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Soils represent the largest terrestrial reservoir of organic carbon, and the balance between soil organic carbon (SOC) formation and loss will drive powerful carbon-climate feedbacks over the coming century. To date, efforts to predict SOC dynamics have rested on pool-based models, which assume classes of SOC with internally homogenous physicochemical properties. However, emerging evidence suggests that soil carbon turnover is not dominantly controlled by the chemistry of carbon inputs, but rather by restrictions on microbial access to organic matter in the spatially heterogeneous soil environment. The dynamic processes that control the physicochemical protection of carbon translate poorly to pool-based SOC models; as a result, we are challenged to mechanistically predict how environmental change will impact movement of carbon between soils and the atmosphere. Here, we propose a novel conceptual framework to explore controls on belowground carbon cycling: Probabilistic Representation of Organic Matter Interactions within the Soil Environment (PROMISE). In contrast to traditional model frameworks, PROMISE does not attempt to define carbon pools united by common thermodynamic or functional attributes. Rather, the PROMISE concept considers how SOC cycling rates are governed by the stochastic processes that influence the proximity between microbial decomposers and organic matter, with emphasis on their physical location in the soil matrix. We illustrate the applications of this framework with a new biogeochemical simulation model that traces the fate of individual carbon atoms as they interact with their environment, undergoing biochemical transformations and moving through the soil pore space. We also discuss how the PROMISE framework reshapes dialogue around issues related to SOC management in a changing world. We intend the PROMISE framework to spur the development of new hypotheses, analytical tools, and model structures across disciplines that will illuminate mechanistic controls on the flow of carbon between plant, soil, and atmospheric pools.

We thank Baveye and colleagues (2021) for calling attention to the important role of soil structure in driving patterns of belowground carbon cycling - in fact, the rich literature on soil spatial heterogeneity directly inspired aspects of our PROMISE model framework (Waring et al. 2020). However, as we argue below, the key innovation of the PROMISE model does not lie solely in its acknowledgement of soil spatial structure. Rather, it hinges on the way PROMISE allows stochastic movement of particles throughout the soil pore space to decouple the chemical attributes of organic matter from its belowground residence time.

We concur with Azizi-Rad et al. (2021) that it is vital to critically evaluate and compare different soil carbon models, and we welcome the opportunity to further describe the unique contribution of the PROMISE model (Waring et al. 2020) to this literature. The PROMISE framework does share many features with established biogeochemical models, as our original manuscript highlighted in Table 1, and our work builds upon model innovations developed by many different groups, including that of Azizi-Rad and colleagues. Yet, the PROMISE framework is distinctive due to where it places mechanistic emphasis, and how these mechanisms are formalized in the mathematical model structure.

Nutrient amendment diminished bacterial functional diversity, consolidating carbon flow through fewer bacterial taxa. Here, we show strong differences in the bacterial taxa responsible for respiration from four ecosystems, indicating the potential for taxon-specific control over soil carbon cycling. Trends in functional diversity, defined as the richness of bacteria contributing to carbon flux and their equitability of carbon use, paralleled trends in taxonomic diversity although functional diversity was lower overall. Among genera common to all ecosystems, Bradyrhizobium, the Acidobacteria genus RB41, and Streptomyces together composed 45–57% of carbon flow through bacterial productivity and respiration. Bacteria that utilized the most carbon amendment (glucose) were also those that utilized the most native soil carbon, suggesting that the behavior of key soil taxa may influence carbon balance. Mapping carbon flow through different microbial taxa as demonstrated here is crucial in developing taxon-sensitive soil carbon models that may reduce the uncertainty in climate change projections., The fate of soil carbon depends on microbial processes, but whether different microbial taxa have individualistic effects on carbon fluxes is unknown. Here the authors use 16 S amplicon sequencing and stable isotopes to show how taxonomic differences influence bacterial respiration and carbon cycling across four ecosystems.

Empirical evidence for the response of soil carbon cycling to the combined effects of warming, drought and diversity loss is scarce. Microbial carbon use efficiency (CUE) plays a central role in regulating the flow of carbon through soil, yet how biotic and abiotic factors interact to drive it remains unclear. Here, we combine distinct community inocula (a biotic factor) with different temperature and moisture conditions (abiotic factors) to manipulate microbial diversity and community structure within a model soil. While community composition and diversity are the strongest predictors of CUE, abiotic factors modulated the relationship between diversity and CUE, with CUE being positively correlated with bacterial diversity only under high moisture. Altogether these results indicate that the diversity × ecosystem-function relationship can be impaired under non-favorable conditions in soils, and that to understand changes in soil C cycling we need to account for the multiple facets of global changes., Microbial carbon use efficiency has an important role in soil C cycling. Here the authors test the interactive effects of temperature and moisture and manipulate microbial community composition in soil microcosms, showing a positive relationship between microbial diversity and CUE that is contingent on abiotic conditions.

