An integrated metagenomic, metabolomic and transcriptomic survey of Populus across genotypes and environments.

Bridging molecular information to ecosystem-level processes would provide the capacity to understand system vulnerability and, potentially, a means for assessing ecosystem health. Here, we present an integrated dataset containing environmental and metagenomic information from plant-associated microbial communities, plant transcriptomics, plant and soil metabolomics, and soil chemistry and activity characterization measurements derived from the model tree species Populus trichocarpa. Soil, rhizosphere, root endosphere, and leaf samples were collected from 27 different P. trichocarpa genotypes grown in two different environments leading to an integrated dataset of 318 metagenomes, 98 plant transcriptomes, and 314 metabolomic profiles that are supported by diverse soil measurements. This expansive dataset will provide insights into causal linkages that relate genomic features and molecular level events to system-level properties and their environmental influences.

Stronger fertilization effects on aboveground versus belowground plant properties across nine U.S. grasslands.

Increased nutrient inputs due to anthropogenic activity are expected to increase primary productivity across terrestrial ecosystems, but changes in allocation aboveground versus belowground with nutrient addition have different implications for soil carbon (C) storage. Thus, given that roots are major contributors to soil C storage, understanding belowground net primary productivity (BNPP) and biomass responses to changes in nutrient availability is essential to predicting carbon-climate feedbacks in the context of interacting global environmental changes. To address this knowledge gap, we tested whether a decade of nitrogen (N) and phosphorus (P) fertilization consistently influenced aboveground and belowground biomass and productivity at nine grassland sites spanning a wide range of climatic and edaphic conditions in the continental United States. Fertilization effects were strong aboveground, with both N and P addition stimulating aboveground biomass at nearly all sites (by 30% and 36%, respectively, on average). P addition consistently increased root production (by 15% on average), whereas other belowground responses to fertilization were more variable, ranging from positive to negative across sites. Site-specific responses to P were not predicted by the measured covariates. Atmospheric N deposition mediated the effect of N fertilization on root biomass and turnover. Specifically, atmospheric N deposition was positively correlated with root turnover rates, and this relationship was amplified with N addition. Nitrogen addition increased root biomass at sites with low N deposition but decreased it at sites with high N deposition. Overall, these results suggest that the effects of nutrient supply on belowground plant properties are context dependent, particularly with regard to background N supply rates, demonstrating that site conditions must be considered when predicting how grassland ecosystems will respond to increased nutrient loading from anthropogenic activity.

Soil carbon stocks in temperate grasslands differ strongly across sites but are insensitive to decade-long fertilization.

Enhancing soil carbon (C) storage has the potential to offset human-caused increases in atmospheric CO2 . Rising CO2 has occurred concurrently with increasing supply rates of biologically limiting nutrients such as nitrogen (N) and phosphorus (P). However, it is unclear how increased supplies of N and P will alter soil C sequestration, particularly in grasslands, which make up nearly a third of non-agricultural land worldwide. Here, we leverage a globally distributed nutrient addition experiment (the Nutrient Network) to examine how a decade of N and P fertilization (alone and in combination) influenced soil C and N stocks at nine grassland sites spanning the continental United States. We measured changes in bulk soil C and N stocks and in three soil C fractions (light and heavy particulate organic matter, and mineral-associated organic matter fractions). Nutrient amendment had variable effects on soil C and N pools that ranged from strongly positive to strongly negative, while soil C and N pool sizes varied by more than an order of magnitude across sites. Piecewise SEM clarified that small increases in plant C inputs with fertilization did not translate to greater soil C storage. Nevertheless, peak season aboveground plant biomass (but not root biomass or production) was strongly positively related to soil C storage at seven of the nine sites, and across all nine sites, soil C covaried with moisture index and soil mineralogy, regardless of fertilization. Overall, we show that site factors such as moisture index, plant productivity, soil texture, and mineralogy were key predictors of cross-site soil C, while nutrient amendment had weaker and site-specific effects on C sequestration. This suggests that prioritizing the protection of highly productive temperate grasslands is critical for reducing future greenhouse gas losses arising from land use change.

Microbial seasonality promotes soil respiratory carbon emission in natural ecosystems: A modeling study.

