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Roots and the associated soil directly affected by root activity, termed the rhizosphere, have both been extensively studied and recognized for their crucial role in soil functioning. The formation of the rhizosphere is primarily driven by the effect of roots on shaping the physical structure of the soil, which in turn has direct feedbacks on the interactions between physical, biological and chemical processes. As a result, the rhizosphere is a hot spot for microbial activity, cycling of nutrients and turnover of organic matter. Despite the pivotal role of soil structure in controlling rhizosphere processes, we still lack a quantitative description and understanding of the interrelationships of root-systems and soil in the creation and stabilization of soil structure. We provide a comprehensive review of current knowledge and novel insights into processes that drive the formation and stabilization of soil structure in the rhizosphere. These processes are regulated by multiple indirect and direct pathways, involving root growth, the production of rhizodeposits and root hairs, as well as the activity of soil microorganisms and fauna. Further, we highlight that rhizosphere processes may persist and evolve after root death to an extent currently largely unknown. Finally, we identify five pertinent challenges that should be addressed to fully apprehend rhizosphere processes and thus harness the potential resilience of plant-soil interactions. These challenges include refining structural assessment and sampling of rhizosheaths, examining the rhizosphere in-situ and bridging the gap between solid phase and pore scale research. In our view, overcoming these obstacles can be accomplished by combining the power of imaging and isotopic approaches, especially at the field scale, encompassing diverse soils and plant species. The ultimate objective of future research should be to upscale rhizosphere processes by conducting more field experiments in concert with modeling efforts

There is growing recognition of the potential of migration to contribute to climate-change adaptation. Yet, there is limited evidence to what degree, under what conditions, for whom, and with which limitations this is effectively the case. We argue that this results from a lack of recognition and systematic incorporation of sociospatiality—the nested, networked, and intersectional nature of migration-as-adaptation. Our central objective is to utilize the translocal social-resilience approach to overcome these gaps, to identify processes and structures that shape the social resilience of translocal livelihood systems, and to illustrate the mechanisms behind the multiplicity of possible resilience outcomes. Translocal livelihood constellations anchored in rural Thailand as well as in domestic and international destinations of Thai migrants serve as illustrative empirical cases. Data were gathered through a multisited and mixed-methods research design. This paper highlights the role of the distinct but interlinked situations and operational logics at places of origin and destination, as well as the different positionalities and resulting vulnerabilities, roles, commitments, and practices of individuals and households with regard to resilience. Based on the empirical results, the paper distills a generalized typology of five broad categories of resilience outcomes, which explicitly considers sociospatiality. Our approach helps to grasp the complexity of migration-as-adaptation and to avoid simplistic conclusions about the benefits and costs of migration for adaptation—both of which are necessary for sound, evidence-based, migration-as-adaptation policymaking.

Noninvasive imaging of soils with X-ray CT has proven to be a useful method to assess soil structure from a pore space perspective. In contrast, methods like cone penetration tests reflect soil structure from the perspective of the soil matrix as assessed by its mechanical strength. Because both the gray value (GV) obtained with X-ray CT and the penetration resistance (PR) obtained with a cone penetration test depend on soil density there should be a relationship between the two. To the best of our knowledge, no studies attempted so far to investigate the nature of the PR ∼ GV relationship and to understand how well PR and GV are correlated. We aimed at bridging that gap and carried out a combined analysis of local GV and PR with undisturbed soil cores sampled in two soil textures, i.e., loam and sand. To carry out the GV measurements, we developed a new approach which considers an adaptive volume of the zone of influence of the penetrometer tip as a function of soil density. For sand and when looking at samples individually, the correlation between PR and GV was best when the soil microscale heterogeneity was high, i.e., when dense and loose zones of soil were present on the course of the penetrometer tip. For loam, the correlation between PR and GV was not dependent on soil heterogeneity. When looking at the whole dataset, the agreement between PR and GV was better in loam than in sand, with a distance correlation metric of 0.66 for loam and 0.34 for sand, respectively. For loam, the relationship PR ∼ GV had a trend which was similar to that of a hyperbola, i.e., with escalating PR values in a narrow GV range. For sand, no particular model could be recognized. In order to provide a proof-of-concept on how to generate 3D PR maps, the co-located measurements of GV and PR were used to establish an empirical relationship and X-ray CT was used to extrapolate it in 3D. This was carried out with the loam dataset by fitting a hyperbolic

