Invited Speaker: Dr Francis Hui

January 13, 2020

All Under One Roof – The Rise of Joint Species Distribution Modeling in Ecology

Biography:

Francis Hui is a Senior Lecturer in Statistics at the Australian National University. Having completed his PhD at the University of New South Wales in 2014, Francis moved to Canberra to undertake a postdoctoral fellowship at the ANU, and has been willingly stuck there since. His research spans a mixture of methodological, computational, and applied statistics, including longitudinal and correlated data analysis using mixed and/or marginal models, dimension reduction and variable selection, and approximate statistical estimation and inference. Much of his applications are motivated by joint modeling in community ecology, and temporal analysis of social and environmental drivers for mental health. All of his research is complemented by copious amounts of tea drinking and unhealthy amounts of anime watching.

Talk Overview:

Prompted by improvements in computing power and an increasing number of scientific questions that are multi-response in nature, the landscape of statistical analysis in community ecology has undergone a major shift in the last five years with the explosion of joint species distribution modeling. In this talk, I will provide an overview of how such models (which are largely based around the use of latent variables or some variation thereof) have come to dominate the discipline, and how they have been adapted to solve questions by ecologists regarding the environmental and biotic processes driving species assemblages. I will then offer an (opinionated) view of where-to-next for joint species distribution models, including the use of “modern” statistical approaches such as covariance/correlation regression and spatio-temporal methods, and the growing software market. Finally, I will discuss related research opportunities across other disciplines where latent variable models are applied, such as in the analysis of multi-environmental field trials in plant breeding.