus polymyxa A-8 in Escherichia coli and characterization of the recombinant enzyme. PLoS ONE 9, e111622 (2014).
Google Scholar
Sorensen, J. W., Dunivin, T. K., Tobin, T. C. & Shade, A. Ecological selection for small microbial genomes along a temperate-to-thermal soil gradient. Nat. Microbiol. 4, 55–61 (2019).
Google Scholar
Pold, G., Grandy, A. S., Melillo, J. M. & DeAngelis, K. M. Changes in substrate availability drive carbon cycle response to chronic warming. Soil Biol. Biochem. 110, 68–78 (2017).
Google Scholar
Yue, H. et al. The microbe-mediated mechanisms affecting topsoil carbon stock in Tibetan grasslands. ISME J. 9, 2012–2020 (2015).
Google Scholar
Xue, K. et al. Warming alters expressions of microbial functional genes important to ecosystem functioning. Front. Microbiol. 7, 668–681 (2016).
Google Scholar
Malik, A. A. et al. Defining trait-based microbial strategies with consequences for soil carbon cycling under climate change. ISME J. 14, 1–9 (2020).
Google Scholar
Johnston, E. R. et al. Responses of tundra soil microbial communities to half a decade of experimental warming at two critical depths. Proc. Natl Acad. Sci. USA 116, 15096–15105 (2019).
Google Scholar
Soong, J. L. et al. Microbial carbon limitation: the need for integrating microorganisms into our understanding of ecosystem carbon cycling. Glob. Change Biol. 26, 1953–1961 (2020).
Google Scholar
Chapin, F. S., Matson, P. A. & Vitousek, P. Principles of Terrestrial Ecosystem Ecology (Springer Science & Business Media, 2011).
Woodcroft, B. J. et al. Genome-centric view of carbon processing in thawing permafrost. Nature 560, 49–54 (2018).
Google Scholar
Oliverio, A. M., Bradford, M. A. & Fierer, N. Identifying the microbial taxa that consistently respond to soil warming across time and space. Glob. Change Biol. 23, 2117–2129 (2017).
Google Scholar
Pold, G. et al. Long-term warming alters carbohydrate degradation potential in temperate forest soils. Appl. Environ. Microbiol. 82, 6518–6530 (2016).
Google Scholar
Morrison, E. W. et al. Warming alters fungal communities and litter chemistry with implications for soil carbon stocks. Soil Biol. Biochem. 132, 120–130 (2019).
Google Scholar
Bai, W., Wang, G., Xi, J., Liu, Y. & Yin, P. Short-term responses of ecosystem respiration to warming and nitrogen addition in an alpine swamp meadow. Eur. J. Soil Biol. 92, 16–23 (2019).
Google Scholar
Tilman, D. Niche tradeoffs, neutrality, and community structure: a stochastic theory of resource competition, invasion, and community assembly. Proc. Natl Acad. Sci. USA 101, 10854–10861 (2004).
Google Scholar
Sharrar, A. M. et al. Bacterial secondary metabolite biosynthetic potential in soil varies with phylum, depth, and vegetation type. mBio 11, e00416–e00420 (2020).
Google Scholar
Qi, J. et al. Drying-wetting cycles: effect on deep soil carbon. Soil Syst. 2, 3 (2018).
Google Scholar
Butcher, K. R., Nasto, M. K., Norton, J. M. & Stark, J. M. Physical mechanisms for soil moisture effects on microbial carbon-use efficiency in a sandy loam soil in the western United States. Soil Biol. Biochem. 150, 107969 (2020).
Google Scholar
Zhou, W. P., Shen, W. J., Li, Y. E. & Hui, D. F. Interactive effects of temperature and moisture on composition of the soil microbial community. Eur. J. Soil Biol. 68, 909–918 (2017).
Google Scholar
Spohn, M., Klaus, K., Wanek, W. & Richter, A. Microbial carbon use efficiency and biomass turnover times depending on soil depth—Implications for carbon cycling. Soil Biol. Biochem. 96, 74–81 (2016).
Google Scholar
Saifuddin, M., Bhatnagar, J. M., Segrè, D. & Finzi, A. C. Microbial carbon use efficiency predicted from genome-scale metabolic models. Nat. Commun. 10, 1–10 (2019).
Google Scholar
Geyer, K. M., Kyker-Snowman, E., Grandy, A. S. & Frey, S. D. Microbial carbon use efficiency: accounting for population, community, and ecosystem-scale controls over the fate of metabolized organic matter. Biogeochemistry 127, 173–188 (2016).
Google Scholar
Dove, N. C., Safford, H. D., Bohlman, G. N., Estes, B. L. & Hart, S. C. High-severity wildfire leads to multi-decadal impacts on soil biogeochemistry in mixed-conifer forests. Ecol. Appl. 30, e02072 (2020).
Google Scholar
Bradford, M. A. et al. Thermal adaptation of soil microbial respiration to elevated temperature. Ecol. Lett. 11, 1316–1327 (2008).
Google Scholar
Walters, W. et al. Improved bacterial 16S rRNA gene (V4 and V4-5) and fungal internal transcribed spacer marker gene primers for microbial community surveys. mSystems 1, e00009–e00015 (2016).
