The effect of Time Scales in Photosynthesis on microalgae Productivity

International audienceMicroalgae are often seen as a potential biofuel producer. In order to predict achievable productivities in the so called raceway culturing system, the dy- namics of photosynthesis has to be taken into account. In particular, the dynami- cal effect of inhibition by an excess of light (photoinhibition) must be represented. We propose a model considering both photosynthesis and growth dynamics. This model involves three different time scales. We study the response of this model to uctuating light with different frequencies by slow/fast approximations. Therefore, we identify three different regimes for which a simplified expression for the model can be derived. These expressions give a hint on productivity improvement which can be expected by stimulating photosynthesis with a faster hydrodynamics

Updating the Lambda modes of a nuclear power reactor

[EN] Starting from a steady state configuration of a nuclear power reactor some situations arise in which the reactor configuration is perturbed. The Lambda modes are eigenfunctions associated with a given configuration of the reactor, which have successfully been used to describe unstable events in BWRs. To compute several eigenvalues and its corresponding eigenfunctions for a nuclear reactor is quite expensive from the computational point of view. Krylov subspace methods are efficient methods to compute the dominant Lambda modes associated with a given configuration of the reactor, but if the Lambda modes have to be computed for different perturbed configurations of the reactor more efficient methods can be used. In this paper, different methods for the updating Lambda modes problem will be proposed and compared by computing the dominant Lambda modes of different configurations associated with a Boron injection transient in a typical BWR reactor. (C) 2010 Elsevier Ltd. All rights reserved.This work has been partially supported by the Spanish Ministerio de Educacion y Ciencia under projects ENE2008-02669 and MTM2007-64477-AR07, the Generalitat Valenciana under project ACOMP/2009/058, and the Universidad Politecnica de Valencia under project PAID-05-09-4285.González Pintor, S.; Ginestar Peiro, D.; Verdú Martín, GJ. (2011). Updating the Lambda modes of a nuclear power reactor. Mathematical and Computer Modelling. 54(7):1796-1801. https://doi.org/10.1016/j.mcm.2010.12.013S1796180154

Numerical modeling of eutrophication dynamics in the shallow coastal ecosystem: A case study in the Maryland and Virginia coastal bays

Shallow coastal bays and lagoons (mean depths \u3c2-3 meters) are important buffer zones and links between terrestrial and deep marine ecosystems. They are inherently vulnerable to eutrophication, and are normally dominated by benthic primary producers such as seagrass, benthic micro- and macroalgae. There is an urgent need for quantitative models that are specifically designed for studying eutrophication dynamics in shallow coastal ecosystems. In this study, a hydrodynamic and water quality modeling system consisting of the hydrodynamic model UnTRIM and the water quality model CE-QUAL-ICM was applied to a representative shallow coastal bay ecosystem, the Maryland and Virginia Coastal Bays (MVCBs). A high-resolution unstructured model grid was generated to resolve the complex geometry. to address the important role played by benthic macroalgae, a benthic macroalgal module, which assimilated macroalgal kinetics from literature and recent laboratory studies, was incorporated into the water quality model framework. The module includes two representative macroalgal species, Ulva lactuca and Gracilaria vermiculophylla , common in the MVCBs, and employs the internal nutrient-limited growth kinetics proposed by Droop. The numerical modeling system has been calibrated against a comprehensive field monitoring data collected by the Maryland Department of Natural Resources in the MVCBs. The data include water level, current velocity, salinity, and major water quality variables, such as chlorophyll a, dissolved oxygen, and nutrients. The calibrated hydrodynamic model was used to calculate the physical transport time scales. The model estimated flushing time for the entire system is on the order of 2-3 months, which are much longer than typical time scales required by most biological processes. In addition, the local residence time is found to be extremely variable throughout the system. Depending on locations, the local residence time can vary from 0 to more than 200 days. The calculated transport time scales were further compared with spatial water quality distributions in the system. The comparisons demonstrate that physical circulations could substantially modulate biological processes in the system. By using the Droop equation, the benthic macroalgae\u27s unique property, the so-called luxury uptake, was satisfactorily captured. Furthermore, the characteristic boom-and-bust life cycle of benthic macroalgae was qualitatively simulated using a box model. The expanded water quality model that includes the benthic macroalgal module reproduced both temporal and spatial distributions of observed benthic macroalgae and major water quality variables reasonably well in the MVCBs. The model results indicate that benthic macroalgae are highly important in regulating ecosystem metabolism in areas where they are abundant. Moreover, spring phytoplankton bloom was substantially suppressed when benthic macroalgae were present. The incorporation of a benthic macroalgal module also improved the model\u27s predictive capability in simulating dissolved oxygen in shallow ecosystems affected by benthic macroalgae. In terms of nutrient budget, the model estimated that benthic macroalgae retain approximately 10% of annual nonpoint source nitrogen inputs from the watershed based on the simulation of year 2004. This is lower than that contributed by benthic microalgae reported in other shallow coastal bays such as the Lynnhaven Bay. It is suspected that the restricted distribution of benthic macroalgae in the MVCBs limited their role from the whole bay perspective. With the incorporation of a benthic macroalgae module, the overall water quality model prediction capability is improved

