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Climate change jeopardizes human health, global biodiversity, and sustainability of the biosphere. To make reliable predictions about climate change, scientists use Earth system models (ESMs) that integrate physical, chemical, and biological processes occurring on land, the oceans, and the atmosphere. Although critical for catalyzing coupled biogeochemical processes, microorganisms have traditionally been left out of ESMs. Here, we generate a "top 10" list of priorities, opportunities, and challenges for the explicit integration of microorganisms into ESMs. We discuss the need for coarse-graining microbial information into functionally relevant categories, as well as the capacity for microorganisms to rapidly evolve in response to climate-change drivers. Microbiologists are uniquely positioned to collect novel and valuable information necessary for next-generation ESMs, but this requires data harmonization and transdisciplinary collaboration to effectively guide adaptation strategies and mitigation policy.

Widespread tree mortality events occur during periods of severe drought in temperate conifer forests and are expected to become more frequent in many areas due to climate change. Improved mapping of individual tree mortality is needed to identify risk factors and design effective conservation strategies. In this study, we used National Ecological Observatory Network (NEON) lidar and multispectral reflectance airborne observations to map individual tree mortality over a 160 km2 area during and after the 2012–2016 drought for two sites in California's Sierra National Forest. We used NEON lidar to derive tree locations and crown perimeters and multispectral data to map tree mortality for more than 1 million trees. We found that 25.4% of the trees in our study area died between 2013 and 2017, with considerably higher mortality at the lower-elevation Soaproot Saddle site. Between 2017 and 2019, an additional 2.0%–2.8% of the trees died each year. Two wildfires in 2020 and 2021 increased tree mortality within burned area perimeters by 49%–89% between 2019 and 2021. Consistent with previous work, we found that tree mortality risk increased as a function of tree height. Tree mortality was positively associated with distance from rivers, trees per hectare, and decreasing slope at the lower elevation site. In contrast, increasing slope was positively associated with tree mortality at the higher elevation site. Our approach and dataset provide a means to study the combined effects of drought and wildfire on tree mortality and may improve projections of forest resilience under a changing climate.

Global change experiments often observe shifts in bacterial community composition based on 16S rRNA gene sequences. However, this genetic region can mask a large amount of genetic and phenotypic variation among bacterial strains sharing even identical 16S regions. As such, it remains largely unknown whether variation at the sub-16S level, sometimes termed microdiversity, responds to environmental perturbations and whether such changes are relevant to ecosystem processes. Here, we investigated microdiversity within Curtobacterium, the dominant bacterium found in the leaf litter layer of soil, to simulated drought and nitrogen addition in a field experiment. We first developed and validated Curtobacterium-specific primers of the groEL gene to assess microdiversity within this lineage. We then tracked the response of this microdiversity to simulated global change in two adjacent plant communities, grassland and coastal sage scrub (CSS). Curtobacterium microdiversity responded to drought but not nitrogen addition, indicating variation within the genus of drought tolerance but not nitrogen response. Further, the response of microdiversity to drought depended on the ecosystem, suggesting that litter substrate selects for a distinct composition of microdiversity that is constrained in its response, perhaps related to tradeoffs in resource acquisition traits. Supporting this interpretation, a metagenomic analysis revealed that the composition of Curtobacterium-encoded carbohydrate-active enzymes (CAZymes) varied distinctly across the two ecosystems. Identifying the degree to which relevant traits are phylogenetically conserved may help to predict when the aggregated response of a 16S-defined taxon masks differential responses of finer-scale bacterial diversity to global change. IMPORTANCE Microbial communities play an integral role in global biogeochemical cycling, but our understanding of how global change will affect microbial community structure and functioning remains limited. Microbiome analyses typically aggregate large amounts of genetic diversity which may obscure finer variation in traits. This study found that fine-scale diversity (or microdiversity) within the bacterial genus Curtobacterium was affected by simulated global changes. However, the degree to which this was true depended on the type of global change, as the composition of Curtobacterium microdiversity was affected by drought, but not by nitrogen addition. Further, these changes were associated with variation in carbon degradation traits. Future work might improve predictions of microbial community responses to global change by considering microdiversity.

Soil microbiomes play a key role in driving biogeochemical cycles of the Earth system. As drought frequency and intensity increase due to climate change, soil microbes and the processes they control will be impacted. Even after a drought ends, microbiomes and other systems take time to recover and may display a memory of previous climate conditions. Still, the mechanisms involved in these legacy effects remain unclear, making it difficult to predict climate and biogeochemical rates in the future. Here, we used a trait-based microbiome model (DEMENTpy) to implement trade-off-mediated mechanisms that may lead to drought legacy effects on litter decomposition. Trade-offs were assumed to follow the Y-A-S framework that defines three primary life-history strategies of microorganisms: high growth Yield, resource Acquisition, and Stress tolerance. We represented cellular trade-offs between osmolytes required for drought tolerance and investment in enzymes involved in litter decomposition. Simulations were run under varying levels of drought severity and dispersal. With high levels of dispersal, no legacy effects were predicted by DEMENTpy following drought. With limited dispersal, severe drought resulted in a persistent legacy of altered community-level traits and reduced litter decomposition. Moderate drought resulted in a transient legacy that disappeared after two years, consistent with recent empirical observations in Southern California ecosystems. These results imply that greater movement along the trade-off between enzyme investment and osmolyte production resulted in stronger legacy effects. More generally, factors that shift the position of a microbiome in YAS space may alter the legacy outcome following drought. Our trait-based modeling study motivates additional empirical measurements to quantify YAS traits and trade-offs that are needed to make accurate predictions of soil microbiome resilience and functioning. Also, our study illustrates an emerging approach for representing trait trade-offs in microbiomes and vegetation that dictate ecosystem responses to drought and other environmental perturbations.

