Abstract of PhD Thesis

Global change impact on biodiversity function

Caroline Brophy, University College Dublin (2008)

The study of competition among species has a long history in Science dating back as far as the first ecological experiment carried out by Darwin in the early 1800’s. Still today, however, the need for continued and efficient studies of competition and biodiversity are evident. In particular understanding the effects of global change on competition and biodiversity in ecosystems has become increasingly important both nationally and internationally. The effects of competitive interactions among species in ecosystems and how species dynamics of communities will develop as global change continues could imply major evolutionary consequences in ecology which in turn could have serious implications for human health and world economics.

Despite substantial progress, ecologists recognize that research in multi-species systems requires a new level of sophistication in experimental designs, and statistical analyses. If ecological research is to properly understand the impact of competition and biodiversity on ecosystem services, then such challenges need to be overcome. Further understanding of competition among species in ecological systems and the effect of global change on it through statistical modelling is the main theme in this thesis.

It is a major challenge to simultaneously understand all mechanisms and drivers of forces in ecosystems and so assessment is frequently done on individual components of the system one at a time and combined for a unified understanding. In this thesis four statistical frameworks for assessing competition are developed. Each concentrates on competition in ecosystems at either the below ground or above ground level and assesses a particular ecosystem response recorded at either the individual level, the genotypic level, community level or multivariate community level. Together the chapters can give insight to competition in ecosystems.

A wide range of statistical and biological issues are addressed in detail throughout this thesis. The two strands, the development of modelling techniques and eliciting biologically valuable information from datasets, successfully complement each other in challenging ways. The central aim of this thesis is to develop and apply statistical modelling techniques in non-standard situations to assess impacts of competition and global change on ecosystems in ecology.

Several biological results were established through the statistical modelling applications in this thesis. These include the following:

  1. A more complete framework for the analysis of reproductive output in plants is provided for plant ecologists. Applying this framework identified a strong effect of relative size within a competitive plant stand size hierarchy on reproductive allocation (RA) for the plant species Sinapis arvensis, with greater size relative to neighbours substantially increasing RA.
  2. Elevated atmospheric CO2 reverses the dominance structure of genotypes in populations of the highly allergenic and invasive plant common ragweed (Ambrosia artimisiifolia).
  3. Competitive interactions have been identified among different strains of rhizobium bacteria which may have implications for the nitrogen fixing ability of legume species.
  4. Increased understanding of grassland systems and the factors that affect system dynamics over time, in particular, Dactylis glomerata was identified as a dominant species over time regardless of its initial relative abundance in mixture across a wide climatic gradient in a multi-site experiment.