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Soil carbon (C) responses to environmental change represent a major source of uncertainty in the global carbon cycle. Feedbacks between soil C stocks and climate drivers could impact atmospheric CO2 levels, further altering the climate. Here, we analyzed and intercompared the soil C change in multiple Earth system models (ESMs) of the Coupled Model Intercomparison Project phases 5 and 6 (CMIP5 and CMIP6). Earth system models predicted global soil C gains under the high emission scenario, with soils taking up 43.9 Pg [95%CI: 9.2–78.5 Pg] C on average during the 21st century. The variation in global soil C change declined significantly from CMIP5 to CMIP6 models. Dominant processes underlying soil C change at global or biome scales differed among models and in many cases between the two phases for the same models. Model structure accounted for more than 60% variation of the global soil C change predicted by CMIP5 ESMs, but only 36% for CMIP6 models. Although current Earth system model predictions were converging on increased soil C storage during the 21st century, this consensus obscured substantial model disagreement on the mechanisms and spatial variation of soil C response to climate change.

Atmospheric nitrogen (N) deposition is enriching soils with N across biomes. Soil N enrichment can increase plant productivity and affect microbial activity, thereby increasing soil organic carbon (SOC), but such responses vary across biomes. Drylands cover ~45% of Earth's land area and store ~33% of global SOC contained in the top 1 m of soil. Nitrogen fertilization could, therefore, disproportionately impact carbon (C) cycling, yet whether dryland SOC storage increases with N remains unclear. To understand how N enrichment may change SOC storage, we separated SOC into plant-derived, particulate organic C (POC), and largely microbially derived, mineral-associated organic C (MAOC) at four N deposition experimental sites in Southern California. Theory suggests that N enrichment increases the efficiency by which microbes build MAOC (C stabilization efficiency) if soil pH stays constant. But if soils acidify, a common response to N enrichment, then microbial biomass and enzymatic organic matter decay may decrease, increasing POC but not MAOC. We found that N enrichment had no effect on C fractions except for a decrease in MAOC at one site. Specifically, despite reported increases in plant biomass in three sites and decreases in microbial biomass and extracellular enzyme activities in two sites that acidified, POC did not increase. Furthermore, microbial C use and stabilization efficiency increased in a non-acidified site, but without increasing MAOC. Instead, MAOC decreased by 16% at one of the sites that acidified, likely because it lost 47% of the exchangeable calcium (Ca) relative to controls. Indeed, MAOC was strongly and positively affected by Ca, which directly and, through its positive effect on microbial biomass, explained 58% of variation in MAOC. Long-term effects of N fertilization on dryland SOC storage appear abiotic in nature, such that drylands where Ca-stabilization of SOC is prevalent and soils acidify, are most at risk for significant C loss.

Nitrogen enrichment due to atmospheric nitrogen deposition has affected plant growth and microbial activity globally, leading to an increase in soil organic carbon in many ecosystems. Drylands cover ~45% of the global land area and constitute ~32% of the global carbon stocks, but the response of dryland carbon storage to atmospheric nitrogen deposition remains unclear and understudied relative to mesic systems. Observations from mesic systems suggest that nitrogen enrichment can increase the efficiency by which microbes incorporate carbon into mineral-associated forms if pH stays constant. Under acidification, a common response to nitrogen deposition, microbial biomass and enzymatic organic matter decay often decrease, leading to a build-up in plant-derived particulate organic carbon. However, in drylands, where organic carbon often associates with mineral surfaces via Ca-bridging, acidification may also abiotically decrease mineral-associated organic carbon if Ca is leached. In this study we tested how experimental nitrogen deposition affects different soil organic carbon fractions in drylands through microbial and abiotic effects.We used four long-running nitrogen deposition experiments in Mediterranean shrub- and grassland ecosystems in Southern California, where two of the sites showed strong nitrogen-induced acidification (pH drop by ~1.5 units). We studied changes in soil organic carbon fractions, soil extracellular enzyme activity, microbial carbon stabilization efficiency and exchangeable Ca. Experimental nitrogen deposition had relatively small effects on soil organic carbon storage, which appeared to be mostly driven by soil physicochemical changes. Particulate organic carbon did not increase despite previously reported increases in plant biomass and decreases in microbial biomass and extracellular enzyme activity in acidified sites. Furthermore, microbial carbon stabilization efficiency was unaffected by N fertilization in non-acidified sites and decreased in short-term but not long-term incubations in acidified sites. Importantly, mineral-associated organic carbon decreased significantly by 20% in response to N fertilization at one of the acidified sites, likely as result of pH-induced loss of Ca, which dropped by 48%. Our measurements suggest that long-term effects of nitrogen fertilization on dryland carbon storage might be primarily abiotic in nature, such that drylands, which may undergo acidification and where Ca-stabilization of soil organic carbon is prevalent, may be most at risk for loss of mineral-associated organic carbon.

