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At least 217 records · Page 12

Mineral-associated organic matter is heterogeneous and structured by hydrophobic, charged, and polar interactions

The formation of mineral-associated organic matter (MAOM) is a key phenomenon that may explain the slow turnover rates of carbon in soil organic matter (SOM). Despite this, important details pertaining to the structure and dynamics of MAOM remain unknown. In the present study, we use replica-exchange molecular dynamics simulations to gain insight into the structure of MAOM on the surface of prototypical phyllosilicate clay and Fe-oxide minerals, montmorillonite and goethite, fine-grained minerals that strongly impact soil carbon dynamics in temperate and tropical regions, respectively. We examine the impact of aqueous chemistry through the presence of either Na + or Ca 2 + charge balancing counterions. Our results are consistent with the hypothesized multilayer sorption (“onion-skin”) model of MAOM and help to explain previous observations regarding the patchy distribution of SOM on mineral surfaces. In particular, the SOM coatings are partial and laterally heterogeneous, and water retains extensive access to mineral surfaces even when significant SOM sorption occurs. Low molecular weight neutral SOM molecules ( < 200 Da) infrequently interact with the mineral surfaces nor their sorbed organic matter coatings and are increasingly labile with decreasing molecular weight. This observation is inconsistent with a central feature of the predominant soil continuum model of SOM and suggests that further iterations of the conceptual model may be required.

54 ENVIRONMENTAL SCIENCES↗

Multi-site evaluation of stratified and balanced sampling of soil organic carbon stocks in agricultural fields

Estimating soil organic carbon (SOC) stocks in agricultural fields is essential for environmental and agronomic research, management, and policy. Stratified sampling is a classic strategy for estimating mean soil properties, and has recently been codified in SOC monitoring protocols. However, for the specific task of estimating the SOC stock of an agricultural field, concrete guidance is needed for which covariates to stratify on and how much stratification can improve estimation efficiency. It is also unknown how stratified sampling of SOC stocks compares to modern alternatives, notably doubly balanced sampling. To address these gaps, we collected high-density (average of 7 samples ha -1 ) and deep (average of 75 cm) measurements of SOC stocks at eight commercial fields under maize-soybean production in two US Midwestern states. We combined these measurements with a Bayesian geostatistical model to evaluate stratified and balanced sampling strategies that use a set of readily-available geographic, topographic, spectroscopic, and soil survey data. We examined the number of samples needed to achieve a given level of SOC stock estimation accuracy. While stratified sampling using these variables enables an average sample size reduction of 17% (95% CI, 11% to 23%) compared to simple random sampling, doubly balanced sampling is consistently more efficient, reducing sample sizes by 32% (95% CI, 25% to 37%). The data most important to these efficiency gains are a remotely-sensed SOC index, SSURGO estimates of SOC stocks, and the topographic wetness index. We conclude that in order to meet the urgent challenge of climate change, SOC stocks in agricultural fields could be more efficiently estimated by taking advantage of this readily-available data, especially with doubly balanced sampling.

54 ENVIRONMENTAL SCIENCES↗

Conservation management decreases surface runoff and soil erosion

Conservation management practices – including agroforestry, cover cropping, no-till, reduced tillage, and residue return – have been applied for decades to control surface runoff and soil erosion, yet results have not been integrated and evaluated across cropping systems. In this study we collected data comparing agricultural production with and without conservation management strategies. We used a bootstrap resampling analysis to explore interactions between practice type, soil texture, surface runoff, and soil erosion. We then used a correlation analysis to relate changes in surface runoff and soil erosion to 13 other soil health and agronomic indicators, including soil organic carbon, soil aggregation, infiltration, porosity, subsurface leaching, and cash crop yield. Across all conservation management practices, surface runoff and erosion had respective mean decreases of 67% and 80% compared with controls. Use of cover cropping provided the largest decreases in erosion and surface runoff, thus emphasizing the importance of maintaining continuous vegetative cover on soils. Coarse- and medium-textured soils had greater decreases in both erosion and runoff than fine-textured soils. Changes in surface runoff and soil erosion under conservation management were highly correlated with soil organic carbon, aggregation, porosity, infiltration, leaching, and yield, showing that conservation practices help drive important interactions between these different facets of soil health. This study offers the first large-scale comparison of how different conservation agriculture practices reduce surface runoff and soil erosion, and at the same time provides new insight into how these interactions influence the improvement or loss of soil health.

