Dennis E. Rolston

Responses of soil microbial processes and community structure to tillage events and implications for soil quality

The short-term responses of soil microbial processes and community structure to perturbation constitute one aspect of soil quality. Such responses are often associated with an increase in the emissions of greenhouse gases (i.e., CO2, NO, or N2O) and the accumulation and potential loss of nitrate by leaching. Here we describe our recent work on responses of soil carbon and nitrogen dynamics, microbial biomass, and microbial community structure to a tillage event in intensively managed vegetable crop systems in California. Our results indicate that CO2 emission is high for the first day after tillage, but respiration declines or remains constant, suggesting that physical processes are responsible for the high flux from the soil surface. Net mineralization and nitrate accumulation increase for several days after tillage, and this can be accompanied by higher denitrification rates. Tillage causes immediate changes in microbial community structure, based on phospholipid fatty acid (PLFA) analysis, but little concomitant change in total microbial biomass. Tillage events contribute to decreased soil quality by increasing emissions of greenhouse gases, and increasing the potential for nitrate leaching to groundwater, and these negative aspects must be weighed against the benefits of tillage for increasing the health and productivity of some crops. D 2003 Elsevier Science B.V. All rights reserved.

Microbial responses to simulated tillage in cultivated and uncultivated soils

Tillage is known to have long-term eAects on organic matter and labile pools of nutrients in soil, but the short-term changes in microbial dynamics and activity after tillage are less well understood. We investigated the immediate eAects of simulated tillage on microbial community structure as determined by phospholipid fatty acid (PLFA) profiles, microbial activity, and carbon (C) and nitrogen (N) pools. Intact cores were obtained from Chualar sandy loam soils under grassland and vegetable production. The top 15 cm of soil was sieved to simulate tillage, then the cores were incubated in the greenhouse. Sampling took place 1 day before the tillage simulation and throughout the next 2 weeks. In the grassland soil, multivariate analysis showed changes in PLFA profiles within hours, indicating rapid changes in microbial community structure. Specific PLFA markers indicated a reduction in microeukaryotic biomass as well as an increase in a microbial stress marker after sieving. Respiration (as determined by soil incubation in sealed containers) decreased immediately after sieving and continued to decline through the next 14 days. Sieving was followed by a continuous accumulation of nitrate. In the vegetable soil, the changes in PLFA profiles were slow and gradual. The PLFA stress indicator rose only slightly. Microbial activity and biomass were low, and only small changes occurred in most variables. A decline in respiration and an increase in nitrate occurred several days after sieving. In both soils, decreased soil moisture may have contributed to changes in soil responses after sieving. Short-term responses to tillage may be less pronounced in soils with a long history of cultivation because of a relatively resilient microbial community and/or because lower initial microbial biomass and nutrient pools preclude a strong response to disturbance. 7 2000 Elsevier Science Ltd. All rights reserved.

Relations Between Specific Surface Area and Soil Physical and Chemical Properties

The total specific surface area (SA) is a factor that can relate grain-scale properties to macro-scale physical and chemical properties of a porous medium. It is, therefore, advantageous to establish the relationships between SA and general soil physical properties. In this study we investigated

Modeling diffusion and reaction in soils : IX. The Buckingham-Burdine-Campbell equation for gas diffusivity in undisturbed soil

