La modélisation dynamique des systèmes écologiques constitue une méthode incontournable pour comprendre,prédire et contrôler la dynamique des écosystèmes semi-naturels, qui fait intervenir des processuscomplexes. Le principal objectif de cette thèse est de développer un modèle permettant de simuler la dynamiqueà moyen terme de la végétation herbacée dans les prairies permanentes, en tenant compte à lafois de la productivité et de la biodiversité. Les prairies sont des réservoirs présentant une forte biodiversitévégétale, qui soutiennent de nombreux services écosystémiques. Sur le plan agricole, cette importantediversité contribue à la qualité de la production fourragère, et de plus, elle permet une plus grande résistancede la végétation face à des changements climatiques (réchauffement moyen, vagues de chaleur etde sécheresse).Pourtant, cette notion clé de biodiversité n’est que faiblement prise en considération dans la modélisationde l’écosystème prairial : elle est souvent absente ou alors présente sous une forme très simplifiée. Enréponse à ces considérations, ces travaux de thèse présentent la construction d’un modèle de successionbasé sur des processus, décrit par un système d’équations différentielles ordinaires, qui représente ladynamique de la végétation aérienne des prairies tempérées. Ce modèle intègre les principaux facteursécologiques impactant la croissance et la compétition des espèces herbacées, et peut s’ajuster à n’importequel niveau de diversité, par le choix du nombre et de l’identité des espèces initialement présentes dansl’assemblage. Ce formalisme mécaniste de modélisation nous permet alors d’analyser les relations qui lientdiversité, productivité et stabilité, en réponse à différentes conditions climatiques et différents modes degestion agricole.[...]Ces résultats soulignent alors le besoin de prendre en compte le rôle clé joué par la biodiversité dansles modèles de l’écosystème prairial, de par son impact sur le comportement des dynamiques simulées.De plus, pour rendre correctement compte des interactions au sein de la végétation, le nombre d’espècesconsidéré dans le modèle doit être suffisamment important. Enfin, nous comparons les simulations devégétation de ce modèle à des mesures issues de deux sites expérimentaux, la prairie de fauche d’Oensingen,et le pâturage de Laqueuille. Les résultats de ces comparaisons sont encourageants et soulignentla pertinence du choix et de la représentation des processus écologiques clés qui composent ce modèlemécaniste.Ce travail de thèse propose donc un modèle, en total adéquation avec les besoins actuels en terme demodélisation de l’écosystème prairial, qui permet de mieux comprendre la dynamique de la végétationherbacée et les interactions entre productivité, diversité et stabilité. / Dynamic modelling of ecological systems is an essential method to understand, predict and control thedynamics of semi-natural ecosystems, which involves complex processes. The main objective of this PhDthesis is to develop a simulation model of the medium- and long-term dynamics of the herbaceous vegetationin permanent grasslands, taking into account both biodiversity and productivity. Grasslandecosystems are often hot spots of biodiversity, which contributes to the temporal stability of their services.On an agricultural perspective, this important biodiversity contributes to the forage quality, andbesides, it induces a higher ability of the vegetation cover to resist to different climatic scenarios (globalwarming, heat and drought waves).However, this key aspect of biodiversity is only poorly included in grassland models : often absent ofmodelling or included in a very simple form. Building on those considerations, this PhD work exposes thewriting of a process-based succession model, described by a system of Ordinary Differential Equationsthat simulates the aboveground vegetation dynamics of a temperate grassland. This model implementedthe main ecological factors involved in growth and competition processes of herbaceous species, and couldbe adjust to any level of diversity, by varying the number and the identity of species in the initial plantcommunity. This formalism of mechanistic models allows us to analyse relationships that link diversity,productivity and stability, in response to different climatic conditions and agricultural management.In mathematical grassland models, plant communities may be represented by a various number of statevariables, describing biomass compartments of some dominant species or plant functional types. The sizeof the initial species pool could have consequences on the outcome of the simulated ecosystem dynamicsin terms of grassland productivity, diversity, and stability. This choice could also influence the modelsensitivity to forcing parameters. To address these issues, we developed a method, based on sensitivityanalysis tools, to compare behaviour of alternative versions of the model that only differ by the identityand number of state variables describing the green biomass, here plant species. This method shows aninnovative aspect, by performing this model sensitivity analysis by using multivariate regression trees. Weassessed and compared the sensitivity of each instance of the model to key forcing parameters for climate,soil fertility, and defoliation disturbances. We established that the sensitivity to forcing parameters ofcommunity structure and species evenness differed markedly among alternative models, according tothe diversity level. We show a progressive shift from high importance of soil fertility (fertilisation level,mineralization rate) to high importance of defoliation (mowing frequency, grazing intensity) as the sizeof the species pool increased.These results highlight the need to take into account the role of species diversity to explain the behaviourof grassland models. Besides, to properly take into account those interactions in the grassland cover, theconsidered species pool size considered in the model needs to be high enough. Finally, we compare modelsimulations of the aboveground vegetation to measures from two experimental sites, the mowing grasslandof Oensingen, and the grazing grassland of Laqueuille. Results of these comparison are promising andhighlight the relevance of the choice and the representation of the different ecological processes includedin this mechanistic model.Thus, this PhD work offers a model, perfectly fitting with current needs on grassland modelling, whichcontribute to a better understanding of the herbaceous vegetation dynamics and interactions betweenproductivity, diversity and stability.

