The water retention curve (WRC) and the hydraulic conductivity function (HCF) are key ingredients in most analytical and numerical models for flow and transport in unsaturated porous media. Despite ...their formal derivation for a representative elementary volume (REV) of soil complex pore spaces, these two hydraulic functions are rooted in pore-scale capillarity and viscous flows that, in turn, are invoked to provide interpretation of measurements and processes, such as linking WRC with the more difficult to measure HCF. Numerous conceptual and parametric models were proposed for the representation of processes within soil pore spaces and inferences concerning the two hydraulic functions (WRC and HCF) from surrogate variables. We review some of the primary models and highlight their physical basis, assumptions, advantages, and limitations. The first part focuses on the representation and modeling of WRC, including recent advances such as capillarity in angular pores and film adsorption and present empirical models based on easy to measure surrogate properties (pedotransfer functions). In the second part, we review the HCF and focus on widely used models that use WRC information to predict the saturated and unsaturated hydraulic conductivity. In the third part, we briefly review issues related to parameter equivalence between models, hysteresis in WRC, and effects of structural changes on hydraulic functions. Recent technological advances and monitoring networks offer opportunities for extensive hydrological information of high quality. The increase in measurement capabilities highlights the urgent need for building a hierarchy of parameters and model structures suitable for different modeling objectives and predictions across spatial scales. Additionally, the commonly assumed links between WRC and HCF must be reevaluated and involve more direct measurements of HCF. The modeling of flow and transport through structured and special porous media may require special functions and reflecting modifications in the governing equations. Finally, the impact of dynamics and transient processes at fluid interfaces on flow regimes and hydraulic properties necessitate different modeling and representation strategies beyond the present REV-based framework.
Microorganisms capable of biomineralization can catalyze mineral precipitation by modifying local physical and chemical conditions. In porous media, such as soil and rock, these microorganisms live ...and function in highly heterogeneous physical, chemical and ecological microenvironments, with strong local gradients created by both microbial activity and the pore-scale structure of the subsurface. Here, we focus on extracellular bacterial biomineralization, which is sensitive to external heterogeneity, and review the pore-scale processes controlling microbial biomineralization in natural and engineered porous media. We discuss how individual physical, chemical and ecological factors integrate to affect the spatial and temporal control of biomineralization, and how each of these factors contributes to a quantitative understanding of biomineralization in porous media. We find that an improved understanding of microbial behavior in heterogeneous microenvironments would promote understanding of natural systems and output in diverse technological applications, including improved representation and control of fluid mixing from pore to field scales. We suggest a range of directions by which future work can build from existing tools to advance each of these areas to improve understanding and predictability of biomineralization science and technology.
The formation of cracks and emergence of shearing planes and other modes of rapid macroscopic failure in geologic granular media involve numerous grain scale mechanical interactions often generating ...high frequency (kHz) elastic waves, referred to as acoustic emissions (AE). These acoustic signals have been used primarily for monitoring and characterizing fatigue and progressive failure in engineered systems, with only a few applications concerning geologic granular media reported in the literature. Similar to the monitoring of seismic events preceding an earthquake, AE may offer a means for non-invasive, in-situ, assessment of mechanical precursors associated with imminent landslides or other types of rapid mass movements (debris flows, rock falls, snow avalanches, glacier stick-slip events). Despite diverse applications and potential usefulness, a systematic description of the AE method and its relevance to mechanical processes in Earth sciences is lacking. This review is aimed at providing a sound foundation for linking observed AE with various micro-mechanical failure events in geologic granular materials, not only for monitoring of triggering events preceding mass mobilization, but also as a non-invasive tool in its own right for probing the rich spectrum of mechanical processes at scales ranging from a single grain to a hillslope. We review first studies reporting use of AE for monitoring of failure in various geologic materials, and describe AE generating source mechanisms in mechanically stressed geologic media (e.g., frictional sliding, micro-crackling, particle collisions, rupture of water bridges, etc.) including AE statistical features, such as frequency content and occurrence probabilities. We summarize available AE sensors and measurement principles. The high sampling rates of advanced AE systems enable detection of numerous discrete failure events within a volume and thus provide access to statistical descriptions of progressive collapse of systems with many interacting mechanical elements such as the fiber bundle model (FBM). We highlight intrinsic links between AE characteristics and established statistical models often used in structural engineering and material sciences, and outline potential applications for failure prediction and early-warning using the AE method in combination with the FBM. The biggest challenge to application of the AE method for field applications is strong signal attenuation. We provide an outlook for overcoming such limitations considering emergence of a class of fiber-optic based distributed AE sensors and deployment of acoustic waveguides as part of monitoring networks.
