Building soil sustainability from root-soil interface traits.

Great potential exists to harness plant traits at the root-soil interface, mainly rhizodeposition and root hairs, to 'build' soils with better structure that can trap more carbon and resources, resist climate stresses, and promote a healthy microbiome. These traits appear to have been preserved in modern crop varieties, but scope exists to improve them further because they vary considerably between genotypes and respond to environmental conditions. From emerging evidence, rhizodeposition can act as a disperser, aggregator, and/or hydrogel in soil, and root hairs expand rhizosheath size. Future research should explore impacts of selecting these traits on plants and soils concurrently, expanding from model plants to commercial genotypes, and observing whether impacts currently limited to glasshouse studies occur in the field.

Three-Dimensional Study of F. graminearum Colonisation of Stored Wheat: Post-Harvest Growth Patterns, Dry Matter Losses and Mycotoxin Contamination.

Fusarium causes significant post-harvest quality losses and mycotoxin contamination in stored wheat but the colonisation dynamics of the grain and how this may be affected by the initial inoculum position in the grain mass is poorly understood. This study examined the 3D growth kinetics and mycotoxin production (deoxynivalenol and zearalenone) by F. graminearum during hyphal colonisation from different initial inoculum positions in wheat microcosms (top-centre, bottom-centre, and bottom-side) maintained at two water activities (aw; 0.95 and 0.97). Clear jars were used to visually follow the colonisation dynamics. Fungal respiration and associated dry matter loss (DML) and ergosterol were also quantified. Colonisation dynamics was shown to be affected by the inoculation position. At the end of the colonisation process, fungal respiration and DML were driven by the inoculation position, and the latter also by the prevailing aw. Fungal biomass (ergosterol) was mainly affected by the aw. The initial inoculum position did not affect the relative mycotoxin production. There was a positive correlation between respiration and ergosterol, and between mycotoxin production and colonisation indicators. We suggest that spatially explicit predictive models can be used to better understand the colonisation patterns and mycotoxin contamination of stored cereal commodities and to aid more effective post-harvest management.

Soil aggregates as biogeochemical reactors: Not a way forward in the research on soil-atmosphere exchange of greenhouse gases.

The goal of this comment is to show that the "aggregate reactor" framework recently proposed in an article published in this journal is severely limited by two kinds of indeterminacy. The first is related to the size of aggregates, which is not defined precisely. The second issue is with the impossibility to replicate boundary conditions that are identical to what chunks of soils would have experienced in their natural state. We suggest that the study of GHG release in undisturbed soil samples is a better way to proceed forward.

Emergent Properties of Microbial Activity in Heterogeneous Soil Microenvironments: Different Research Approaches Are Slowly Converging, Yet Major Challenges Remain.

Over the last 60 years, soil microbiologists have accumulated a wealth of experimental data showing that the bulk, macroscopic parameters (e.g., granulometry, pH, soil organic matter, and biomass contents) commonly used to characterize soils provide insufficient information to describe quantitatively the activity of soil microorganisms and some of its outcomes, like the emission of greenhouse gasses. Clearly, new, more appropriate macroscopic parameters are needed, which reflect better the spatial heterogeneity of soils at the microscale (i.e., the pore scale) that is commensurate with the habitat of many microorganisms. For a long time, spectroscopic and microscopic tools were lacking to quantify processes at that scale, but major technological advances over the last 15 years have made suitable equipment available to researchers. In this context, the objective of the present article is to review progress achieved to date in the significant research program that has ensued. This program can be rationalized as a sequence of steps, namely the quantification and modeling of the physical-, (bio)chemical-, and microbiological properties of soils, the integration of these different perspectives into a unified theory, its upscaling to the macroscopic scale, and, eventually, the development of new approaches to measure macroscopic soil characteristics. At this stage, significant progress has been achieved on the physical front, and to a lesser extent on the (bio)chemical one as well, both in terms of experiments and modeling. With regard to the microbial aspects, although a lot of work has been devoted to the modeling of bacterial and fungal activity in soils at the pore scale, the appropriateness of model assumptions cannot be readily assessed because of the scarcity of relevant experimental data. For significant progress to be made, it is crucial to make sure that research on the microbial components of soil systems does not keep lagging behind the work on the physical and (bio)chemical characteristics. Concerning the subsequent steps in the program, very little integration of the various disciplinary perspectives has occurred so far, and, as a result, researchers have not yet been able to tackle the scaling up to the macroscopic level. Many challenges, some of them daunting, remain on the path ahead. Fortunately, a number of these challenges may be resolved by brand new measuring equipment that will become commercially available in the very near future.

