Biofilms are antibiotic-resistant bacterial aggregates that grow on moist surfaces and can trigger hospitalacquired infections. They provide a classical example in biology where the dynamics of cellular communities may be observed and studied. Gene expression regulates cell division and differentiation, which affect the biofilm architecture. Mechanical and chemical processes shape the resulting structure. We gain insight into the interplay between cellular and mechanical processes during biofilm development on air-agar interfaces by means of a hybrid model. Cellular behavior is governed by stochastic rules informed by a cascade of concentration fields for nutrients, waste, and autoinducers. Cellular differentiation and death alter the structure and the mechanical properties of the biofilm, which is deformed according to Föppl-Von Kármán equations informed by cellular processes and the interaction with the substratum. Stiffness gradients due to growth and swelling produce wrinkle branching. We are able to reproduce wrinkled structures often formed by biofilms on air-agar interfaces, as well as spatial distributions of differentiated cells commonly observed with B. subtilis.

Barbaro, A., Einarsson, B., Birnir, B., Sigurðsson, S., Valdimarsson, H., Pálsson, Ó. K., Sveinbjörnsson, S., and Sigurðsson, Þ. 2009. Modelling and simulations of the migration of pelagic fish. – ICES Journal of Marine Science, 66: 826–838. We applied an interacting particle model to the Icelandic capelin stock to reproduce the spawning migration route for three different years, successfully predicting the route for 2008. Using available temperature data and approximated currents, and without using artificial forcing terms or a homing instinct, our model was able to reproduce the observed migration routes from all 3 years. By a sensitivity analysis, we identified oceanic temperature and the balance between the influence of interaction among particles and the particles' response to temperature as the control parameters most significant in determining the migration route. One significant contribution of this paper is the inclusion of orders of magnitude more particles than similar models, which affects the global behaviour of the model by propagating information about surrounding temperature through the school more efficiently. To maintain the same dynamics between different simulations, we argue a linear relationship between the time-step, radii of interactions, and the spatial resolution, and we argue that these scale as N−1/2, where N is the number of particles.

A stochastic model is used to assess the effect of external parameters on the development of submerged biofilms on smooth and rough surfaces. The model includes basic cellular mechanisms, such as division and spreading, together with an elementary description of the interaction with the surrounding flow and probabilistic rules for extracellular polymeric substance matrix generation, cell decay, and adhesion. Insight into the interplay of competing mechanisms such as the flow or the nutrient concentration change is gained. Erosion and growth processes combined produce biofilm structures moving downstream. A rich variety of patterns are generated: shrinking biofilms, patches, ripplelike structures traveling downstream, fingers, mounds, streamerlike patterns, flat layers, and porous and dendritic structures. The observed regimes depend on the carbon source and the type of bacteria.

Marine Protected Areas (MPA) are important management tools shown to protect marine organisms, restore biomass, and increase fisheries yields. While MPAs have been successful in meeting these goals for many relatively sedentary species, highly mobile organisms may get few benefits from this type of spatial protection due to their frequent movement outside the protected area. The use of a large MPA can compensate for extensive movement, but testing this empirically is challenging, as it requires both large areas and sufficient time series to draw conclusions. To overcome this limitation, MPA models have been used to identify designs and predict potential outcomes, but these simulations are highly sensitive to the assumptions describing the organism’s movements. Due to recent improvements in computational simulations, it is now possible to include very complex movement assumptions in MPA models (e.g. Individual Based Model). These have renewed interest in MPA simulations, which implicitly assume that increasing the detail in fish movement overcomes the sensitivity to the movement assumptions. Nevertheless, a systematic comparison of the designs and outcomes obtained under different movement assumptions has not been done. In this paper, we use an individual based model, interconnected to population and fishing fleet models, to explore the value of increasing the detail of the movement assumptions using four scenarios of increasing behavioral complexity: a) random, diffusive movement, b) aggregations, c) aggregations that respond to environmental forcing (e.g. sea surface temperature), and d) aggregations that respond to environmental forcing and are transported by currents. We then compare these models to determine how the assumptions affect MPA design, and therefore the effective protection of the stocks. Our results show that the optimal MPA size to maximize fisheries benefits increases as movement complexity increases from ~10% for the diffusive assumption to ~30% when full environment forcing was used. We also found that in cases of limited understanding of the movement dynamics of a species, simplified assumptions can be used to provide a guide for the minimum MPA size needed to effectively protect the stock. However, using oversimplified assumptions can produce suboptimal designs and lead to a density underestimation of ca. 30%; therefore, the main value of detailed movement dynamics is to provide more reliable MPA design and predicted outcomes. Large MPAs can be effective in recovering overfished stocks, protect pelagic fish and provide significant increases in fisheries yields. Our models provide a means to empirically test this spatial management tool, which theoretical evidence consistently suggests as an effective alternative to managing highly mobile pelagic stocks.