Drought represents a significant stress to microorganisms and is known to reduce microbial activity and organic matter decomposition in Mediterranean ecosystems. However, we lack a detailed understanding of the drought stress response of microbial decomposers. Here we present metatranscriptomic and metabolomic data on the physiological response of in situ microbial communities on plant litter to long-term drought in Californian grass and shrub ecosystems. We hypothesised that drought causes greater microbial allocation to stress tolerance relative to growth pathways. In grass litter, communities from the decade-long ambient and reduced precipitation treatments had distinct taxonomic and functional profiles. The most discernable physiological signatures of drought were production or uptake of compatible solutes to maintain cellular osmotic balance, and synthesis of capsular and extracellular polymeric substances as a mechanism to retain water. The results show a clear functional response to drought in grass litter communities with greater allocation to survival relative to growth that could affect decomposition under drought. In contrast, communities on chemically more diverse and complex shrub litter had smaller physiological differences in response to long-term drought but higher investment in resource acquisition traits across precipitation treatments, suggesting that the functional response to drought is constrained by substrate quality. Our findings suggest, for the first time in a field setting, a trade off between microbial drought stress tolerance, resource acquisition and growth traits in plant litter microbial communities.

The temperature sensitivity of soil processes is of major interest, especially in light of climate change. Originally formulated to explain the temperature dependence of chemical reactions, the Arrhenius equation, and related Q10 temperature coefficient, has a long history of application to soil biological processes. However, empirical data indicate that Q10 and Arrhenius model are often poor metrics of temperature sensitivity in soils. In this opinion piece, we aim to (a) review alternative approaches for characterizing temperature sensitivity, focusing on macromolecular rate theory (MMRT); (b) provide strategies and tools for implementing a new temperature sensitivity framework; (c) develop thermal adaptation hypotheses for the MMRT framework; and (d) explore new questions and opportunities stemming from this paradigm shift. Microbial ecologists should consider developing and adopting MMRT as the basis for predicting biological rates as a function of temperature. Improved understanding of temperature sensitivity in soils is particularly pertinent as microbial response to temperature has a large impact on global climate feedbacks.

Most of the carbon (C) that enters the soil is broken down by the microbial community and either respired or stored in soil depending on the microbial allocation strategy. Changes in how the microbial community uses C can significantly affect soil C pool sizes, so new models have begun to explicitly represent microbial allocation. Most models use a parameter called carbon use efficiency (CUE) to represent microbial allocation, which partitions consumed C between respiration and growth. Here we compare a “Typical Microbial Model” with this representation of microbial allocation to two other models. One is the “Microbial Allocation Model” that represents CUE as an emergent property of the microbial community, explicitly modeling multiple processes involved in CUE. The second is the “Two-Pool Biomass Model” that similarly accounts for CUE as an emergent property but also represents the biomass using two C pools with different turnover times. We assessed the models’ relative ability to track a14C-glucose tracer pulse over three weeks through the extractable C pool, the microbial biomass, and respiration. We also used the 14C data to test how estimates of microbial CUE change during the incubation. Our results suggest that CUE estimates in soil are sensitive to incubation timing and are at no point stable. Isotopic data can best parameterize models when a time course of measurements is used. Our model comparison showed that the Two-Pool Biomass Model best fit our data. Using the Two-Pool Biomass model to represent microbial allocation is more biologically realistic and better matches the dynamics observed in our microbial C partitioning data. Mechanistic biogeochemical models should consider using a dynamic allocation scheme to represent CUE, rather than assuming a static value.

