SEGUL go to... Sheffield!

The northern hemisphere seabird breeding is currently approaching its end; guillemots are leaping from the cliffs, pufflings are leaving their burrows and kittiwakes are fledgling from their nests.

SEGUL have had a busy season assisting with seabird fieldwork and research at numerous different colonies around the UK and Europe, but last week three members headed to the landlocked city of Sheffield.

Here Steph Harris and Ruth Dunn share their experiences of the British Ecological Society's Quantitative and Movement Ecology joint meeting.


Both the Quantitative Ecology and Movement Ecology themed days were packed with fascinating presentations, showcasing cutting-edge research in ecology. From the latest developments in spatial modelling, to integrating physiology with demography and movement, to novel bio-logging applications, a clear theme from the meeting was improving understanding of biological systems on both a larger and finer scale.

I found the broad range of talks on movement models especially interesting. Lots of people presented interesting applications of hidden Markov models (HMMs), used to characterise behaviours from time series data. Karine Heerah spoke on combining HMMs with spectral analysis to study cyclic behaviours in sea bass, while Grant Hopcraft used HMMs of wildebeest migration to show how starvation drives switches between movement and encamped phases of migration. Théo Michelot and Paul Blackwell talked about getting away from modelling behavioural switching in discrete time, and instead using continuous time to more accurately model movement.

My talk also featured use of HMMs. I’ve been working on links between personality and movement in kittiwakes breeding in Svalbard. The birds exhibit huge individual variation in their foraging movements, and our work tries to understand why. I use HMMs to identify where at-sea kittiwakes forage, and from these locations measure individual site fidelity (how consistent birds are in where they go to forage). I test how birds respond to a novel object (we use a plastic penguin toy, known as Butch) to get a measure of their personality, and see how a bird’s personality affects its foraging movements.

I really enjoyed the BES SIG, and came away with a notebook full of pointers, thoughts and ideas sparked by presentations and chats in between.


It was great to hear James Grecian, research fellow at the University of St Andrews, starting the meeting off with a plenary on his ongoing research into harp seal migration. Harp seals live in the Arctic and rely on sea ice to breed and forage and are therefore susceptible to variability in sea ice concentrations. James highlighted the importance of studying the movement of these animals throughout the whole of the annual cycle, thereby encompassing the multiple threats that they might face at different times of year.

I also explored the concept of researching year-round animal movement within the talk that I gave. Whilst I have recently published work on auk diving behaviour immediately after the breeding season, I am currently working to piece together how guillemots survive the entire annual cycle. I am using fine-scale movement data to identify whether guillemot are swimming, diving, flying or resting, whilst also researching their broad-scale winter movements and migration strategies.

I am finding that lots of guillemots stay in the North Sea – an area that James referred to as an urbanised marine environment – throughout the whole year. I am looking forward to finding out how the birds utilise this ecosystem throughout the annual cycle and how the different strategies that they employ affect how much energy they use each day.

Another talk that I enjoyed was given by Natasha Klappstein who won the Methods in Ecology and Evolution sponsored prize for the best student talk. She uses data on polar bear movement in order to construct energy landscapes.

The BES SIG provided a fantastic opportunity to hear more about how researchers are doing similar things to me with some really exciting datasets and fascinating study systems.

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