Termites are important ecosystem engineers in tropical habitats, with different feeding groups able to decompose wood, grass, litter, and soil organic matter. In most tropical regions, termite abundance and species diversity are assumed to increase with rainfall, with highest levels found in rainforests. However, in the Australian tropics, this pattern is thought to be reversed, with lower species richness and termite abundance found in rainforest than drier habitats. The potential mechanisms underlying this pattern remain unclear. We compared termite assemblages (abundance, activity, diversity, and feeding group composition) across five sites along a precipitation gradient (ranging from ∼800 to 4,000 mm annual rainfall), spanning dry and wet savanna habitats, wet sclerophyll, and lowland and upland rainforests in tropical North Queensland. Moving from dry to wet habitats, we observed dramatic decreases in termite abundance in both mounds and dead wood occupancy, with greater abundance and activity at savanna sites (low precipitation) compared with rainforest or sclerophyll sites (high precipitation). We also observed a turnover in termite species and feeding group diversity across sites that were close together, but in different habitats. Termite species and feeding group richness were highest in savanna sites, with 13 termite species from wood-, litter-, grass-, dung-, and soil-feeding groups, while only five termite species were encountered in rainforest and wet sclerophyll sites—all wood feeders. These results suggest that the Australian termite diversity anomaly may be partly driven by how specific feeding groups colonized habitats across Australia. Consequently, termites in Australian rainforests may be less important in ecosystem processes, such as carbon and nutrient cycling during decomposition, compared with termites in other tropical rainforests.

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 (' 10 year) 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.

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.

Resource acquisition and growth yield are fundamental microbial traits that affect biogeochemical processes and have consequences for ecosystem functioning. However, there is a lack of empirical observations linking these traits. Using a landscape-scale survey of temperate near-neutral pH soils, we show tradeoffs in key community-level parameters linked to these traits. Increased investment into extracellular enzymes estimated using specific potential enzyme activity was associated with reduced growth yield obtained using carbon use efficiency measures from stable isotope tracing. Reduction in growth yield was linked more to carbon than nitrogen acquisition highlighting smaller stoichiometric than energetic constraints on community metabolism in examined soils.

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.

Fungal metabolic rates could increase under climate warming but may be counteracted by mechanisms of physiological acclimation and evolutionary adaptation. We hypothesized that Vmax and Km parameters of Neurospora discreta extracellular enzymes would acclimate to warmer temperatures through compensatory mechanisms. We also predicted that evolution under warmer temperatures would alter enzyme parameters and fungal respiration through adaptive mechanisms. In contrast to these predictions, growth at higher temperature (22 °C versus 16 °C) increased the temperature-corrected Vmax of three enzymes. The carbon substrate used for fungal growth (lignin versus sucrose) had a much greater impact on enzyme Vmax than temperature. Following experimental evolution, the enzymatic parameters of Neurospora strains did not adapt to higher temperatures as hypothesized; rather, enzyme Vmax values were unaffected, and respiration rates increased. Together, these results suggest that physiological and evolutionary mechanisms are unlikely to counteract soil carbon losses driven by saprotrophic fungi under climate warming.

Shift in precipitation regime could greatly alter plant and microbial activity, and thus the contemporary and future ecosystem dynamics in grasslands. We investigated how changes in snow depth affect plants, microbes and their relationships after 10 consecutive years of snow treatments in different steppes. We selected 8 snow fences along a mean annual precipitation (MAP) gradient from 225 to 375 mm in Inner Mongolia. For each snow fence, study plots were set up at 7 transects with different levels of snow depth. We found that ecosystem properties, including soil moisture, the biomass and nitrogen (N) pools of microbes and plants, the fungi: bacteria ratio and the grass: forb ratio, increased with increasing snow depth at the drier sites with lower MAP, but not at the wetter sites with higher MAP. At any given site, the sensitivity of these ecosystem properties to changes in snow depth was determined by the slopes of these variables against snow depth. The results showed that the sensitivity of these ecosystem properties to changes in snow depth decreased linearly with increase in MAP levels. In addition, we also found that increased snow depth shifted the relationship between microbial and plant biomass from positive to negative. Our work reveals the importance of snow water in regulating plant and microbial processes in temperate steppes, especially under lower MAP conditions. The greater plant and microbial biomass and the shift of community toward greater fungi: bacteria and grass: forb ratio imply that increased snowmelt input alleviated water limitation in temperate steppes and altered plant and microbial communities. Our study helps to better predict that how changes in winter precipitation could affect the biomass and composition of plants and soil microbes in grasslands.