Phenotypic plasticity of traits is commonly measured in plants to improve understanding of organismal and ecosystem responses to climate change but is far less studied for microbes. Specifically, decomposer fungi are thought to display high levels of phenotypic plasticity and their functions have important implications for ecosystem dynamics. Assessing the phenotypic plasticity of fungal traits may therefore be important for predicting fungal community response to climate change. Here, we assess the phenotypic plasticity of 15 fungal isolates (12 species) from a Southern California grassland. Fungi were incubated on litter at five moisture levels (ranging from 4–50% water holding capacity) and at five temperatures (ranging from 4–36 °C). After incubation, fungal biomass and activities of four extracellular enzymes (cellobiohydrolase (CBH), β-glucosidase (BG), β-xylosidase (BX), and N-acetyl-β-D-glucosaminidase (NAG)) were measured. We used response surface methodology to determine how fungal phenotypic plasticity differs across the moisture-temperature gradient. We hypothesized that fungal biomass and extracellular enzyme activities would vary with moisture and temperature and that the shape of the response surface would vary between fungal isolates. We further hypothesized that more closely related fungi would show more similar response surfaces across the moisture-temperature gradient. In support of our hypotheses, we found that plasticity differed between fungi along the temperature gradient for fungal biomass and for all the extracellular enzyme activities. Plasticity also differed between fungi along the moisture gradient for BG activity. These differences appear to be caused by variation mainly at the moisture and temperature extremes. We also found that more closely related fungi had more similar extracellular enzymes activities at the highest temperature. Altogether, this evidence suggests that with global warming, fungal biodiversity may become increasingly important as functional traits tend to diverge along phylogenetic lines at higher temperatures.

Climate and regional air quality models predict that Southern California will experience longer and more severe droughts, and possibly wetter, more intense storms and changing nitrogen (N) deposition. We investigated how the three major soil greenhouse gas (GHG) fluxes respond to 4–6 years of exposure to a full-factorial experiment of reduced and augmented precipitation crossed with increased N in a semi-arid grassland in Irvine, CA, USA. The mean emission fluxes across all treatments were 249.8 mg CO2 m−2 h−1, -16.41 μg CH4 m−2 h−1, and 2.24 μg N2O m−2 h−1. Added N plots released 3.5 times more N2O than ambient N plots, and N treatment and soil moisture interacted, such that volumetric soil moisture in added N plots correlated positively with N2O release. Soil moisture, which was higher in the added water plots, correlated positively with respiration. CH4 consumption increased with soil moisture in the drought treatment, an opposite trend to that observed in most other studies. Our data suggest that CH4 consumption, N2O production, and soil respiration will decline if Southern California grasslands experience more frequent and extreme droughts. However, when drought is followed by high rainfall, the additional moisture will likely increase CH4 consumption and N2O release in periodic pulses. Overall, climatic shifts in this ecosystem may lead to a decrease in overall soil GHG emissions to the atmosphere. However, increased N deposition to Southern California will likely lead to increased N2O release and a shift in the dominant N loss pathway toward gaseous release of N. If N deposition continues to increase along with severity and duration of drought, our data predict a decrease in global warming potential (GWP) of 17.2% from this ecosystem.

Soil-atmosphere exchange significantly influences the global atmospheric abundances of carbon dioxide (CO2 ), methane (CH4 ), and nitrous oxide (N2 O). These greenhouse gases (GHGs) have been extensively studied at the soil profile level and extrapolated to coarser scales (regional and global). However, finer scale studies of soil aggregation have not received much attention, even though elucidating the GHG activities at the full spectrum of scales rather than just coarse levels is essential for reducing the large uncertainties in the current atmospheric budgets of these gases. Through synthesizing relevant studies, we propose that aggregates, as relatively separate micro-environments embedded in a complex soil matrix, can be viewed as biogeochemical reactors of GHGs. Aggregate reactivity is determined by both aggregate size (which determines the reactor size) and the bulk soil environment including both biotic and abiotic factors (which further influence the reaction conditions). With a systematic, dynamic view of the soil system, implications of aggregate reactors for soil-atmosphere GHG exchange are determined by both an individual reactor's reactivity and dynamics in aggregate size distributions. Emerging evidence supports the contention that aggregate reactors significantly influence soil-atmosphere GHG exchange and may have global implications for carbon and nitrogen cycling. In the context of increasingly frequent and severe disturbances, we advocate more analyses of GHG activities at the aggregate scale. To complement data on aggregate reactors, we suggest developing bottom-up aggregate-based models (ABMs) that apply a trait-based approach and incorporate soil system heterogeneity.

