Individual Based Modeling

Coastal habitats that serve as nursery grounds for numerous marine species are badly degraded, yet the traditional means of modeling populations of exploited marine species handle spatiotemporal changes in habitat characteristics and life history dynamics poorly, if at all. To explore how nursery habitat degradation impacts recruitment of a mobile, benthic species, we developed a spatially explicit, individual-based model that describes the recruitment of Caribbean spiny lobster (Panulirus argus) in the Florida Keys, where a cascade of environmental disturbances has reconfigured nursery habitat structure. In recent years, the region has experienced a series of linked perturbations, among them, seagrass die-offs, cyanobacteria blooms, and the mass mortality of sponges. Sponges are important shelters for juvenile spiny lobster, an abundant benthic predator that also sustains Florida's most valuable fishery. In the model, we simulated monthly settlement of individual lobster postlarvae and the daily growth, mortality, shelter selection, and movement of individual juvenile lobsters on a spatially explicit grid of habitat cells configured to represent the Florida Keys coastal nursery. Based on field habitat surveys, cells were designated as either seagrass or hardbottom, and hard-bottom cells were further characterized in terms of their shelter-and sizespecific lobster carrying capacities. The effect of algal blooms on sponge mortality, hence lobster habitat structure, was modeled based on the duration of exposure of each habitat cell to the blooms. Ten-year simulations of lobster recruitment with and without algal blooms suggest that the lobster population should be surprisingly resilient to massive disturbances of this type. Data not used in model development showed that predictions of large changes in lobster shelter utilization, yet small effects on recruitment in response to blooms, were realistic. The potentially severe impacts of habitat loss on recruitment were averted by compensatory changes in habitat utilization and mobility by larger individuals, coupled with periods of fortuitously high larval settlement. Our model provides an underutilized approach for assessing habitat effects on open populations with complex life histories, and our results illustrate the potential pitfalls of relying on intuition to infer the effects of habitat perturbations on upper trophic levels.

Many studies have examined the relationship between the built environment and health. Yet, the question of how and why the environment influences health behavior remains largely unexplored. As health promotion interventions work through the individuals in a targeted population, an explicit understanding of individual behavior is required to formulate and evaluate intervention strategies. Bringing in concepts from various fields, this paper proposes the use of an activity-based modeling approach for understanding and predicting, from the bottom up, how individuals interact with their environment and each other in space and time, and how their behaviors aggregate to population-level health outcomes.

Biofilm growth and transport in confined systems frequently occur in natural and engineered systems. Designing customizable engineered porous materials for controllable biofilm transportation properties could significantly improve the rapid utilization of biofilms as engineered living materials for applications in pollution alleviation, material self-healing, energy production, and many more. We combine Bayesian optimization (BO) and individual-based modeling to conduct design optimizations for maximizing different porous materials' (PM) biofilm transportation capability. We first characterize the acquisition function in BO for designing 2-dimensional porous membranes. We use the expected improvement acquisition function for designing lattice metamaterials (LM) and 3-dimensional porous media (3DPM). We find that BO is 92.89% more efficient than the uniform grid search method for LM and 223.04% more efficient for 3DPM. For all three types of structures, the selected characterization simulation tests are in good agreement with the design spaces approximated with Gaussian process regression. All the extracted optimal designs exhibit better biofilm growth and transportability than unconfined space without substrates. Our comparison study shows that PM stimulates biofilm growth by taking up volumetric space and pushing biofilms' upward growth, as evidenced by a 20% increase in bacteria cell numbers in unconfined space compared to porous materials, and 128% more bacteria cells in the target growth region for PM-induced biofilm growth compared with unconfined growth. Our work provides deeper insights into the design of substrates to tune biofilm growth, analyzing the optimization process and characterizing the design space, and understanding biophysical mechanisms governing the growth of biofilms. Keywords Individual-based modeling • biofilm • metamaterials • Bayesian optimization • porous media

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Coastal habitats that serve as nursery grounds for numerous marine species are badly degraded, yet the traditional means of modeling populations of exploited marine species handle spatiotemporal changes in habitat characteristics and life history dynamics poorly, if at all. To explore how nursery habitat degradation impacts recruitment of a mobile, benthic species, we developed a spatially explicit, individual-based model that describes the recruitment of Caribbean spiny lobster (Panulirus argus) in the Florida Keys, where a cascade of environmental disturbances has reconfigured nursery habitat structure. In recent years, the region has experienced a series of linked perturbations, among them, seagrass die-offs, cyanobacteria blooms, and the mass mortality of sponges. Sponges are important shelters for juvenile spiny lobster, an abundant benthic predator that also sustains Florida's most valuable fishery. In the model, we simulated monthly settlement of individual lobster postlarvae and the daily growth, mortality, shelter selection, and movement of individual juvenile lobsters on a spatially explicit grid of habitat cells configured to represent the Florida Keys coastal nursery. Based on field habitat surveys, cells were designated as either seagrass or hardbottom, and hard-bottom cells were further characterized in terms of their shelter-and sizespecific lobster carrying capacities. The effect of algal blooms on sponge mortality, hence lobster habitat structure, was modeled based on the duration of exposure of each habitat cell to the blooms. Ten-year simulations of lobster recruitment with and without algal blooms suggest that the lobster population should be surprisingly resilient to massive disturbances of this type. Data not used in model development showed that predictions of large changes in lobster shelter utilization, yet small effects on recruitment in response to blooms, were realistic. The potentially severe impacts of habitat loss on recruitment were averted by compensatory changes in habitat utilization and mobility by larger individuals, coupled with periods of fortuitously high larval settlement. Our model provides an underutilized approach for assessing habitat effects on open populations with complex life histories, and our results illustrate the potential pitfalls of relying on intuition to infer the effects of habitat perturbations on upper trophic levels.