Carbon use efficiency (CUE), the proportion of carbon (C) consumed by microbes that is converted into biomass, is an important parameter for soil C models with explicit microbial controls. While often considered as a single parameter, CUE is an emergent property of multiple microbial processes, including assimilation efficiency, biomass-specific respiration, enzyme production, and respiratory costs of enzyme production. These processes occur over variable time scales and imply different fates for C, and the same emergent CUE value can result when C is allocated in fundamentally different ways (e.g. a high investment in enzyme production vs. a high assimilation cost). We developed a model that represents the individual processes underlying emergent CUE to test how shifts in microbial allocation alter equilibrium soil C pool sizes. We found that an increase in emergent CUE that results from a change in assimilation efficiency, biomass specific respiration, or respiration costs from enzyme production causes soil organic C (SOC) to decline, while the same change in emergent CUE resulting from a change in enzyme production causes SOC to increase. We also used the model to test the sensitivity of CUE from isotopic C tracer estimates to changes in microbial allocation processes. We found that these estimates do not account for the same microbial processes represented by emergent CUE in models. We propose that considering microbial processes explicitly rather than representing CUE as a single parameter can improve data-model integration. In addition, modeling microbial processes explicitly will account for a wider range of possible outcomes from shifts in microbial C allocation, such as when increased SOC results from increasing CUE.

In this Brief Communications Arising Reply, the affiliation for author P. H. Templer was incorrectly listed as 'Department of Ecology & Evolutionary Biology, University of California Irvine, Irvine, California 92697, USA' instead of 'Department of Biology, Boston University, Boston, Massachusetts 02215, USA'. This has been corrected online.

To better understand mechanisms of carbon (C) and nitrogen (N) dynamics under anthropogenic N enrichment, we examined frequencies of C- and N-targeting genes in litter fungi. In particular, we tested the hypothesis that N enrichment selects for C-targeting genes but against N-targeting genes, if fungi preferentially invest resources in acquisition of growth-limiting nutrients. We conducted a fully-factorial litter and microbial transplant in a N fertilization experiment in Southern California grassland. The transplant design enabled us to contrast direct effects of N fertilization in the environment, indirect effects of N-induced shifts in the microbial community, and indirect effects of N-induced changes in plant litter chemistry. For each treatment, we assessed frequencies of select well-annotated fungal functional genes: cellulose-targeting AA9 genes (for C acquisition) versus ammonium transporter genes and amino acid permease genes (for N acquisition). We found that our hypothesis was upheld only with regard to shifts in the microbial community. Specifically, when grown in the same environment and litter, fungi from the N-fertilized plots displayed greater frequencies of cellulose-targeting AA9 genes from basidiomycetes, but smaller frequencies of ammonium transporter genes and amino acid permease genes, when compared to fungi from the control plots. In contrast, N fertilization in the plot environment was associated with higher frequencies of amino acid permease genes and ammonium transporter genes. Likewise, plant litter from the N-fertilized plots selected for higher frequencies of ammonium transporter genes. Altogether, we found fairly inconsistent effects of N enrichment on fungal functional genes related to C and N acquisition. Even if the genetic capacity of the fungal community to acquire C versus N changes owing to shifts in the microbial community, direct effects of N fertilization and indirect effects of litter chemistry may offset the response.

Many regions on Earth are expected to become drier with climate change, which may impact nitrogen (N) cycling rates and availability. We used a meta-analytical approach on the results of field experiments that reduced precipitation and measured N supply (i.e., indices of N mineralization), soil microbial biomass, inorganic N pools (ammonium (NH4+) and nitrate (NO3−)), and nitrous oxide (N2O) emissions. We hypothesized that N supply and N2O emissions would be relatively insensitive to precipitation reduction and that reducing precipitation would increase extractable NH4+ and NO3− concentrations because microbial processes continue, whereas plant N uptake diminishes with drought. In support of this hypothesis, extractable NH4+ increased by 25% overall with precipitation reduction; NH4+ also increased significantly with increasing magnitude of precipitation reduction. In contrast, N supply and extractable NO3− did not change and N2O emissions decreased with reduced precipitation. Across studies microbial biomass appeared unchanged, yet from the diversity of studies, it was clear that proportionally smaller precipitation reductions increased microbial biomass, whereas larger proportional reductions in rainfall reduced microbial biomass; there was a positive intercept (P = 0.005) and a significant negative slope (P = 0.0002) for the regression of microbial biomass versus % precipitation reduction (LnR = −0.009 × (% precipitation reduction) + 0.4021). Our analyses imply that relative to other N variables, N supply is less sensitive to reduced precipitation, whereas processes producing N2O decline. Drought intensity and duration, through sustained N supply, may control how much N becomes vulnerable to loss via hydrologic and gaseous pathways upon rewetting dry soils.

Microbial decomposers produce extracellular enzymes to degrade complex plant polymers, making plant C available for metabolism and eventual respiration back to the atmosphere as CO2. Knowledge of how extracellular enzyme kinetics and microbial activity vary with climate is therefore valuable for predicting how future carbon cycling may be affected by climate change, but studies investigating such dynamics in more xeric ecosystems are underrepresented in the literature. We investigated how microbial biomass, litter chemistry, and extracellular enzymes (Vmax and Km) and their temperature sensitivities varied along a Mediterranean climate gradient in southern California. Total microbial biomass did not vary among sites along the gradient in either the dry or the wet season. In contrast, extracellular enzyme Vmax and Km varied as a function of fungal biomass and substrate availability. We also found that Vmax and Km of most enzymes were more sensitive to temperature in colder sites than in warmer sites, though this relationship was seasonal for Vmax. Observed enzyme Vmax and Km were indicative of extracellular enzyme accumulation in the drier sites along the gradient, which may contribute to the large pulses of respiration that follow rewetting events in these xeric systems. Variation in enzyme characteristics along the gradient indicate that as these systems become more arid in the future, enzyme dynamics will shift from smaller, potentially more active pools to larger, potentially less active enzyme pools that accumulate over dry periods. In addition, rates of enzymatic decomposition will likely be most sensitive to rising temperatures in the coldest sites along our gradient.