Tree mortality rates are increasing within tropical rainforests as a result of global environmental change. When trees die, gaps are created in forest canopies and carbon is transferred from the living to deadwood pools. However, little is known about the effect of tree-fall canopy gaps on the activity of decomposer communities and the rate of deadwood decay in forests. This means that the accuracy of regional and global carbon budgets is uncertain, especially given ongoing changes to the structure of rainforest ecosystems. Therefore, to determine the effect of canopy openings on wood decay rates and regional carbon flux, we carried out the first assessment of deadwood mass loss within canopy gaps in old-growth rainforest. We used replicated canopy gaps paired with closed canopy sites in combination with macroinvertebrate accessible and inaccessible woodblocks to experimentally partition the relative contribution of microbes vs. termites to decomposition within contrasting understorey conditions. We show that over a 12month period, wood mass loss increased by 63% in canopy gaps compared with closed canopy sites and that this increase was driven by termites. Using LiDAR data to quantify the proportion of canopy openings in the study region, we modelled the effect of observed changes in decomposition within gaps on regional carbon flux. Overall, we estimate that this accelerated decomposition increases regional wood decay rate by up to 18.2%, corresponding to a flux increase of 0.27MgCha-1 year-1 that is not currently accounted for in regional carbon budgets. These results provide the first insights into how small-scale disturbances in rainforests can generate hotspots for decomposer activity and carbon fluxes. In doing so, we show that including canopy gap dynamics and their impacts on wood decomposition in forest ecosystems can help improve the predictive accuracy of the carbon cycle in land surface models.

Author(s): Finks, SS; Weihe, C; Kimball, S; Allison, SD; Martiny, AC; Treseder, KK; Martiny, JBH | Abstract: Global changes such as increased drought and atmospheric nitrogen deposition perturb both the microbial and plant communities that mediate terrestrial ecosystem functioning. However, few studies consider how microbial responses to global changes may be influenced by interactions with plant communities. To begin to address the role of microbial–plant interactions, we tested the hypothesis that the response of microbial communities to global change depends on the plant community. We characterized bacterial and fungal communities from 395 plant litter samples taken from the Loma Ridge Global Change Experiment, a decade-long global change experiment in Southern California that manipulates rainfall and nitrogen levels across two adjacent ecosystems, a grassland and a coastal sage scrubland. The differences in bacterial and fungal composition between ecosystems paralleled distinctions in plant community composition. In addition to the direct main effects, the global change treatments altered microbial composition in an ecosystem-dependent manner, in support of our hypothesis. The interaction between the drought treatment and ecosystem explained nearly 5% of the variation in bacterial community composition, similar to the variation explained by the ecosystem-independent effects of drought. Unexpectedly, we found that the main effect of drought was approximately four times as strong on bacterial composition as that of nitrogen addition, which did not alter fungal or plant composition. Overall, the findings underscore the importance of considering plant–microbe interactions when considering the transferability of the results of global change experiments across ecosystems.

The potential consequences of global warming for ecosystem carbon stocks are a major concern, particularly in high-latitude regions where soil carbon pools are especially large. Research on soil and plant carbon responses to warming are often based on short-term (' 10year) warming experiments. Furthermore, carbon budgets from boreal forests, which contain at least 10–20% of the global soil carbon pool, have shown mixed responses to warming. In this study, we measured carbon and nitrogen budgets (i.e., soil and understory vegetation carbon and nitrogen stocks) from a 13-year greenhouse warming experiment in an Alaskan boreal forest. Although there were no differences in total aboveground + belowground pools, the carbon in the moss biomass and in the soil organic layer significantly decreased with the warming treatment (− 88.3% and − 19.1%, respectively). Declines in moss biomass carbon may be a consequence of warming-associated drying, while shifts in the soil microbial community could be responsible for the decrease in carbon in the soil organic layer. Moreover, in response to warming, aboveground plant biomass carbon tended to increase while root biomass carbon tended to decrease, so carbon allocation may shift aboveground with warming. Overall these results suggest that permafrost-free boreal forests are susceptible to soil carbon loss with warming.