Google Scholar
Caporaso, J. G. et al. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 7, 335–336 (2010).
Google Scholar
Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2013).
Google Scholar
Edgar, R. C. UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat. Methods 10, 996–998 (2013).
Google Scholar
Zhang, Z., Schwartz, S., Wagner, L. & Miller, W. A greedy algorithm for aligning DNA sequences. J. Comput. Biol. 7, 203–214 (2000).
Google Scholar
Nguyen, N. H. et al. FUNGuild: An open annotation tool for parsing fungal community datasets by ecological guild. Fungal Ecol. 20, 241–248 (2016).
Google Scholar
Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).
Google Scholar
Menzel, P., Ng, K. L. & Krogh, A. Fast and sensitive taxonomic classification for metagenomics with Kaiju. Nat. Commun. 7, 11257 (2016).
Google Scholar
Hyatt, D. et al. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics 11, 119 (2010).
Google Scholar
Buchfink, B., Xie, C. & Huson, D. H. Fast and sensitive protein alignment using DIAMOND. Nat. Methods 12, 59–60 (2015).
Google Scholar
Eddy, S. R. Accelerated profile HMM searches. PLoS Comput. Biol. 7, e1002195 (2011).
Google Scholar
Li, D. et al. MEGAHIT v1.0: A fast and scalable metagenome assembler driven by advanced methodologies and community practices. Methods 102, 3–11 (2016).
Google Scholar
Bushnell, B. BBMap: A Fast, Accurate, Splice-Aware Aligner. No. LBNL-7065E (Ernest Orlando Lawrence Berkeley National Laboratory, 2014).
Nurk, S., Meleshko, D., Korobeynikov, A. & Pevzner, P. A. metaSPAdes: a new versatile metagenomic assembler. Genome Res. 27, 824–834 (2017).
Google Scholar
Xue, Y., Jonassen, I., Øvreås, L. & Taş, N. Metagenome-assembled genome distribution and key functionality highlight importance of aerobic metabolism in Svalbard permafrost. FEMS Microbiol Ecol. 96, fiaa057 (2020).
Google Scholar
Wu, Y.-W., Simmons, B. A. & Singer, S. W. MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets. Bioinformatics 32, 605–607 (2016).
Google Scholar
Kang, D. D., Froula, J., Egan, R. & Wang, Z. MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities. PeerJ 3, e1165 (2015).
Google Scholar
Sieber, C. M. K. et al. Recovery of genomes from metagenomes via a dereplication, aggregation and scoring strategy. Nat. Microbiol. 3, 836–843 (2018).
Google Scholar
Parks, D. H., Imelfort, M., Skennerton, C. T., Hugenholtz, P. & Tyson, G. W. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 25, 1043–1055 (2015).
Google Scholar
Jain, C., Rodriguez-R, L. M., Phillippy, A. M., Konstantinidis, K. T. & Aluru, S. High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries. Nat. Commun. 9, 5114 (2018).
Google Scholar
Bowers, R. M. et al. Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea. Nat. Biotechnol. 35, 725–731 (2017).
Google Scholar
Chaumeil, P.-A., Mussig, A. J., Hugenholtz, P. & Parks, D. H. GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database. Bioinformatics 36, 1925–1927 (2019).
Aziz, R. K. et al. The RAST server: rapid annotations using subsystems technology. BMC Genomics 9, 1–15 (2008).
Google Scholar
Arkin, A. P. et al. KBase: The United States Department of Energy Systems Biology Knowledgebase. Nat. Biotechnol. 36, 566–569 (2018).
Google Scholar
Zhou, Z., Tran, P., Liu, Y., Kieft, K. & Anantharaman, K. METABOLIC: a scalable high-throughput metabolic and biogeochemical functional trait profiler based on microbial genomes. bioRxiv https://doi.org/10.1101/761643 (2019).
Emiola, A. & Oh, J. High throughput in situ metagenomic measurement of bacterial replication at ultra-low sequencing coverage. Nat. Commun. 9, 1–8 (2018).
Google Scholar
Binkley, D. & Hart, S. C. in Advances in Soil Science (ed. Stewart, B. A.) 57–112 (Springer New York, 1989).
Fox, J. & Weisberg, S. An R companion to applied regression Ch.4. (Sage, 2019).
Bates, D., Maechler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).
Google Scholar
McMurdie, P. J. & Holmes, S. phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE 8, e61217 (2013).
Google Scholar
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).
Google Scholar
Oksanen, J. et al. vegan: Community Ecology Package. https://cran.r-project.org/web/packages/vegan/index.html (2013).
Lozupone, C. & Knight, R. UniFrac: a new phylogenetic method for comparing microbial communities. Appl. Environ. Microbiol. 71, 8228–8235 (2005).
Google Scholar
Bruns, T. D., White, T. J. & Taylor, J. W. Fungal molecular systematics. Annu. Rev. Ecol. Evol. Syst. 22, 525–564 (1991).
Google Scholar
Source: Ecology - nature.com