Numerous field studies have found changes in soil respiration and microbial abundance under experimental warming. Yet, it is uncertain whether the magnitude of these responses remains consistent over the long-term. We performed a meta-analysis on 25 field experiments to examine how warming effects on soil respiration, microbial biomass, and soil microbial C respond to the duration of warming. For each parameter, we hypothesized that effect sizes of warming would diminish as the duration of warming increased. In support of our hypothesis, warming initially increased soil respiration, but the magnitude of this effect declined significantly as warming progressed as evidenced by the two longest studies in our meta-analysis. In fact, after 10 years of warming, soil respiration in warmed treatments was similar to controls. In contrast, warming effect sizes for fungal biomass, bacterial biomass, and soil microbial C did not respond significantly to the duration of warming. Microbial acclimation, community shifts, adaptation, or reductions in labile C may have ameliorated warming effects on soil respiration in the long-term. Accordingly, long-term soil C losses might be smaller than those suggested by short-term warming studies.

The majority of the Earth's terrestrial carbon is stored in the soil. If anthropogenic warming stimulates the loss of this carbon to the atmosphere, it could drive further planetary warming. Despite evidence that warming enhances carbon fluxes to and from the soil, the net global balance between these responses remains uncertain. Here we present a comprehensive analysis of warming-induced changes in soil carbon stocks by assembling data from 49 field experiments located across North America, Europe and Asia. We find that the effects of warming are contingent on the size of the initial soil carbon stock, with considerable losses occurring in high-latitude areas. By extrapolating this empirical relationship to the global scale, we provide estimates of soil carbon sensitivity to warming that may help to constrain Earth system model projections. Our empirical relationship suggests that global soil carbon stocks in the upper soil horizons will fall by 30 ± 30 petagrams of carbon to 203 ± 161 petagrams of carbon under one degree of warming, depending on the rate at which the effects of warming are realized. Under the conservative assumption that the response of soil carbon to warming occurs within a year, a business-as-usual climate scenario would drive the loss of 55 ± 50 petagrams of carbon from the upper soil horizons by 2050. This value is around 12-17 per cent of the expected anthropogenic emissions over this period. Despite the considerable uncertainty in our estimates, the direction of the global soil carbon response is consistent across all scenarios. This provides strong empirical support for the idea that rising temperatures will stimulate the net loss of soil carbon to the atmosphere, driving a positive land carbon-climate feedback that could accelerate climate change.

The remarkable complexity of soil and its importance to a wide range of ecosystem services presents major challenges to the modeling of soil processes. Although major progress in soil models has occurred in the last decades, models of soil processes remain disjointed between disciplines or ecosystem services, with considerable uncertainty remaining in the quality of predictions and several challenges that remain yet to be addressed. First, there is a need to improve exchange of knowledge and experience among the different disciplines in soil science and to reach out to other Earth science communities. Second, the community needs to develop a new generation of soil models based on a systemic approach comprising relevant physical, chemical, and biological processes to address critical knowledge gaps in our understanding of soil processes and their interactions. Overcoming these challenges will facilitate exchanges between soil modeling and climate, plant, and social science modeling communities. It will allow us to contribute to preserve and improve our assessment of ecosystem services and advance our understanding of climate-change feedback mechanisms, among others, thereby facilitating and strengthening communication among scientific disciplines and society. We review the role of modeling soil processes in quantifying key soil processes that shape ecosystem services, with a focus on provisioning and regulating services. We then identify key challenges in modeling soil processes, including the systematic incorporation of heterogeneity and uncertainty, the integration of data and models, and strategies for effective integration of knowledge on physical, chemical, and biological soil processes. We discuss how the soil modeling community could best interface with modern modeling activities in other disciplines, such as climate, ecology, and plant research, and how to weave novel observation and measurement techniques into soil models. We propose the establishment of an international soil modeling consortium to coherently advance soil modeling activities and foster communication with other Earth science disciplines. Such a consortium should promote soil modeling platforms and data repository for model development, calibration and intercomparison essential for addressing contemporary challenges.

Although numerous warming experiments have examined the impacts of elevated temperature on soil microbial activities, most are based on responses from a single site. To investigate how precipitation regime regulates warming effects on the carbon cycle, we conducted manipulative warming experiments in desert steppe, typical steppe, and meadow steppe along a precipitation gradient in northern China. Soil temperature, moisture, microbial biomass C (MBC), N (MBN), and microbial respiration were measured from 2006 to 2009. Soil moisture was significantly reduced by warming in the typical steppe but not affected in the desert and meadow steppe. Across the 4 years, warming decreased MBC and microbial respiration in the desert and typical steppe but not in the meadow steppe. The magnitude of warming-induced reductions in MBC and microbial respiration declined as site precipitation increased. Across the three sites, the changes in soil MBC, MBN, and microbial respiration were all positively correlated with annual precipitation and changes in belowground net primary productivity. Our results suggest that precipitation regime controls the response of soil microbial activity and biomass to warming, possibly by regulating soil moisture and substrate availability. With increasing precipitation, the stimulatory effects of warming on soil microbial activity and biomass outweigh the inhibitory effects due to declining soil moisture.

