In 2008, we built an artificial nesting construction for Common Murres Uria aalge, the Karlsö Auk Lab, on an island in the Baltic Sea (Hentati-Sundberg et al., 2012). The aim was to create an environment in which the birds could be readily monitored and accessed, and technological equipment easily installed. In this current paper, we report on murre recruitment to the Auk Lab over the first decade, assess the performance of the birds living on the lab compared to natural cliff ledges, and revisit the original research questions. We conclude that the tremendous developments in sensor technology (video surveillance, automated scales, thermal cameras, weather sensors) and artificial intelligence was not anticipated 10 years ago. Several major scientific insights, including the effects of eagle disturbances and heat stress on the murres, have come as surprises and have been driven mainly by technology's potential to deliver data with a resolution unattainable using traditional field studies. The dramatic increase in data volumes has partly been paired by automated analysis methods, but some aspects of the new technology, notably individual identification, have been more difficult than anticipated. The investment costs for information technology infrastructure, data storage, and processing capacity have also been substantial. We finish the paper by sketching out new research questions that will guide the next decade at the Auk Lab and repeating an invitation for research collaborations beyond our planned research focus.

Many key ecological dynamics such as biomass distributions are only detectable on a fine spatiotemporal scale. Autonomous data collection with Unmanned Surface Vehicles (USV) creates new possibilities for cost efficient and high-resolution aquatic data sampling. However, the spatial coverage and sampling resolution remain uncertain due to the novelty of the technology. Further, there is no established method for analysing such fine-scale autocorrelated data without aggregation, potentially compromising data resolution. We here used a USV with an echosounder, a conductivity-temperature sensor and a flourometer to collect data from April–July 2019–2023 in a 60x80km area in the central Baltic Sea. The USV covered a total distance of 8000 nmi, over 42–81 days per year, with an average speed of 0.5 m/s. We combined the hydroacoustic data with publicly available oceanographic data from Copernicus Marine Service Information (CMSI) to describe seasonal distribution dynamics of a small pelagic fish community. Key oceanographic variables collected by the USV were correlated with CMSI estimates at daily/monthly resolution, respectively, to test for suitability to scale (Temperature 0.99/0.97; Salinity −0.77/−0.26; Chlorophyll-a 0.12/0.28). We investigated two approaches of Species Distribution Models (SDMs): generalized additive models (GAM) versus spatiotemporal generalized linear mixed effect models (GLMM). The GLMMs explained the observed data better than the GAMs (R2 0.31 and 0.20, respectively). The addition of environmental variables increased the explanatory capability of GAM and GLMM by 25 % and ∼ 3 %, respectively. Due to the high data resolution, we found significant amounts of positive autocorrelation (R: 0.05–0.30) across more than 50 sequential observations (>6 hours). However, we found that diel patterns in fish detection strongly affected the abundance estimates due to vertically migrating species hiding in the ‘acoustic dead zone’ near the seabed. Such dynamics could only be estimated and corrected for in predictions on the high-resolution data, complicating the trade-off between autocorrelation and high-resolution for SDMs. We compared estimates and effect sizes/directions in identical SDMs on 2x2km/month aggregated (i.e non-autocorrelated) observations and non-aggregated (i.e. autocorrelated) observations, and found relatively little difference in spatiotemporal estimates (r = 0.80). For the first time, we predicted the distribution of a small pelagic fish community at a high spatial resolution, in an area essential to breeding top predators, opening up for new applications in ecological studies locally and globally.

Climate change research on seabirds has so far focused mainly on indirect effects acting via impacts at lower trophic levels. However, seabirds that breed in exposed sites may also be vulnerable to direct impacts from extreme weather events such as heatwaves, which are projected to increase in both severity and frequency with climate change. Yet there are relatively few field studies of how breeding seabirds respond to heatwaves. Here, we used video footage from a breeding colony of common guillemots Uria aalge in the Baltic Sea over 4 consecutive breeding seasons (2019−2022) to explore responses to air temperature and sun exposure. We found a positive relationship between temperature and 2 thermoregulatory behaviours: panting and postural changes. In addition, we show that as temperatures increase, breeding partners spend less time together at the colony. At the highest temperatures, some birds even temporarily abandon their eggs and chicks. Of 48 breeding failures recorded on video over 4 breeding seasons, we documented 13 cases directly associated with heat stress (corresponding to ca. 9% of all 150 breeding attempts recorded); 11 of these occurred during 2 periods with sunshine and particularly high temperatures in 2020 and 2022. Using a larger data set (>500 breeding attempts over 12 seasons), we also identified a clear increase in the probability of egg loss at higher temperatures. As such, the responses of breeding seabirds to heatwaves could have important demographic consequences in some populations, especially as heatwaves continue to increase in frequency and magnitude.

