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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 (Ψo) and matric (Ψm) 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 ΔΨo and ΔΨm 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 ΔΨo and ΔΨm values slowed bacterial dispersal in the system, leading to decelerated growth and benzoate degradation. In contrast, dispersal networks facilitated bacterial movement at ΔΨo and ΔΨm values between 0 and -0.5 MPa and thus improved the absolute biodegradation performance by up to 52 and 119% for ΔΨo and ΔΨm, 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., (Copyright © 2016, American Society for Microbiology. All Rights Reserved.)

Bacterial degradation is an ecosystem service that offers a promising method for the remediation of contaminated soils. To assess the dynamics and efficiency of bacterial degradation, reliable microbial simulation models, along with the relevant processes, are required. We present an approach aimed at improving reliability by studying the relevance and implications of an important concept from theoretical ecology in the context of a bacterial system: conditional dispersal denoting that the dispersal strategy depends on environmental conditions. Different dispersal strategies, which either incorporate or neglect this concept, are implemented in a bacterial model and results are compared to data obtained from laboratory experiments with Pseudomonas putida colonies growing on glucose agar. Our results show that, with respect to the condition of resource uptake, the model's correspondence to experimental data is significantly higher for conditional than for unconditional bacterial dispersal. In particular, these results support the hypothesis that bacteria disperse less when resources are abundant. We also show that the dispersal strategy has a considerable impact on model predictions for bacterial degradation of resources: disregarding conditional bacterial dispersal can lead to overestimations when assessing the performance of this ecosystem service.