To make predictions about the carbon cycling consequences of rising global surface temperatures, Earth system scientists rely on mathematical soil biogeochemical models (SBMs). However, it is not clear which models have better predictive accuracy, and a rigorous quantitative approach for comparing and validating the predictions has yet to be established. In this study, we present a Bayesian approach to SBM comparison that can be incorporated into a statistical model selection framework. We compared the fits of linear and nonlinear SBMs to soil respiration data compiled in a recent meta-analysis of soil warming field experiments. Fit quality was quantified using Bayesian goodness-of-fit metrics, including the widely applicable information criterion (WAIC) and leave-one-out cross validation (LOO). We found that the linear model generally outperformed the nonlinear model at fitting the meta-analysis data set. Both WAIC and LOO computed higher overfitting risk and effective numbers of parameters for the nonlinear model compared to the linear model, conditional on the data set. Goodness of fit for both models generally improved when they were initialized with lower and more realistic steady-state soil organic carbon densities. Still, testing whether linear models offer definitively superior predictive performance over nonlinear models on a global scale will require comparisons with additional site-specific data sets of suitable size and dimensionality. Such comparisons can build upon the approach defined in this study to make more rigorous statistical determinations about model accuracy while leveraging emerging data sets, such as those from long-term ecological research experiments.

Soils contain more carbon than the atmosphere and vegetation combined. An increased flow of carbon from the atmosphere into soil pools could help mitigate anthropogenic emissions of carbon dioxide and climate change. Yet we do not know how quickly soils might respond because the age distribution of soil carbon is uncertain. Here we used 789 radiocarbon (∆14C) profiles, along with other geospatial information, to create globally gridded datasets of mineral soil ∆14C and mean age. We found that soil depth is a primary driver of ∆14C, whereas climate (for example, mean annual temperature) is a major control on the spatial pattern of ∆14C in surface soil. Integrated to a depth of 1 m, global soil carbon has a mean age of 4,830 ± 1,730 yr, with older carbon in deeper layers and permafrost regions. In contrast, vertically resolved land models simulate ∆14C values that imply younger carbon ages and a more rapid carbon turnover. Our data-derived estimates of older mean soil carbon age suggest that soils will accumulate less carbon than predicted by current Earth system models over the twenty-first century. Reconciling these models with the global distribution of soil radiocarbon will require a better representation of the mechanisms that control carbon persistence in soils. Soils may accumulate less carbon and with a slower turnover than Earth system models predict, according to analysis of the age distribution of global soil carbon, which finds that the mean age of soil carbon is older than that in simulated in models.