Seasonality is a key feature of the biosphere and the seasonal dynamics of soil carbon (C) emissions represent a fundamental mechanism regulating the terrestrial-climate interaction. We applied a microbial explicit model-CLM-Microbe-to evaluate the impacts of microbial seasonality on soil C cycling in terrestrial ecosystems. The CLM-Microbe model was validated in simulating belowground respiratory fluxes, that is, microbial respiration, root respiration, and soil respiration at the site level. On average, the CLM-Microbe model explained 72% (n = 19, p < 0.0001), 65% (n = 19, p < 0.0001), and 71% (n = 18, p < 0.0001) of the variation in microbial respiration, root respiration, and soil respiration, respectively. We then compared the model simulations of soil respiratory fluxes and soil organic C content in top 1 m between the CLM-Microbe model with (CLM-Microbe) and without (CLM-Microbe_wos) seasonal dynamics of soil microbial biomass in natural biomes. Removing soil microbial seasonality reduced model performance in simulating microbial respiration and soil respiration, but led to slight differences in simulating root respiration. Compared with the CLM-Microbe, the CLM-Microbe_wos underestimated the annual flux of microbial respiration by 0.6%-32% and annual flux of soil respiration by 0.4%-29% in natural biomes. Correspondingly, the CLM-Microbe_wos estimated higher soil organic C content in top 1 m (0.2%-7%) except for the sites in Arctic and boreal regions. Our findings suggest that soil microbial seasonality enhances soil respiratory C emissions, leading to a decline in SOC storage. An explicit representation of soil microbial seasonality represents a critical improvement for projecting soil C decomposition and reducing the uncertainties in global C cycle projection under the changing climate.

Soil organic carbon cycling in response to simulated soil moisture variation under field conditions.

The combination of extended dry periods and high intensity rainfall, common in the southeastern US, leads to greater variability in soil moisture and consequently increases uncertainty to microbial processes pertinent to soil carbon (C) mineralization. However, field-based findings on soil moisture sensitivity to soil C cycling are very limited. Therefore, a field experiment was conducted in 2018 and 2019 on a soybean (Glycine max L.) cropland in the southeastern US with three soil moisture treatments: drought (simulated using rainout-shelter from June to October in each year), rainfed (natural precipitation), and irrigated (irrigation and precipitation). Soil respiration was measured weekly from May to November in both years. Soil samples were collected multiple times each year from 0-5, 5-15, and 15-30 cm depths to determine microbial biomass C (MBC), extractable organic C (EOC), hydrolytic enzyme activities, and fungal abundance. The cumulative respiration under drought compared to other treatments was lower by 32% to 33% in 2018 and 38% to 45% in 2019. Increased MBC, EOC, and fungal abundance were observed under drought than other treatments. Specific enzyme activity indicated fewer metabolically active microbes under drought treatment compared to rainfed and irrigated treatments. Also, maintenance of enzyme pool was observed under drought condition. These results provide critical insights on microbial metabolism in response to soil moisture variation and how that influences different pools of soil C under field conditions.

Biological mechanisms may contribute to soil carbon saturation patterns.

Increasing soil organic carbon (SOC) storage is a key strategy to mitigate rising atmospheric CO2 , yet SOC pools often appear to saturate, or increase at a declining rate, as carbon (C) inputs increase. Soil C saturation is commonly hypothesized to result from the finite amount of reactive mineral surface area available for retaining SOC, and is accordingly represented in SOC models as a physicochemically determined SOC upper limit. However, mineral-associated SOC is largely microbially generated. In this perspective, we present the hypothesis that apparent SOC saturation patterns could emerge as a result of ecological constraints on microbial biomass-for example, via competition or predation-leading to reduced C flow through microbes and a reduced rate of mineral-associated SOC formation as soil C inputs increase. Microbially explicit SOC models offer an opportunity to explore this hypothesis, yet most of these models predict linear microbial biomass increases with C inputs and insensitivity of SOC to input rates. Synthesis of 54 C addition studies revealed constraints on microbial biomass as C inputs increase. Different hypotheses limiting microbial density were embedded in a three-pool SOC model without explicit limits on mineral surface area. As inputs increased, the model demonstrated either no change, linear, or apparently saturating increases in mineral-associated and particulate SOC pools. Taken together, our results suggest that microbial constraints are common and could lead to reduced mineral-associated SOC formation as input rates increase. We conclude that SOC responses to altered C inputs-or any environmental change-are influenced by the ecological factors that limit microbial populations, allowing for a wider range of potential SOC responses to stimuli. Understanding how biotic versus abiotic factors contribute to these patterns will better enable us to predict and manage soil C dynamics.

