From diversity to complexity: Microbial networks in soils.

Network analysis has been used for many years in ecological research to analyze organismal associations, for example in food webs, plant-plant or plant-animal interactions. Although network analysis is widely applied in microbial ecology, only recently has it entered the realms of soil microbial ecology, shown by a rapid rise in studies applying co-occurrence analysis to soil microbial communities. While this application offers great potential for deeper insights into the ecological structure of soil microbial ecosystems, it also brings new challenges related to the specific characteristics of soil datasets and the type of ecological questions that can be addressed. In this Perspectives Paper we assess the challenges of applying network analysis to soil microbial ecology due to the small-scale heterogeneity of the soil environment and the nature of soil microbial datasets. We review the different approaches of network construction that are commonly applied to soil microbial datasets and discuss their features and limitations. Using a test dataset of microbial communities from two depths of a forest soil, we demonstrate how different experimental designs and network constructing algorithms affect the structure of the resulting networks, and how this in turn may influence ecological conclusions. We will also reveal how assumptions of the construction method, methods of preparing the dataset, and definitions of thresholds affect the network structure. Finally, we discuss the particular questions in soil microbial ecology that can be approached by analyzing and interpreting specific network properties. Targeting these network properties in a meaningful way will allow applying this technique not in merely descriptive, but in hypothesis-driven research. Analysing microbial networks in soils opens a window to a better understanding of the complexity of microbial communities. However, this approach is unfortunately often used to draw conclusions which are far beyond the scientific evidence it can provide, which has damaged its reputation for soil microbial analysis. In this Perspectives Paper, we would like to sharpen the view for the real potential of microbial co-occurrence analysis in soils, and at the same time raise awareness regarding its limitations and the many ways how it can be misused or misinterpreted.

Numerical modelling of the effect of intermittent upwelling events on plankton blooms.

In the marine environment, biological processes are strongly affected by oceanic currents, particularly by eddies (vortices) formed by the hydrodynamic flow field. Employing a kinematic flow field coupled to a population dynamical model for plankton growth, we study the impact of an intermittent upwelling of nutrients on triggering harmful algal blooms (HABs). Though it is widely believed that additional nutrients boost the formation of HABs or algal blooms in general, we show that the response of the plankton to nutrient plumes depends crucially on the mesoscale hydrodynamic flow structure. In general, nutrients can either be quickly washed out from the observation area, or can be captured by the vortices in the flow. The occurrence of either scenario depends on the relation between the time scales of the vortex formation and nutrient upwelling as well as the time instants at which upwelling pulses occur and how long they last. We show that these two scenarios result in very different responses in plankton dynamics which makes it very difficult to predict whether nutrient upwelling will lead to a HAB or not. This may in part explain why observational data are sometimes inconclusive in establishing a connection between upwelling events and plankton blooms.

Cooperative response and clustering: Consequences of membrane-mediated interactions among mechanosensitive channels.

Mechanosensitive channels are ion channels which act as cells' safety valves, opening when the osmotic pressure becomes too high and making cells avoid damage by releasing ions. They are found on the cellular membrane of a large number of organisms. They interact with each other by means of deformations they induce in the membrane. We show that collective dynamics arising from the interchannel interactions lead to first- and second-order phase transitions in the fraction of open channels in equilibrium relating to the formation of channel clusters. We show that this results in a considerable delay of the response of cells to osmotic shocks, and to an extreme cell-to-cell stochastic variations in their response times, despite the large numbers of channels present in each cell. We discuss how our results are relevant for E. coli.

Aggregation and fragmentation dynamics in random flows: From tracers to inertial aggregates.

We investigate the aggregation and fragmentation dynamics of tracers and inertial aggregates in random flows leading to steady-state size distributions. Our objective is to elucidate the impact of changes in aggregation rates due to differences in advection dynamics, especially with respect to the influence of inertial effects. This aggregation process is, at the same time, balanced by fragmentation triggered by local hydrodynamic stress. Our study employs an individual-particle-based model, tracking the position, velocity, and size of each aggregate. We compare the steady-state size distribution formed by tracers and inertial aggregates, characterized by different sizes and densities. On the one hand, we show that the size distributions change their shape with changes in the dilution rate of the suspension. On the other hand, we obtain that the size distributions formed with different binding strengths between monomers can be rescaled to a single form with the use of a characteristic size for both dense inertial particles and tracer monomers. Nevertheless, this last scaling relation also fails if the size distribution contains aggregates that behave as tracer-like and inertial-like, which results in a crossover between different scalings.

Influence of the history force on inertial particle advection: gravitational effects and horizontal diffusion.

We analyze the effect of the Basset history force on the sedimentation or rising of inertial particles in a two-dimensional convection flow. When memory effects are neglected, the system exhibits rich dynamics, including periodic, quasiperiodic, and chaotic attractors. Here we show that when the full advection dynamics is considered, including the history force, both the nature and the number of attractors change, and a fractalization of their basins of attraction appears. In particular, we show that the history force significantly weakens the horizontal diffusion and changes the speed of sedimentation or rising. The influence of the history force is dependent on the size of the advected particles, being stronger for larger particles.

Collective response of self-organized clusters of mechanosensitive channels.

Mechanosensitive channels are ion channels activated by membrane tension. We investigate the influence of the spatial distribution of bacterial mechanosensitive channels on activation (gating). Based on elastic short-range interactions we map this physical process onto an Ising-like model, which enables us to predict the clustering of channels and the effects of clustering on their gating. We conclude that the aggregation of channels and the consequent interactions among them leads to a global cooperative gating behavior with potentially dramatic consequences for the cell.