Dr Philipp Boersch‑Supan

Quantitative Ecologist

Research Projects

Citizen Science   Seabirds   Bayesian Inference   Seamounts & Islands   Open ocean   Disease Ecology  

Citizen Science & Bird Populations  

The British Trust for Ornithology combines professional field ornithology and a network of over 60,000 volunteers to monitor change in the environment. I am part of the scientific team analysing these rich datasets which deliver the information used to plan and assess conservation action, and to inform decision-making processes for the benefits of society, wildlife and the natural world. I am also involved in research towards new and improved statistical methods for citizen science data sets.

Papers:   Boersch-Supan et al. (2019) Robustness of simple avian population trend models
  Isaac et al. (2019) Data integration for large-scale models of species distributions

Seabird Ecology 

Bioenergetics and foraging movements of Antarctic albatrosses

Albatrosses are the largest seabirds and top-predators of the open ocean, but their numbers are declining and many species are now endangered. I am using a combination of mathematical and statistical models and several decades of observational data to understand the factors affecting the population dynamics of these birds by studying their bioenergetics and foraging strategies.

Papers:   Johnson, Boersch-Supan et al. (2017) Sampling scale and movement model identifiability
  Boersch-Supan et al. (2017) Surface temperatures of albatross eggs and nests

Find out more about this project on the Albatross Project website.
Slides from my WSC2015 talk on metabolic models for albatrosses

Foraging phenology and chick-provisioning in macaroni penguins 

With a global population of over 11 million individuals macaroni penguins are not only the most numerous penguins, but also the largest consumers of prey among all seabirds. I am using an automatic weighbridge to study body weights and foraging movements of marked and unmarked penguins at a study colony on Bird Island, South Georgia to better understand how macaronis forage during the breeding season, how they balance provisioning their chicks with the need to maintain their own body condition, and whether they modulate their foraging and migration phenology in response to local prey availability.

This work relies on a data base of several hundred thousand body mass time series collected over a decade. This poses computational challenges for data processing and analysis. I have addressed part of this challenge by creating an R wrapper for some very fast time series similarity search algorithms.

Paper: Boersch-Supan (2016): rucrdtw: Fast time series subsequence search in R
Software: rucrdtw: R Bindings for the UCR Suite

Bayesian inference for dynamic models of biological systems 

Differential equations (DEs) are commonly used to model the temporal evolution of dynamic systems in science and engineering, but statistical methods for comparing DE models to data and for parameter inference are relatively poorly developed. This is especially problematic in the presence of latent model states or parameters, when observations are noisy or when only a small number of observed time points are available.
Bayesian approaches offer a coherent framework for parameter inference that can account for multiple sources of uncertainty, while making use of prior information. This approach further offers a rigorous methodology modeling the link between unobservable model states and parameters, and observable quantities.

Paper: Boersch-Supan & Johnson (2018): Two case studies detailing Bayesian inference for dynamic energy budget models

Boersch-Supan et al. (2016): deBInfer: Bayesian inference for dynamical models of biological systems in R
Software: https://github.com/pboesu/debinfer

Ecology of seamounts and islands  

Seamounts and islands protrude into the open ocean, introducing hard boundaries to an otherwise largely unbounded habitat. Above water, they offer breeding habitat for air-breathing marine predators such as seabirds and seals. Below the waves, the abrupt topography can trap small pelagic animals, exposing them to predators and/or concentrating them on island slopes and the summits and flanks of submarine banks. I have studied seabird assemblages on islands, as well as the effect of abrupt topography on the distribution of pelagic biota and their predator-prey interactions.

Borrelle, Boersch-Supan et al. (2016): Recovery of seabirds on islands eradicated of invasive predators
Letessier TB et al. (2016): Enhanced pelagic biomass around coral atolls
Letessier TB et al. (2015): Seamount influences on mid-water shrimps (Decapoda) and gnathophausiids …

Open ocean ecology 

Oceanic scattering layers & pelagic biogeography

A substantial proportion of biomass below the photic zone is concentrated in so called sound scattering layers which can be observed with echosounders. Scattering layers are often species-rich and include animals like laternfishes, squids and deep-water prawns. They are an important prey source for predators such as tuna, oceanic sharks and marine mammals. They also play an important role in marine biogeochemical cycles. I have studied the distribution and biogeographic zonation of scattering layers in the southern Indian Ocean.

Boersch-Supan et al. (2015): The distribution of pelagic scattering layers across the Southwest Indian Ocean
Boersch-Supan et al. (2012). Elephant seal foraging dives track prey distribution, not temperature …

Marine biogeography

I have also contributed to biogeographic studies of marine animals ranging from pelagic microbes to hydrothermal vent animals.

Djurhuus, Boersch-Supan et al. (2017): Microbial biogeography tracks water-mass features
Laptikovsky V, Boersch-Supan PH et al. (2015): Cephalopods of the Southwest Indian Ocean Ridge
Rogers et al. (2012): Discovery of Southern Ocean deep-sea hydrothermal vent communities

Disease and Vector Ecology 

More recently I have become interested in building models to answer questions from disease and vector ecology, and have contributed to studies investigating vector behaviour, environmental drivers of disease prevalence, and other disease-related projects.

Ryan, Lippi, Boersch-Supan et al. 2017: Quantifying Seasonal and Diel Variation in Anopheline and Culex Human Biting Rates in Southern Ecuador
Youker-Smith, Boersch-Supan et al. 2018:Environmental drivers of ranavirus in free living amphibians in constructed ponds