Bringing function to structure: Root-soil interactions shaping phosphatase activity throughout a soil profile in Puerto Rico.

Large areas of highly productive tropical forests occur on weathered soils with low concentrations of available phosphorus (P). In such forests, root and microbial production of acid phosphatase enzymes capable of mineralizing organic phosphorus is considered vital to increasing available P for plant uptake.We measured both root and soil phosphatase throughout depth and alongside a variety of root and soil factors to better understand the potential of roots and soil biota to increase P availability and to constrain estimates of the biochemical mineralization within ecosystem models.We measured soil phosphatase down to 1 m, root phosphatase to 30 cm, and collected data on fine-root mass density, specific root length, soil P, bulk density, and soil texture using soil cores in four tropical forests within the Luquillo Experimental Forest in Puerto Rico.We found that soil phosphatase decreased with soil depth, but not root phosphatase. Furthermore, when both soil and root phosphatase were expressed per soil volume, soil phosphatase was 100-fold higher that root phosphatase.Both root and soil factors influenced soil and root phosphatase. Soil phosphatase increased with fine-root mass density and organic P, which together explained over 50% of the variation in soil phosphatase. Over 80% of the variation in root phosphatase per unit root mass was attributed to specific root length (positive correlation) and available (resin) P (negative correlation). Synthesis: Fine-root traits and soil P data are necessary to understand and represent soil and root phosphatase activity throughout the soil column and across sites with different soil conditions and tree species. These findings can be used to parameterize or benchmark estimates of biochemical mineralization in ecosystem models that contain fine-root biomass and soil P distributions throughout depth.

Evaluation of engineered sorbents for the sorption of mercury from contaminated bank soils: a column study.

As a global environmental pollutant, mercury (Hg) threatens our water resources and presents a substantial risk to human health. The rate and extent of immobilization of Hg2+ (hereafter, Hg) on engineered sorbents (Thiol-SAMMS®, pine biochar, SediMite™, Organoclay™ PM-199, and quartz sand as a control) was evaluated using flow-through column experiments. The effectiveness of the sorbents was based on (1) the percentage of Hg removed in relation to the total amount of Hg passing the sorbent column, and (2) the rate of Hg uptake compared to the nonreactive tracer bromide (Br-). All sorbents removed Hg to a certain extent, but none of the sorbents removed all the Hg introduced to the columns. Thiol-SAMMS showed the highest mean percentage of Hg removed (87% ± 2.9%), followed by Organoclay PM-199 (71% ± 0.4%), pine biochar (57% ± 22.3%), SediMite (61% ± 0.8%), and the control quartz sand (11% ± 5.6%). Thiol-SAMMS was the only sorbent to exhibit retardation of Hg in comparison to the conservative tracer Br-. For the remaining sorbents, Br- along with low concentrations of Hg were eluted within the first 3 pore volumes, indicating limited retardation of Hg. Overall, removal of Hg by sorbents was substantial, suggesting that sorbents might be suitable for deployment in contaminated environments. High concentrations of DOM leaching from the soil columns likely influenced the speciation of Hg and inhibited sorption to the sorbents. Incomplete removal of Hg by any sorbent suggests that additional optimization is needed to increase efficiency.

Multi-year incubation experiments boost confidence in model projections of long-term soil carbon dynamics.

