Fungal–bacterial interactions are highly diverse and contribute to many ecosystem processes. Their emergence under common environmental stress scenarios however, remains elusive. Here we use a synthetic microbial ecosystem based on the germination of Bacillus subtilis spores to examine whether fungal and fungal-like (oomycete) mycelia reduce bacterial water and nutrient stress in an otherwise dry and nutrient-poor microhabitat. We find that the presence of mycelia enables the germination and subsequent growth of bacterial spores near the hyphae. Using a combination of time of flight- and nanoscale secondary ion mass spectrometry (ToF- and nanoSIMS) coupled with stable isotope labelling, we link spore germination to hyphal transfer of water, carbon and nitrogen. Our study provides direct experimental evidence for the stimulation of bacterial activity by mycelial supply of scarce resources in dry and nutrient-free environments. We propose that mycelia may stimulate bacterial activity and thus contribute to sustaining ecosystem functioning in stressed habitats.

Fungal mycelia serve as effective dispersal networks for bacteria in water-unsaturated environments, thereby allowing bacteria to maintain important functions, such as biodegradation. However, poor knowledge exists on the effects of dispersal networks at various osmotic (Ψ _o ) and matric (Ψ _m ) potentials, which contribute to the water potential mainly in terrestrial soil environments. Here we studied the effects of artificial mycelium-like dispersal networks on bacterial dispersal dynamics and subsequent effects on growth and benzoate biodegradation at ΔΨ _o and ΔΨ _m values between 0 and −1.5 MPa. In a multiple-microcosm approach, we used a green fluorescent protein (GFP)-tagged derivative of the soil bacterium Pseudomonas putida KT2440 as a model organism and sodium benzoate as a representative of polar aromatic contaminants. We found that decreasing ΔΨ _o and ΔΨ _m values slowed bacterial dispersal in the system, leading to decelerated growth and benzoate degradation. In contrast, dispersal networks facilitated bacterial movement at ΔΨ _o and ΔΨ _m values between 0 and −0.5 MPa and thus improved the absolute biodegradation performance by up to 52 and 119% for ΔΨ _o and ΔΨ _m , respectively. This strong functional interrelationship was further emphasized by a high positive correlation between population dispersal, population growth, and degradation. We propose that dispersal networks may sustain the functionality of microbial ecosystems at low osmotic and matric potentials.

Soil is populated by highly diverse microbial communities mediating important processes and functions. The distribution of microbes, however, is neither uniform nor random. Instead, it is dictated by physical, chemical, and biological processes and conditions and varying over small spatial and temporal scales. The feedbacks between these processes make the soil-microbe complex a self-organizing system capable of adapting to the continuously changing conditions mainly driven by the highly fluctuating water content. For making meaningful predictions on the spatiotemporal dynamics of soil microbes and their functions, we need to integrate knowledge from physics, chemistry, and biology in our modeling approaches. Here, we review modeling studies with a focus on spatiotemporal dynamics of bacteria and bacterial functions in soil microhabitats. We compare these studies along four dimensions: specific aim, model type (individual-based, population-based), scale, and considered physical, chemical, biological processes and aspects. A special emphasis is laid on modeling approaches considering processes and aspects influencing the spatial distribution of bacteria such as motility, vector-based dispersal and biofilm formation. This includes factors like soil structure, carbon and oxygen gradients, temporal variations in hydration conditions or anthropogenic disturbance events. By assessing the importance of different microscale bacterial processes, this review should contribute to the ongoing discussion on challenges related to the upscaling from the microscopic via the profile to the landscape scale. Recent technical advances to observe bacteria in soils or soil-like environments combined with multidisciplinary collaborations will help to shed light on currently understudied physical, chemical and biological interactions in the soil-microbe complex.

The increasing demand for biomass for food, animal feed, fibre and bioenergy requires optimization of soil productivity, while at the same time, protecting other soil functions such as nutrient cycling and buffering, carbon storage, habitat for biological activity and water filter and storage. Therefore, one of the main challenges for sustainable agriculture is to produce high yields while maintaining all the other soil functions. Mechanistic simulation models are an essential tool to fully understand and predict the complex interactions between physical, biological and chemical processes of soils that generate those functions. We developed a soil model to simulate the impact of various agricultural management options and climate change on soil functions by integrating the relevant processes mechanistically and in a systemic way. As a special feature, we include the dynamics of soil structure induced by tillage and biological activity, which is especially relevant in arable soils. The model operates on a 1D soil profile consisting of a number of discrete layers with dynamic thickness. We demonstrate the model performance by simulating crop growth, root growth, nutrient and water uptake, nitrogen cycling, soil organic matter turnover, microbial activity, water distribution and soil structure dynamics in a long‐term field experiment including different crops and different types and levels of fertilization. The model is able to capture essential features that are measured regularly including crop yield, soil organic carbon, and soil nitrogen. In this way, the plausibility of the implemented processes and their interactions is confirmed. Furthermore, we present the results of explorative simulations comparing scenarios with and without tillage events to analyse the effect of soil structure on soil functions. Since the model is process‐based, we are confident that the model can also be used to predict quantities that have not been measured or to estimate the effect of management measures and climate states not yet been observed. The model thus has the potential to predict the site‐specific impact of management decisions on soil functions, which is of great importance for the development of a sustainable agriculture that is currently also on the agenda of the ‘Green Deal’ at the European level.

Terrestrial microbial ecosystems are exposed to many types of disturbances varying in their spatial and temporal characteristics. The ability to cope with these disturbances is crucial for maintaining microbial ecosystem functions, especially if disturbances recur regularly. Thus, understanding microbial ecosystem dynamics under recurrent disturbances and identifying drivers of functional stability and thresholds for functional collapse is important. Using a spatially explicit ecological model of bacterial growth, dispersal, and substrate consumption, we simulated spatially heterogeneous recurrent disturbances and investigated the dynamic response of pollutant biodegradation – exemplarily for an important ecosystem function. We found that thresholds for functional collapse are controlled by the combination of disturbance frequency and spatial configuration (spatiotemporal disturbance regime). For rare disturbances, the occurrence of functional collapse is promoted by low spatial disturbance fragmentation. For frequent disturbances, functional collapse is almost inevitable. Moreover, the relevance of bacterial growth and dispersal for functional stability also depends on the spatiotemporal disturbance regime. Under disturbance regimes with moderate severity, microbial properties can strongly affect functional stability and shift the threshold for functional collapse. Similarly, networks facilitating bacterial dispersal can delay functional collapse. Consequently, measures to enhance or sustain bacterial growth/dispersal are promising strategies to prevent functional collapses under moderate disturbance regimes.