PhD thesis of Nikolaos Alexandridis (UBO) defended on 28/03/2017
Supervisors: Cédric Bacher, Fred Jean
Benthic macroinvertebrates are part of a complex network of interactions with their abiotic environment, their resources and with each other. The spatial and temporal scales of the processes that form the basis for these interactions have traditionally restricted their empirical study throughthe development of statistical models. Mechanistic models, being free of logistical limitations, offer an alternative tool for the study of potential community assembly mechanisms. Their development is, however, restricted by a lack of knowledge on the mechanisms that structure benthic communities. In the context of this thesis, the first chapter of the manuscript attempts a review of the statistical and mechanistic modelling tools that have been applied to marine benthic macroinvertebrates. The objective is to identify a technique that would allow the study of the dynamic behaviour of benthic biodiversity in a spatially explicit way based on existing datasets.
The implementation of a mechanistic modelling framework seems fitting, but it requires the derivation of a limited number of model entities with a clear functional role. The second chapter of the manuscript employs the emergent group hypothesis in order to do that in a way that is objective and testable. It combines an abundance dataset of benthic macroinvertebrate species from the Rance estuary collected in 1995 with a matrix of biological traits that describe the role of 240 species in 7 general community assembly mechanisms. The resulting aggregation into 20 functional groups is tested against the assumptions of the emergent group hypothesis. The generally positive results support the ability of the grouping to represent functional diversity in the Rance estuary. A first look at the emergent groups also provides some insight into the potential role of a few general mechanisms in shaping benthic communities.
The lack of quantitative knowledge for the attribution of relationships among the previously derived functional components is still important. The third chapter of the manuscript addresses this issue based on ecological theories that predict the existence of functional trade-offs operating at both large and small spatial scales. The former represent processes of environmental filtering, while the latter involve trade-offs with respect to life history characteristics. Observed trait associations appear to agree with these predictions, in support of the potential of the respective processes to shape benthic communities in the Rance estuary. In a first inception of the system, elements of ecological theory and expert knowledge are incorporated in the form of general rules of interaction into 2 qualitative models of the 20 functional groups. The general stability of these models illustrates their potential to constitute a plausible representation of the natural world. Their structure could offer clues to the direction that the system might take in response to perturbations.
In spite of the interest in developing and analysing qualitative mathematical models, the goal of studying the dynamic and spatially explicit behaviour of benthic biodiversity can only be reached by a model with the same characteristics. The fourth chapter of the manuscript presents the architecture of an individual-based model, primarily transferring the rules of interaction from the qualitative models to a dynamic and spatially explicit framework. It is the first version of a model that allows the transition from the level of individuals to that of the Rance estuary. The sensitivity analysis of the model can identify the key processes controlling the spatial and temporal behaviour of benthic biodiversity. These results are discussed in the context of the development of a general modelling framework and its transferability to other sites with the goal of assessing the functioning and potential response of benthic ecosystems to perturbations.