Global soil organic carbon (SOC) stocks may decline with a warmer climate. However, model projections of changes in SOC due to climate warming depend on microbially-driven processes that are usually parameterized based on laboratory incubations. To assess how lab-scale incubation datasets inform model projections over decades, we optimized five microbially-relevant parameters in the Microbial-ENzyme Decomposition (MEND) model using 16 short-term glucose (6-day), 16 short-term cellulose (30-day) and 16 long-term cellulose (729-day) incubation datasets with soils from forests and grasslands across contrasting soil types. Our analysis identified consistently higher parameter estimates given the short-term versus long-term datasets. Implementing the short-term and long-term parameters, respectively, resulted in SOC loss (-8.2 ± 5.1% or -3.9 ± 2.8%), and minor SOC gain (1.8 ± 1.0%) in response to 5 °C warming, while only the latter is consistent with a meta-analysis of 149 field warming observations (1.6 ± 4.0%). Comparing multiple subsets of cellulose incubations (i.e., 6, 30, 90, 180, 360, 480 and 729-day) revealed comparable projections to the observed long-term SOC changes under warming only on 480- and 729-day. Integrating multi-year datasets of soil incubations (e.g., > 1.5 years) with microbial models can thus achieve more reasonable parameterization of key microbial processes and subsequently boost the accuracy and confidence of long-term SOC projections.

COSORE: A community database for continuous soil respiration and other soil-atmosphere greenhouse gas flux data.

Globally, soils store two to three times as much carbon as currently resides in the atmosphere, and it is critical to understand how soil greenhouse gas (GHG) emissions and uptake will respond to ongoing climate change. In particular, the soil-to-atmosphere CO2 flux, commonly though imprecisely termed soil respiration (RS ), is one of the largest carbon fluxes in the Earth system. An increasing number of high-frequency RS measurements (typically, from an automated system with hourly sampling) have been made over the last two decades; an increasing number of methane measurements are being made with such systems as well. Such high frequency data are an invaluable resource for understanding GHG fluxes, but lack a central database or repository. Here we describe the lightweight, open-source COSORE (COntinuous SOil REspiration) database and software, that focuses on automated, continuous and long-term GHG flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation. Contributed datasets are mapped to a single, consistent standard, with metadata on contributors, geographic location, measurement conditions and ancillary data. The design emphasizes the importance of reproducibility, scientific transparency and open access to data. While being oriented towards continuously measured RS , the database design accommodates other soil-atmosphere measurements (e.g. ecosystem respiration, chamber-measured net ecosystem exchange, methane fluxes) as well as experimental treatments (heterotrophic only, etc.). We give brief examples of the types of analyses possible using this new community resource and describe its accompanying R software package.

Effects of nitrogen fertilization and bioenergy crop type on topsoil organic carbon and total Nitrogen contents in middle Tennessee USA.

Nitrogen (N) fertilization affects bioenergy crop growth and productivity and consequently carbon (C) and N contents in soil, it however remains unclear whether N fertilization and crop type individually or interactively influence soil organic carbon (SOC) and total N (TN). In a three-year long fertilization experiment in switchgrass (SG: Panicum virgatum L.) and gamagrass (GG: Tripsacum dactyloides L.) croplands in Middle Tennessee USA, soil samples (0-15cm) were collected in plots with no N input (NN), low N input (LN: 84 kg N ha-1 yr-1 in urea) and high N input (HN: 168 kg N ha-1 yr-1 in urea). Besides SOC and TN, the aboveground plant biomass was also quantified. In addition to a summary of published root morphology data based on a separated mesocosm experiment, the root leachable dissolved organic matter (DOM) of both crops was also measured using archived samples. Results showed no significant interaction of N fertilization and crop type on SOC, TN or plant aboveground biomass (ABG). Relative to NN, HN (not LN) significantly increased SOC and TN in both crops. Though SG showed a 15-68% significantly higher ABG than GG, GG showed a 9.3-12% significantly higher SOC and TN than SG. The positive linear relationships of SOC or TN with ABG were identified for SG. However, GG showed structurally more complex and less readily decomposed root DOM, a larger root volume, total root length and surface area than SG. Collectively, these suggested that intensive N fertilization could increase C and N stocks in bioenergy cropland soils but these effects may be more likely mediated by the aboveground biomass in SG and root chemistry and morphology in GG. Future studies are expected to examine the root characteristics in different bioenergy croplands under the field fertilization experiment.

Nitrogen Fertilization Restructured Spatial Patterns of Soil Organic Carbon and Total Nitrogen in Switchgrass and Gamagrass Croplands in Tennessee USA.

