Dr Crispin M. Mutshinda

I am interested in the interplay of random drift and niche-mediated (non-neutral) processes in driving the dynamics and structure of ecological communities.

Currently I am designing hierarchical Bayesian models and Markov Chain Monte-Carlo algorithms to identify potential trait-based phytoplankton clusters and investigate whether such a clustering can enhance the predictive power of phytoplankton community biomass models.

For my PhD, I examined the prevailing assembly theories in community ecology, and developed comprehensive models of community dynamics with regard to neutral and niche-mediated factors. I analyzed real-world community time series from a range of taxa to show on empirical grounds that natural communities are primarily shaped by environmental forcing, the impact of inter-specific interactions remaining broadly week, lending support to niche differentiation.

Upon the completion of my PhD, I worked as a post-doctoral researcher in the Biometry Research Group at the University of Helsinki, Finland, developing Bayesian models for quantitative trait locus (QTL) mapping. One result of this research project is an extension of LASSO known as Extended Bayesian LASSO (EBL) for QTL mapping and unobserved phenotype prediction. I subsequently held a post-doctoral position at Mount Allison designing Bayesian models of phytoplankton community dynamics. I lately worked as a post-doctoral position at HEC Montreal in a project dealing with robust Bayesian analysis of extreme values.