Ecological research and monitoring need to be able to rapidly convey information that can form the basis of scientifically sound management. Automated sensor systems, especially if combined with artificial intelligence, can contribute to such rapid high-resolution data retrieval. Here, we explore the prospects of automated methods to generate insights for seabirds, which are often monitored for their high conservation value and for being sentinels for marine ecosystem changes. We have developed a system of video surveillance combined with automated image processing, which we apply to common murres Uria aalge. The system uses a deep learning algorithm for object detection (YOLOv5) that has been trained on annotated images of adult birds, chicks and eggs, and outputs time, location, size and confidence level of all detections, frame-by-frame, in the supplied video material. A total of 144 million bird detections were generated from a breeding cliff over three complete breeding seasons (2019–2021). We demonstrate how object detection can be used to accurately monitor breeding phenology and chick growth. Our automated monitoring approach can also identify and quantify rare events that are easily missed in traditional monitoring, such as disturbances from predators. Further, combining automated video analysis with continuous measurements from a temperature logger allows us to study impacts of heat waves on nest attendance in high detail. Our automated system thus produces comparable, and in several cases significantly more detailed, data than those generated from observational field studies. By running in real time on the camera streams, it has the potential to supply researchers and managers with high-resolution up-to-date information on seabird population status. We describe how the system can be modified to fit various types of ecological research and monitoring goals and thereby provide up-to-date support for conservation and ecosystem management. 

Density-dependent prey depletion around breeding colonies has long been considered an important factor controlling the population dynamics of colonial animals.1, 2, 3, 4 Ashmole proposed that as seabird colony size increases, intraspecific competition leads to declines in reproductive success, as breeding adults must spend more time and energy to find prey farther from the colony.¹ Seabird colony size often varies over several orders of magnitude within the same species and can include millions of individuals per colony.^5,6 As such, colony size likely plays an important role in determining the individual behavior of its members and how the colony interacts with the surrounding environment.⁶ Using tracking data from murres (Uria spp.), the world’s most densely breeding seabirds, we show that the distribution of foraging-trip distances scales to colony size^0.33 during the chick-rearing stage, consistent with Ashmole’s halo theory.^1,2 This pattern occurred across colonies varying in size over three orders of magnitude and distributed throughout the North Atlantic region. The strong relationship between colony size and foraging range means that the foraging areas of some colonial species can be estimated from colony sizes, which is more practical to measure over a large geographic scale. Two-thirds of the North Atlantic murre population breed at the 16 largest colonies; by extrapolating the predicted foraging ranges to sites without tracking data, we show that only two of these large colonies have significant coverage as marine protected areas. Our results are an important example of how theoretical models, in this case, Ashmole’s version of central-place-foraging theory, can be applied to inform conservation and management in colonial breeding species.

The widespread lockdowns put in place to limit the spread of the new coronavirus disease (COVID-19) offers a rare opportunity in understanding how human presence influence ecosystems. Using data from long-term seabird monitoring, we reveal a previously concealed guarding effect by tourist groups on an iconic seabird colony in the Baltic Sea. The absence of tourists in 2020 lead to a sevenfold increase in presence of white-tailed eagles Haliaeetus albicilla, a sevenfold increase in their disturbance of breeding common murres Uria aalge and causing 26% lower murre productivity than the long-term average. Eagles did not prey on murres, but their frequent disturbances delayed egg laying and facilitated egg predation from herring gulls Larus argentatus and hooded crows Corvus cornix. Based on our findings, we suggest that human presence could be used as a strategic measure in guarding seabird colonies, and that a social-ecological systems perspective is vital for long-term success in protected area management.

The global lockdown to mitigate COVID-19 pandemic health risks has altered human interactions with nature. Here, we report immediate impacts of changes in human activities on wildlife and environmental threats during the early lockdown months of 2020, based on 877 qualitative reports and 332 quantitative assessments from 89 different studies. Hundreds of reports of unusual species observations from around the world suggest that animals quickly responded to the reductions in human presence. However, negative effects of lockdown on conservation also emerged, as confinement resulted in some park officials being unable to perform conservation, restoration and enforcement tasks, resulting in local increases in illegal activities such as hunting. Overall, there is a complex mixture of positive and negative effects of the pandemic lockdown on nature, all of which have the potential to lead to cascading responses which in turn impact wildlife and nature conservation. While the net effect of the lockdown will need to be assessed over years as data becomes available and persistent effects emerge, immediate responses were detected across the world. Thus, initial qualitative and quantitative data arising from this serendipitous global quasi-experimental perturbation highlights the dual role that humans play in threatening and protecting species and ecosystems. Pathways to favorably tilt this delicate balance include reducing impacts and increasing conservation effectiveness.