Nitrogen (N) fertilizers can potentially alter spatial distribution of soil organic carbon (SOC) and total nitrogen (TN)  concentrations in croplands such as switchgrass (SG: Panicum virgatum L.) and gamagrass (GG: Tripsacum dactyloides L.), but it remains unclear whether these effects are the same between crops and under different rates of fertilization. 13C and 15N are  two important proxy measures of soil biogeochemistry, but they were rarely examined as to their spatial distributions in soil. Based on a three-year long fertilization experiment in Middle Tennessee, USA, the top mineral horizon soils (0-15 cm) were collected using a spatially explicit design within two 15-m2 plots under three fertilization treatments in SG and GG croplands. A total of 288 samples were collected based on 12 plots and 24 samples in each plot. The fertilization treatments were no N input (NN), low N input (LN: 84 kg N ha-1 in urea) and high N input (HN: 168 kg N ha-1 in urea). The SOC, TN, SOC/TN (C: N), δ13C and δ15N were quantified and their within-plot variations and spatial distributions were achieved via descriptive and geostatistical methods. Results showed that SG generally displayed 10~120% higher plot-level variations in all variables than GG, and the plot-level variations were 20~77% higher in NN plots than LN and HN plots in SG but they were comparable in unfertilized and fertilized plots in GG. Relative to NN, LN and HN showed more significant surface trends and spatial structures in SOC and TN in both croplands, and the fertilization effect appeared more pronounced in SG. Spatial patterns in C: N, δ13C and δ15N were comparable among different fertilization treatments in both croplands. The descending within-plot variations were also identified among variables (SOC > TN > δ15N > C: N > δ13C). This study demonstrated that N fertilizations generally reduced the plot-level variance and simultaneously re-established spatial structures of SOC and TN in bioenergy croplands, which little varied with fertilization rate but was more responsive in switchgrass cropland.

Genome-Resolved Proteomic Stable Isotope Probing of Soil Microbial Communities Using 13CO2 and 13C-Methanol.

Stable isotope probing (SIP) enables tracking the nutrient flows from isotopically labeled substrates to specific microorganisms in microbial communities. In proteomic SIP, labeled proteins synthesized by the microbial consumers of labeled substrates are identified with a shotgun proteomics approach. Here, proteomic SIP was combined with targeted metagenomic binning to reconstruct metagenome-assembled genomes (MAGs) of the microorganisms producing labeled proteins. This approach was used to track carbon flows from 13CO2 to the rhizosphere communities of Zea mays, Triticum aestivum, and Arabidopsis thaliana. Rhizosphere microorganisms that assimilated plant-derived 13C were capable of metabolic and signaling interactions with their plant hosts, as shown by their MAGs containing genes for phytohormone modulation, quorum sensing, and transport and metabolism of nutrients typical of those found in root exudates. XoxF-type methanol dehydrogenases were among the most abundant proteins identified in the rhizosphere metaproteomes. 13C-methanol proteomic SIP was used to test the hypothesis that XoxF was used to metabolize and assimilate methanol in the rhizosphere. We detected 7 13C-labeled XoxF proteins and identified methylotrophic pathways in the MAGs of 8 13C-labeled microorganisms, which supported the hypothesis. These two studies demonstrated the capability of proteomic SIP for functional characterization of active microorganisms in complex microbial communities.

Dissolved organic matter reduces the effectiveness of sorbents for mercury removal.

Mercury (Hg) contamination of soils and sediments impacts numerous environments worldwide and constitutes a challenging remediation problem. In this study, we evaluate the impact of dissolved organic matter (DOM) on the effectiveness of eight sorbent materials considered for Hg remediation in soils and sediments. The materials include both engineered and unmodified materials based on carbon, clays, mesoporous silica and a copper alloy. Initially, we investigated the kinetics of Hg(II) complexation with DOM for a series of Hg:DOM ratios. Steady-state Hg-DOM complexation occurred within 48 to 120 h, taking longer time at higher Hg:DOC (dissolved organic carbon) molar ratios. In subsequent equilibrium experiments, Hg(II) was equilibrated with DOM at a defined Hg:DOC molar ratio (2.4 ·â€¯10-6) for 170 h and used in batch experiments to determine the effect of DOM on Hg partition coefficients and sorption isotherms by comparing Hg(II) and Hg-DOM. Hg sorption capacities of all sorbents were severely limited in the presence of DOM as a competing ligand. Thiol-SAMMS®, SediMite™ and pine biochar were most effective in reducing Hg concentrations. While pine biochar and lignin-derived carbon processed at high temperatures released negligible amounts of anions into solution, leaching of sulfate and chloride was observed for most engineered sorbent materials. Sulfate may stimulate microbial communities harboring sulfate reducing bacteria, which are considered one of the primary drivers of microbial mercury methylation in the environment. The results highlight potential challenges arising from the application of sorbents for Hg remediation in the field.