Marine ecosystems are increasingly exposed to anthropogenic disturbances that cause animals to change behavior and move away from potential foraging grounds. Here we present a process-based modeling framework for assessing population consequences of such sub-lethal behavioral effects. It builds directly on how disturbances influence animal movements, foraging and energetics, and is therefore applicable to a wide range of species. To demonstrate the model we assess the impact of wind farm construction noise on the North Sea harbor porpoise population. Subsequently, we demonstrate how the model can be used to minimize population impacts of disturbances through spatial planning. Population models that build on the fundamental processes that determine animal fitness have a high predictive power in novel environments, making them ideal for marine management. K E Y W O R D S agent-based model, anthropogenic disturbances, cumulative effects, displacement, harbor porpoise, individual-based modeling, marine spatial planning, movement model, Phocoena phocoena This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

The biogeography of speciation and what can be learned about the past mode of speciation from current biogeography of sister species are recurrent problems in evolution. We used a trait-and individual-based, eco-evolutionary model to simulate adaptive radiations and recorded the geographical overlap of species during and after evolutionary branching (speciation). We compared the spatial overlap among sister species in the fully saturated community with the overlap at the speciation event. The mean geographic overlap at speciation varied continuously from complete (sympatry) to none (allopatry), depending on local and regional environmental heterogeneity and the rate of dispersal. The distribution of overlap was, however, in some cases considerably bimodal. This tendency was most expressed at large values of regional heterogeneity, corresponding to sharp environmental contrasts. The mean geographic overlap also varied during the course of a radiation, sometimes with a consistent negative trend over time. The speciations that resulted in currently observable end community sister species were therefore not an unbiased sample of all speciations throughout the radiation. Postspeciation range shifts (causing increased overlap) occurred most frequently when dispersal was high or when local habitat heterogeneity was low. Our results help us understand how the patterns of geographic mode of speciation emerge. We also show the difficulty in inferring the geographical speciation mode from phylogenies and the biogeography of extant species.

Biofilms pose significant problems for engineers in diverse fields, such as marine science, bioenergy, and biomedicine, where effective biofilm control is a long-term goal. The adhesion and surface mechanics of biofilms play crucial roles in generating and removing biofilm. Designing customized nanosurfaces with different surface topologies can alter the adhesive properties to remove biofilms more easily and greatly improve long-term biofilm control. To rapidly design such topologies, we employ individual-based modeling and Bayesian optimization to automate the design process and generate different active surfaces for effective biofilm removal. Our framework successfully generated optimized functional nanosurfaces for improved biofilm removal through applied shear and vibration. Densely distributed short pillar topography is the optimal geometry to prevent biofilm formation. Under fluidic shearing, the optimal topography is to sparsely distribute tall, slim, pillar-like structures. When subjected to either vertical or lateral vibrations, thick trapezoidal cones are found to be optimal. Optimizing the vibrational loading indicates a small vibration magnitude with relatively low frequencies is more efficient in removing biofilm. Our results provide insights into various engineering fields that require surface-mediated biofilm control. Our framework can also be applied to more general materials design and optimization.

Biofilms are communities of sessile microorganisms attached to a surface and imbedded in a matrix of extracellular polysaccharide substances. These communities can be found in diverse aquatic environments, such as in industrial pipes and in humans. By forming microcolony structures, which are highly resistant to adverse physical conditions as well as antimicrobial agents, biofilms are very problematic when associated with e.g. persistent infections. In order to find new ways of controlling biofilm growth, the processes involved in biofilm development must be investigated further. The main interest of this study is the occurrence of void formation inside biofilms. This phenomenon has been observed in several studies and has been correlated to cell death inside the microcolonies. The occurrence of cell death has recently been associated with the presence of nitric oxide in the biofilm. In this study, the implications of nitric oxide accumulation on biofilm development were investigated using an individual-based model. Specifically, the role of nitric oxide in void formation was considered. A large number of simulations were run using different parameter settings in order to determine if nitric oxide could account for the occurrence of void formation observed experimentally. The general predictions made by the model system showed agreement to some experimental data, but not to others. Sloughing, the detachment of chunks of cells from the biofilm, was observed in the majority of simulations. In some cases, the model also predicted the presence of live cells inside the voids, which has been observed experimentally.

The biophysical mechanisms influencing larval distribution and their impacts on the metapopulation dynamics of sandy beaches, particularly the connectivity patterns associated with larval dispersal, are poorly understood. Here, we identify larval connectivity patterns of the mole crab Emerita brasiliensis in the coast of Uruguay. A biophysical individual based model (IBM) of larval transport was coupled to a regional high-resolution physical model to estimate the monthly and interannual variation of larval connectivity, as well as the impact of the length of the reproductive period on it. Larval connectivity showed marked interannual variations, which were mainly related to interannual changes in seasonal winds and associated ocean circulation patterns, particularly during La Ni˜na years. The southernmost area where E. brasiliensis occurs only received larvae from the nearest release area in November and January spawning events during a strong La Niñaa year, characterized by intense northeasterly winds. The Uruguayan coast constitutes the leading (poleward) edge of the distribution of E. brasiliensis, where climate change effects are projected to intensify. Extrapolation of these results to a climate change scenario with stronger La Ni˜na events, suggest that larval transport to southernmost beaches will become more probable.