Soil carbon (C) is a critical component of Earth system models (ESMs), and its diverse representations are a major source of the large spread across models in the terrestrial C sink from the third to fifth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Improving soil C projections is of a high priority for Earth system modeling in the future IPCC and other assessments. To achieve this goal, we suggest that (1) model structures should reflect real-world processes, (2) parameters should be calibrated to match model outputs with observations, and (3) external forcing variables should accurately prescribe the environmental conditions that soils experience. First, most soil C cycle models simulate C input from litter production and C release through decomposition. The latter process has traditionally been represented by first-order decay functions, regulated primarily by temperature, moisture, litter quality, and soil texture. While this formulation well captures macroscopic soil organic C (SOC) dynamics, better understanding is needed of their underlying mechanisms as related to microbial processes, depth-dependent environmental controls, and other processes that strongly affect soil C dynamics. Second, incomplete use of observations in model parameterization is a major cause of bias in soil C projections from ESMs. Optimal parameter calibration with both pool- and flux-based data sets through data assimilation is among the highest priorities for near-term research to reduce biases among ESMs. Third, external variables are represented inconsistently among ESMs, leading to differences in modeled soil C dynamics. We recommend the implementation of traceability analyses to identify how external variables and model parameterizations influence SOC dynamics in different ESMs. Overall, projections of the terrestrial C sink can be substantially improved when reliable data sets are available to select the most representative model structure, constrain parameters, and prescribe forcing fields.

Bacteria and fungi drive the decomposition of dead plant biomass (litter), an important step in the terrestrial carbon cycle. Here we investigate the sensitivity of litter microbial communities to simulated global change (drought and nitrogen addition) in a California annual grassland. Using 16S and 28S rDNA amplicon pyrosequencing, we quantify the response of the bacterial and fungal communities to the treatments and compare these results to background, temporal (seasonal and interannual) variability of the communities. We found that the drought and nitrogen treatments both had significant effects on microbial community composition, explaining 2-6% of total compositional variation. However, microbial composition was even more strongly influenced by seasonal and annual variation (explaining 14-39%). The response of microbial composition to drought varied by season, while the effect of the nitrogen addition treatment was constant through time. These compositional responses were similar in magnitude to those seen in microbial enzyme activities and the surrounding plant community, but did not correspond to a consistent effect on leaf litter decomposition rate. Overall, these patterns indicate that, in this ecosystem, temporal variability in the composition of leaf litter microorganisms largely surpasses that expected in a short-term global change experiment. Thus, as for plant communities, future microbial communities will likely be determined by the interplay between rapid, local background variability and slower, global changes.

Microbes influence soil organic matter decomposition and the long-term stabilization of carbon (C) in soils. We contend that by revising the representation of microbial processes and their interactions with the physicochemical soil environment, Earth system models (ESMs) will make more realistic global C cycle projections. Explicit representation of microbial processes presents considerable challenges due to the scale at which these processes occur. Thus, applying microbial theory in ESMs requires a framework to link micro-scale process-level understanding and measurements to macro-scale models used to make decadal- to century-long projections. Here we review the diversity, advantages, and pitfalls of simulating soil biogeochemical cycles using microbial-explicit modeling approaches. We present a roadmap for how to begin building, applying, and evaluating reliable microbial-explicit model formulations that can be applied in ESMs. Drawing from experience with traditional decomposition models, we suggest the following: (1) guidelines for common model parameters and output that can facilitate future model intercomparisons; (2) development of benchmarking and model-data integration frameworks that can be used to effectively guide, inform, and evaluate model parameterizations with data from well-curated repositories; and (3) the application of scaling methods to integrate microbial-explicit soil biogeochemistry modules within ESMs. With contributions across scientific disciplines, we feel this roadmap can advance our fundamental understanding of soil biogeochemical dynamics and more realistically project likely soil C response to environmental change at global scales.

Differences in relative availability of nitrate vs. phosphate may contribute to regional variations in plankton elemental stoichiometry. As a representative of the globally abundant marine Synechococcus, strain WH8102 was grown in 16 chemostats up to 52 d at a fixed growth rate with nitrogen-phosphorus ratios (N : Psupply) of 1-50. Initially, the phosphate and nitrate concentrations in the vessel decreased when the respective nutrient was limiting. Cell growth generally stabilized, although several chemostats had apparent oscillations in biomass. We observed extensive plasticity in the elemental content and ratios. N : Pcell matched the supply values between N : Psupply 5 and 20. The C : Pcell followed a similar trend. In contrast, the mean C : Ncell was 6.8 and did not vary as a function of supply ratios. We also observed that induction of alkaline phosphatase, the fraction of P allocated to nucleic acids, and the lipid sulfoquinovosyldiacylglycerol : phosphatidyglycerol ratio inversely correlated with P availability. Our results suggest that this extensive plasticity in the elemental content and ratios depends both on the external nutrient availability as well as past growth history. Thus, our study provides a quantitative understanding of the regulation of the elemental stoichiometry of an abundant ocean phytoplankton lineage.