Microscale Heterogeneity of the Spatial Distribution of Organic Matter Can Promote Bacterial Biodiversity in Soils: Insights From Computer Simulations.

There is still no satisfactory understanding of the factors that enable soil microbial populations to be as highly biodiverse as they are. The present article explores in silico the hypothesis that the heterogeneous distribution of soil organic matter, in addition to the spatial connectivity of the soil moisture, might account for the observed microbial biodiversity in soils. A multi-species, individual-based, pore-scale model is developed and parameterized with data from 3 Arthrobacter sp. strains, known to be, respectively, competitive, versatile, and poorly competitive. In the simulations, bacteria of each strain are distributed in a 3D computed tomography (CT) image of a real soil and three water saturation levels (100, 50, and 25%) and spatial heterogeneity levels (high, intermediate, and low) in the distribution of the soil organic matter are considered. High and intermediate heterogeneity levels assume, respectively, an amount of particulate organic matter (POM) distributed in a single (high heterogeneity) or in four (intermediate heterogeneity) randomly placed fragments. POM is hydrolyzed at a constant rate following a first-order kinetic, and continuously delivers dissolved organic carbon (DOC) into the liquid phase, where it is then taken up by bacteria. The low heterogeneity level assumes that the food source is available from the start as DOC. Unlike the relative abundances of the 3 strains, the total bacterial biomass and respiration are similar under the high and intermediate resource heterogeneity schemes. The key result of the simulations is that spatial heterogeneity in the distribution of organic matter influences the maintenance of bacterial biodiversity. The least competing strain, which does not reach noticeable growth for the low and intermediate spatial heterogeneities of resource distribution, can grow appreciably and even become more abundant than the other strains in the absence of direct competition, if the placement of the resource is favorable. For geodesic distances exceeding 5 mm, microbial colonies cannot grow. These conclusions are conditioned by assumptions made in the model, yet they suggest that microscale factors need to be considered to better understand the root causes of the high biodiversity of soils.

Toward Modeling the Resistance and Resilience of "Below-ground" Fungal Communities: A Mechanistic and Trait-Based Approach.

The role of fungi in shaping ecosystems is well evidenced and there is growing recognition of their importance among scientists and the general public. Establishing and separating the role of key local (soil chemical, biological, and physical properties) and global (climate, dispersal limitation) drivers in fungal community structure and functioning is currently a source of frustration to mycologists. The quest to determine niche processes and environmental characteristics shaping fungal community structure, known to be important for plant and animal communities, is proving difficult, resulting in the acknowledgment that niche neutral processes (climate, dispersal limitations) may dominate. The search for predictable patterns in fungal community structure may have been restricted as the "appropriate" scales at which to measure community structure and characterize the environment have not been fully determined yet, and the focus on taxonomy makes it difficult to link environmental characteristics to fungal traits. While key determinants of microbial community composition have been uncovered for some functional groups, the differential response of functional groups is largely unknown. Before we can truly understand what drives the development of microbial community structure, an understanding of the autecology of major fungal taxa and how they interact with their immediate environment (from the micro- up to kilometer scale) is urgently needed. Furthermore, key information and empirical data is missing at the microscale due to experimental difficulties in mapping this heterogeneous and opaque environment. We therefore present a framework that would help generate this much-needed empirical data and information at the microscale, together with modeling approaches to link the spatial and temporal scales. The latter is important as we propose that there is much to be gained by linking our understanding of fungal community responses across scales, in order to develop species and community-environment-function predictive models.

Three-Dimensional Mapping of Soil Chemical Characteristics at Micrometric Scale by Combining 2D SEM-EDX Data and 3D X-Ray CT Images.

There is currently a significant need to improve our understanding of the factors that control a number of critical soil processes by integrating physical, chemical and biological measurements on soils at microscopic scales to help produce 3D maps of the related properties. Because of technological limitations, most chemical and biological measurements can be carried out only on exposed soil surfaces or 2-dimensional cuts through soil samples. Methods need to be developed to produce 3D maps of soil properties based on spatial sequences of 2D maps. In this general context, the objective of the research described here was to develop a method to generate 3D maps of soil chemical properties at the microscale by combining 2D SEM-EDX data with 3D X-ray computed tomography images. A statistical approach using the regression tree method and ordinary kriging applied to the residuals was developed and applied to predict the 3D spatial distribution of carbon, silicon, iron, and oxygen at the microscale. The spatial correlation between the X-ray grayscale intensities and the chemical maps made it possible to use a regression-tree model as an initial step to predict the 3D chemical composition. For chemical elements, e.g., iron, that are sparsely distributed in a soil sample, the regression-tree model provides a good prediction, explaining as much as 90% of the variability in some of the data. However, for chemical elements that are more homogenously distributed, such as carbon, silicon, or oxygen, the additional kriging of the regression tree residuals improved significantly the prediction with an increase in the R2 value from 0.221 to 0.324 for carbon, 0.312 to 0.423 for silicon, and 0.218 to 0.374 for oxygen, respectively. The present research develops for the first time an integrated experimental and theoretical framework, which combines geostatistical methods with imaging techniques to unveil the 3-D chemical structure of soil at very fine scales. The methodology presented in this study can be easily adapted and applied to other types of data such as bacterial or fungal population densities for the 3D characterization of microbial distribution.

