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<p>Microbial decomposition of soil organic matter is one of the major drivers of nutrient and carbon cycling in terrestrial ecosystems. Soils are spatially heterogeneous habitats built up hierarchically from µm- to mm-sized aggregates that provide a complex pore system. An enormous diversity of microbes occupies this physically and chemically heterogeneous pore space. Although, in recent decades the consensus has largely been established, that microbial processes are strongly affected by the architecture of the soil pore space and the patchiness of the substrate distribution within it, still, the integration of pore network characteristics in models of microbial activity is scarce. </p> <p>We use an individual-based modelling approach to address the following questions:</p> <ul> <li>How does pore network architecture affect the efficiency of microbial organic matter decomposition?</li> <li>How do pore network properties like average node degree, shortest path length, and clustering coefficient affect the efficiency of organic matter decomposition?</li> <li>What is the effect of additional heterogeneity in pore sizes or distribution of substrate between pores on microbial efficiency?</li> </ul> <p>To incorporate the spatial structure the soil pore space that forms microhabitats is modelled as nodes of a network. Specific attributes are assigned to the nodes to describe their physical and biochemical conditions. Microbes inhabit a certain fraction of microhabitats (nodes) of the network and degrade organic matter that is available to them. Depending on microbial growth neighboring pores can be invaded  through the connecting links. <br /> We were able to identify a number of network properties that affect the spread of microorganisms trough the network and the subsequent decomposition efficiency of the total substrate available in the system. While high clustering of nodes enables nearly complete decomposition of substrate, the presence of highly connected nodes (hubs) can decrease the efficiency of decomposition and lead to higher amount of substrate that remains undegraded. Regarding microbial growth parameters, the system shows a threshold behaviour. If microbial growth stays below a certain threshold value, microbes live only in the initially occupied pores and are not able to invade new pores. When the substrate concentration or the growth rate reaches the threshold value, there is a jump to large-scale invasion of all reachable pores in the network and much higher efficiency in the decomposition. In addition, high heterogeneity in substrate concentration or pore sizes lead to lower invasion efficiency, lower decomposition rate and a higher amount of substrate that is left at the end. Overall, we found that the spatial structure of the pore network had a more pronounced effect on microbial decomposition efficiencies than microbial physiological parameters, such as maximum microbial growth rates or extracellular enzyme kinetics. <br /> Our findings allow for better understanding of the impact of soil pore network architecture on microbial processes. This is of high relevance when modelling the response of soil microbial communities to climate change.</p>

<p>Soil is organizationally complex and spatially heterogeneous with exceptional microbial diversity that varies in time and space. Hotspots of microbial activity are prevalent, yet they are patchy and periodic and it remains intractable to represent this level of detail in macro-scale soil microbial models. Most macro-scale microbial models have, therefore, been focused on exploring theory and capturing select processes in a simplified way. However, effective equations that account for population- and community-level controls may be needed to suitably capture emergent feedbacks at macro-scales. In this study, we explore the effective relationships that emerge between spatially aggregated carbon pools in a micro-scale soil model with competition and space constraints. Specifically, we use an individual-based, spatially explicit model to simulate the response of soil microbes to a range of scenarios with increasing carbon inputs, including spatially-uniform (homogeneous) and spatially-clumped (heterogeneous) increases, where the input flux integrated over the total area is the same in both scenarios. The latter is meant to mimic hotspots of carbon inputs, for example, in the rhizosphere or near preferential flow paths. We find that competition between microbes and the probability of invasion from neighboring microsites plays a critical role in emergent density-dependent dynamics of microbial growth and turnover. Our study elucidates the role of population-level controls on microbial turnover at macro-scales, and motivates careful consideration of scale-dependent model representations. </p>

<p>Passive dispersal of different materials in ocean flows has gotten considerable attention over the last decade to increase our knowledge about the distribution of seeds plants among islands and coastal areas, the transport of larvae of different organisms between habitats and the transport of litter. Most studies have treated these objects as tracers to investigate distribution patterns and connectivity between different areas. We compare this approach with a study that considers the objects' size and density and discusses the deviation from the tracer approach. To this end, we introduce a two-dimensional kinematic velocity field which allows us to study the connectivity between an arbitrary number of islands located at arbitrary but prescribed positions in an open flow of a given direction. First, the mixing induced by the islands, which act as obstacles in the flow, was accounted for with the inclusion of a von K\'arm\'an vortex street in the wake of each island. Furthermore, we accounted for the size and density of particles approximated as spheres. Finally, we treated the particles as inertial particles experiencing various forces in the flow and computed their trajectories in a given flow field by solving the Maxey-Riley equations. In this way, we have constructed a Lagrangian flow network reflecting the connectivity between islands depending on the properties of the finite-size particles and comparing them with the motion of tracers. We show that the density differences, the flow properties, and the islands' position geometry substantially change the connectivity between islands. That change leads to segregating inertial particles according to their size and density. Nevertheless, the most striking observation is how the tracer transport (independently of geometry) overestimates the probabilities for specific pathways. In fact, the connectivity for inertial particles is much sparser than for tracers, such that certain pathways have extremely low probabilities; they practically do not exist. These results suggest that the transport probabilities can be highly under or overestimated by tracers' often-used approximation of inertial particles.</p>