Mechanistic population models for ecological risk assessment and decision support: The importance of good conceptual model diagrams

The use of mechanistic population models as research and decision-support tools in ecology and ecological risk assessment (ERA) is increasing. This growth has been facilitated by advances in technology, allowing the simulation of more complex systems, as well as by standardized approaches for model development, documentation, and evaluation. Mechanistic population models are particularly useful for simulating complex systems, but the required model complexity can make them challenging to communicate. Conceptual diagrams that summarize key model elements, as well as elements that were considered but not included, can facilitate communication and understanding of models and increase their acceptance as decision-support tools. Currently, however, there are no consistent standards for creating or presenting conceptual model diagrams (CMDs), and both terminology and content vary widely. Here, we argue that greater consistency in CMD development and presentation is an important component of good modeling practice, and we provide recommendations, examples, and a free web app (pop-cmd.com) for achieving this for population models used for decision support in ERAs. Integr Environ Assess Manag 2024;00:1-9. © 2023 SETAC.

Local buffer mechanisms for population persistence

Assessing and predicting the persistence of populations is essential for the conservation and control of species. Here, we argue that local mechanisms require a better conceptual synthesis to facilitate a more holistic consideration along with regional mechanisms known from metapopulation theory. We summarise the evidence for local buffer mechanisms along with their capacities and emphasise the need to include multiple buffer mechanisms in studies of population persistence. We propose an accessible framework for local buffer mechanisms that distinguishes between damping (reducing fluctuations in population size) and repelling (reducing population declines) mechanisms. We highlight opportunities for empirical and modelling studies to investigate the interactions and capacities of buffer mechanisms to facilitate better ecological understanding in times of ecological upheaval.

McComedy: A user-friendly tool for next-generation individual-based modeling of microbial consumer-resource systems

Individual-based modeling is widely applied to investigate the ecological mechanisms driving microbial community dynamics. In such models, the population or community dynamics emerge from the behavior and interplay of individual entities, which are simulated according to a predefined set of rules. If the rules that govern the behavior of individuals are based on generic and mechanistically sound principles, the models are referred to as next-generation individual-based models. These models perform particularly well in recapitulating actual ecological dynamics. However, implementation of such models is time-consuming and requires proficiency in programming or in using specific software, which likely hinders a broader application of this powerful method. Here we present McComedy, a modeling tool designed to facilitate the development of next-generation individual-based models of microbial consumer-resource systems. This tool allows flexibly combining pre-implemented building blocks that represent physical and biological processes. The ability of McComedy to capture the essential dynamics of microbial consumer-resource systems is demonstrated by reproducing and furthermore adding to the results of two distinct studies from the literature. With this article, we provide a versatile tool for developing next-generation individual-based models that can foster understanding of microbial ecology in both research and education.

Microorganisms such as bacteria and fungi can be found in virtually any natural environment. To better understand the ecology of these microorganisms–which is important for several research fields including medicine, biotechnology, and conservation biology–researchers often use computer models to simulate and predict the behavior of microbial communities. Commonly, a particular technique called individual-based modeling is used to generate structurally realistic models of these communities by explicitly simulating each individual microorganism. Here we developed a tool called McComedy that helps researchers applying individual-based modeling efficiently without having to program low-level processes, thus allowing them to focus on their actual research questions. To test whether McComedy is not only convenient to use but also generates meaningful models, we used it to reproduce previously reported findings of two other research groups. Given that our results could well recapitulate and furthermore extend the original findings, we are confident that McComedy is a powerful and versatile tool that can help to address fundamental questions in microbial ecology.

