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 and how land-use change effects native fish, spatial simulation to unravel vegetation-fire feedbacks, individual (agent)-based models to explore forest dynamics, seed dispersal by large ratites and dinosaurs (!), and the movement of seabirds, and computational text-mining methods to understand patterns of scientific production in ecology. We are (generally) agnostic about languages and platforms, but most of us tend to use R, Python, Julia, and/or NetLogo.