58 GEOSCIENCES↗

Arbuscular mycorrhizal trees cause a higher carbon to nitrogen ratio of soil organic matter decomposition via rhizosphere priming than ectomycorrhizal trees

Tree roots and their associated microbes can significantly influence soil organic matter (SOM) decomposition, i.e., the rhizosphere priming effect. This effect is expected to be greater in trees associated with arbuscular mycorrhizal (AM) fungi, which produce higher extracellular enzymes especially surrounding hyphae, than in trees associated with ectomycorrhizal (ECM) fungi. In this work, we selected five tree species associated with AM (Juglans mandshurica Maxim. and Cunninghamia lanceolata (Lamb.) Hook.) or ECM (Picea koraiensis Nakai, Quercus mongolica Fischer ex Turcz. and Larix kaempferi (Lamb.) Carriere). We grew tree seedlings inside of cores lined with different mesh sizes to investigate how roots, hyphae and exudates influence soil carbon (C) and nitrogen (N) mineralization via the rhizosphere priming effect, using a 13 C natural abundance approach and a 15 N pool dilution method, concurrently. We found that tree seedlings significantly accelerated soil C decomposition by on average 78%, i.e., positive priming, compared to unplanted control pots. AM-associated trees induced 2.1 times greater soil C decomposition than ECM-associated trees across all mesh sizes. In contrast, gross N mineralization did not differ between tree-mycorrhizal associations. Compared to ECM counterparts, AM-associated trees had higher C- and lower N-degrading enzyme activities. Consequently, AM-associated trees induced a significantly higher C:N ratio of SOM decomposition than their ECM counterparts, which could be associated with the differences in soil enzyme activities for C and N degradation. Further, for both AM- and ECM-associated trees, we found no significant influences of mesh size on soil C decomposition, suggesting that the rhizosphere priming effect of mycorrhizal symbiosis was predominantly driven by root exudates. We conclude that SOM decomposition caused by AM-associated trees may have a higher C:N ratio than that by ECM-associated trees mainly due to differences in microbial enzyme investment. Our findings imply that tree-mycorrhizal associations are capable of modulating soil biogeochemical cycling via the rhizosphere priming effect.

54 ENVIRONMENTAL SCIENCES↗

Evaluating the incentive for soil organic carbon sequestration from carinata production in the Southeast United States

Soil organic carbon (SOC) can be increased by cultivating bioenergy crops to produce low-carbon fuels, improving soil quality and agricultural productivity. This study evaluates the incentives for farmers to sequester SOC by adopting a bioenergy crop, carinata. Two agricultural management scenarios – business as usual (BaU) and a climate-smart (no-till) practice – were simulated using an agent-based modeling approach to account for farmers’ carinata adoption rates within their context of traditional crop rotations, the associated profitability, influences of neighboring farmers, as well as their individual attitudes. Here, using the state of Georgia, US, as a case study, the results show that farmers allocated 1056 × 10 3 acres (23.8%; 2.47 acres is equivalent to 1 ha) of farmlands by 2050 at a contract price of $\$6.5$ per bushel of carinata seeds and with an incentive of $50Mg -1 CO2e SOC sequestered under the BaU scenario. In contrast, at the same contract price and SOC incentive rate, farmers allocated 1152 × 10 3 acres (25.9%) of land under the no-till scenario, while the SOC sequestration was 483.83 × 10 3 Mg CO2e, which is nearly four times the amount under the BaU scenario. Thus, this study demonstrated combinations of seed prices and SOC incentives that encourage farmers to adopt carinata with climate-smart practices to attain higher SOC sequestration benefits.