© 2015, Springer-Verlag Berlin Heidelberg. Climate change is expected to alter the mechanisms controlling soil organic matter (SOM) stabilization. Under climate change, soil warming and drying could affect the enzymatic mechanisms that control SOM turnover and dependence on substrate concentration. Here, we used a greenhouse climate manipulation in a mature boreal forest soil to test two specific hypotheses: (1) Rates of decomposition decline at lower substrate concentrations, and (2) reductions in soil moisture disproportionately constrain the degradation of low-concentration substrates. Using constructed soil cores, we measured decomposition rates of two polymeric substrates, starch and cellulose, as well as enzyme activities associated with degradation of these substrates. The greenhouse manipulation increased temperature by 0.8 °C and reduced moisture in the constructed cores by up to 90 %. We rejected our first hypothesis, as the rate of starch decomposition did not decrease with declining starch concentration under control conditions, but we did find support for hypothesis two: Drying led to lower decomposition rates for low-concentration starch. We observed a threefold reduction in soil respiration rates in bulk soils in the greenhouses over a 4-month period, but the C losses from the constructed cores did not vary among our treatments. Activities of enzymes that degrade cellulose and starch were elevated in the greenhouse treatments, which may have compensated for moisture constraints on the degradation of the common substrate (i.e., cellulose) in our constructed cores. This study confirms that substrate decomposition can be concentration-dependent and suggests that climate change effects on soil moisture could reduce rates of decomposition in well-drained boreal forest soils lacking permafrost.

Global ecosystem models may require microbial components to accurately predict feedbacks between climate warming and soil decomposition, but it is unclear what parameters and levels of complexity are ideal for scaling up to the globe. Here we conducted a model comparison using a conventional model with first-order decay and three microbial models of increasing complexity that simulate short- to long-term soil carbon dynamics. We focused on soil carbon responses to microbial carbon use efficiency (CUE) and temperature. Three scenarios were implemented in all models: constant CUE (held at 0.31), varied CUE (-0.016 °C-1), and 50 % acclimated CUE (-0.008 °C-1). Whereas the conventional model always showed soil carbon losses with increasing temperature, the microbial models each predicted a temperature threshold above which warming led to soil carbon gain. The location of this threshold depended on CUE scenario, with higher temperature thresholds under the acclimated and constant scenarios. This result suggests that the temperature sensitivity of CUE and the structure of the soil carbon model together regulate the long-term soil carbon response to warming. Equilibrium soil carbon stocks predicted by the microbial models were much less sensitive to changing inputs compared to the conventional model. Although many soil carbon dynamics were similar across microbial models, the most complex model showed less pronounced oscillations. Thus, adding model complexity (i.e. including enzyme pools) could improve the mechanistic representation of soil carbon dynamics during the transient phase in certain ecosystems. This study suggests that model structure and CUE parameterization should be carefully evaluated when scaling up microbial models to ecosystems and the globe. © 2014 Springer Science+Business Media Dordrecht.

Marine microbial communities mediate many biogeochemical transformations in the ocean. Consequently, processes such as primary production and carbon (C) export are linked to nutrient regeneration and are influenced by the resource demand and elemental composition of marine microbial biomass. Laboratory studies have demonstrated that differential partitioning of element resources to various cellular components can directly influence overall cellular elemental ratios, especially with respect to growth machinery (i.e., ribosomal RNA) and phosphorus (P) allocation. To investigate whether allocation to RNA is related to biomass P content and overall C: P biomass composition in the open ocean, we characterized patterns of P allocation and C: P elemental ratios along an environmental gradient of phosphate supply in the North Atlantic subtropical gyre (NASG) from 35.67° N, 64.17° W to 22.676° N, 65.526° W. Because the NASG is characterized as a P-stressed ecosystem, we hypothesized that biochemical allocation would reflect sensitivity to bioavailable phosphate, such that greater phosphate supply would result in increased allocation toward P-rich RNA for growth. We predicted these changes in allocation would also result in lower C: P ratios with increased phosphate supply. However, bulk C: P ratios were decoupled from allocation to nucleic acids and did not appear to vary systematically across a phosphate supply gradient of 2.2-14.7 μ4mol m-2 d-1. Overall, we found that C: P ratios ranged from 188 to 306 along the transect, and RNA represented only 6-12% of total particulate P, whereas DNA represented 11-19%. We did find that allocation to RNA was positively correlated with phosphate supply rate, suggesting a consistent physiological response in biochemical allocation to resource supply within the whole community. These results suggest that community composition and/or nonnucleic acid P pools may influence ecosystem-scale variation in C: P stoichiometry more than nucleic acid allocation or P supply in diverse marine microbial communities. ©Author(s) 2014.

In most terrestrial environments, our knowledge of the elemental composition and stoichiometry of microorganisms stems from indirect whole community analyses. In contrast, we have little direct knowledge of the elemental composition of specific microorganisms and the variation between and within Fungi and Bacteria. To address this issue, we isolated and identified the elemental content of 87 strains of Fungi and Bacteria isolated from grassland leaf litter. The isolated strains were affiliated with a broad range of diversity including Ascomycota and Basidiomycota for Fungi, and Proteobacteria, Bacteroidetes, and Actinobacteria for Bacteria. The C:P and C:N but not N:P ratios were significantly higher in Fungi than in Bacteria. Extensive strain variation in elemental composition was partly linked to phylogeny and growth rate. Across all strains, the geometric mean C:N:P was 88:15:1. This overall ratio was significantly higher than reported for other leaf litter and terrestrial whole communities but closer to the canonical Redfield ratio characterizing marine microorganisms. This result warrants further investigation into the discrepancy between whole community and isolated strain elemental ratios. © 2014 Elsevier Ltd.

