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.


  • Computational approaches to ecological questions
  • FAIR and Open Science
  • Data visualisation
  • Dabbling in artistic pursuits


  • MSc in Ecology and Biodiversity, 2020

    Stockholms Universitet | Sweden

  • BSc (Hons) in Plant Sciences, 2017

    University of Pretoria | South Africa




Plant Functional Traits Courses


Poisot Lab

Quantitative and computational ecology lab headed by Timothée Poisot

Recent Publications

From a crisis to an opportunity: Eight insights for doing science in the Covid-19 era and beyond

The COVID-19 crisis has forced researchers in Ecology to change the way we work almost overnight. Nonetheless, the pandemic has …
From a crisis to an opportunity: Eight insights for doing science in the Covid-19 era and beyond



Project Wombat

Wombling (not about actual wombats), edge detection, spatial boundaries and how we can apply this to ecological networks.

Making better predictions of ecological networks through machine learning (done right)

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.

The complexity of ecological networks using SVD entropy

Ecological networks are very complex - who would’ve thought!.


An R4DS weekly data project initiative emphasising the use of tidyverse to summarise and visualise data