54 ENVIRONMENTAL SCIENCES↗

Unexpected mechanism for glucose-primed soil organic carbon mineralization under an anaerobic–aerobic transition

Redox reactions are important for cycling of carbon (C) in soils frequently subject to fluctuations in redox conditions, such as wetland soils, which contribute around one third of the global terrestrial C reservoir. Priming effects (PE), induction of changes in C mineralization due to additions of energy-rich organic carbon (OC) substrates, have been largely ignored during redox transitions in current modelling and experimental efforts for evaluating C cycles. In this study, we investigated the effects of glucose input on the mineralization of soil OC during an anaerobic-aerobic transition. Substantially more soil OC was mineralized under aerobic conditions in samples that received glucose under preceding anaerobic conditions compared to controls that did not receive glucose and to samples that received glucose under aerobic-only conditions. Our results reveal a novel PE by which glucose indirectly primes the mineralization of soil OC by increasing the reductive release of iron oxide-associated OC under anaerobic conditions, followed by a dramatic positive PE when aerobic conditions are reestablished. Inclusion of this novel indirect priming mechanism is crucial for accurately predicting the contribution of atmospheric greenhouse gases from soils experiencing redox fluctuations (e.g.,wetlands).

54 ENVIRONMENTAL SCIENCES↗

Field experiments show no consistent reductions in soil microbial carbon in response to warming

Soil microbes play an essential role in maintaining soil functions and services, but the dynamics of soil microbial biomass carbon (MBC) under global climate change remain unclear. Recently, Patoine et al. combined a global MBC data set with Random Forest modeling and reported that global MBC decreased over 1992–2013, mainly driven by increasing temperatures. Contrarily, using MBC field observations from soil warming manipulation experiments and in-situ long-term measurements across the globe, we found that MBC showed no significant changes under soil warming. Our findings indicate that soil MBC is unlikely to have decreased significantly due to the global warming of 0.28 °C during 1992–2013, and that further mechanistic studies are needed to understand potential changes in MBC under climate change.

54 ENVIRONMENTAL SCIENCES↗

MOFLUX Intensified Soil Moisture Extremes Decrease Soil Organic Carbon Decomposition: Modeling Archive

This Modeling Archive is in support the publication “Intensified Soil Moisture Extremes Decrease Soil Organic Carbon Decomposition: A Mechanistic Modeling Analysis” (Liang et al., 2021). Here we provide model code, inputs, outputs and evaluation datasets for the Microbial ENzyme Decomposition (MEND) model for the Missouri Ozarks AmeriFlux eddy covariance measurement site (MOFLUX) near Ashland, Missouri USA. The MEND model was developed with explicit representation of microbial and enzyme pools to mechanistically simulate the role of microbial organisms and extracellular enzymes in soil organic carbon (SOC) decomposition. Long-term SOC dynamics under intensified moisture extremes are studied using the MEND model that is parameterized with 11 years of measurements from the MOFLUX forest. The model explicitly represents microbial dormancy and resuscitation, different types of SOC-degrading enzymes, and how they vary with changes in soil moisture (Wang et al. 2015, 2019). A combination of two levels of frequency and severity of soil moisture, as well as a control with normal interannual variability, are used to simulate a range of moisture scenarios over 100 years. The code of Microbial-ENzyme Decomposition (MEND) as well as the input and output data are included in the archive. A user’s manual (MEND_Readme.pdf) is included with instructions for compiling and running the model to simulate soil organic carbon decomposition under various moisture scenarios. This dataset contains the modelling archive contained within a compressed (*.zip) file, a file-level metadata file in comma separate (*.csv) format, and two instructional files in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗

The soil health assessment protocol and evaluation applied to soil organic carbon

The concept of soil health has evolved over the past several decades, recognizing that dynamic soil property response to management and land use is highly dependent on site-specific factors that must be considered when interpreting soil health measurements. Initially, the Soil Management Assessment Framework (SMAF) and Comprehensive Assessment of Soil Health (CASH) were developed and used globally for scoring soil health indicators. However, both SMAF and CASH frameworks were developed using a relatively small dataset and their interpretation curves were not validated at the nationwide scale. Expanding upon these concepts, we propose the Soil Health Assessment Protocol and Evaluation (SHAPE) tool. The SHAPE was developed using 14,680 soil organic C (SOC) observations from across the United States, and accounts for edaphic and climate factors at the continental scale. Data were compiled from the literature, the Cornell Soil Health Laboratory, and the Kellogg Soil Survey Laboratory. In this approach, scoring curves are Bayesian model-based estimates of the conditional cumulative distribution function (CDF) for defined soil peer groups reflecting five soil texture and five soil suborder classes adjusted for mean annual temperature and precipitation. Specifically, SHAPE produces scores between 0 and 1 (0–100%) for measured SOC values that reflect the quantile or position within the conditional CDF along with measures of uncertainty. Herein, we focus on development of the SHAPE scoring curve for SOC with our case studies. SHAPE is a flexible, quantitative tool that provides a regionally relevant interpretation of this key soil health indicator.