Rising temperatures are expected to reduce global soil carbon (C) stocks, driving a positive feedback to climate change1-3. However, the mechanisms underlying this prediction are not well understood, including how temperature affects microbial enzyme kinetics, growth efficiency (MGE), and turnover4,5. Here, in a laboratory study, we show that microbial turnover accelerates with warming and, along with enzyme kinetics, determines the response of microbial respiration to temperature change. In contrast, MGE, which is generally thought to decline with warming6-8, showed no temperature sensitivity. A microbial-enzyme model suggests that such temperature sensitive microbial turnover would promote soil C accumulation with warming, in contrast to reduced soil C predicted by traditional biogeochemical models. Furthermore, the effect of increased microbial turnover differs from the effects of reduced MGE, causing larger increases in soil C stocks. Our results demonstrate that the response of soil C to warming is affected by changes in microbial turnover. This control should be included in the next generation of models to improve prediction of soil C feedbacks to warming.

Microbial phenol oxidases and peroxidases mediate biogeochemical processes in soils, including microbial acquisition of carbon and nitrogen, lignin degradation, carbon mineralization and sequestration, and dissolved organic carbon export. Measuring oxidative enzyme activities in soils is more problematic than assaying hydrolytic enzyme activities because of the non-specific, free radical nature of the reactions and complex interactions between enzymes, assay substrates, and the soil matrix. We compared three substrates commonly used to assay phenol oxidase and peroxidase in soil: pyrogallol (PYGL, 1,2,3-trihydroxybenzene), l-DOPA (l-3,4-dihydroxyphenylalanine), and ABTS (2,2'-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid). We measured substrate oxidation in three soils across a pH gradient from 3.0 to 10.0 to determine the pH optimum for each substrate. In addition, we compared activities across 17 soils using the three substrates. In general, activities on the substrates followed the trend PYGL>. l-DOPA>ABTS and were inversely related to substrate redox potential. PYGL and ABTS were not suitable substrates at pH>5, and ABTS oxidation often declined with addition of peroxide to the assay. Absolute and relative oxidation rates varied widely among substrates in relation to soil type and assay pH. We also tested whether autoclaved or combusted soils could be used as negative controls for the influence of abiotic factors (e.g., soil mineralogy) on oxidative activity. However, neither autoclaving nor combustion produced reliable negative controls because substrate oxidation still occurred; in some cases, these treatments enhanced substrate oxidation rates. For broad scale studies, we recommend that investigators use all three substrates to assess soil oxidation potentials. For focused studies, we recommend evaluating substrates before choosing a single option, and we recommend assays at both the soil pH and a reference pH (e.g., pH 5.0) to determine the effect of assay pH on oxidase activity. These recommendations should contribute to greater comparability of oxidase potential activities across studies. © 2013 Elsevier Ltd.

Abstract. Marine microbial communities mediate many biogeochemical transformations in the ocean. Consequently, processes such as primary production and carbon (C) export are linked to nutrient regeneration and are influenced by the resource demand and elemental composition of marine microbial biomass. Laboratory studies have demonstrated that differential partitioning of element resources to various cellular components can directly influence overall cellular elemental ratios, especially with respect to growth machinery (i.e., ribosomal RNA) and phosphorus (P) allocation. To investigate whether allocation to RNA is related to biomass P content and overall C : P biomass composition in the open ocean, we characterized patterns of P allocation and C : P elemental ratios along an environmental gradient of P-supply in the North Atlantic subtropical gyre (NASG) from 35.67° N 64.17° W to 22.67° N 65.52° W. Because the NASG is characterized as a P-stressed ecosystem, we hypothesized that biochemical allocation would reflect sensitivity to bioavailable P, such that greater P supply would result in increased allocation toward P-rich RNA for growth. We expected these changes in allocation to also result in lower C : P ratios with increased P supply. In contrast to our predictions however, bulk C : P ratios were decoupled from allocation to nucleic acids and did not vary systematically across a P supply gradient of 2.2–14.7 μmol m–2 d–1. Overall, we found that C : P ratios ranged from 188–306 along the transect, and RNA represented only 6–12% of total particulate P, whereas DNA represented 11–19%. However, we did find that allocation to RNA was positively correlated with SRP supply rate, suggesting a consistent physiological response in biochemical allocation to resource supply within the whole community. These results suggest that community composition or non-nucleic acid P pools may influence ecosystem scale variation in C : P stoichiometry more than nucleic acid allocation or prevailing environmental conditions in diverse marine microbial communities.

Society relies on Earth system models (ESMs) to project future climate and carbon (C) cycle feedbacks. However, the soil C response to climate change is highly uncertain in these models and they omit key biogeochemical mechanisms. Specifically, the traditional approach in ESMs lacks direct microbial control over soil C dynamics. Thus, we tested a new model that explicitly represents microbial mechanisms of soil C cycling on the global scale. Compared with traditional models, the microbial model simulates soil C pools that more closely match contemporary observations. It also projects a much wider range of soil C responses to climate change over the twenty-first century. Global soils accumulate C if microbial growth efficiency declines with warming in the microbial model. If growth efficiency adapts to warming, the microbial model projects large soil C losses. By comparison, traditional models project modest soil C losses with global warming. Microbes also change the soil response to increased C inputs, as might occur with CO2 or nutrient fertilization. In the microbial model, microbes consume these additional inputs; whereas in traditional models, additional inputs lead to C storage. Our results indicate that ESMs should simulate microbial physiology to more accurately project climate change feedbacks. © 2013 Macmillan Publishers Limited. All rights reserved .