Ecology of Contaminant Biotransformation in the Mycosphere: Role of Transport Processes

Fungi and bacteria often share common microhabitats. Their co-occurrence and coevolution give rise to manifold ecological interactions in the mycosphere, here defined as the microhabitats surrounding and affected by hyphae and mycelia. The extensive structure of mycelia provides ideal "logistic networks" for transport of bacteria and matter in structurally and chemically heterogeneous soil ecosystems. We describe the characteristics of the mycosphere as a unique and highly dynamic bacterial habitat and a hot spot for contaminant biotransformation. In particular, we emphasize the role of the mycosphere for (i) bacterial dispersal and colonization of subsurface interfaces and new habitats, (ii) matter transport processes and contaminant bioaccessibility, and (iii) the functional stability of microbial ecosystems when exposed to environmental fluctuations such as stress or disturbances. Adopting concepts from ecological theory, the chapter disentangles bacterial-fungal impacts on contaminant biotransformation in a systemic approach that interlinks empirical data from microbial ecosystems with simulation data from computational models. This approach provides generic information on key factors, processes, and ecological principles that drive microbial contaminant biotransformation in soil. We highlight that the transport processes create favorable habitat conditions for efficient bacterial contaminant degradation in the mycosphere. In-depth observation, understanding, and prediction of the role of mycosphere transport processes will support the use of bacterial-fungal interactions in nature-based solutions for contaminant biotransformation in natural and man-made ecosystems, respectively.

Functional Resistance to Recurrent Spatially Heterogeneous Disturbances Is Facilitated by Increased Activity of Surviving Bacteria in a Virtual Ecosystem

Bacterial degradation of organic compounds is an important ecosystem function with relevance to, e.g., the cycling of elements or the degradation of organic contaminants. It remains an open question, however, to which extent ecosystems are able to maintain such biodegradation function under recurrent disturbances (functional resistance) and how this is related to the bacterial biomass abundance. In this paper, we use a numerical simulation approach to systematically analyze the dynamic response of a microbial population to recurrent disturbances of different spatial distribution. The spatially explicit model considers microbial degradation, growth, dispersal, and spatial networks that facilitate bacterial dispersal mimicking effects of mycelial networks in nature. We find: (i) There is a certain capacity for high resistance of biodegradation performance to recurrent disturbances. (ii) If this resistance capacity is exceeded, spatial zones of different biodegradation performance develop, ranging from no or reduced to even increased performance. (iii) Bacterial biomass and biodegradation dynamics respond inversely to the spatial fragmentation of disturbances: overall biodegradation performance improves with increasing fragmentation, but bacterial biomass declines. (iv) Bacterial dispersal networks can enhance functional resistance against recurrent disturbances, mainly by reactivating zones in the core of disturbed areas, even though this leads to an overall reduction of bacterial biomass.

Mycelium-mediated transfer of water and nutrients stimulates bacterial activity in dry and oligotrophic environments

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.

The maintenance of bacterial and fungal activity is essential for ecosystem functioning, particularly in dry soils where the two phyla co-exist. Here, Worrich and colleagues show experimentally that mycelia traffic water and nutrients and thereby stimulate bacterial activity in stressful conditions.

Bacterial Dispersal Promotes Biodegradation in Heterogeneous Systems Exposed to Osmotic Stress

Contaminant biodegradation in soils is hampered by the heterogeneous distribution of degrading communities colonizing isolated microenvironments as a result of the soil architecture. Over the last years, soil salinization was recognized as an additional problem especially in arid and semiarid ecosystems as it drastically reduces the activity and motility of bacteria. Here, we studied the importance of different spatial processes for benzoate biodegradation at an environmentally relevant range of osmotic potentials (ΔΨo) using model ecosystems exhibiting a heterogeneous distribution of the soil-borne bacterium Pseudomonas putida KT2440. Three systematically manipulated scenarios allowed us to cover the effects of (i) substrate diffusion, (ii) substrate diffusion and autonomous bacterial dispersal, and (iii) substrate diffusion and autonomous as well as mediated bacterial dispersal along glass fiber networks mimicking fungal hyphae. To quantify the relative importance of the different spatial processes, we compared these heterogeneous scenarios to a reference value obtained for each ΔΨo by means of a quasi-optimal scenario in which degraders were ab initio homogeneously distributed. Substrate diffusion as the sole spatial process was insufficient to counteract the disadvantage due to spatial degrader heterogeneity at ΔΨo ranging from 0 to -1 MPa. In this scenario, only 13.8-21.3% of the quasi-optimal biodegradation performance could be achieved. In the same range of ΔΨo values, substrate diffusion in combination with bacterial dispersal allowed between 68.6 and 36.2% of the performance showing a clear downwards trend with decreasing ΔΨo. At -1.5 MPa, however, this scenario performed worse than the diffusion scenario, possibly as a result of energetic disadvantages associated with flagellum synthesis and emerging requirements to exceed a critical population density to resist osmotic stress. Network-mediated bacterial dispersal kept biodegradation almost consistently high with an average of 70.7 ± 7.8%, regardless of the strength of the osmotic stress. We propose that especially fungal network-mediated bacterial dispersal is a key process to achieve high functionality of heterogeneous microbial ecosystems also at reduced osmotic potentials. Thus, mechanical stress by, for example, soil homogenization should be kept low in order to preserve fungal network integrity.