54 ENVIRONMENTAL SCIENCES↗

Carbon content of soil fractions varies with season, rainfall, and soil fertility across a lowland tropical moist forest gradient

Tropical forests contain some of the largest soil carbon (C) stocks on Earth, making them broadly relevant to terrestrial-climate feedbacks, yet our understanding of how their soil organic C (SOC) fractions vary over space and time is limited. We studied effects of season, fertility, and mean annual precipitation (MAP) on the C contents of soil fractions across 14 lowland forests in Panama. We measured free-debris, occluded-debris, and mineral-associated SOC fractions, as well as soluble C associated with each fraction. We hypothesized that mineral-associated SOC would be greatest in infertile, strongly weathered soils with large reactive mineral contents. We also hypothesized that the debris SOC fractions would accumulate during the dry season, reflecting seasonal increases in litterfall. To address this, we compared soil fractions in wet and dry seasons from fertile and infertile soils across a range of 1809 – 2864 mm MAP. The C content (mg C / g soil) of all soil fractions varied with fertility and MAP: specifically, free-debris SOC was greatest in wet, high-fertility soils, and occluded-debris SOC was greater in high-fertility than low-fertility soils. The mineral-associated SOC fraction, which contained the majority of bulk soil C, showed increasing C content with greater MAP in infertile sites, presumably driving similar spatial patterns in the bulk soil. Only the free-debris SOC fraction showed strong seasonal variation, increasing in mass during the dry season. Nitrogen behaved similarly to C. In summary, soil C contents increased with MAP in infertile sites but not fertile sites, driven by the mineral-associated SOC fraction. The dry season had greater free-debris SOC, but this seasonal trend was not apparent in bulk soil C, likely because of the small size of the free-debris SOC fraction. Furthermore, changes in the quantity and seasonality of precipitation, which are projected for tropical forests, might shift spatial and temporal patterns of soil C storage, which would in turn influence forest-climate feedbacks for this C-rich biome.

54 ENVIRONMENTAL SCIENCES↗

Root carbon interation with soil minerals is dynamic, leaving a legacy of microbially derived residues

Minerals preserve the oldest most persistent soil carbon, and mineral characteristics appear to play a critical role in the formation of soil organic matter (SOM) associations. To test the hypothesis that carbon source and soil microorganisms also influence mineral-SOM associations, we incubated permeable minerals bags in soil microcosms with and without plants, in a 13CO2 labelling chamber. Mineral bags contained quartz, ferrihydrite, kaolinite, or native soil minerals isolated via density separation. Using 13C-NMR, FTICR-MS, and lipidomics, we traced plant-derived carbon onto minerals harvested from microcosms at three plant growth stages, characterizing total carbon, 13C enrichment, and SOM chemistry. While C accumulation was rapid and mineral-dependent, the accumulated amount was not significantly affected by the presence of plant roots. However, the rhizosphere did shape the chemistry of mineral-associated SOM. Minerals incubated in the rhizosphere were associated with a more diverse array of compounds with different C functional groups (carbonyl, aromatics, carbohydrates, lipids) than minerals incubated in a bulk soil control. These diverse rhizosphere-derived compounds may represent a “transient fraction” of mineral SOM, rapidly exchanging with mineral surfaces. Our results also suggest that many of the lipids which persist on minerals are microbially-derived with a large fraction of fungal lipids.