Microbes decompose soil organic matter (SOM), yet it is unclear how substrate inputs (i.e., stoichiometry) directly mediate microbial activities and community dynamics. We hypothesized that C+N input has the largest effect on microbial respiration and community structure, followed by C input and N input. Soils were collected from four ecosystems (grassland, pinon-juniper, ponderosa pine, mixed conifer) and amended with NH4NO3 (N only; 100 μg g−1 wk−1), 13C-glucose (C only; 1000 μg g−1 wk−1), or C+N in a five-week laboratory incubation. We found that C+N input induced the greatest total respiration while C input induced the greatest SOM-derived respiration (i.e., priming effect) across ecosystems. Shifts in community composition were the largest with C+N input, followed by C input, and showed little response to N input. C only and C+N inputs increased both of the relative and absolute abundances of Actinobacteria and Proteobacteria (α, β, γ), but reduced the relative abundances of Verrucomicrobia and δ-Proteobacteria. C+N input increased the relative abundances of Bacillales, Rhizobiales, Burkholderiales and of 9 families, and reduced the relative abundances of Myxococcales and of 12 families, but showed little effect on the absolute abundances of these bacterial taxa. N input reduced the absolute abundances of Actinobacteria, Proteobacteria, and Verrucomicrobia but did not affect their relative abundances in the mixed conifer soil; by contrast, N input reduced relative abundances of δ-Proteobacteria and increased the relative abundances of γ-Proteobacteria but did not affect their absolute abundances in the ponderosa pine soil. We also found that substrate inputs were the main driver of SOM decomposition, microbial respiration and diversity, while soil ecosystem was the main driver of community composition and abundances of most bacterial phyla. Our work suggests that substrate stoichiometry has predictable effects on soil C cycling, microbial diversity and community composition, but has variable effects on microbial abundances, and that incorporating bacterial gene copies in abundance calculations can help more accurately estimate microbial responses across taxonomic levels and ecosystems.

Climate warming can affect the temperature sensitivity of microbial activity and growth efficiency, possibly explained by changes to microbially unavailable carbon (C) protected within in soil aggregates. We assessed physical protection by crushing macroaggregates (250–2000 μm) and microaggregates (

Fertilizer inputs affect plant uptake of native soil nitrogen (N), yet the underlying mechanisms remain elusive. To increase mechanistic insight into this phenomenon, we evaluated the effect of fertilizer addition on mineralization (in the absence of plants) and plant uptake of native soil N. We synthesized 43 isotope tracer (15N) studies and estimated the effects of fertilizer addition using meta-analysis. We found that organic fertilizer tended to reduce native soil N mineralization (−99 kg ha−1 year−1; p = 0.09) while inorganic fertilizer tended to increase N priming (58 kg ha−1 year−1; p = 0.17). In contrast, both organic and inorganic fertilizers significantly increased plant uptake of native soil N (179 and 107 kg ha−1 year−1). Organic fertilizer had greater effect on plant uptake than on mineralization of native soil N (p

Labile carbon (C) input to soil can accelerate or slow the decomposition of soil organic matter, a phenomenon called priming. However, priming is difficult to predict, making its relationship with C input elusive. To assess this relationship, we added 13C-glucose at five levels (8 to 1606 μg C g−1 week−1) to the soil from four different ecosystems for seven weeks. We observed a positive linear relationship between C input and priming in all soils: priming increased from negative or no priming at low C input to strong positive priming at high C input. However, the sensitivity of priming to C input varied among soils and between ways of expressing C input, and decreased with elevation. Positive substrate thresholds were detected in three soils (56 to 242 μg C g−1 week−1), suggesting the minimum C input required to trigger positive priming. Carbon input expressed as a fraction of microbial biomass explained 16.5% less variation in priming than did C input expressed as a fraction of dry soil mass, indicating that priming is not strongly related to the size of the soil microbial biomass. We conclude that priming increases with the rate of labile C input, once that rate exceeds a threshold, but the magnitude of increase varies among soils. Further research on mechanisms causing the variation of priming sensitivity to increasing labile C input might help promote a quantitative understanding of how such phenomenon impacts soil C cycling, offering the potential to improve earth system models.