Accurate description of gas diffusivity (ratio of gas diffusion coefficients in soil and free air, D s /D 0 ) in undisturbed soils is a prerequisite for predicting in situ transport and fate of volatile organic chemicals and greenhouse gases. Reference point gas diffusivities (R p ) in completely dry soil were estimated for 20 undisturbed soils by assuming a power function relation between gas diffusivity and air-filled porosity (e). Among the classical gas diffusivity models, the Buckingham (1904) expression, equal to the soil total porosity squared, best described R p . Inasmuch as our previous works (Parts III, VII, VIII) implied a soil-type dependency of D s /D 0 (e) in undisturbed soils, the Buckingham R p expression was inserted in two soil- type-dependent D s /D 0 (e) models. One D s /D 0 (e) model is a function of pore-size distribution (the Campbell water retention parameter used in a modified Burdine capillary tube model), and the other is a calibrated, empirical function of soil texture (silt + sand fraction). Both the Buckingham-Burdine-Campbell (BBC) and the Buckingham/soil texture-based D s /D 0 (e) models described well the observed soil type effects on gas diffusivity and gave improved predictions compared with soil type independent models when tested against an independent data set for six undisturbed surface soils (11-46% clay). This study emphasizes that simple but soil-type-dependent power function D s /D 0 (e) models can adequately describe and predict gas diffusivity in undisturbed soil. We recommend the new BBC model as basis for modeling gas transport and reactions in undisturbed soil systems.

Modeling Diffusion and Reaction in Soils: VII. Predicting Gas and Ion Diffusivity in Undisturbed and Sieved Soils

The classical Penman (1940) and Millington-Quirk (1960, 1961) diffusivity models were transformed into general form by introducing a tortuosity parameter, m. Compared with measured diffusivities close to phase saturation (soil-water and soil-air saturation for ion and gas diffusivity, respectively), the Penman (1940) model was superior to the Millington-Quirk models independent of diffusion type. The combined use of the Penman model to predict the diffusivity at phase saturation together with a general Millington-Quirk model to predict relative decrease in diffusivity with decreasing phase content was labeled the Penman-Millington-Quirk (PMQ) model. The best fit of the new PMQ model to measured data was obtained with m = 3 (high tortuosity) and m = 6 (medium tortuosity) for gas diffusivity in undisturbed and sieved soils, respectively, and m = 1 (high tortuosity) for ion diffusivity. Measurements did not suggest a significant difference between ion diffusivity in undisturbed, sieved, or aggregated soils. The differences in m-values between diffusion types are likely caused by different diffusion pathways and geometries for ion and gas diffusivity as well as a large effect of soil heterogeneity and spatial variability on gas diffusivity. The PMQ model predicted gas diffusivity in sieved and undisturbed soil well, but a soil-type dependent model (Part IV ofthis series) was superior for predicting ion diffusivity. The new models seem promising for more accurately predicting gas and ion diffusion and, therefore, for improving simulations of diffusion-constrained chemical and biological reactions in soils.

Modeling diffusion and reaction in soils : I. A diffusion and reaction corrected finite difference calculation scheme

Numerically accurate calculation of stimultaneous diffusion and reaction in soil systems is a prerequisite for realistic model simulations of diffusion-controlled chemical fate processes and analysis of experimental data. Recent studies have shown that the inclusion of a first-order reaction term in

Nitric and nitrous oxide emissions following fertilizer application to agricultural soil: Biotic and abiotic mechanisms and kinetics

Emissions of nitric and nitrous oxide (NO and N2O) from agricultural soils may have several consequences, including impacts on local tropospheric and global stratospheric chemistry. Elevated NO and N2O emissions following application of anhydrous ammonia to an agricultural field in California were driven by the biological generation of nitrite (NO2−) and subsequent abiotic decomposition of nitrous acid (HNO2). Maximum fluxes of > 1000 ng NO-N cm−2 h−1 and > 400 ng N2O-N cm−2 h−1 were observed, and emissions of > 100 ng NO-N cm−2 h−1 and > 50 ng N2O-N cm−2 h−1 persisted for >4 weeks. Laboratory experiments were performed to determine rate coefficients and activation energies for HNO2-mediated NO and N2O production. Kinetic parameters describing the conversion of NO to N2O were measured and were found to vary with water-filled pore space (WFPS). Regression models incorporating HNO2, WFPS, and temperature accounted for 75–77% of the variability in field fluxes. A previously developed NO emissions model was modified to incorporate a kinetic expression for HNO2- and temperature-dependent production. The model tended to underestimate fluxes under low-flux conditions and overestimate fluxes under high-flux conditions. These data indicate that (1) control of acidity may be an effective means for minimizing gaseous N losses from fertilized soils and possibly for improving air quality in rural areas, (2) the transformation of HNO2-derived NO may be an important mechanism of N2O production even under relatively aerobic conditions, and (3) mechanistic models which account for spatial heterogeneity and transient conditions may be required to better predict field NO fluxes.

