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Soil hydraulic properties are an important factor to optimize and adapt water management for a given crop. Pedotransfer functions (PTFs) present a solution to predict soil variables such as hydraulic properties, using fundamental soil properties. In this research, we compared two sources of soil information: iSDAsoil data and field data, in four regions in Morocco. We then used this data to evaluate published data and developed new PTFs using soil information to estimate soil gravimetric moisture content at saturation (w0), field capacity (w330) and permanent wilting point (w15000). A total of 331 samples were collected from four regions: Doukkala, Gharb-Loukous, Moulouya and Tadla. The data was divided into calibration and validation datasets. For development of different PTFs, we used simple linear regression, multiple linear regression, regression tree, Cubist algorithm, and random forest approaches. PTFs developed by Dijkerman (Geoderma, 1988, 42, 29–49) presented the best performance, showing lower RMSE, Bias and MAE compared to other PTFs. Using multiple linear regression to develop PTFs, models based on clay, silt and soil organic matter as input variables showed the best performance after calibration (R2 of 0.590, 0.785, 0.786 for w0, w330, and w15000, respectively). Regarding the techniques based on machine learning, random forest showed the best performance after calibration compared with other algorithms (R2 of 0.930, 0.955, 0.954 for w0, w330, and w15000, respectively). PTFs represent a low cost and easy technique to estimate soil hydraulic properties, to improve water management efficiency for the farmers.

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.

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.

In spite of the very significant role that fungi are called to play in agricultural production and climate change over the next two decades, very little is known at this point about the parameters that control the spread of fungal hyphae in the pore space of soils. Monitoring of this process in 3 dimensions is not technically feasible at the moment. The use of transparent micromodels simulating the internal geometry of real soils affords an opportunity to approach the problem in 2 dimensions, provided it is confirmed that fungi would actually want to propagate in such artificial systems. In this context, the key objectives of the research described in this article are to ascertain, first, that the fungus Rhizoctonia solani can indeed grow in a micromodel of a sandy loam soil, and, second, to identify and analyze in detail the pattern by which it spreads in the tortuous pores of the micromodel. Experimental observations show that hyphae penetrate easily inside the micromodel, where they bend frequently to adapt to the confinement to which they are subjected, and branch at irregular intervals, unlike in current computer models of the growth of hyphae, which tend to describe them as series of straight tubular segments. A portion of the time, hyphae in the micromodels also exhibit thigmotropism, i.e., tend to follow solid surfaces closely. Sub-apical branching, which in unconfined situations seems to be controlled by the fungus, appears to be closely connected with the bending of the hyphae, resulting from their interactions with surfaces. These different observations not only indicate different directions to follow to modify current mesoscopic models of fungal growth, so they can apply to soils, but they also suggest a wealth of further experiments using the same set-up, involving for example competing fungal hyphae, or the coexistence of fungi and bacteria in the same pore space.

Simplified experimental systems, often referred to as microcosms, have played a central role in the development of modern ecological thinking on issues ranging from competitive exclusion to examination of spatial resources and competition mechanisms, with important model-driven insights to the field. It is widely recognized that soil architecture is the key driver of biological and physical processes underpinning ecosystem services, and the role of soil architecture and soil physical conditions is receiving growing interest. The difficulty to capture the architectural heterogeneity in microcosms means that we typically disrupt physical architecture when collecting soils. We then use surrogate measures of soil architecture such as aggregate size distribution and bulk-density, in an attempt to recreate conditions encountered in the field. These bulk-measures are too crude and do not describe the heterogeneity at microscopic scales where microorganisms operate. In the current paper we therefore ask the following questions: (i) To what extent can we control the pore geometry at microscopic scales in microcosm studies through manipulation of common variables such as density and aggregate size?; (ii) What is the effect of pore geometry on the growth and spread dynamics of bacteria following introduction into soil? To answer these questions, we focus on Pseudomonas sp. and Bacillus sp. We study the growth of populations introduced in replicated microcosms packed at densities ranging from 1.2 to 1.6 g cm−3, as well as packed with different aggregate sizes at identical bulk-density. We use X-ray CT and show how pore geometrical properties at microbial scales such as connectivity and solid-pore interface area, are affected by the way we prepare microcosms. At a bulk-density of 1.6 g cm−3 the average number of Pseudomonas was 63% lower than at a bulk-density of 1.3 g cm−3. For Bacillus this reduction was 66%. Depending on the physical conditions, bacteria in half the samples took between 1.62 and 9.22 days to spread 1.5 cm. Bacillus did spread faster than Pseudomonas and both did spread faster at a lower bulk-density. Our results highlight the importance that soil physical properties be considered in greater detail in soil microbiological studies than is currently the case.