Rhizosphere, soil organic matter, grassland, 13C-N↗

Lignin lags, leads, or limits the decomposition of litter and soil organic carbon

Lignin’s role in litter and soil organic carbon (SOC) decomposition remains contentious. Lignin decomposition was traditionally thought to increase during midstage litter decomposition, when cellulose occlusion by lignin began to limit mass loss. Alternatively, lignin decomposition could be greatest in fresh litter as a consequence of co-metabolism, and lignin might decompose faster than bulk SOC. To test these competing hypotheses, we incubated 10 forest soils with C 4 grass litter (amended with 13 C-labeled or unlabeled lignin) over 2 yr and measured soil respiration and its isotope composition. Early lignin decomposition was greatest in 5 of 10 soils, consistent with the co-metabolism hypothesis. However, lignin decomposition peaked 6–24 months later in the other five soils, consistent with the substrate-limitation hypothesis; these soils were highly acidic. Rates of lignin, litter, and SOC decomposition tended to converge over time. Cumulative lignin decomposition was never greater than SOC decomposition; lignin decomposition was significantly lower than SOC decomposition in six soils. Net nitrogen mineralization predicted lignin decomposition ratios relative to litter and SOC. Although the onset of lignin decomposition can indeed be rapid, lignin still presents a likely bottleneck in litter and SOC decomposition, meriting a reconsideration of lignin’s role in modern decomposition paradigms.

54 ENVIRONMENTAL SCIENCES↗

A scalable framework for quantifying field-level agricultural carbon outcomes

Agriculture contributes nearly a quarter of global greenhouse gas (GHG) emissions, which is motivating interest in adopting certain farming practices that have the potential to reduce GHG emissions or sequester carbon in soil. The related GHG emission (including N 2 O and CH 4 ) and changes in soil carbon stock are defined here as “agricultural carbon outcomes”. Accurate quantification of agricultural carbon outcomes is the basis for achieving emission reductions for agriculture, but existing approaches for measuring carbon outcomes (including direct measurements, emission factors, and process-based modeling) fall short of achieving the required accuracy and scalability necessary to support credible, verifiable, and cost-effective measurement and improvement of these carbon outcomes. Here we propose a foundational and scalable framework to quantify field-level carbon outcomes for farmland, which is based on the holistic carbon balance of the agroecosystem: Agroecosystem Carbon Outcomes = Environment (E) × Management (M) × Crop (C). Following a comprehensive review of the scientific challenges associated with existing approaches, as well as their tradeoffs between cost and accuracy, we propose that the most viable path for the quantification of field-level carbon outcomes in agricultural land is through an effective integration of various approaches (e.g. diverse observations, sensor/in-situ data, and modeling), defined as the “System-of-Systems” solution. Such a “System-of-Systems” solution should simultaneously comprise the following components: (1) scalable collection of ground truth data and cross-scale sensing of environment variables (E), management practices (M), and crop conditions (C) at the local field level; (2) advanced modeling with necessary processes to support the quantification of carbon outcomes; (3) systematic Model-Data Fusion (MDF), i.e. robust and efficient methods to integrate sensing data and models at each local farmland level; (4) high computation efficiency and artificial intelligence (AI) to scale to millions of individual fields with low cost; and (5) robust and multi-tier validation systems and infrastructures to ensure solution fidelity and true scalability, i.e. the ability of a solution to perform robustly with accepted accuracy on all targeted fields. In this regard, we provide here the detailed scientific rationale, current progress, and future research and development (R&D) priorities to achieve different components of the “System-of-Systems” solution, thus accomplishing the Environment×Management×Crop framework to quantify field-level agricultural carbon outcomes.

54 ENVIRONMENTAL SCIENCES↗

Oxidation of soil organic carbon during an anoxic-oxic transition

Redox reactions of iron (Fe) can play an important role in controlling the stability and transformation of organic carbon (OC) in soils. However, there is limited knowledge about the dynamics of Fe and OC in soils during anoxic-oxic transitions, which are common in temperate and tropical biomes. In this study, we investigated the fate and transformation of Fe and OC during a 5-day oxic incubation of four pre-reduced (8 days anoxic) forest soils. Up to 3.7% of total OC in the pre-reduced soils was oxidized to CO 2 , in conjunction with the oxidation of 31 –84% of the extractable Fe(II). OC oxidation in pre-reduced soils was lower than non-reducedcontrol soils, indicating that recently anoxically-incubated soils support lower OC metabolism upon re-oxidation than consistently oxic soils. Oxic OC oxidation was negatively correlated with the fraction of Fe-bound OC and also the fraction of short-range-ordered (SRO) Fe oxides. These results suggest that association with Fe oxides—especially SRO Fe oxides—can inhibit the availability of OC for oxidation. However, the difference between the oxidation of OC in pre40 reduced soils and consistently oxic controls could not be linked to the moderate changes in the Fe mineral composition during the anoxic-oxic transition, indicating the importance of longer term OC association with Fe oxides, as well as other processes, in regulating the oxidation of OC during the redox fluctuations. OC association with Fe oxides should be considered during simulations of biogeochemical cycling of OC in soils during the redox fluctuations, for which other processes such as the anoxic transformation of OC and response of the microbial community also need to be incorporated.