Microscale heterogeneity explains experimental variability and non-linearity in soil organic matter mineralisation.

Soil respiration represents the second largest CO2 flux from terrestrial ecosystems to the atmosphere, and a small rise could significantly contribute to further increase in atmospheric CO2. Unfortunately, the extent of this effect cannot be quantified reliably, and the outcomes of experiments designed to study soil respiration remain notoriously unpredictable. In this context, the mathematical simulations described in this article suggest that assumptions of linearity and presumed irrelevance of micro-scale heterogeneity, commonly made in quantitative models of microbial growth in subsurface environments and used in carbon stock models, do not appear warranted. Results indicate that microbial growth is non-linear and, at given average nutrient concentrations, strongly dependent on the microscale distribution of both nutrients and microbes. These observations have far-reaching consequences, in terms of both experiments and theory. They indicate that traditional, macroscopic soil measurements are inadequate to predict microbial responses, in particular to rising temperature conditions, and that an explicit account is required of microscale heterogeneity. Furthermore, models should evolve beyond traditional, but overly simplistic, assumptions of linearity of microbial responses to bulk nutrient concentrations. The development of a new generation of models along these lines, and in particular incorporating upscaled information about microscale processes, will undoubtedly be challenging, but appears to be key to understanding the extent to which soil carbon mineralization could further accelerate climate change.

Transparent soil microcosms allow 3D spatial quantification of soil microbiological processes in vivo.

The recently developed transparent soil consists of particles of Nafion, a polymer with a low refractive index (RI), which is prepared by milling and chemical treatment for use as a soil analog. After the addition of a RI-matched solution, confocal imaging can be carried out in vivo and without destructive sampling. In a previous study, we showed that the new substrate provides a good approximation of plant growth conditions found in natural soils. In this paper, we present further development of the techniques for detailed quantitative analysis of images of root-microbe interactions in situ. Using this system it was possible for the first time to analyze bacterial distribution along the roots and in the bulk substrate in vivo. These findings indicate that the coupling of transparent soil with light microscopy is an important advance toward the discovery of the mechanisms of microbial colonisation of the rhizosphere.

The role of the natural environment in the emergence of antibiotic resistance in gram-negative bacteria.

During the past 10 years, multidrug-resistant Gram-negative Enterobacteriaceae have become a substantial challenge to infection control. It has been suggested by clinicians that the effectiveness of antibiotics is in such rapid decline that, depending on the pathogen concerned, their future utility can be measured in decades or even years. Unless the rise in antibiotic resistance can be reversed, we can expect to see a substantial rise in incurable infection and fatality in both developed and developing regions. Antibiotic resistance develops through complex interactions, with resistance arising by de-novo mutation under clinical antibiotic selection or frequently by acquisition of mobile genes that have evolved over time in bacteria in the environment. The reservoir of resistance genes in the environment is due to a mix of naturally occurring resistance and those present in animal and human waste and the selective effects of pollutants, which can co-select for mobile genetic elements carrying multiple resistant genes. Less attention has been given to how anthropogenic activity might be causing evolution of antibiotic resistance in the environment. Although the economics of the pharmaceutical industry continue to restrict investment in novel biomedical responses, action must be taken to avoid the conjunction of factors that promote evolution and spread of antibiotic resistance.

Transparent soil for imaging the rhizosphere.

Understanding of soil processes is essential for addressing the global issues of food security, disease transmission and climate change. However, techniques for observing soil biology are lacking. We present a heterogeneous, porous, transparent substrate for in situ 3D imaging of living plants and root-associated microorganisms using particles of the transparent polymer, Nafion, and a solution with matching optical properties. Minerals and fluorescent dyes were adsorbed onto the Nafion particles for nutrient supply and imaging of pore size and geometry. Plant growth in transparent soil was similar to that in soil. We imaged colonization of lettuce roots by the human bacterial pathogen Escherichia coli O157:H7 showing micro-colony development. Micro-colonies may contribute to bacterial survival in soil. Transparent soil has applications in root biology, crop genetics and soil microbiology.