Ensemble modellingmodeling of Antarctic macroalgal habitats exposed to glacial melt in a polar fjord

Macroalgae are the main primary producers in polar coastal regions and of major importance for the associated heterotrophic communities. On King George Island/Isla 25 de Mayo, West Antarctic Peninsula (WAP) several fjords undergo rapid glacial retreat in response to increasing atmospheric temperatures. Hence, extended meltwater plumes laden with suspended particulate matter (SPM) are generated that hamper primary production during the austral summer season. We used ensemble modeling to approximate changes in the benthic productivity of an Antarctic fjord as a function of SPM discharge. A set of environmental variables was statistically selected and an ensemble of correlative species-distribution models was devised to project scattered georeferenced observation data to a spatial distribution of macroalgae for a “time of measurement” (“tom”) scenario (2008-2015). The model achieved statistically reliable validation results (true scale statistics 0.833, relative operating characteristics 0.975) and explained more than 60% of the modeled macroalgae distribution with the variables “hard substrate” and “SPM”. This “tom” scenario depicts a macroalgae cover of approx. 8% (63 ha) for the total study area (8 km2) and a summer production of approximately 350 t dry weight. Assuming a linear increase of meltwater SPM load over time, two past (1991 and 1998) and two future (2019 and 2026) simulations with varying SPM intensities were applied. The simulation using only 50% of the “tom” scenario SPM amount (simulating 1991) resulted in increased macroalgal distribution (143 ha) and a higher summer production (792 t) compared to the “tom” status and could be validated using historical data. Forecasting the year 2019 from the “tom” status, an increase of 25% SPM results in a predicted reduction of macroalgae summer production to approximately 60% (141 t). We present a first quantitative model for changing fjordic macroalgal production under continued melt conditions at WAP. As meltwater influenced habitats are extending under climate change conditions, our approach can serve to approximate future productivity shifts for WAP fjord systems. The reduction of macroalgal productivity as predicted for Potter Cove may have significant consequences for polar coastal ecosystems under continuing climate change

Modelling Environmental Impacts on Marine Ecosystems and Coral Reefs

Coral reefs are the iconic ecosystem of tropical seas and yet they are under increasing pressure as a result of multiple climatic stressors. This thesis uses observations and models to further understanding of environmental impacts on coral reefs. In particular it examines the impact of rising Sea Surface Temperature (SST) and ocean acidification on coral growth and the frequency of coral bleaching events. UK ocean biogeochemical models are assessed for implementation in the next UK Earth System Model. This analysis finds little evidence that more complex ocean biogeochemical models provide better simulations of large scale biogeochemical features. An established wavelet-based spatial comparison technique is used to analyse the spatial scales that Earth System Models can skillfully simulate patterns of SSTs. It is shown that in coral regions, current models cannot skilfully simulate patterns of historical SST anomalies at sub-regional (<32◦) scales. These findings are used in combination with SST and aragonite saturation state outputs from Earth System Models to show that historical Caribbean coral growth has been influenced by anthropogenic aerosol emissions over the 20th Century. Earth System Model outputs are also used to make projections of global coral bleaching throughout the 21st Century. It is shown that under even the most extreme conventional mitigation scenarios the majority of the world’s coral reefs are projected to experience levels of thermal stress induced bleaching that cause reef degradation throughout the 21st Century. Geoengeering scenarios involving the injection of SO2 into the stratosphere can reduce the projected thermal stress on coral reefs relative to conventional mitigation scenarios but such benefits are shown to be highly dependent on the sensitivity of coral bleaching thresholds to ocean acidification

Dynamical Models of Biology and Medicine

Mathematical and computational modeling approaches in biological and medical research are experiencing rapid growth globally. This Special Issue Book intends to scratch the surface of this exciting phenomenon. The subject areas covered involve general mathematical methods and their applications in biology and medicine, with an emphasis on work related to mathematical and computational modeling of the complex dynamics observed in biological and medical research. Fourteen rigorously reviewed papers were included in this Special Issue. These papers cover several timely topics relating to classical population biology, fundamental biology, and modern medicine. While the authors of these papers dealt with very different modeling questions, they were all motivated by specific applications in biology and medicine and employed innovative mathematical and computational methods to study the complex dynamics of their models. We hope that these papers detail case studies that will inspire many additional mathematical modeling efforts in biology and medicin