A Direct Comparison of Node and Element-based Finite Element Modeling Approaches to Study Tissue Growth

Finite element analysis is a useful tool to model growth of biological tissues and predict how growth can be impacted by stimuli. Previous work has simulated growth using node-based or element-based approaches, and this implementation choice may influence predicted growth, irrespective of the applied growth model. This study directly compared node-based and element-based approaches to understand the isolated impact of implementation method on growth predictions by simulating growth of a bone rudiment geometry, and determined what conditions produce similar results between the approaches. We used a previously reported node-based approach implemented via thermal expansion and an element-based approach implemented via osmotic swelling, and we derived a mathematical relationship to relate the growth resulting from these approaches. We found that material properties (modulus) affected growth in the element-based approach, with growth completely restricted for high modulus values relative to the growth stimulus, and no restriction for low modulus values. The node-based approach was unaffected by modulus. Node- and element- based approaches matched marginally better when the conversion coefficient to relate the approaches was optimized based on results of initial simulations, rather than using the theoretically-predicted conversion coefficient (median difference in node position 0.042 cm vs. 0.052 cm, respectively). In summary, we illustrate here the importance of the choice of implementation approach for modeling growth, provide a framework for converting models between implementation approaches, and highlight important considerations for comparing results in prior work and developing new models of tissue growth.

Stress priming affects fungal competition – evidence from a combined experimental and modeling study

Priming, an inducible stress defense strategy that prepares an organism for an impending stress event, is common in microbes and has been studied mostly in isolated organisms or populations. How the benefits of priming change in the microbial community context and, vice versa, whether priming influences competition between organisms, remains largely unknown. In this combined experimental and modeling study, we developed a cellular automaton model based on dedicated data of different isolates of soil fungi in isolation and pairwise competition experiments. With the model, we simulated growth of the ascomycete Chaetomium elatum competing against other fungi to understand which species traits influence the benefit of priming and the effect of priming on competition. We showed that competition changes the priming benefit compared to isolated growth, and that it depends not only on the primeable species itself, but also on the competitors’ traits such as growth rate, primeability and stress susceptibility. In addition, we showed that priming benefits were not always reflected in the competitive outcome. With this study, we transferred insights on priming from studies in isolation to the community context. This is an important step towards understanding the role of inducible defenses in microbial community assembly and composition.

Emissions of monoterpenes from new Scots pine foliage: dependency on season, stand age and location and importance for models

Models to predict the emissions of biogenic volatile organic compounds (BVOCs) from terrestrial vegetation largely use standardised emission potentials derived from shoot enclosure measurements of mature foliage and usually assume that the contribution of BVOCs from new conifer needles is minor to negligible. Extensive observations have, however, recently demonstrated that the potential of new Scots pine needles to emit several different BVOCs can be up to about 500 times higher than that of the corresponding mature foliage. Thus, we build on these discoveries and investigate the impact of previously neglecting enhanced emissions from new Scots pine foliage on estimates of monoterpene emissions and new atmospheric aerosol particle formation and their subsequent growth. We show that the importance of considering the enhanced monoterpene emission potential of new Scots pine foliage decreases as a function of season, tree age and latitude, and that new foliage is responsible for the majority of the whole tree's foliage emissions of monoterpenes during spring time, independently of tree age and location. Our results suggest that annual monoterpene emission estimates from Finland would increase with up to ~ 25 % if the emissions from new Scots pine foliage were explicitly considered, with the majority being emitted during spring time where also new particle formation has been observed to occur most frequently. We estimate that our findings can lead to increases in predictions of the formation rates of 2 nm particles during spring time by ~ 75–275 % in northern Finland and by ~ 125–865 % in southern Finland. Likewise, simulated growth rates of 2–3 nm particles would increase by ~ 65–175 % in northern Finland and by ~ 110–520 % in southern Finland if the enhanced emissions of monoterpenes from new Scots pine foliage were explicitly considered. Our findings imply that we need to introduce a more comprehensive treatment of the emissions of BVOCs from new coniferous foliage in biogenic emission models.