Interspecific variation in non-breeding aggregation: a multi-colony tracking study of two sympatric seabirds

Abstract

Migration is a widespread strategy for escaping unfavourable conditions during winter, but the extent to which populations that segregate during the breeding season aggregate during the non-breeding season is poorly understood. Low non-breeding season aggregation may be associated with higher likelihood of overlap with threats, but with fewer populations affected, whereas high aggregation may result in a lower probability of exposure to threats, but higher overall severity. We investigated non-breeding distributions and extent of population aggregation in 2 sympatrically breeding auks. We deployed geolocation-immersion loggers on common guillemots Uria aalge and razorbills Alca torda at 11 colonies around the northern UK and tracked their movements across 2 non-breeding seasons (2017-18 and 2018-19). Using 290 guillemot and 135 razorbill tracks, we mapped population distributions of each species and compared population aggregation during key periods of the non-breeding season (post-breeding moult and mid-winter), observing clear interspecific differences. Razorbills were largely distributed in the North Sea, whereas guillemot distributions were spread throughout Scottish coastal waters and the North, Norwegian and Barents Seas. We found high levels of aggregation in razorbills and a strong tendency for colony-specific distributions in guillemots. Therefore, razorbills are predicted to have a lower likelihood of exposure to marine threats, but more severe potential impact due to the larger number of colonies affected. This interspecific difference may result in divergent population trajectories, despite the species sharing protection at their breeding sites. We highlight the importance of taking whole-year distributions into account in spatial planning to adequately protect migratory species.

Modelling and mapping how common guillemots balance their energy budgets over a full annual cycle

“…By applying our methodology to populations of other mobile, wild animals, it will become increasingly possible to generate temporally specific energy gain surfaces at a regional, and even global, level. Producing energy gain surfaces (like those in Figure 3) not only has benefits with regards to the management of both terrestrial and marine resources (Cury et al, 2011; Wood et al, 2019), but also has ecological significance due to the dynamic interspecific and intraspecific competition pressures that occur as species and populations mix throughout their annual cycles (Buckingham et al, 2022; Frederiksen et al, 2012; González‐Solís et al, 2007).…”

Temporal and spatial variability in availability bias has consequences for marine bird abundance estimates during the non-breeding season

“…Dive incidences were classified as occasions where time-depth-recorder depth values exceeded 1 m. To categorise dive incidences as occurring during either daylight, twilight, or nighttime, we extracted time- and population-specific area estimates. To do this, we obtained centroids of each population’s monthly non-breeding distribution from previous work using light-based geolocator devices (Buckingham et al, 2022, 2023; Duckworth et al, 2022; Harris et al, 2010) (Supporting Information S1). We used the ‘ oce ’ R package to extract sun elevation angles at these areas and categorised each dive incidence as occurring during daylight (sun was >0 degrees above the horizon), twilight (sun was 0–15 degrees below the horizon), or nighttime (sun was >15 degrees below the horizon) accordingly.…”

Energetic synchrony throughout the non‐breeding season in common guillemots from four colonies

“…Two locations per day were derived from the geolocators using the R package 'probGLS' (Merkel et al 2016) following the methods from Buckingham et al (2022a). ProbGLS uses an iterative algorithm to determine the most likely track based on light (with day length used to infer latitude and timing of noon used to infer longitude), salt water immersion and temperature data sampled by the geolocator.…”

“…We studied guillemots from four UK breeding colonies, with two located on the west coast of Scotland and two on the east (Supporting information). Guillemots that breed on the same UK coastline are likely to have more similar non‐breeding distributions, as they typically remain distributed in waters on the same side of the UK that they breed on throughout the annual cycle (Buckingham et al 2022a). However, there are fine‐scale environmental differences between the west and east coasts of the UK; for example, environmental heterogeneity is generally greater off the west coast of the UK than the east coast (Trevail et al 2019), water depth is slightly higher off the west coast of the UK (Supporting information), and there is variation in temporal patterns of sea surface temperature between the coasts, with waters off the west coast of the UK typically cooler during late summer, but warmer during mid‐winter (Supporting information).…”