In recent decades X-ray Computed Tomography (X-ray CT) has become a standard technique for non-invasive imaging of the three-dimensional structure of intact soil. The number of working groups worldwide that routinely apply X-ray CT for soil-related research is steadily growing. A consequence of this expanding community is a wealth of methods for the quantification of soil pore structure which are provided through different software toolboxes. There has not yet been a consensus about what a minimum set of metrics would be that is absolutely essential to quantify pore structure. The reasons for that are two-fold. First, soil structure analysis is not an end in itself. It is meant to reveal the heterogeneous small-scale architecture of soil, which is required for a mechanistic understanding of observable processes and phenomena at larger scale such as water movement, solute fluxes, plant–soil interactions, gas emissions or the maintenance of biodiversity. Likewise, the existence of hot spots in biological activity and geochemical processes is a manifestation of microscale processes regulated by soil structure. Depending on the specific focus, different characteristics of the pore structure might be most relevant, e.g. the volume fraction, continuity, size distribution, clustering, or roughness of pores. It is good practice that the set of investigated metrics is tailored accordingly. This is supported by theoretical or empirical evidence regarding the sensitivity of the investigated process to one or another structural feature or their combination. For example, if we are interested in hydraulic conductivity, then we should analyse not only the pore volume but also the pore size distribution and pore connectivity. In contrast, if we are interested in soil aeration, then the volume and spatial distribution pattern of macropores is highly relevant. Also, researchers all tend to stick to established image analysis protocols irrespective of the underlying research question

In this review, we introduce microbially mediated soil processes, the players, their functional traits, and their link to the processes at biogeochemical interfaces (e.g., rhizosphere, detritusphere, (bio)-pores, and aggregate surfaces). A conceptual view emphasizes the central role of the rhizosphere in interactions with other biogeochemical interfaces considering biotic and abiotic dynamic drivers. We discuss an applicability of three groups of traits based on microbial physiology, activity state and genomic functional traits to reflect microbial growth in soil. The sensitivity and credibility of modern molecular approaches to estimate microbial specific growth rates demands further development. A link between functional traits determined by physiological (e.g., respiration, biomarkers) and genomic (e.g., genome size, number of ribosomal gene copies per genome, expression of catabolic versus biosynthetic genes) approaches is strongly affected by environmental conditions such as C and nutrients availability and ecosystem type. We address, therefore, the role of soil physico-chemical conditions and trophic interactions as drivers of microbially mediated soil processes at relevant scales for process localization. The strengths and weaknesses of current approaches (destructive, non-destructive and predictive) for assessing process localization and corresponding estimation of process rates are bridged to the challenges for modelling of microbially mediated processes in heterogeneous soil micro-habitats. Finally, we introduce a conceptual self-regulatory mechanism based on flexible structure of active microbial community. Microbial taxa best suited to each successional stage of substrate decomposition, become dominating and alter the community structure. The rates of decomposition of organic compounds, therefore, are dependent on functional traits of dominating taxa and microbial strategy, which are selected and driven by the local environment.

In this paper, we present and analyze a novel global database of soil infiltration measurements, the Soil Water Infiltration Global (SWIG) database. In total, 5023 infiltration curves were collected across all continents in the SWIG database. These data were either provided and quality checked by the scientists who performed the experiments or they were digitized from published articles. Data from 54 different countries were included in the database with major contributions from Iran, China, and the USA. In addition to its extensive geographical coverage, the collected infiltration curves cover research from 1976 to late 2017. Basic information on measurement location and method, soil properties, and land use was gathered along with the infiltration data, making the database valuable for the development of pedotransfer functions (PTFs) for estimating soil hydraulic properties, for the evaluation of infiltration measurement methods, and for developing and validating infiltration models. Soil textural information (clay, silt, and sand content) is available for 3842 out of 5023 infiltration measurements ( ∼ 76%) covering nearly all soil USDA textural classes except for the sandy clay and silt classes. Information on land use is available for 76% of the experimental sites with agricultural land use as the dominant type ( ∼ 40%). We are convinced that the SWIG database will allow for a better parameterization of the infiltration process in land surface models and for testing infiltration models. All collected data and related soil characteristics are provided online in *.xlsx and *.csv formats for reference, and we add a disclaimer that the database is for public domain use only and can be copied freely by referencing it. Supplementary data are available at https://doi.org/10.1594/PANGAEA.885492 (Rahmati et al., 2018). Data quality assessment is strongly advised prior to any use of this database. Finally, we would like to encourage scientists to extend and update the SWI

Research gaps in understanding flood changes at the catchment scale caused by changes in forest management, agricultural practices, artificial drainage, and terracing are identified. Potential strategies in addressing these gaps are proposed, such as complex systems approaches to link processes across time scales, long-term experiments on physical-chemical-biological process interactions, and a focus on connectivity and patterns across spatial scales. It is suggested that these strategies will stimulate new research that coherently addresses the issues across hydrology, soil and agricultural sciences, forest engineering, forest ecology, and geomorphology.

