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Gavin Simpson

Ph.D., Assistant Professor

Gavin Simpson
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Profile

A geographer by training – I hold a B.Sc. (Hons) in Environmental Geography and a Ph.D. in Geography from the Department of Geography, University College London – now I am more of a statistician and data scientist with broad interests in ecology and environmental science. Since graduate school, I’ve worked as a research scientist on large EU Framework Programme projects, and as a consultant working on the effects of acid rain on remote UK lakes for the UK Government Department for Environment, Food, and Rural Affairs and on a range of other water quality and environmental problems in the UK for regulatory and responsible agencies. Most recently (2013–2021), I was a research scientist in the Institute for Environmental Change and Society, at the University of Regina, Canada, where I ran my own lab.

I’ve worked on a wide range of organisms; from bacteria and algae, to fisheries and everything in between; at local to global scales; on data collected from seconds and minutes, to millennia; on observational data as part of empirical studies and that arising from planned experiments.

My current research interests include approaches to modelling large regional to global spatio-temporal data sets using generalized additive models (GAMs) and functional statistical methods. I’m interested in broad ecosystem responses to environmental change, such as trends in biodiversity at continental scales and shifts in species ranges due to climate and environmental change.

I am an active member of the R and Data Science communities, having used R pretty much daily since before it was version 1.0, and have written and/or maintain several popular R packages. For example, I’m a lead developer on the vegan package for multivariate data analysis (e.g. ordination methods). I also wrote the permute package for restricted permutation tests that allow us to analyse multi-species data from complex experimental designs, that are commonly encountered in ecology and increasingly so in microbiology with the growth in the microbiome research. I am currently developing a package, gratia, to work with GAMs fitted in R.

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