<p dir="ltr">Non-native biological invasions are one of the leading concerns for global biodiversity. The establishment of invasive species reduces local biodiversity, shifts species composition, changes successional trajectories, and alters ecosystem functions. This thesis examines two aspects of invasive plants: (1) the distribution and the most important climatic and anthropogenic drivers of invasive trees across the eastern United States, and (2) an evaluation of invasive plant removal and herbaceous recovery from a government cost-share program that provides financial support for invasive plant management by private landowners.</p><p><br></p><p dir="ltr">Our first study focused on identifying the distribution of invasive trees, and the factors associated with their distribution. This is essential to predicting spread and planning subsequent management. Using USDA Forest Inventory Analysis (FIA) data and random forest modeling, we examined the distribution, and variables associated with the distribution, of invasive tree species. Invasive trees were found in 10,511 out of 299,387 FIA plots. Invasive species basal area and density (trees per ha; TPH) were highest within the central and southern Appalachian Mountains, Michigan, the Northeast, and the southern Coastal Plain of the United States. A random forest model of invasive species basal area (R²= 0.47, RMSE = 0.47) and density (R²=0.46, RMSE=0.50) vs. environmental variables found that both invasive basal area and density were most strongly associated with human footprint, followed by various climatic variables. An equivalent model of native tree basal (R²=0.53, RMSE=9.25) and TPH (R²=0.47, RMSE=8.64) found that native tree basal area and density were most strongly associated with aridity followed by various climatic variables. As human footprint increased, invasive tree basal area and density increased. These results suggest that the distribution of invasive trees is reliant on human alterations to forests.</p><p><br></p><p dir="ltr">Our second study focused on Environmental Quality Incentives Program (EQIP), a federal cost-share program that has provided $25 billion of financial assistance to farmers and non-industrial private forest owners. Few studies have examined whether this program facilitates the recovery of the herbaceous layer while decreasing the dominance of invasive plant species. We surveyed the herbaceous layer of EQIP-treated and untreated (reference) forests across three physiographic regions of Indiana. Using non-metric multidimensional scaling (NMDS) ordination and linear mixed effects models, we evaluated the species composition, richness, diversity, evenness, floristic quality index, and herbaceous-layer cover of EQIP and reference sites. We also used linear mixed models to evaluate how EQIP site treatment affected the diversity of native plant species. Sites treated with EQIP contracts typically had significantly higher native species richness, Shannon’s diversity, and floristic quality than reference sites. There were significant separations in species composition between EQIP treated and reference forests state-wide and in the southern non-glaciated region of Indiana, although composition overlapped between EQIP and reference forests. Our study suggests that EQIP-funded treatments promote increased species richness and diversity. However, the persistent overlap in species composition we observed may signify biotic homogenization due to a long-shared history of anthropogenic disturbances between EQIP and reference sites. Therefore, active restoration of the herbaceous layer might be needed to allow a full recovery after invasive removal.</p>