Reduced carbon use efficiency and increased microbial turnover with soil warming.

Global soil carbon (C) stocks are expected to decline with warming, and changes in microbial processes are key to this projection. However, warming responses of critical microbial parameters such as carbon use efficiency (CUE) and biomass turnover (rB) are not well understood. Here, we determine these parameters using a probabilistic inversion approach that integrates a microbial-enzyme model with 22 years of carbon cycling measurements at Harvard Forest. We find that increasing temperature reduces CUE but increases rB, and that two decades of soil warming increases the temperature sensitivities of CUE and rB. These temperature sensitivities, which are derived from decades-long field observations, contrast with values obtained from short-term laboratory experiments. We also show that long-term soil C flux and pool changes in response to warming are more dependent on the temperature sensitivity of CUE than that of rB. Using the inversion-derived parameters, we project that chronic soil warming at Harvard Forest over six decades will result in soil C gain of <1.0% on average (1st and 3rd quartiles: 3.0% loss and 10.5% gain) in the surface mineral horizon. Our results demonstrate that estimates of temperature sensitivity of microbial CUE and rB can be obtained and evaluated rigorously by integrating multidecadal datasets. This approach can potentially be applied in broader spatiotemporal scales to improve long-term projections of soil C feedbacks to climate warming.

Community proteogenomics reveals the systemic impact of phosphorus availability on microbial functions in tropical soil.

Phosphorus is a scarce nutrient in many tropical ecosystems, yet how soil microbial communities cope with growth-limiting phosphorus deficiency at the gene and protein levels remains unknown. Here, we report a metagenomic and metaproteomic comparison of microbial communities in phosphorus-deficient and phosphorus-rich soils in a 17-year fertilization experiment in a tropical forest. The large-scale proteogenomics analyses provided extensive coverage of many microbial functions and taxa in the complex soil communities. A greater than fourfold increase in the gene abundance of 3-phytase was the strongest response of soil communities to phosphorus deficiency. Phytase catalyses the release of phosphate from phytate, the most recalcitrant phosphorus-containing compound in soil organic matter. Genes and proteins for the degradation of phosphorus-containing nucleic acids and phospholipids, as well as the decomposition of labile carbon and nitrogen, were also enhanced in the phosphorus-deficient soils. In contrast, microbial communities in the phosphorus-rich soils showed increased gene abundances for the degradation of recalcitrant aromatic compounds, transformation of nitrogenous compounds and assimilation of sulfur. Overall, these results demonstrate the adaptive allocation of genes and proteins in soil microbial communities in response to shifting nutrient constraints.

Effect of long-term irrigation patterns on phosphorus forms and distribution in the brown soil zone.

Continuous application of P fertilizers under different irrigation patterns can change soil phosphorus (P) chemical behavior and increase soil P levels that are of environmental concern. To assess the effect of long-term different irrigation patterns on soil P fractions and availability, this study examined sequential changes in soil organic P and inorganic P from furrow irrigation (FI), surface drip irrigation (SUR), and subsurface drip irrigation (SDI) in the brown soil zone (0-60 cm) during 1998 to 2011. Analyses of soil P behavior showed that the levels of total P are frequently high on top soil layers. The total P (TP) contents of the entire soil profiles under three irrigation treatments were 830.2-3180.1 mg/kg. The contents of available P (AP) were 72.6-319.3 mg P/kg soil through soil profiles. The greatest TP and AP contents were obtained within the upper soil layers in FI. Results of Hedley's P fractionation indicate that HCl-P is a dominant form and the proportion to TP ranges from 29% to 43% in all three methods. The contents of various fractions of P were positively correlated with the levels of total carbon (TC), total inorganic carbon (TIC), and calcium (Ca), whereas the P fractions had negative correlation with pH in all soil samples. Regression models proved that NaHCO3-Po was an important factor in determining the amount of AP in FI. H2O-Po, NaHCO3-Po, and NaOH-Pi were related to available P values in SUR. NaHCO3-Po and NaOH-Po played important roles in SDI. The tomato yield under SUR was higher than SDI and FI. The difference of P availability was also controlled by the physicochemical soil properties under different irrigation schedule. SUR was a reasonable irrigation pattern to improve the utilization efficiency of water and fertilizer.

