Computational ecology

The P-lab uses a wide range of tools to explore a diverse suite of ecological questions.  Nearly all of our research is underpinned by some form of empirical investigation (field and/or lab work) but we also make extensive use of statistical and simulation modelling to synthesise and make sense of these ‘messy’ data.  To this end, we have used machine-learning methods to reconstruct disturbance patterns, statistical modelling to understand the role of tree-ferns in NZ’s temperate forests, spatial simulation to unravel vegetation-fire feedbacks, and individual (agent)-based models to explore forest dynamics, seed dispersal by large ratites, and the movement of seabirds.  We are (generally) agnostic about languages and platforms, but most of us tend to use R, Python and/or NetLogo.