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.

Ecosystem regime shifts can have severe ecological and economic consequences, making it a top priority to understand how to make systems more resilient. Theory predicts that spatial connectivity and the local environment interact to shape resilience, but empirical studies are scarce. Here, we use >7000 fish samplings from the Baltic Sea coast to test this prediction in an ongoing, spatially propagating shift in dominance from predatory fish to an opportunistic mesopredator, with cascading effects throughout the food web. After controlling for the influence of other drivers (including increasing mesopredator densities), we find that predatory fish habitat connectivity increases resilience to the shift, but only when densities of fish-eating top predators (seals, cormorants) are low. Resilience also increases with temperature, likely through boosted predatory fish growth and recruitment. These findings confirm theoretical predictions that spatial connectivity and the local environment can together shape resilience to regime shifts.

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. 

Under rapid environmental change, opportunistic species may exhibit dramatic increases in response to the altered conditions, and can in turn have large impacts on the ecosystem. One such species is the three-spined stickleback (Gasterosteus aculeatus), which has shown substantial increases in several aquatic systems in recent decades. Here, we review the population development of the stickleback in the Baltic Sea, a large brackish water ecosystem subject to rapid environmental change. Current evidence points to predatory release being the central driver of the population increases observed in some areas, while both eutrophication and climate change have likely contributed to creating more favourable conditions for the stickleback. The increasing stickleback densities have had profound effects on coastal ecosystem function by impairing the recruitment of piscivorous fish and enhancing the effects of eutrophication through promoting the production of filamentous algae. The increase poses a challenge for both environmental management and fisheries, where a substantial interest from the pelagic fisheries fleet in exploiting the species calls for urgent attention. While significant knowledge gaps remain, we suggest that the case of the Baltic Sea stickleback increase provides generalisable lessons of value for understanding and managing other coastal ecosystems under rapid change.