Biologging devices are providing detailed insights into the behaviour and movement of animals in their natural environments. It is usually assumed that this method of gathering data does not impact on the behaviour observed. However, potential negative effects on birds have rarely been investigated before field-based studies are initiated. Seabirds which both fly and use pursuit diving may be particularly sensitive to increases in drag and load resulting from carrying biologging devices. We studied chick-rearing adult common guillemots Uria aalge equipped with and without back-mounted GPS tags over short deployments of a few days. Concurrently guillemots carried small leg-mounted TDR devices (time-depth recorders) providing activity data throughout. Changes in body mass and breeding success were followed for device equipped and control guillemots. At the colony level guillemots lost body mass throughout the chick-rearing period. When-equipped with the additional GPS tag, the guillemots lost mass at close to twice the rate they did when equipped with only the smaller leg-mounted TDR device. The elevated mass loss suggests an impact on energy expenditure or foraging performance. When equipped with GPS tags diving performance, time-activity budgets and daily patterns of activity were unchanged, yet dive depth distributions differed. We review studies of tag-effects in guillemots Uria sp. finding elevated mass loss and reduced chick-provisioning to be the most commonly observed effects. Less information is available for behavioural measures, and results vary between studies. In general, small tags deployed over several days appear to have small or no measurable effect on the behavioural variables commonly observed in most guillemot tagging studies. However, there may still be impacts on fitness via physiological effects and/or reduced chick-provisioning, while more detailed measures of behaviour (e.g. using accelerometery) may reveal effects on diving and flight performance.

In long-lived species, such as seabirds, immature survival is the most important life history parameter after adult survival. The assessment of immature survival has often been difficult due to extended periods in which young birds remain unobservable at sea. This study presents results on survival of immature Common Murre (Uria aalge) obtained from an extensive mark-recapture study of a large colony at Stora Karlso in the Baltic Sea, Sweden. This colony, in contrast with other colonies, has the unique feature that many 1-year-old birds return to the colony (12%). Between 2006 and 2016, 28,930 chicks were marked at fledging, of which 5,493 individuals were later resighted in the colony. Annual survival and recapture probabilities were estimated using Bayesian Cormack-Jolly-Seber models with four age classes for survival probability, and recapture probability being age and time dependent. Informative prior distributions were used to correct partial observability problems in older age classes (observed at breeding ledges). The estimated survival probability of 1-year-old birds was 0.53 (95% CI = 0.49-0.58), 2-year-old birds was 0.87 (0.79-0.96), 3-year-old birds was 0.96 (0.90-0.99), and 4-to-10-year old bird survival probability was 0.63 (0.61-0.64). Survival estimates for younger age classes were consistent with previous studies. Several biological factors may contribute to the observed decline in survival for older age classes.

Capsule: Foraging behaviour in the Razorbill Alca torda during breeding was similar to that found elsewhere, aside from dive shape.

Aims: To investigate the foraging behaviour of Razorbills during the breeding season at the largest colony in the central Baltic Sea.

Methods: A combination of global positioning system (GPS) and time-depth recorder (TDR) devices were used on Razorbills breeding on the island of Stora Karlso, Baltic Sea, during the chick-rearing period.

Results: Five GPS tracks and nine TDR logs were retrieved from 12 Razorbills, and 7399 dives were analysed. Razorbills foraged south and southwest of the colony. Maximum and mean (+/- sd) foraging range from the colony was 72.7 km and 13.1 +/- 13.5 km, respectively. Mean dive depth (15.3 +/- 2.4 m) and duration (53.1 +/- 8.5 s) were similar to those of a more southern Baltic Sea Razorbill colony. Dive depth had a bimodal distribution, with 70% of dives deeper than 10 m and 30% shallower than 10 m. There was a clear diel foraging pattern with 89% of dives occurring during daytime and a higher proportion of shallow dives at night. Unexpectedly, dives were primarily U-shaped. The Razorbills spent 31% of their overall time activity budget flying or diving.

Conclusion: Aside from dive shape, foraging behaviour was consistent with that reported at other colonies of Razorbills. Inconsistency in dive shape may be due to a bimodal foraging strategy, local prey behaviour or competition with the Common Guillemot Uria aalge.