Organisms influence ecosystems, from element cycling to disturbance regimes, to trophic interactions and to energy partitioning. Microorganisms are part of this influence, and understanding their ecology in nature requires studying the traits of these organisms quantitatively in their natural habitats-a challenging task, but one which new approaches now make possible. Here, we show that growth rate and carbon assimilation rate of soil microorganisms are influenced more by evolutionary history than by climate, even across a broad climatic gradient spanning major temperate life zones, from mixed conifer forest to high-desert grassland. Most of the explained variation (~50% to ~90%) in growth rate and carbon assimilation rate was attributable to differences among taxonomic groups, indicating a strong influence of evolutionary history, and taxonomic groupings were more predictive for organisms responding to resource addition. With added carbon and nitrogen substrates, differences among taxonomic groups explained approximately eightfold more variance in growth rate than did differences in ecosystem type. Taxon-specific growth and carbon assimilation rates were highly intercorrelated across the four ecosystems, constrained by the taxonomic identity of the organisms, such that plasticity driven by environment was limited across ecosystems varying in temperature, precipitation and dominant vegetation. Taken together, our results suggest that, similar to multicellular life, the traits of prokaryotes in their natural habitats are constrained by evolutionary history to a greater degree than environmental variation.

Relationships between microbial genes and performance are often evaluated in the laboratory in pure cultures, with little validation in nature. Here, we show that genomic traits related to laboratory measurements of maximum growth potential failed to predict the growth rates of bacteria in unamended soil, but successfully predicted growth responses to resource pulses: growth increased with 16S rRNA gene copy number and declined with genome size after substrate addition to soils, responses that were repeated in four different ecosystems. Genome size best predicted growth rate in response to addition of glucose alone; adding ammonium with glucose weakened the relationship, and the relationship was absent in nutrient-replete pure cultures, consistent with the idea that reduced genome size is a mechanism of nutrient conservation. Our findings demonstrate that genomic traits of soil bacteria can map to their ecological performance in nature, but the mapping is poor under native soil conditions, where genomic traits related to stress tolerance may prove more predictive. These results remind that phenotype depends on environmental context, underscoring the importance of verifying proposed schemes of trait-based strategies through direct measurement of performance in nature, an important and currently missing foundation for translating microbial processes from genes to ecosystems.

Soil microbial carbon use efficiency (CUE) is a combination of growth and respiration, which may respond differently to climate change depending on physical protection of soil carbon (C) and its availability to microbes. In a mid-latitude hardwood forest in central Massachusetts, 27 years of soil warming (+5 °C) has resulted in C loss and altered soil organic matter (SOM) quality, yet the underlying mechanisms remain unclear. Here, we hypothesized that long-term warming reduces physical aggregate protection of SOM, microbial CUE, and its temperature sensitivity. Soil was separated into macroaggregate (250–2000 μm) and microaggregate (

Organic matter input to soils can accelerate the decomposition of native soil carbon (C), a process called the priming effect. Priming is ubiquitous and exhibits some consistent patterns, but a general explanation remains elusive, in part because of variation in the response across different ecosystems, and because of a diversity of proposed mechanisms, including microbial activation, stoichiometry, and community shifts. Here, we conducted five-week incubations of four soils (grassland, pinon-juniper, ponderosa pine, mixed conifer), varying the amount of substrate added (as 13C-glucose, either 350 or 1000 μg C g−1 week−1) and either with no added nitrogen (N), or with sufficient N (as NH4NO3) to bring the C-to-N ratio of the added substrate to 10. Using four different ecosystems enabled testing the generality of mechanisms underlying the priming effect. The responses of priming to the amount and C-to-N ratio of the added substrate were consistent across ecosystems: priming increased with the rate of substrate addition and declined when the C-to-N ratio of the substrate was reduced. However, structural equation models failed to confirm intermediate responses postulated to mediate the priming effect, including responses postulated to be mediated by stoichiometry and microbial activation. Specifically, priming was not clearly associated with changes in microbial biomass or turnover, nor with extracellular enzyme activities or the microbial C-to-N ratio. The strongest explanatory pathways in the structural equation models were the substrate, soil, and C-to-N ratio treatments themselves, with no intermediates, suggesting that either these measurements lacked sufficient sensitivity to reveal causal relationships, or the actual drivers for priming were not included in the ancillary measurements. While we observed consistent changes in priming caused by the amount and C-to-N ratio of the added substrate across a wide array of soils, our findings did not clearly conform to common models offered for the priming effect. Because priming is a residual flux involving diverse substrates of varying chemical composition, a simple and generalizable explanation of the phenomenon may be elusive.

