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 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 and species distributions, 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.
Recent representative publications
- Bellvé, A.M., Wilmshurst, J.M., Wood, J.R., Whitehead, E., Scofield, RR.P., Worthy, T.H. Gaskin, C.P. & Perry, G.L.W. 2025 Burrowing into the past: extending niche space models of Procellariiform breeding grounds by merging fossil and historic data. Diversity and Distributions 31: e70032. Open access.
- Simpkins, C.E., Bellingham, P.J., Reihana, K. Brock, J.M.R. & Perry, G.L.W. 2025. Evaluating the effects of two newly emerging plant pathogens on northern Aotearoa-New Zealand forests using an individual-based model. Ecological Modelling 500, 110938. Open access.
- Lester, P.J., O’Sullivan, D., & Perry, G.L.W. 2023. Gene drives for invasive wasp control: Extinction is unlikely, with suppression dependent on dispersal and growth rates. Ecological Applications, e2912. Open access.
A full post-2021 publication list for the P-Lab is here.