Bioinformatics, Biological Sciences, Complex Systems, Ecological Research
Bayesian Methods, Computational Tools for Data Science, Data Mining, Deep Learning, Dynamical Models, Graph Theory and Graph-based Methods, Mathematics, Network Analysis, Statistical Modeling, Statistics, Time Series Analysis

Annette Ostling

Associate Professor

Ecology and Evolutionary Biology

Biodiversity in nature can be puzzlingly high in the light of competition between species, which arguably should eventually result in a single winner. The coexistence mechanisms that allow for this biodiversity shape the dynamics of communities and ecosystems. My research focuses on understanding the mechanisms of competitive coexistence, how competition influences community structure and diversity, and what insights observed patterns of community structure might provide about competitive coexistence.

I am interested in the use and development of data science approaches to draw insights regarding coexistence mechanisms from the structural patterns of ecological communities with respect to species’ functional traits, relative abundance, spatial distribution, and phylogenetic relatedness, through as community dynamics proceed. I am also interested in the use of Maximum Likelihood and Bayesian approaches for fitting demographic models to forest census data sets, demographic models that can then be used to quantitatively assess the role of different competitive coexistence mechanisms.