Author(s): Malik, Ashish; Griffiths, Robert; Allison, Steven | Abstract: Microbial physiology may be critical for projecting future changes in soil carbon. Still, predicting the ecosystem implications of microbial processes remains a challenge. We argue that this challenge can be met by identifying microbial life history strategies based on their phenotypic characteristics, or traits, and representing these strategies in models simulating different environmental conditions. By adapting several theories from macroecology, we define microbial high yield (Y), resource acquisition (A), and stress tolerance (S) strategies. Using multi-omics and carbon stable isotope probing tools, we empirically validated our Y-A-S framework by studying variations in community traits along gradients of resource availability and abiotic conditions arising from anthropogenic change. Across a Britain-wide land use intensity gradient, we used isotope tracing and metaproteomics to show that microbial resource acquisition and stress tolerance traits trade off with growth yield measured as carbon use efficiency. Reduced community growth yield with intensification was linked to decreased microbial biomass and increased biomass-specific respiration which subsequently translated into lower organic carbon storage in such soil systems. We concluded that less-intensive management practices have more potential for carbon storage through increased microbial growth yield by greater channelling of substrates into biomass synthesis. In Californian grass and shrub ecosystems, we used metatranscriptomics and metabolomics to infer traits of in situ microbial communities on plant leaf litter in response to long-term drought. This experimental set-up provided gradients of resource availability and water stress. We observed that drought causes greater microbial allocation to stress tolerance. The most discernable physiological adaptations to drought in litter communities were production or uptake of compatible solutes like trehalose and ectoine as well as inorganic ions to maintain cellular osmotic balance. Grass communities also increased expression of genes for synthesis of capsular and extracellular polymeric substances possibly as a mechanism to retain water. These results showed a clear functional response to drought in grass litter communities with greater allocation to survival relative to growth that reduced decomposition under drought. In contrast, communities on chemically complex shrub litter had smaller differences in gene expression and metabolite profiles in response to drought, suggesting that the drought stress response is constrained by litter chemistry which also reduces decomposition rates. Overall, our findings suggest trade-offs between drought stress tolerance, resource acquisition and growth yield in communities across different ecosystems. These empirical studies demonstrate how trade-offs in key microbial traits can have consequences on soil carbon decomposition and storage. We recommend the use of our Y-A-S framework in experimental and modelling studies to mechanistically link microbial communities to system-level processes.

Microorganisms are critical in terrestrial carbon cycling because their growth, activity and interactions with the environment largely control the fate of recent plant carbon inputs as well as protected soil organic carbon [1, 2]. Soil carbon stocks reflect a balance between microbial decomposition of organic carbon and stabilisation of microbial assimilated carbon. The balance can shift under altered environmental conditions [3], and new research suggests that knowledge of microbial physiology may be critical for projecting changes in soil carbon and improving the prognosis of climate change feedbacks [4–7]. Still, predicting the ecosystem implications of microbial processes remains a challenge. Here we argue that this challenge can be met by identifying microbial life history strategies based on an organism’s phenotypic characteristics, or traits, and representing these strategies in ecosystem models. What are the key microbial traits for soil carbon cycling under environmental change? Microbial growth and survival in soil are impacted by multiple traits that determine responses to varying resource availability and fluctuating abiotic conditions [8]. Cellular maintenance activities (those that do not produce growth) include production of extracellular enzymes to degrade and acquire resources, biomolecular repair mechanisms, maintenance of cellular integrity, osmotic balance, defence, antagonism, cell signalling and motility [9–11]. It is conceivable that microbial investment into maintenance activities would be generally high in soils, with their highly heterogeneous and temporally variable resource distribution and stressful abiotic conditions like extremes of moisture, temperature, pH and salinity [12, 13]. Selective pressures in suboptimal environmental conditions could lead to greater cellular-level physiological allocation to maintenance relative to growth traits (Fig. 1) thereby impacting soil carbon cycling processes. Open in a separate window Fig. 1 Schematic showing cellular C flux that includes depolymerisation, substrate uptake, assimilation, dissimilation, biomass synthesis and non-growth production. Extracellular enzyme production represents investment in resource acquisition, stress protein production is linked to stress tolerance mechanisms, and biomass production reflects higher growth yield. Forked arrows signify metabolic points where hypothesised tradeoffs in traits might occur. The expected empirical relationships among the key traits are also shown

