I work as a senior statistician within the Offshore Renewables group at BioSS.

My work focuses on the application of (spatial) predictive models to real-world wildlife management problems, with an emphasis on large marine vertebrates such as cetaceans, seabirds, and sharks across different ecosystems (coastal, offshore), spatial scales (local to global), and bioregions (temperate to tropical).

I am particularly interested in the development of statistical methods that can inform impact assessments in the marine environment, and in the design of software tools for decision support. In the past, this has typically involved combinations of species distribution modelling, Bayesian hierarchical modelling, agent-based modelling, and population modelling.

I also have general interests in abundance estimation, integrated population models, and GIS. I currently act as Associate Editor for Methods in Ecology and Evolution, and as Review Editor for Endangered Species Research.

Recent projects/outputs include:

• Quantifying and visualising extrapolation in spatially-explicit ecological models projected into novel covariate space (dsmextra R package).
• Using reversible-jump MCMC to fit and select between Bayesian multi-species behavioural dose-response functions in cetaceans exposed to military sonar (espresso R package).
• Bioenergetic modelling to predict the population consequences of disturbance from offshore wind development on critically endangered North Atlantic right whales (narwind R package)
• Spatial analysis of citizen science and platform-of-opportunity data.
• Simulation modelling for understanding how sampling uncertainty  affects predictions of wildlife responses to noise.

Further information: pjbouchet.github.io