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Eco-evolutionary modeling of soil microbial decomposition in a warming climate

Abstract : One major source of uncertainty in global climate predictions is the extent to which global warming will increase atmospheric CO2 concentrations through enhanced microbial decomposition of soil organic matter. There is therefore a critical need for models that mechanistically link decomposition to the dynamics of microbial communities, and integration of these mechanistic models in global projection models of the Earth system. Mathematical models of soil microbial decomposition models have recently been introduced to predict soil C stocks and heterotrophic soil respiration, especially in the context of climate change. Thus far, models focused on physiological and ecological mechanisms of microbial responses, leaving the role of evolutionary adaptation poorly understood. My thesis addresses this gap and evaluates the hypothesis that microbial evolutionary adaptation to warming can have a significant impact on the global carbon cycle. After reviewing mechanistic, non- evolutionary microbial models of decomposition, I construct an eco-evolutionary spatially explicit, stochastic model, scaling up from microscopic processes acting at the level of cells and extracellular molecules. I use an approximated version of the model (spatially implicit, deterministic) to investigate the eco-evolutionary response of a soil microbe-enzyme system to warming, under three possible scenarios for the influence of temperature on microbial activity. In the absence of microbial evolution, warming results in soil carbon loss to the atmosphere (an amplification of climate change) in all scenarios. Microbial evolutionary adaptation generally aggravates soil carbon loss in cold ecosystems, and may aggravate, buffer or even reverse carbon loss in warm ecosystems. Constraining the model with observations from five contrasting biomes reveals evolutionary aggravation of soil carbon loss to be the most likely outcome. Earth-scale projections of carbon stocks that integrate my eco-evolutionary model support the prediction of a significant global aggravation of soil C loss due to microbial evolution. Dormant soils, in which microbial activity is very low, play a special role in the long-term eco-evolutionary dynamics of global soil carbon, since in these regions, the negative effect of evolution on soil carbon stocks may not kick in until the microbial community shifts from dormant to active, and may thus be delayed by decades. Overall, my work is a first step toward predictive modeling of eco- evolutionary dynamics of carbon cycling; it also lays the ground for a broad future research program that will empirically test model predictions about the role of evolutionary mechanisms in different systems across the globe, by leveraging the growing global archive of soil metagenomics data to quantify variations in microbial metabolic functions and their response to selection. Mots clés en français (10 max) : changement climatique, cycle du carbone, décomposition, projections globales, évolution microbienne, dynamiques adaptatives, rétroaction sol-climat, évolution de la coopération, modèles individu-centrés.Mots clés en anglais : climate change, carbon cycle, decomposition, global predictions, microbial evolution, adaptive dynamics, soil-climate feedbacks, evolution of cooperation, individual-based models.
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Elsa Abs. Eco-evolutionary modeling of soil microbial decomposition in a warming climate. Symbiosis. Université Sorbonne Paris Cité, 2019. English. ⟨NNT : 2019USPCC029⟩. ⟨tel-02614092⟩

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