Soils are faced with man-made chemical stress factors, such as the input of organic or metal-containing pesticides, in combination with non-chemical stressors like soil compaction and natural disturbance like drought. Although multiple stress factors are typically co-occurring in soil ecosystems, research in soil sciences on this aspect is limited and focuses mostly on single structural or functional endpoints. A mechanistic understanding of the reaction of soils to multiple stressors is currently lacking.Based on a review of resilience theory, we introduce a new concept for research on the ability of polluted soil (xenobiotics or other chemical pollutants as one stressor) to resist further natural or anthropogenic stress and to retain its functions and structure. There is strong indication that pollution as a primary stressor will change the system reaction of soil, i.e., its resilience, stability and resistance. It can be expected that pollution affects the physiological adaption of organisms and the functional redundancy of the soil to further stress. We hypothesize that the recovery of organisms and chemical-physical properties after impact of a follow-up stressor is faster in polluted soil than in non-polluted soil, i.e., polluted soil has a higher dynamical stability (dynamical stability = 1 / recovery time), whereas resilience of the contaminated soil is lower compared to that of not or less contaminated soil. Thus, a polluted soil might be more prone to change into another system regime after occurrence of further stress. We highlight this issue by compiling the literature exemplarily for the effects of Cu contamination and compaction on soil functions and structure.We propose to intensify research on effects of combined stresses involving a multidisciplinary team of experts and provide suggestions for corresponding experiments. Our concept offers thus a framework for system level analysis of soils paving the way to enhanc

In arable farming systems, the term ‘subsoil’ refers to the soil beneath the tilled or formerly tilled soil horizon whereas the latter one is denoted as ‘topsoil’. To date, most agronomic and plant nutrition studies have widely neglected subsoil processes involved in nutrient acquisition by crop roots. Based on our current knowledge it can be assumed that subsoil properties such as comparatively high bulk density, low air permeability, and poverty of organic matter, nutrients and microbial biomass are obviously adverse for nutrient acquisition, and sometimes subsoils provide as little as less than 10% of annual nutrient uptake in fertilised arable fields. Nevertheless, there is also strong evidence indicating that subsoil can contribute to more than two-thirds of the plant nutrition of N, P and K, especially when the topsoil is dry or nutrient-depleted. Based on the existing literature, nutrient acquisition from arable subsoils may be conceptualised into three major process components: (I) mobilisation from the subsoil, (II) translocation to the shoot and long-term accumulation in the Ap horizon and (III) re-allocation to the subsoil. The quantitative estimation of nutrient acquisition from the subsoil requires the linking of field experiments with mathematical modelling approaches on different spatial scales including Process Based Models for the field scale and FunctionaleStructural Plant Models for the plant scale. Possibilities to modify subsoil properties by means of agronomic management are limited, but ‘subsoiling’ e i.e. deep mechanical loosening e as well as the promotion of biopore formation are two potential strategies for increasing access to subsoil resources for crop roots in arable soils. The quantitative role of biopores in the nutrient acquisition from the subsoil is still unclear, and more research is needed to determine the bioaccessibility of nutrients in subsoil horizons.

Aerodynamic noise from the rod wake-airfoil interactions at M=0.2 and Re_D=46,000 is computed by solving the linearized perturbed compressible equations (LPCE), with the acoustic source and hydrodynamic flow variables computed from the incompressible LES. A 2D LPCE calculation is conducted at zero spanwise wave-number (k_z=0) with an assumption of statistical homogeneity in the spanwise direction. Then, a 2D Kirchhoff method is used to extrapolate the sound field at the acoustic far-field boundary (40D) up to the microphone location (185D away from the airfoil chord center). Finally, a power spectrum density (PSD) for actual span (30D) is predicted by Oberais correction method for 3D spectral acoustic pressure and spanwise coherence function for the wall pressure. The computational results for flow and acoustics are critically validated with the experimental data measured at the Ecole Centrale de Lyon.