By Alice Edney, DPhil Zoology
What comes to mind when you hear the word ‘seagull’? A large, noisy bird that steals chips and ice cream at the beach? Or perhaps a small bird found on rugged coastal cliffs, flying large distances across the open ocean in search of fish? I expect most are familiar with the former, however, not all seagulls are the same. Instead, there are actually many species of seabird within the gull family (Laridae), all of which could be called ‘seagulls’. This family includes the well-known Herring Gull Larus argentatus of chip stealing fame, but also many other species, including their smaller relative, the Black-legged Kittiwake Rissa tridactyla (hereafter kittiwake), which is the subject of my research (Fig 1).
Despite being less familiar among the general public, the kittiwake is the most numerous gull species (Coulson 2011). It is found throughout the Northern Hemisphere, spending the winter months at sea and returning to cliffs from March to August to breed. In spite of being the most numerous gull, kittiwakes have suffered rapid population declines over the past 40 years, which show no evidence of slowing. This worrying trend has led to their classification as ‘Vulnerable’ on the International Union for Conservation of Nature (IUCN) Red List (BirdLife International 2019). In the British Isles alone, the breeding population has decreased by 23% since the mid-1980s (Mitchell et al. 2004). However, this pattern of loss is not limited to kittiwakes. In fact, almost half of seabird species show negative population trends, making seabirds one of the most threatened groups of birds (Birdlife International 2012, Croxall et al. 2012).
Declines in seabird populations are particularly concerning, as their position near the top of the marine food chain means loss of seabirds can reflect wider disruption to marine ecosystems (Reynolds et al. 2019). Understanding where and why species like the kittiwake are affected is therefore essential for conservation at both the species and ecosystem level. So far, fisheries bycatch, invasive species and climate change have been identified as major threats to seabirds generally (Dias et al. 2019); although unravelling local threats, such as nest predation, from wider impacts, like climate change, requires data on a massive scale.
In order to assess population trends and the factors affecting seabird survival and breeding success, monitoring is needed across many locations and years. This can be prohibitively expensive in terms of time and money, and is often difficult, as many species breed in remote locations that are hard to access, especially during inclement weather (Southwell & Emmerson 2015). Consequently, the spatial and temporal scale of seabird monitoring is often small (Paleczny et al. 2015).
To help overcome these challenges, my research uses time-lapse cameras to remotely monitor breeding kittiwakes across the North Atlantic (Fig 2). The cameras take one photo per hour and can capture images in locations and at times when human observation would be almost impossible, including in harsh conditions, remote places and at night. Nevertheless, despite the excellent opportunities afforded by camera monitoring, the number of raw images collected can quickly exceed researchers’ processing capabilities, especially for a DPhil student with a deadline. One method of processing huge volumes of data is to use volunteer citizen scientists to annotate photographs, and potentially use these image annotations to later train computer algorithms to learn to recognise birds (Jones et al. 2020). This is where I need your help!
All of the images I use are uploaded onto the Zooniverse platform, as part of our citizen science project, Seabird Watch. Here, users are asked to click on birds in each image and classify them as either an ‘adult’ or ‘chick’. While my project focuses on kittiwakes, users are also asked to look out for guillemots and ‘other’ animals, like predatory Arctic foxes (Fig 3). The information from these images will enable more detailed analysis, such as determining the timing and causes of nest success versus failure, and how this might vary across species’ ranges and in response to environmental conditions. Anyone with internet access can participate and every click counts. So, why not become a seabird spy and help save seabirds from your sofa?
BirdLife International. 2012. Spotlight on seabirds. Presented as part of the BirdLife State of the world’s birds website. Available at: http://www.birdlife.org/datazone (accessed 18 December 2021).
BirdLife International. 2019. Rissa tridactyla (amended version of 2018 assessment). The IUCN Red List of Threatened Species 2019: e.T22694497A155617539. Available at: https://dx.doi.org/10.2305/IUCN.UK.2018-2.RLTS.T22694497A155617539.en (accessed 18 December 2021).
Coulson, J. 2011. The Kittiwake. London, UK: T. and A.D. Polser.
Croxall, J.P., Butchart, S.H.M., Lascelles, B., Stattersfield, A.J., Sullivan, B., Symes, A. & Taylor, P. 2012. Seabird conservation status, threats and priority actions: a global assessment. Bird Conservation International 22: 1–34.
Dias, M.P., Martin, R., Pearmain, E.J., Burfield, I.J., Small, C., Phillips, R.A., Yates, O., Lascelles, B., Borboroglu, P.G. & Croxall, J.P. 2019. Threats to seabirds: A global assessment. Biological Conservation 237: 525–537.
Jones, F.M., Arteta, C., Zisserman, A., Lempitsky, V., Lintott, C.J. & Hart, T. 2020. Processing citizen science- and machine-annotated time-lapse imagery for biologically meaningful metrics. Scientific Data 7: 1–15.
Mitchell, I., Newton, S., Ratcliffe, N., Dunn, T. 2004. Seabird Populations of Britain and Ireland: results of the Seabird 2000 census (1998-2002). London, UK: T. and A.D. Poyser.
Paleczny, M., Hammill, E., Karpouzi, V. & Pauly, D. 2015. Population Trend of the World’s Monitored Seabirds, 1950-2010. PLoS One 10.
Reynolds, S.J., Hughes, B.J., Wearn, C.P., Dickey, R.C., Brown, J., Weber, N.L., Weber, S.B., Paiva, V.H. & Ramos, J.A. 2019. Long-term dietary shift and population decline of a pelagic seabird—A health check on the tropical Atlantic? Global Change Biology 25: 1383–1394.
Southwell, C. & Emmerson, L. 2015. Remotely-operating camera network expands Antarctic seabird observations of key breeding parameters for ecosystem monitoring and management. Journal for Nature Conservation 23: 1–8.