The magnitude and direction of carbon cycle feedbacks under climate warming remain uncertain due to insufficient knowledge about the temperature sensitivities of soil microbial processes. Enzymatic rates could increase at higher temperatures, but this response could change over time if soil microbes adapt to warming. We used the Arrhenius relationship, biochemical transition state theory, and thermal physiology theory to predict the responses of extracellular enzyme Vmax and Km to temperature. Based on these concepts, we hypothesized that Vmax and Km would correlate positively with each other and show positive temperature sensitivities. For enzymes from warmer environments, we expected to find lower Vmax , Km , and Km temperature sensitivity but higher Vmax temperature sensitivity. We tested these hypotheses with isolates of the filamentous fungus Neurospora discreta collected from around the globe and with decomposing leaf litter from a warming experiment in Alaskan boreal forest. For Neurospora extracellular enzymes, Vmax Q10 ranged from 1.48 to 2.25, and Km Q10 ranged from 0.71 to 2.80. In agreement with theory, Vmax and Km were positively correlated for some enzymes, and Vmax declined under experimental warming in Alaskan litter. However, the temperature sensitivities of Vmax and Km did not vary as expected with warming. We also found no relationship between temperature sensitivity of Vmax or Km and mean annual temperature of the isolation site for Neurospora strains. Declining Vmax in the Alaskan warming treatment implies a short-term negative feedback to climate change, but the Neurospora results suggest that climate-driven changes in plant inputs and soil properties are important controls on enzyme kinetics in the long term. Our empirical data on enzyme Vmax , Km , and temperature sensitivities should be useful for parameterizing existing biogeochemical models, but they reveal a need to develop new theory on thermal adaptation mechanisms.

The frequency and intensity of drought are expected to increase in the future, yet the consequences for soil microbial communities and functioning remain unclear. Processes such as decomposition could be maintained if microbial communities become more drought tolerant. However, increased drought tolerance might involve physiological costs with uncertain consequences for ecosystem processes. Here we used the trait-based model DEMENT to quantify the sensitivity of microbial traits, community dynamics, and litter decomposition to variation in drought tolerance costs. These costs were imposed as a physiological tradeoff between drought tolerance and carbon use efficiency. We ran simulations across a range of drought tolerance costs and with climate forcing from ambient and drought treatments in a Southern California grassland that experiences seasonal summer drought. As expected, zero or low costs of tolerance allowed drought-tolerant taxa to increase in abundance under ambient simulation conditions. More drought tolerant communities had greater microbial biomass but lower extracellular enzyme investment due to biological feedbacks involving enzyme production. These two responses counteracted one another, leaving decomposition unchanged relative to virtual microbial communities with no drought tolerance. Simulated decomposition rates were one-third lower under drought treatment, but there were no differences in microbial drought tolerance compared to simulations forced with ambient climate. This model result suggests that seasonal drought is a more important environmental filter than reduced precipitation during the wet season in our Mediterranean climate system. Overall, our simulations indicate that microbial community responses to drought are not likely to increase decomposition rates, even if CUE costs are low. Using the simulation approach described here, the DEMENT model could be modified to incorporate additional mechanisms of microbial drought tolerance and their associated physiological costs as new empirical data become available.

Plant residues and soil organic matter are predominantly decomposed by exoenzymes. Many soil carbon models now represent enzymatic decomposition, but the mathematical formulation of this process has been debated over the last 15 years. Some models apply the traditional “forward” Michaelis-Menten equation to represent enzyme kinetics, whereas others apply the “reverse” Michaelis-Menten equation, which assumes that kinetic rates saturate at high enzyme concentrations. Recently the equilibrium chemistry approximation (ECA) has been proposed as an alternative to both Michaelis-Menten formulations. However, because of methodological limitations, in-situ enzyme kinetics—especially in the context of soil system heterogeneity—have been difficult to verify experimentally. Therefore, the overarching goal of our study was to evaluate different enzyme kinetic formulations using model-based evidence at microbial to ecosystem scales. We used a spatially explicit individual- and trait-based microbial model, DEMENT, to circumvent methodological challenges. Although DEMENT assumes forward Michaelis-Menten kinetics at local scales, at the grid scale we found saturating relationships between degradation rate and both substrate concentrations and enzyme concentrations that fit the forward and reverse Michaelis-Menten equations, respectively, at specific successional stages during decomposition. Although forward and reverse Michaelis-Menten equations emerged under some conditions, only the ECA adequately represented decay rates emerging from the spatial-temporal variation in substrate and enzyme concentrations throughout the decomposition process. Our results support a more widespread adoption of the ECA equation in soil biogeochemical modelling at ecosystem scales.

A novel technique based on isotope analysis shows that, compared to ecosystem type, evolutionary history explains more variation in bacterial growth traits along an elevation gradient. This knowledge could help move microbial ecologists toward improved predictive models of soil processes.

