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
Are we writing scientific articles so as to fit a certain rhyme scheme i.e. is the art of the free verse dying out?
Detecting spatial boundaries between communities is fun - what about if we try and do the same for ecological networks
Some thoughts on why RStudio is great and makes reproducibility that little bit easier to attain. In retrospect this turned into a RMarkdown post…
Wombling (not about actual wombats); edge detection; spatial boundaries; and how we can apply this to ecological networks.
What does the future of predicting networks look like? And what types of questions should we be asking?
Singular Value Decomposition; network complexity; network prediction and possibly some network assembly.