A Scientist in training (and self-diagnosed theoretical ecologist) who loves playing outside in the mountains and wants to understand why communities are structured the way that they are. Being the
maths geek nerd that I am my PhD has taken on a distinctly computational flavour and aims to help us improve our understanding and ability to make more global generalisations about ecological communities - although I sometimes find myself reverting back to my ‘microecology’ roots and getting caught up in the weeds at times 🙈. Current interests include (but are not limited to): ecological networks, species traits, the role of scale and how all that fits together as a member of the amazing (if you ask me) Poisot Lab along with a (seemingly) ever growing list of side projects.
A plant ecologist by inclination I can usually be found gushing about how cute a particular grass (or succulent) is, hanging off of the side of a mountain or going on bike-ventures to various coffee shops. When the weather forces me indoors I’m most likely spending way more time than I need to trying to automate a process that could be done in a few minutes, exercising my creative side (I produce a fortnightly comic for the Ecology for the Masses blog) or trying to find new (and pretty) ways in which to visualise data and results i.e. combining my geeky self with my artistic alter-ego.
MSc in Ecology and Biodiversity, 2020
Stockholms Universitet | Sweden
BSc (Hons) in Plant Sciences, 2017
University of Pretoria | South Africa
Some thoughts on why RStudio is great and makes reproducibility that little bit easier to attain. In retrospect this turned into a RMarkdown post…
2 weeks into PhD and chill and your supervisor hits you with an idea for a manuscript due in 1.5 months, while you’re working remotely (in a different continent & timezone no less) and during a pandemic. It all turned out okay in the end though - I think.
It’s happening! The PhD journey has started and we’re already talking projects and publications.
A graduate student lead project which aims at trying to develop a roadmap for the many, future potential paths of predicting ecological networks using machine learning.
Ecological networks are very complex - who would’ve thought!.