Microbial dormancy improves development and experimental validation of ecosystem model.

Climate feedbacks from soils can result from environmental change followed by response of plant and microbial communities, and/or associated changes in nutrient cycling. Explicit consideration of microbial life-history traits and functions may be necessary to predict climate feedbacks owing to changes in the physiology and community composition of microbes and their associated effect on carbon cycling. Here we developed the microbial enzyme-mediated decomposition (MEND) model by incorporating microbial dormancy and the ability to track multiple isotopes of carbon. We tested two versions of MEND, that is, MEND with dormancy (MEND) and MEND without dormancy (MEND_wod), against long-term (270 days) carbon decomposition data from laboratory incubations of four soils with isotopically labeled substrates. MEND_wod adequately fitted multiple observations (total C-CO2 and (14)C-CO2 respiration, and dissolved organic carbon), but at the cost of significantly underestimating the total microbial biomass. MEND improved estimates of microbial biomass by 20-71% over MEND_wod. We also quantified uncertainties in parameters and model simulations using the Critical Objective Function Index method, which is based on a global stochastic optimization algorithm, as well as model complexity and observational data availability. Together our model extrapolations of the incubation study show that long-term soil incubations with experimental data for multiple carbon pools are conducive to estimate both decomposition and microbial parameters. These efforts should provide essential support to future field- and global-scale simulations, and enable more confident predictions of feedbacks between environmental change and carbon cycling.

Representation of dormant and active microbial dynamics for ecosystem modeling.

Dormancy is an essential strategy for microorganisms to cope with environmental stress. However, global ecosystem models typically ignore microbial dormancy, resulting in notable model uncertainties. To facilitate the consideration of dormancy in these large-scale models, we propose a new microbial physiology component that works for a wide range of substrate availabilities. This new model is based on microbial physiological states and the major parameters are the maximum specific growth and maintenance rates of active microbes and the ratio of dormant to active maintenance rates. A major improvement of our model over extant models is that it can explain the low active microbial fractions commonly observed in undisturbed soils. Our new model shows that the exponentially-increasing respiration from substrate-induced respiration experiments can only be used to determine the maximum specific growth rate and initial active microbial biomass, while the respiration data representing both exponentially-increasing and non-exponentially-increasing phases can robustly determine a range of key parameters including the initial total live biomass, initial active fraction, the maximum specific growth and maintenance rates, and the half-saturation constant. Our new model can be incorporated into existing ecosystem models to account for dormancy in microbially-driven processes and to provide improved estimates of microbial activities.

Spatial arrangement of organic compounds on a model mineral surface: implications for soil organic matter stabilization.

The complexity of the mineral-organic carbon interface may influence the extent of stabilization of organic carbon compounds in soils, which is important for global climate futures. The nanoscale structure of a model interface was examined here by depositing films of organic carbon compounds of contrasting chemical character, hydrophilic glucose and amphiphilic stearic acid, onto a soil mineral analogue (Al2O3). Neutron reflectometry, a technique which provides depth-sensitive insight into the organization of the thin films, indicates that glucose molecules reside in a layer between Al2O3 and stearic acid, a result that was verified by water contact angle measurements. Molecular dynamics simulations reveal the thermodynamic driving force behind glucose partitioning on the mineral interface: The entropic penalty of confining the less mobile glucose on the mineral surface is lower than for stearic acid. The fundamental information obtained here helps rationalize how complex arrangements of organic carbon on soil mineral surfaces may arise.