CLAESSEN David

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Crop pathogens are known to rapidly adapt to agricultural practices. Although cultivar resistance breakdown and resistance to pesticides have been broadly studied, little is known about the adaptation of crop pathogens to fertilization regimes and no epidemiological model has addressed that question. However, this is a critical issue for developing sustainable low-input agriculture. In this article, we use a model of life history evolution of biotrophic wheat fungal pathogens in order to understand how they could adapt to changes in fertilization practices. We focus on a single pathogen life history trait, the latent period, which directly determines the amount of resources allocated to growth and reproduction along with the speed of canopy colonization. We implemented three fertilization scenarios, corresponding to major effects of increased nitrogen fertilization on crops: (i) increase in nutrient concentration in leaves, (ii) increase of leaf lifespan, and (iii) increase of leaf number (tillering) and size that leads to a bigger canopy size. For every scenario, we used two different fitness measures to identify putative evolutionary responses of latent period to changes in fertilization level. We observed that annual spore production increases with fertilization, because it results in more resources available to the pathogens. Thus, diminishing the use of fertilizers could reduce biotrophic fungal epidemics. We found a positive relationship between the optimal latent period and fertilization when maximizing total spore production over an entire season. In contrast, we found a negative relationship between the optimal latent period and fertilization when maximizing the within-season exponential growth rate of the pathogen. These contrasting results were consistent over the three tested fertilization scenarios. They suggest that between-strain diversity in the latent period, as has been observed in the field, may be due to diversifying selection in different cultural environments.

Background and Aims Disease models can improve our understanding of dynamic interactions in pathosystems and thus support the design of innovative and sustainable strategies of crop protections. However, most epidemiological models focus on a single type of pathogen, ignoring the interactions between different parasites competing on the same host and how they are impacted by properties of the canopy. This study presents a new model of a disease complex coupling two wheat fungal diseases, caused by Zymoseptoria tritici (septoria) and Puccinia triticina (brown rust), respectively, combined with a functional–structural plant model of wheat. Methods At the leaf scale, our model is a combination of two sub-models of the infection cycles for the two fungal pathogens with a sub-model of competition between lesions. We assume that the leaf area is the resource available for both fungi. Due to the necrotic period of septoria, it has a competitive advantage on biotrophic lesions of rust. Assumptions on lesion competition are first tested developing a geometrically explicit model on a simplified rectangular shape, representing a leaf on which lesions grow and interact according to a set of rules derived from the literature. Then a descriptive statistical model at the leaf scale was designed by upscaling the previous mechanistic model, and both models were compared. Finally, the simplified statistical model has been used in a 3-D epidemiological canopy growth model to simulate the diseases dynamics and the interactions at the canopy scale. Key Results At the leaf scale, the statistical model was a satisfactory metamodel of the complex geometrical model. At the canopy scale, the disease dynamics for each fungus alone and together were explored in different weather scenarios. Rust and septoria epidemics showed different behaviours. Simulated epidemics of brown rust were greatly affected by the presence of septoria for almost all the tested scenarios, but the reverse was not the case. However, shortening the rust latent period or advancing the rust inoculum shifted the competition more in favour of rust, and epidemics became more balanced. Conclusions This study is a first step towards the integration of several diseases within virtual plant models and should prompt new research to understand the interactions between canopy properties and competing pathogens.

Environmental factors (physical, chemical and biological) influence the composition of marine phytoplankton communities. In addition, dynamic transport can also impact the relative abundance of organisms within these communities. Consequently, phytoplankton biomasses, as well as the nature of the organisms that compose them, show significant variability both spatially (bioregionalization) and temporally (successions). Coastal regions are particularly contrasted areas in which environmental gradients are generally marked. Thus, the Iroise Sea is characterized by the presence of a seasonal tidal front (Ushant front), particularly productive, which separates two distinct regimes. To the east of the front, the waters of the continental shelf are regularly made homogeneous by the presence of strong tidal currents, whereas the offshore area is subject to a seasonal cycle marked by a summer vertical stratification. This is therefore a suitable region for a more general study of the mechanisms of interaction between frontal structures and phytoplankton diversity. The more specific aim of this thesis is to characterize, with the help of 3D modelling, the nature and diversity of phytoplankton in the Iroise Sea, both in terms of functional groups and phenotypic diversity, during a seasonal cycle in general and more particularly during the summer period at the frontal zone.The first results obtained showed that the composition in functional groups of phytoplankton presents a marked seasonal cycle, mainly influenced by the depth of the mixing layer. During winter, picoplankton dominate throughout the study area. Stratification, which begins in April, leads to a phytoplankton bloom dominated by microphytoplankton (mainly diatoms). The summer period then corresponds to the establishment of a bio-regionalization of environmental conditions in the Iroise Sea with (i) the mixed coastal zone which remains highly productive and dominated by diatoms and (ii) the offshore zone, in which autotrophic growth is limited by surface nutrients, which favors the coexistence of microphytoplankton and picophytoplankton. The results show a zone of high diversity at the surface, slightly shifted towards the west with respect to the frontal zone (in which the biomass is maximum). At this diversity maximum, the importance of vertical exchanges (upwelling and mixing) on the warm (stratified) side of the front was highlighted. Thus, a mixture between ubiquitous phenotypes present in the mixed zone east of the front and picoplankton, originating from both the subsurface chlorophyll maximum and the oligotrophic surface to the west, is observed in the diversity maximum.Finally, a last study on the effect of the spring/neap tidal cycle allowed us to understand, for the first time, the processes that explain the impact of this cycle on the modification of phytoplankton biomass and on the composition of the community in terms of phenotypic diversity in the homogeneous coastal system. The results show an increase in the total biomass as well as in the proportion of diatoms and a decrease in diversity during the stratification periods associated with neap tides.

