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| Formato: | Recurso digital |
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Zenodo
2025
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| Acceso en línea: | https://doi.org/10.5281/zenodo.15641316 |
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- <h2>Arctic Diatom Dynamic Flux Balance Analysis (dFBA) Models</h2> <p>Dynamic flux balance analysis models for simulating Arctic phytoplankton bloom dynamics and climate change impacts on marine carbon sequestration. This repository contains Python implementations of genome-scale metabolic models for both non-symbiotic (<em>Thalassiosira</em> sp.) and symbiotic (<em>Chaetoceros</em> sp. with <em>Anabaena</em> sp.) diatom communities.</p> <h3>Key Features</h3> <ul> <li>Temperature-dependent RuBisCo kinetics with Arctic-specific parameterization</li> <li>Location and time-dependent solar irradiance calculations using SMARTS2</li> <li>Symbiotic nutrient transfer modeling between diatoms and cyanobacteria</li> <li>Diatom succession pattern simulation (early <em>Thalassiosira</em> to late <em>Chaetoceros</em> blooms)</li> <li>Climate change scenario analysis for Arctic Ocean conditions</li> </ul> <h3>Applications</h3> <ul> <li>Predicting phytoplankton bloom timing, intensity, and carbon fixation under warming scenarios</li> <li>Evaluating ecosystem resilience mechanisms through diatom-cyanobacteria symbiosis</li> <li>Assessing climate change impacts on Arctic marine carbon sequestration</li> </ul> <p>The models integrate empirical environmental parameters with constraint-based metabolic modeling to simulate annual phytoplankton life cycles and their response to changing Arctic conditions.</p>