Applications of percolation theory to fungal spread with synergy.

There is increasing interest in the use of the percolation paradigm to analyse and predict the progress of disease spreading in spatially structured populations of animals and plants. The wider utility of the approach has been limited, however, by several restrictive assumptions, foremost of which is a strict requirement for simple nearest-neighbour transmission, in which the disease history of an individual is influenced only by that of its neighbours. In a recent paper, the percolation paradigm has been generalized to incorporate synergistic interactions in host infectivity and susceptibility, and the impact of these interactions on the invasive dynamics of an epidemic has been demonstrated. In the current paper, we elicit evidence that such synergistic interactions may underlie transmission dynamics in real-world systems by first formulating a model for the spread of a ubiquitous parasitic and saprotrophic fungus through replicated populations of nutrient sites and subsequently fitting and testing the model using data from experimental microcosms. Using Bayesian computational methods for model fitting, we demonstrate that synergistic interactions are necessary to explain the dynamics observed in the replicate experiments. The broader implications of this work in identifying disease-control strategies that deflect epidemics from invasive to non-invasive regimes are discussed.

The effect of heterogeneity on invasion in spatial epidemics: from theory to experimental evidence in a model system.

Heterogeneity in host populations is an important factor affecting the ability of a pathogen to invade, yet the quantitative investigation of its effects on epidemic spread is still an open problem. In this paper, we test recent theoretical results, which extend the established "percolation paradigm" to the spread of a pathogen in discrete heterogeneous host populations. In particular, we test the hypothesis that the probability of epidemic invasion decreases when host heterogeneity is increased. We use replicated experimental microcosms, in which the ubiquitous pathogenic fungus Rhizoctonia solani grows through a population of discrete nutrient sites on a lattice, with nutrient sites representing hosts. The degree of host heterogeneity within different populations is adjusted by changing the proportion and the nutrient concentration of nutrient sites. The experimental data are analysed via Bayesian inference methods, estimating pathogen transmission parameters for each individual population. We find a significant, negative correlation between heterogeneity and the probability of pathogen invasion, thereby validating the theory. The value of the correlation is also in remarkably good agreement with the theoretical predictions. We briefly discuss how our results can be exploited in the design and implementation of disease control strategies.

Fungal colonization in soils with different management histories: modeling growth in three-dimensional pore volumes.

Despite the importance of fungi in soil functioning they have received comparatively little attention, and our understanding of fungal interactions and communities is lacking. This study aims to combine a physiologically based model of fungal growth with digitized images of internal pore volume of samples of undisturbed soil from contrasting management practices to determine the effect of physical structure on fungal growth dynamics. We quantified pore geometries of the undisturbed-soil samples from two contrasting agricultural practices, conventionally plowed (chisel plow) (CT) and no till (NT), and from native-species vegetation land use on land that was taken out of production in 1989 (NS). Then we modeled invasion of a fungal species within the soil samples and evaluated the role of soil structure on the progress of fungal colonization of the soil pore space. The size of the studied pores was > or =110 microm. The dynamics of fungal invasion was quantified through parameters of a mathematical model fitted to the fungal invasion curves. Results indicated that NT had substantially lower porosity and connectivity than CT and NS soils. For example, the largest connected pore volume occupied 79% and 88% of pore space in CT and NS treatments, respectively, while it only occupied 45% in NT. Likewise, the proportion of pore space available to fungal colonization was much greater in NS and CT than in NT treatment, and the dynamics of the fungal invasion differed among the treatments. The relative rate of fungal invasion at the onset of simulation was higher in NT samples, while the invasion followed a more sigmoidal pattern with relatively slow invasion rates at the initial time steps in NS and CT samples. Simulations allowed us to elucidate the contribution of physical structure to the rates and magnitudes of fungal invasion processes. It appeared that fragmented pore space disadvantaged fungal invasion in soils under long-term no-till, while large connected pores in soils under native vegetation or in tilled agriculture promoted the invasion.

Environmental modification and niche construction: developing O2 gradients drive the evolution of the Wrinkly Spreader.