The functional and taxonomic biogeography of marine microbial systems reflects the current state of an evolving system. Current models of marine microbial systems and biogeochemical cycles do not reflect this fundamental organizing principle. Here, we investigate the evolutionary adaptive potential of marine microbial systems under environmental change and introduce explicit Darwinian adaptation into an ocean modelling framework, simulating evolving phytoplankton communities in space and time. To this end, we adopt tools from adaptive dynamics theory, evaluating the fitness of invading mutants over annual timescales, replacing the resident if a fitter mutant arises. Using the evolutionary framework, we examine how community assembly, specifically the emergence of phytoplankton cell size diversity, reflects the combined effects of bottom-up and top-down controls. When compared with a species-selection approach, based on the paradigm that "Everything is everywhere, but the environment selects", we show that (i) the selected optimal trait values are similar. (ii) the patterns emerging from the adaptive model are more robust, but (iii) the two methods lead to different predictions in terms of emergent diversity. We demonstrate that explicitly evolutionary approaches to modelling marine microbial populations and functionality are feasible and practical in time-varying, space-resolving settings and provide a new tool for exploring evolutionary interactions on a range of timescales in the ocean.

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This thesis is part of the broad field of research on the evolution of life history traits. Life history traits are directly involved in the reproduction and survival, and thus the selective value, of organisms. Interest in life history traits is motivated by the immense diversity of these traits in the living world. In particular, there is a great diversity of aging patterns in nature. This thesis addresses the evolution of aging in natural populations. As with most life history traits, theoretical research on the evolution of aging has been conducted in the context of a single, stable population living in a constant environment. The goal of this thesis is to predict how aging evolves when populations are structured in space and when the environment varies in time and space. My approach has been mainly theoretical, but I have been able to explore some questions with data collected in natural populations. In the introduction, I present the necessary elements to consider when looking at the evolution of life history traits in age-structured populations. I make the observation that these populations are subject to environmental variations and structured in space. In the first part, I show that environmental variations, in time and space, can affect senescence patterns. I use quantitative genetic methods where I hypothesize that mutations have an environment and age specific effect. In the second part, I focus on the consequences of extinction-recolonization dynamics on the resource sharing strategy between survival and reproduction of individuals according to their age. In particular, I show that dispersal is a source of variability for this strategy and examine how dispersers and non-dispersersers differ in their life history traits in 3 data sets. Overall, my results show that taking into account the complex ecological and environmental conditions in which organisms live provides insight into the diversity of aging patterns in nature. Finally, I give a short review of this thesis and then give possible perspectives to my research and more generally to research on the evolution of aging.

The geographical structuring of populations is a central issue in evolutionary theory. Various analyses have helped to understand its influence on the evolution of species. Nevertheless, the landscape, defined as the set of biotic and abiotic elements that characterize the spatial structuring of populations, is considered as static by formal models of evolution. However, many geological, climatic, ecological and anthropic processes change the landscape at various scales of space and time. Populations are thus repeatedly subjected to fragmentation and mergers, varying their ecological interactions as well as the nature, intensity and conditions of action of the evolutionary mechanisms at work. The objective of this thesis is to determine, with the help of theoretical models, the influence of these landscape dynamics on the evolution of species. At the micro-evolutionary level, we show that probability and time of allele fixation are strongly altered by even simple landscape dynamics. At the meso-evolutionary level, we show that allopatry and sympatry can act in concert in the speciation process, and that complex landscape dynamics can easily generate radiation. Our work reveals that in order to understand species evolution, it is necessary to take into account the way populations are and have been fragmented, but also the time scales associated with the dynamics of this spatial structuring: these determine the combinations and interactions of evolutionary mechanisms producing new species and altering the structure of metacommunities.