Nitrogen use efficiency (NUE) is a crucial index for developing sustainable bioenergy cropping systems. The objective of this study was to examine switchgrass (Panicum virgatum L.) NUE by using a low-cost organic amendment under different harvest frequencies. Aerobically digested biosolids were applied at 0, 153, 306, and 459 kg N ha−1 in a small plot study, and lime-stabilized biosolids were applied at 0, 77, and 154 kg N ha−1 in a field-scale study in Virginia, USA. Switchgrass was harvested once or twice per season. Switchgrass N concentration and N removal were measured to estimate switchgrass NUE, annual N recovery (ANR), and partial factor productivity (PFP). Across N rates, biosolid application increased biomass N concentration and removal by 29 % and 84 % and decreased NUE, ANR, and PFP in the plot study, but effects were inconsistent in the field study. Low NUE, ANR, and PFP obtained with a single, end-of-season harvest were likely functions of low feedstock N concentrations. Switchgrass harvested in summer had highest N concentrations. Cutting twice per season removed more N than cutting once; the resulting increase in NUE reflects differences in feedstock N concentrations rather than differences in yield. Our results suggest that biosolids can be applied as an alternative N source to support plant growth, and cutting once per season is preferable in sustainable biofuel production systems.

Biofuel crops have relatively low economic value, and potential to grow them with low-cost inputs is essential for economic viability. Use of biosolids as a fertility source has not been explored at the field scale for switchgrass (Panicum virgatum L.), a potential bioenergy crop. This study tested harvest management and biosolids rate effects on switchgrass production, quality, and theoretical ethanol yield in Virginia, USA. Switchgrass (cv. “Cave-in-Rock”) was annually cut once (winter) or twice (summer and winter) for 2 years. Biosolids were applied once at 0, 77, and 154 kg N ha−1 in May 2011; urea was applied once at 146 kg N ha−1 for comparison. Feedstock yield and quality parameters (neutral and acid detergent fibers, cellulose, hemicellulose, lignin, and ash) were measured and used to compute theoretical ethanol potential (TEP) and theoretical ethanol yield (TEY). Cutting twice per season produced greater biomass yields than cutting once (6.6 vs 5.4 Mg ha−1) in 2011 but not in 2012. Cutting once per season produced feedstock with greater TEP (513 vs 433 L Mg−1) and TEY (2,980 vs 2,680 L ha−1) in both years. Biosolids and urea increased biomass yields by 11 % (0.6 Mg ha−1) and TEY by 13 % (352 L Mg−1), but both decreased TEP by 1 % (7.1 L Mg−1 biomass). Cutting once per season is advantageous in producing more TEY given comparable biomass yield and superior feedstock quality. Biosolids were a suitable alternate N source and could boost biomass and biofuel production while reducing input costs in switchgrass-based bioenergy systems.

Sustainable development of a bioenergy industry will require low-cost, high-yielding biomass feedstock of desirable quality. Switchgrass (Panicum virgatum L.) is one of the primary feedstock candidates in North America, but the potential to grow this biomass crop using fertility from biosolids has not been fully explored. The objective of this study was to examine the effects of harvest frequency and biosolids application on switchgrass in Virginia, USA. ‘Cave-in-Rock’ switchgrass from well-established plots was cut once (November) or twice (July and November) per year between 2010 and 2012. Class A biosolids were applied once at rates of 0, 153, 306, and 459 kg N ha−1 in May 2010. Biomass yield, neutral and acid detergent fiber, cellulose, hemicellulose, lignin, and ash were determined. Theoretical ethanol potential (TEP, l ethanol Mg−1 biomass) and yield (TEY, l ethanol ha−1) were calculated based on cellulose and hemicellulose concentrations. Cutting twice per season produced greater biomass yields than one cutting (11.7 vs. 9.8 Mg ha−1) in 2011, but no differences were observed in other years. Cutting once produced feedstock with greater TEP (478 vs. 438 l Mg−1), but no differences in TEY between cutting frequencies. Biosolids applied at 153, 306, and 459 kg N ha−1 increased biomass yields by 25%, 37%, and 46%, and TEY by 25%, 34%, and 42%, respectively. Biosolids had inconsistent effects on feedstock quality and TEP. A single, end-of-season harvest likely will be preferred based on apparent advantages in feedstock quality. Biosolids can serve as an effective alternative to N fertilizer in switchgrass-to-energy systems.

International audience; High-throughput RNA sequencing offers broad opportunities to explore the Earth RNA virome. Mining 5,150 diverse metatranscriptomes uncovered >2.5 million RNA virus contigs. Analysis of >330,000 RNA-dependent RNA polymerases (RdRPs) shows that this expansion corresponds to a 5-fold increase of the known RNA virus diversity. Gene content analysis revealed multiple protein domains previously not found in RNA viruses and implicated in virus-host interactions. Extended RdRP phylogeny supports the monophyly of the five established phyla and reveals two putative additional bacteriophage phyla and numerous putative additional classes and orders. The dramatically expanded phylum Lenarviricota, consisting of bacterial and related eukaryotic viruses, now accounts for a third of the RNA virome. Identification of CRISPR spacer matches and bacteriolytic proteins suggests that subsets of picobirnaviruses and partitiviruses, previously associated with eukaryotes, infect prokaryotic hosts.