Boreal ecosystems store 10-20% of global soil carbon and may warm by 4-7°C over the next century. Higher temperatures could increase the activity of boreal decomposers and indirectly affect decomposition through other ecosystem feedbacks. For example, permafrost melting will likely alleviate constraints on microbial decomposition and lead to greater soil CO2 emissions. However, wet boreal ecosystems underlain by permafrost are often CH4 sources, and permafrost thaw could ultimately result in drier soils that consume CH4, thereby offsetting some of the greenhouse warming potential of soil CO2 emissions. Climate change is also likely to increase winter precipitation and snow depth in boreal regions, which may stimulate decomposition by moderating soil temperatures under the snowpack. As temperatures and evapotranspiration increase in the boreal zone, fires may become more frequent, leading to additional permafrost loss from burned ecosystems. Although post-fire decomposition could also increase due to higher soil temperatures, reductions in microbial biomass and activity may attenuate this response. Other feedbacks such as soil drying, increased nutrient mineralization, and plant species shifts are either weak or uncertain. We conclude that strong positive feedbacks to decomposition will likely depend on permafrost thaw, and that climate feedbacks will probably be weak or negative in boreal ecosystems without permafrost. However, warming manipulations should be conducted in a broader range of boreal systems to validate these predictions. © 2011 Elsevier Ltd and The British Mycological Society.

The factors driving β-diversity (variation in community composition) yield insights into the maintenance of biodiversity on the planet. Here we tested whether the mechanisms that underlie bacterial β-diversity vary over centimeters to continental spatial scales by comparing the composition of ammonia-oxidizing bacteria communities in salt marsh sediments. As observed in studies of macroorganisms, the drivers of salt marsh bacterial β-diversity depend on spatial scale. In contrast to macroorganism studies, however, we found no evidence of evolutionary diversification of ammonia-oxidizing bacteria taxa at the continental scale, despite an overall relationship between geographic distance and community similarity. Our data are consistent with the idea that dispersal limitation at local scales can contribute to β-diversity, even though the 16S rRNA genes of the relatively common taxa are globally distributed. These results highlight the importance of considering multiple spatial scales for understanding microbial biogeography.

Hartley et al. question whether reduction in Rmass, under experimental warming, arises because of the biomass method. We show the method they treat as independent yields the same result. We describe why the substrate-depletion hypothesis may not solely explain observed responses, and urge caution in interpretation of the seasonal data. © 2009 Blackwell Publishing Ltd/CNRS.

1. In the conventional view of soil carbon (C) cycling, mycorrhizal fungi are primarily considered vectors for plant C input to soils. However, there is accumulating evidence that mycorrhizal fungi may also contribute to the direct loss of soil C by acting as decomposers, that is by producing extracellular lytic enzymes and metabolizing soil C. 2. Most of the evidence that mycorrhizal fungi can act as decomposers comes from studies of ericoid and ectomycorrhizal fungi, although there is increasing experimental evidence for a role of arbuscular mycorrhizal fungi in soil C decomposition. Decomposition by mycorrhizal fungi implies that soil C balance is subjected to the ecological factors that affect both plant and fungal symbionts; this interaction has important consequences for how soil C stocks respond to global change. 3. In this synthesis, we propose a new model of soil C cycling, including decomposition of soil C by mycorrhizal fungi, and we evaluate how this new integrative model alters our predictions of soil C feedbacks to global change. We present three hypothetical mechanisms by which mycorrhizal fungi may metabolize significant quantities of soil C. The first hypothesis ('Plan B' hypothesis) is that mycorrhizal fungi metabolize soil C as an alternate C source when supplies of photosynthate from the host plant are low. Our second hypothesis ('Coincidental Decomposer' hypothesis) is that mycorrhizal fungi decompose soil C as a consequence of mining soil for organic nutrients. The third hypothesis ('Priming Effects' hypothesis) is that mycorrhizal fungi decompose soil C when allocation of plant photosynthate to mycorrhizal roots is high, such that plant C 'primes' the growth and activity of mycorrhizal fungi. 4. Further empirical tests of these hypotheses will clarify the role of mycorrhizal fungi in soil C balance and improve our understanding of soil C responses to global change. © 2008 The Authors.

We assessed the degree to which ectomycorrhizal fungi exploit organic nitrogen in situ. In an Alaskan boreal forest, we identified pairs of sporocarps from five taxa of ectomycorrhizal fungi. We added 13C-labeled alanine to the soil surrounding one sporocarp within each pair; the second served as an unlabeled control. Peak rates of 13C-respiration from alanine were higher in the labeled sporocarp plots than the controls, indicating that the 13C-alanine was detectably respired from the soil. “Reference” plots adjacent to the sporocarps served as an indication of background 13C-respiration rates released by the soil community as a whole. Ectomycorrhizal sporocarps displayed higher 13C-respiration rates than their reference plots. Thus, the sporocarps and associated mycorrhizal mycelium appeared to contribute significantly to the release of alanine-derived 13CO2, confirming the hypothesis that ectomycorrhizal fungi may access soil amino acid pools under natural conditions.