The evolutionary success of the novel Wrinkly Spreader (WS) genotypes in diversifying Pseudomonas fluorescens SBW25 populations in static liquid microcosms has been attributed to the greater availability of O(2) at the air-liquid (A-L) interface where the WS produces a physically cohesive-class biofilm. However, the importance of O(2) gradients in SBW25 adaptation has never been examined. We have explicitly tested the role of O(2) in evolving populations using microsensor profiling and experiments conducted under high and low O(2) conditions. Initial colonists of static microcosms were found to establish O(2) gradients before significant population growth had occurred, converting a previously homogenous environment into one containing a resource continuum with high and low O(2) regions. These gradients were found to persist for long periods by which time significant numbers of WS had appeared colonising the high O(2) niches. Growth was O(2) limited in static microcosms, but high O(2) conditions like those found near the A-L interface supported greater growth and favoured the emergence of WS-like genotypes. A fitness advantage to biofilm formation was seen under high but not low O(2) conditions, suggesting that the cost of biofilm production could only be offset when O(2) levels above the A-L interface were high. Profiling of mature WS biofilms showed that they also contained high and low O(2) regions. Niches within these may support further diversification and succession of the developing biofilm population. O(2) availability has been found to be a major factor underlying the evolutionary success of the WS genotype in static microcosms and illustrates the importance of this resource continuum in microbial diversification and adaptation.

Estimation of multiple transmission rates for epidemics in heterogeneous populations.

One of the principal challenges in epidemiological modeling is to parameterize models with realistic estimates for transmission rates in order to analyze strategies for control and to predict disease outcomes. Using a combination of replicated experiments, Bayesian statistical inference, and stochastic modeling, we introduce and illustrate a strategy to estimate transmission parameters for the spread of infection through a two-phase mosaic, comprising favorable and unfavorable hosts. We focus on epidemics with local dispersal and formulate a spatially explicit, stochastic set of transition probabilities using a percolation paradigm for a susceptible-infected (S-I) epidemiological model. The S-I percolation model is further generalized to allow for multiple sources of infection including external inoculum and host-to-host infection. We fit the model using Bayesian inference and Markov chain Monte Carlo simulation to successive snapshots of damping-off disease spreading through replicated plant populations that differ in relative proportions of favorable and unfavorable hosts and with time-varying rates of transmission. Epidemiologically plausible parametric forms for these transmission rates are compared by using the deviance information criterion. Our results show that there are four transmission rates for a two-phase system, corresponding to each combination of infected donor and susceptible recipient. Knowing the number and magnitudes of the transmission rates allows the dominant pathways for transmission in a heterogeneous population to be identified. Finally, we show how failure to allow for multiple transmission rates can overestimate or underestimate the rate of spread of epidemics in heterogeneous environments, which could lead to marked failure or inefficiency of control strategies.

Empirical evidence of spatial thresholds to control invasion of fungal parasites and saprotrophs.

• The ability to forecast invasion of harmful and beneficial organisms is becoming increasingly important in agricultural and horticultural production systems as well as in natural plant communities. • In this paper we examine the spread of a fungus through a population of discrete sites on a lattice, using replicable, yet stochastically variable experimental microcosms. • We combine epidemiological concepts to summarise fungal growth dynamics with percolation theory to derive and test the following hypotheses: first fungal invasion into a population of susceptible sites on a lattice can be stopped by a threshold proportion of randomly removed sites; second random removal of susceptible sites from a population introduces a shield which can prevent invasion of unprotected sites; and third the rate at which a susceptible population is invaded reduces with increasing number of randomly protected sites. • The broader consequences of thresholds for fungal invasion in natural and agricultural systems are discussed briefly.

Effect of bulk density on the spatial organisation of the fungus Rhizoctonia solani in soil.

Abstract The mycelial growth form of eucarpic fungi allows for a highly effective spatial exploration of the soil habitat. However, understanding mycelial spread through soil has been limited by difficulties of observation and quantification of fungi as they spread through this matrix. We report on a study on the effects of soil structure by altering the soil bulk density, on the spatial exploration of soil by the fungus Rhizoctonia solani using a soil thin-sectioning technique. First we quantified fungal densities in microscopic images (0.44 mm(2)). At this scale, hyphae were either absent, or present as minor fragments, typically occupying less than 1% surface area of the thin section. From contiguous microscopic images we then produced large-scale (6.21 cm(2)) spatial distribution maps of fungal hyphae. These maps were superimposed onto soil structural maps, which quantify the degree of porosity in each microscopic image. Alterations in soil structure by changing the bulk density are shown to affect the distribution of the fungus within the soil. The volume of soil explored by the fungus increased with increasing bulk density. This was associated with a shift from a few large pore spaces to more evenly distributed small-scale pores. Fungal hyphae were present in all porosity classes within each bulk density, including areas that contain less than 5% visible pore space. However, fungal hyphae were more often found in areas with a higher porosity, in particular at low soil bulk densities. The results show that soil structure is a major component in the spatial exploration of soil by fungi.