Applications of digital imaging and analysis in seabird monitoring and research

Abstract

Rapid advances in digital imaging technology offer efficient and cost‐effective methods for measuring seabird abundance, breeding success, phenology, survival and diet. These methods can facilitate understanding of long‐term population trends, and the design and implementation of successful conservation strategies. This paper reviews the suitability of satellites, manned aircraft, unmanned aerial vehicles (UAVs), and fixed‐position, handheld and animal‐borne cameras for recording digital photographs and videos used to measure seabird demographic and behavioural parameters. It considers the disturbance impacts, accuracy of results obtained, cost‐effectiveness and scale of monitoring possible compared with ‘traditional’ fieldworker methods. Given the ease of collecting large amounts of imagery, image processing is an important step in realizing the potential of this technology. The effectiveness of manual, semi‐automated and automated image processing is also reviewed. Satellites, manned aircraft and UAVs have most commonly been used for population counts. Spatial resolution is lowest in satellites, limiting monitoring to large species and those with obvious signs of presence, such as penguins. Conversely, UAVs have the highest spatial resolution, which has allowed fine‐scale measurements of foraging behaviour. Time‐lapse cameras are more cost‐effective for collecting time‐series data such as breeding success and phenology, as human visits are only required infrequently for maintenance. However, the colony of interest must be observable from a single vantage point. Handheld, animal‐borne and motion‐triggered cameras have fewer cost‐effective uses but have provided information on seabird diet, foraging behaviour and nest predation. The last of these has been important for understanding the impact of invasive mammals on seabird breeding success. Advances in automated image analysis are increasing the suitability of digital photography and videography to facilitate and/or replace traditional seabird monitoring methods. Machine‐learning algorithms, such as Pengbot, have allowed rapid identification of birds, although training requires thousands of pre‐annotated photographs. Digital imaging has considerable potential in seabird monitoring, provided that appropriate choices are available for both image capture technology and image processing. These technologies offer opportunities to collect data in remote locations and increase the number of sites monitored. The potential to include such solutions in seabird monitoring and research will develop as the technology evolves, which will be of benefit given funding challenges in monitoring and conservation.

Spatial and temporal variation in foraging of breeding red‐throated divers

“…Due to the remote locations of many of the nests and the extreme sensitivity of the species to disturbance, we were not able to regularly monitor RTD nests across all sites, both to minimise the effect our attendance had on behaviour and minimise ethical concerns arising from disturbance. Future study could deploy remote camera traps to maximise information on nest attendance while minimising human presence (Edney and Wood 2020). In addition, the lack of precise foraging locations of birds meant we were unable to link foraging to local environmental conditions, so could not relate foraging behaviour to environmental influences such as tidal cycles and hydrographic features (Skov and Prins 2001) and future studies should try to also track birds with GPS if this can be achieved without additional disturbance.…”

Raspberry Pi nest cameras: An affordable tool for remote behavioral and conservation monitoring of bird nests

“…The use of photography and video systems to remotely monitor wildlife has become increasingly popular (see reviews : Cutler & Swann, 1999;Edney & Wood, 2020;Hereward et al, Under review;Swann et al, 2004;Trolliet et al, 2014). This is because remote-monitoring cameras can greatly reduce the time and effort required to collect observational field data and are typically less invasive than direct observation by researchers in the field (Cutler & Swann, 1999;Trolliet et al, 2014).…”

“…There are a wide range of camera systems available (see reviews: Cutler & Swann, 1999;Edney & Wood, 2020;Hereward et al, Under review;Swann et al, 2004;Trolliet et al, 2014), but these can be split broadly into (a) commercially (vendor) built systems (e.g., Meek & Pittet, 2012;Trolliet et al, 2014) or (b) bespoke (user-built) microcomputer systems (Allan et al, 2018;Greenville & Emery, 2016;Johnston & Cox, 2017).…”

Using camera traps to determine occupancy and breeding in burrowing seabirds

“…Use of camera traps in ecological studies has become common because they can provide time series data on the activity of individuals (Wearn and Glover-Kapfer, 2019). They have been used to measure seabird breeding phenology and provide indices of abundance for above-ground nesting species, but their use in studies of burrowing seabirds has mainly been limited to understanding predation pressures by invasive alien species (Edney and Wood, 2020). Fischer et al (2017) assessed the suitability of camera traps for studying diving-petrels Pelecanoides spp.…”