Effects of Facilitated Bacterial Dispersal on the Degradation and Emission of a Desorbing Contaminant

The quantitative relationship between a compound's availability for biological removal and ecotoxicity is a key issue for retrospective risk assessment and remediation approaches. Here, we investigated the impact of facilitated bacterial dispersal at a model soil-atmosphere interface on the release, degradation, and outgassing of a semivolatile contaminant. We designed a laboratory microcosm with passive dosing of phenanthrene (PHE) to a model soil-atmosphere interface (agar surface) in the presence and absence of glass fibers known to facilitate the dispersal of PHE-degrading Pseudomonas fluorescens LP6a. We observed that glass fibers (used as a model to mimic a fungal hyphal network) resulted in (i) increased bacterial surface coverage, (ii) effective degradation of matrix-bound PHE, and (iii) substantially reduced PHE emission to locations beyond the contamination zone even at low bacterial surface coverage. Our data suggest that bacterial dispersal networks such as mycelia promote the optimized spatial arrangement of microbial populations to allow for effective contaminant degradation and reduction of potential hazard to organisms beyond a contaminated zone.

Highways versus pipelines: contributions of two fungal transport mechanisms to efficient bioremediation

Based on experimental studies, two different fungus-mediated transport mechanisms have been suggested to facilitate the bacterial degradation of organic soil pollutants: bacteria may use liquid films around fungal hyphae for quick dispersal ('fungal highways'), and fungi may take up and translocate pollutants through their mycelial network ('fungal pipelines'). Both mechanisms are anticipated to enhance the bioavailability of pollutants to degrading bacteria. Using a microbial simulation model, we therefore investigated their respective efficiency in increasing biodegradation performance. We analysed networks that act either as bacterial dispersal vectors or as pollutant translocation vectors or as a combination of both. Our results suggest that each mechanism can improve biodegradation performance. The degree of improvement, however, varies distinctly depending on the environmental conditions, and is even negligible under certain conditions. Mycelial networks acting as 'highways' allow bacteria to overcome motility restrictions and reach remote areas, whereas networks acting as 'pipelines' may initiate degradation by bringing remote pollutants to bacteria. As a consequence, highest biodegradation improvements often emerge from the combination of both mechanisms. We conclude that 'fungal highways' as well as 'fungal pipelines' should be considered for developing novel bioremediation strategies based on fungus-mediated transport in soils.

The relevance of conditional dispersal for bacterial colony growth and biodegradation

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.

Dispersal networks for enhancing bacterial degradation in heterogeneous environments

Successful biodegradation of organic soil pollutants depends on their bioavailability to catabolically active microorganisms. In particular, environmental heterogeneities often limit bacterial access to pollutants. Experimental and modelling studies revealed that fungal networks can facilitate bacterial dispersal and may thereby improve pollutant bioavailability. Here, we investigate the influence of such bacterial dispersal networks on biodegradation performance under spatially heterogeneous abiotic conditions using a process-based simulation model. To match typical situations in polluted soils, two types of abiotic conditions are studied: heterogeneous bacterial dispersal conditions and heterogeneous initial resource distributions. The model predicts that networks facilitating bacterial dispersal can enhance biodegradation performance for a wide range of these conditions. Additionally, the time horizon over which this performance is assessed and the network's spatial configuration are key factors determining the degree of biodegradation improvement. Our results support the idea of stimulating the establishment of fungal mycelia for enhanced bioremediation of polluted soils.