58 GEOSCIENCES↗

The Deep Soil Organic Carbon Response to Global Change

Over 70% of soil organic carbon (SOC) is stored at a depth greater than 20 cm belowground. A portion of this deep SOC actively cycles on annual to decadal timescales and is sensitive to global change. However, deep SOC responses to global change likely differ from surface SOC responses because biotic controls on SOC cycling become weaker as mineral controls predominate with depth. Here, we synthesize the current information on deep SOC responses to the global change drivers of warming, shifting precipitation, elevated CO 2 , and land use and land cover change. Most deep SOC responses can only be hypothesized because few global change studies measure deep soils, and even fewer global change experiments manipulate deep soils. We call on scientists to incorporate deep soils into their manipulations, measurements, and models so that the response of deep SOC can be accounted for in projections of nature-based climate solutions and terrestrial feedbacks to climate change.

54 ENVIRONMENTAL SCIENCES↗

Convergence in simulating global soil organic carbon by structurally different models after data assimilation

Abstract Current biogeochemical models produce carbon–climate feedback projections with large uncertainties, often attributed to their structural differences when simulating soil organic carbon (SOC) dynamics worldwide. However, choices of model parameter values that quantify the strength and represent properties of different soil carbon cycle processes could also contribute to model simulation uncertainties. Here, we demonstrate the critical role of using common observational data in reducing model uncertainty in estimates of global SOC storage. Two structurally different models featuring distinctive carbon pools, decomposition kinetics, and carbon transfer pathways simulate opposite global SOC distributions with their customary parameter values yet converge to similar results after being informed by the same global SOC database using a data assimilation approach. The converged spatial SOC simulations result from similar simulations in key model components such as carbon transfer efficiency, baseline decomposition rate, and environmental effects on carbon fluxes by these two models after data assimilation. Moreover, data assimilation results suggest equally effective simulations of SOC using models following either first‐order or Michaelis–Menten kinetics at the global scale. Nevertheless, a wider range of data with high‐quality control and assurance are needed to further constrain SOC dynamics simulations and reduce unconstrained parameters. New sets of data, such as microbial genomics‐function relationships, may also suggest novel structures to account for in future model development. Overall, our results highlight the importance of observational data in informing model development and constraining model predictions.

54 ENVIRONMENTAL SCIENCES↗

Intensified Soil Moisture Extremes Decrease Soil Organic Carbon Decomposition: A Mechanistic Modeling Analysis

Earth system models have predicted that there will be more frequent and severe precipitation and drought events in terrestrial ecosystems. Microbially mediated decomposition of soil organic carbon (SOC) tends to increase as soils wet and decrease as soils dry. However, the long-term SOC change under intensified moisture extremes remains poorly known as it depends on the frequency and intensity of soil drying and wetting. In this study, we explored long-term SOC dynamics under scenarios of alternating drying-wetting cycles using the Microbial-ENzyme Decomposition model, a mechanistic microbial model. The model was parameterized with 11 years of observations from a temperate deciduous broadleaf forest site, showing satisfactory model performance in both model calibration (R 2 = 0.67) and validation (R 2 = 0.69) against heterotrophic respiration. We then used the model to simulate the long-term SOC dynamics under five scenarios of alternating drying-wetting cycles with different frequencies and severities over a period of 100 years. Results showed that the changes in active microbial biomass C and the corresponding turnover rates of SOC pools were more sensitive to soil drying than soil wetting. As a result, the cumulative soil carbon emission from microbial respiration decreased by 433.7 g C m -2 after the 100-year simulation in the highest frequency and intensity moisture scenario, but was not significantly affected by the lowest frequency and intensity scenario. This study emphasizes the nonlinear response of SOC decomposition to soil moisture changes, which causes decreased decomposition by microbes under drying that is, not compensated by increased decomposition under wetting conditions.

58 GEOSCIENCES↗