Herbaceous communities are critical to the functioning of forest ecosystems. They recycle nutrients, help prevent erosion, provide critical microhabitats and maintain biodiversity. In the eastern United States, most hardwood forests are growing on land once entirely cleared or used for some form of agriculture. Although some of these forests are nearly 150 years old, they still have depauperate native herbaceous communities when compared to remaining old-growth forests. This long-term depletion may result from dispersal limitation or environmental limitation. I tested the hypothesis that dispersal was the primary factor contributing to the absence of five spring-flowering herbaceous species in four secondary mesic hardwood forests. I transplanted adults and sowed fresh propagules into chosen forests. By establishing negative controls, I showed that propagules of experimental species were not incidentally dispersed and would not have been present at the sites had I not introduced them. In all four sites, seeds of three ant-dispersed species germinated and adults of these species survived, flowered and self-sowed viable propagules. These results strongly indicated dispersal limitation in all sites. Another ant-dispersed species showed evidence of being dispersal-limited in at least two sites. The limitations of one gravity-dispersed species were unclear. I discuss results from the first year after transplanting and offer management suggestions to facilitate the return of these species to degraded forests.

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.