The metabolic diversity present in microbial communities enables cooperation toward accomplishing more complex tasks than possible by a single organism. Members of a consortium communicate by ...exchanging metabolites or signals that allow them to coordinate their activity through division of labor. In contrast with monocultures, evidence suggests that microbial consortia self-organize to form spatial patterns, such as observed in biofilms or in soil aggregates, that enable them to respond to gradient, to improve resource interception and to exchange metabolites more effectively. Current biotechnological applications of microorganisms remain rudimentary, often relying on genetically engineered monocultures (e.g., pharmaceuticals) or mixed-cultures of partially known composition (e.g., wastewater treatment), yet the vast potential of "microbial ecological power" observed in most natural environments, remains largely underused. In line with the Unified Microbiome Initiative (UMI) which aims to "discover and advance tools to understand and harness the capabilities of Earth's microbial ecosystems," we propose in this concept paper to capitalize on ecological insights into the spatial and modular design of interlinked microbial consortia that would overcome limitations of natural systems and attempt to optimize the functionality of the members and the performance of the engineered consortium. The topology of the spatial connections linking the various members and the regulated fluxes of media between those modules, while representing a major engineering challenge, would allow the microbial species to interact. The modularity of such spatially linked microbial consortia (SLMC) could facilitate the design of scalable bioprocesses that can be incorporated as parts of a larger biochemical network. By reducing the need for a compatible growth environment for all species simultaneously, SLMC will dramatically expand the range of possible combinations of microorganisms and their potential applications. We briefly review existing tools to engineer such assemblies and optimize potential benefits resulting from the collective activity of their members. Prospective microbial consortia and proposed spatial configurations will be illustrated and preliminary calculations highlighting the advantages of SLMC over co-cultures will be presented, followed by a discussion of challenges and opportunities for moving forward with some designs.
The reliable partitioning of the terrestrial latent heat flux into evaporation (E) and transpiration (T) is important for linking carbon and water cycles and for better understanding ecosystem ...functioning at local, regional and global scales. Previous research revealed that the transpiration-to-evapotranspiration ratio (T/ET) is well constrained across ecosystems and is nearly independent of vegetation characteristics and climate. Here we investigated the reasons for such a global constancy in present-day T/ET by jointly analysing observations and process-based model simulations. Using this framework, we also quantified how the ratio T/ET could be influenced by changing climate. For present conditions, we found that the various components of land surface evaporation (bare soil evaporation, below canopy soil evaporation, evaporation from interception), and their respective ratios to plant transpiration, depend largely on local climate and equilibrium vegetation properties. The systematic covariation between local vegetation characteristics and climate, resulted in a globally constrained value of T/ET = ∼70 9% for undisturbed ecosystems, nearly independent of specific climate and vegetation attributes. Moreover, changes in precipitation amounts and patterns, increasing air temperatures, atmospheric CO2 concentration, and specific leaf area (the ratio of leaf area per leaf mass) was found to affect T/ET in various manners. However, even extreme changes in the aforementioned factors did not significantly modify T/ET.
Identification of mechanisms that promote and maintain the immense microbial diversity found in soil is a central challenge for contemporary microbial ecology. Quantitative tools for systematic ...integration of complex biophysical and trophic processes at spatial scales, relevant for individual cell interactions, are essential for making progress. We report a modeling study of competing bacterial populations cohabiting soil surfaces subjected to highly dynamic hydration conditions. The model explicitly tracks growth, motion and life histories of individual bacterial cells on surfaces spanning dynamic aqueous networks that shape heterogeneous nutrient fields. The range of hydration conditions that confer physical advantages for rapidly growing species and support competitive exclusion is surprisingly narrow. The rapid fragmentation of soil aqueous phase under most natural conditions suppresses bacterial growth and cell dispersion, thereby balancing conditions experienced by competing populations with diverse physiological traits. In addition, hydration fluctuations intensify localized interactions that promote coexistence through disproportional effects within densely populated regions during dry periods. Consequently, bacterial population dynamics is affected well beyond responses predicted from equivalent and uniform hydration conditions. New insights on hydration dynamics could be considered in future designs of soil bioremediation activities, affect longevity of dry food products, and advance basic understanding of bacterial diversity dynamics and its role in global biogeochemical cycles.