Author(s): Wang, Bin; Brewer, Paul E; Shugart, Herman H; Lerdau, Manuel T; Allison, Steven D

Drought represents a significant stress to soil microorganisms and is known to reduce microbial activity and organic matter decomposition in Mediterranean ecosystems. However, we still lack a detailed understanding of the drought stress adaptations of microbial decomposers. We hypothesised that drought causes greater microbial allocation to stress tolerance relative to growth pathways. Here we present metatranscriptomic and metabolomic data on the physiological response ofin situmicrobial communities on plant leaf litter to long-term drought and pulse wetting in Californian grass and shrub ecosystems. Wetting litter after a long dry summer caused only subtle shifts in gene expression. On grass litter, communities from the decade-long ambient and reduced precipitation treatments had distinct functional profiles. The most discernable physiological adaptations to drought were production or uptake of compatible solutes to maintain cellular osmotic balance, and synthesis of capsular and extracellular polymeric substances as a mechanism to retain water. The results show a clear functional response to drought in grass litter communities with greater allocation to survival relative to growth that could affect decomposition under drought. In contrast, communities on chemically more diverse and complex shrub litter had smaller physiological differences in response to long-term drought but higher investment in resource acquisition traits across treatments, suggesting that the functional response to drought is constrained by substrate quality. Our findings suggest, for the first time in a field setting, a trade-off between microbial drought stress tolerance, resource acquisition and growth traits in leaf litter microbial communities.

The soil environment contains the largest pool of organic carbon on the Earth’s surface, with soil carbon residency and flux controlled by microbial metabolism. Despite the fact that microbial interactions have metabolic implications, these interactions are often overlooked in conceptual models of the soil carbon cycle. Here, we hypothesize that microbial interactions are intrinsically coupled to carbon cycling through eco-evolutionary principles. Interactions drive phenotypic responses that result in allocation pattern shifts and changes in carbon use efficiency. These changes promote alterations in resource availability and community structure, thereby creating selective pressures that contribute to diffuse evolutionary mechanisms. The outcomes then feed back into microbial metabolic operations with consequences for carbon turnover, continuing a feedback loop of microbial interactions, evolutionary processes, and the carbon cycle.

Nitramines are potentially carcinogenic by-products of amines used in post-combustion CO2-capture. The influence of monoethanol (MEA)-, monomethyl (MMA)-, and dimethyl (DMA)-nitramines on the growth of environmental strains of bacteria, Pseudomonas fluorescens (P. fluorescens) and Rhodococcus spp. (R. spp.), was investigated in the laboratory. Additionally, the persistence of the nitramines in the presence of bacteria was determined. Growth of R. spp. was found to be sensitive to MMA-nitramine (EC50 = 157 mg L−1), while P. fluorescens growth was insensitive to all nitramines tested. Moreover, P. fluorescens was capable of degrading 8–10% of the nitramines during the 33 h experiments. Results from this study provide insight into important processes of bacterial response to nitramines that merit further investigation considering the ongoing implementation of CO2 capture technology.

Bacteria and fungi drive decomposition, a fundamental process in the carbon cycle, yet the importance of microbial community composition for decomposition remains elusive. Here, we used an 18-month reciprocal transplant experiment along a climate gradient in Southern California to disentangle the effects of the microbial community versus the environment on decomposition. Specifically, we tested whether the decomposition response to climate change depends on the microbial community. We inoculated microbial decomposers from each site onto a common, irradiated leaf litter within "microbial cages" that prevent microbial exchange with the environment. We characterized fungal and bacterial composition and abundance over time and investigated the functional consequences through litter mass loss and chemistry. After 12 months, microbial communities altered both decomposition rate and litter chemistry. Further, the functional measurements depended on an interaction between the community and its climate in a manner not predicted by current theory. Moreover, microbial ecologists have traditionally considered fungi to be the primary agents of decomposition and for bacteria to play a minor role. Our results indicate that not only does climate change and transplantation have differential legacy effects among bacteria and fungi, but also that bacterial communities might be less functionally redundant than fungi with regards to decomposition. Thus, it may be time to reevaluate both the role of microbial community composition in its decomposition response to climate and the relative roles of bacterial and fungal communities in decomposition.