Modeling diffusion and reaction in soils. III. Predicting gas diffusivity from the campbell soil-water retention model

Improved prediction of gas diffusivity in soils is essential to the development of better gas transport and fate models. Empirical equations analogous to three well known capillary tube models for unsaturated hydraulic conductivity, based on the Campbell soil-water retention function, were used to p

Reduction of Perchlorate and Nitrate by Microbial Communities in Vadose Soil

ABSTRACT Perchlorate contamination is a concern because of the increasing frequency of its detection in soils and groundwater and its presumed inhibitory effect on human thyroid hormone production. Although significant perchlorate contamination occurs in the vadose (unsaturated) zone, little is known about perchlorate biodegradation potential by indigenous microorganisms in these soils. We measured the effects of electron donor (acetate and hydrogen) and nitrate addition on perchlorate reduction rates and microbial community composition in microcosm incubations of vadose soil. Acetate and hydrogen addition enhanced perchlorate reduction, and a longer lag period was observed for hydrogen (41 days) than for acetate (14 days). Initially, nitrate suppressed perchlorate reduction, but once perchlorate started to be degraded, the process was stimulated by nitrate. Changes in the bacterial community composition were observed in microcosms enriched with perchlorate and either acetate or hydrogen. Denaturing gradient gel electrophoresis analysis and partial sequencing of 16S rRNA genes recovered from these microcosms indicated that formerly reported perchlorate-reducing bacteria were present in the soil and that microbial community compositions were different between acetate- and hydrogen-amended microcosms. These results indicate that there is potential for perchlorate bioremediation by native microbial communities in vadose soil.

MODELING DIFFUSION AND REACTION IN SOILS: X. A UNIFYING MODEL FOR SOLUTE AND GAS DIFFUSIVITY IN UNSATURATED SOIL

Diffusion processes in the soil water and air phases often govern transport and fate of nutrients, pesticides, and toxic chemicals in the vadose zone. This final paper in a 10-part series on diffusion-reaction processes in soils concerns the development of a unifying model platform for predicting solute and gas diffusion coefficients as functions of fluid-phase (water or air) content and pore-size distribution in unsaturated soils. We find that the Buckingham (1904) expression predicts solute diffusivities in water-saturated porous media more accurately than other classical expressions and, extended with a pore-size distribution-based term, yields a new and accurate model for solute diffusivity in unsaturated soil. The same was shown for gas diffusivity in undisturbed soil in Part IX of this series. Thus, the predictive diffusivity models can be rewritten in a common form with two model parameters that vary between solute and gas diffusivity and, in the case of gas diffusivity, also between undisturbed and repacked soil. It is suggested that the two parameters in this unified diffusivity model (UDM) represent porous media (solids-induced) tortuosity (T) and water-induced fluid phase disconnectivity (W), respectively, with W increasing with clay content for solute diffusion but being constant (repacked soil) or decreasing (undisturbed soil) for gas diffusion. Tested against data for 77 soils, the UDM model was markedly more accurate than commonly used soil-type independent models, with 35–50% (gas diffusivity) and 75% (solute diffusivity) reduction in root mean square error of prediction. The use of the new UDM to predict effective diffusion of sorbing chemicals in the soil water and air phases is illustrated. The UDM concept enables a new definition of the relative diffusion coefficient in soil, i.e. relative to the diffusion coefficient in a fluid-saturated porous media instead of in free water or air. This provides new possibilities for analyzing tortuosity phenomena in the soil water and air phases and their effects on diffusive and convective transport parameters in unsaturated soil.