Natural soil is characterized as a complex habitat with patchy hydrated islands and spatially variable nutrients that is in a constant state of change due to wetting-drying dynamics. Soil microbial ...activity is often concentrated in sparsely distributed hotspots that contribute disproportionally to macroscopic biogeochemical nutrient cycling and greenhouse gas emissions. The mechanistic representation of such dynamic hotspots requires new modeling approaches capable of representing the interplay between dynamic local conditions and the versatile microbial metabolic adaptations. We have developed IndiMeSH (Individual-based Metabolic network model for Soil Habitats) as a spatially explicit model for the physical and chemical microenvironments of soil, combined with an individual-based representation of bacterial motility and growth using adaptive metabolic networks. The model uses angular pore networks and a physically based description of the aqueous phase as a backbone for nutrient diffusion and bacterial dispersal combined with dynamic flux balance analysis to calculate growth rates depending on local nutrient conditions. To maximize computational efficiency, reduced scale metabolic networks are used for the simulation scenarios and evaluated strategically to the genome scale model. IndiMeSH was compared to a well-established population-based spatiotemporal metabolic network model (COMETS) and to experimental data of bacterial spatial organization in pore networks mimicking soil aggregates. IndiMeSH was then used to strategically study dynamic response of a bacterial community to abrupt environmental perturbations and the influence of habitat geometry and hydration conditions. Results illustrate that IndiMeSH is capable of representing trophic interactions among bacterial species, predicting the spatial organization and segregation of bacterial populations due to oxygen and carbon gradients, and provides insights into dynamic community responses as a consequence of environmental changes. The modular design of IndiMeSH and its implementation are adaptable, allowing it to represent a wide variety of experimental and in silico microbial systems.
Burrows resulting from earthworm activity are important for supporting various physical and ecological soil processes. Earthworm burrowing activity is quantified using models for earthworm ...penetration and cavity expansion that consider soil moisture and mechanical properties. Key parameters in these models are the maximal pressures exerted by the earthworm's hydroskeleton (estimated at 200 kPa). We designed a special pressure chamber that directly measures the pressures exerted by moving earthworms under different confining pressures to delineate the limits of earthworm activity in soils at different mechanical and hydration states. The chamber consists of a Plexiglas prism fitted with inner flexible tubing that hosts the earthworm. The gap around the tubing is pressurized using water, and the earthworm's peristaltic motion and concurrent pressure fluctuations were recorded by a camera and pressure transducer. A model that links the earthworm's kinematics with measured pressure fluctuations was developed. Resulting maximal values of radial pressures for anecic and endogeic earthworms were 130 kPa and 195 kPa, respectively. Mean earthworm peristaltic frequencies were used to quantify burrowing rates that were in agreement with previous results. The study delineates mechanical constraints to soil bioturbation by earthworms by mapping the elastic behaviour in the measurement chamber onto the expected elasto-viscoplastic environment of natural soils.
Abstract
Earth system models use soil information to parameterize hard-to-measure soil hydraulic properties based on pedotransfer functions. However, current parameterizations rely on sample-scale ...information which often does not account for biologically-promoted soil structure and heterogeneities in natural landscapes, which may significantly alter infiltration-runoff and other exchange processes at larger scales. Here we propose a systematic framework to incorporate soil structure corrections into pedotransfer functions, informed by remote-sensing vegetation metrics and local soil texture, and use numerical simulations to investigate their effects on spatially distributed and areal averaged infiltration-runoff partitioning. We demonstrate that small scale soil structure features prominently alter the hydrologic response emerging at larger scales and that upscaled parameterizations must consider spatial correlations between vegetation and soil texture. The proposed framework allows the incorporation of hydrological effects of soil structure with appropriate scale considerations into contemporary pedotransfer functions used for land surface parameterization.
Moisture content is a critical variable for the harvesting, processing, storing and marketing of cereal grains, oilseeds and legumes. Efficient and accurate determination of grain moisture content ...even with advanced nondestructive techniques, remains a challenge due to complex water-retaining biological structures and hierarchical composition and geometry of grains that affect measurement interpretation and require specific grain-dependent calibration. We review (1) the primary factors affecting permittivity measurements used in practice for inferring moisture content in grains; (2) develop novel methods for estimating critical parameters for permittivity modeling including packing density, porosity, water binding surface area and water phase permittivity and (3) represent the permittivity of packs of grains using dielectric mixture theory as a function of moisture content applied to high moisture corn (as a model grain). Grain permittivity measurements are affected by their free and bound water contents, chemical composition, temperature, constituent shape, phase configuration and measurement frequency. A large fraction of grain water is bound exhibiting reduced permittivity compared to that of free water. The reduced mixture permittivity and attributed to hydrophilic surfaces in starches, proteins and other high surface area grain constituents. The hierarchal grain structure (i.e., kernel, starch grain, lamella, molecule) and the different constituents influence permittivity measurements due to their layering, geometry (i.e., kernel or starch grain), configuration and water-binding surface area. Dielectric mixture theory offers a physically-based approach for modeling permittivity of agricultural grains and similar granular media.
PDF
