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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.

1. Timing of breeding, an important driver of fitness in many populations, is widely studied in the context of global change, yet despite considerable efforts to identify environmental drivers of seabird nesting phenology, for most populations we lack evidence of strong drivers. Here we adopt an alternative approach, examining the degree to which different populations positively covary in their annual phenology to infer whether phenological responses to environmental drivers are likely to be (i) shared across species at a range of spatial scales, (ii) shared across populations of a species, or (iii) idiosyncratic to populations. 2. We combined 51 long-term datasets on breeding phenology spanning 50 years from nine seabird species across 29 North Atlantic sites and examined the extent to which different populations share early versus late breeding seasons depending on a hierarchy of spatial scales comprising breeding site, small-scale region, large-scale region and the whole North Atlantic. 3. In about a third of cases we found laying dates of populations of different species sharing the same breeding site or small-scale breeding region were positively correlated, which is consistent with the hypothesis that they share phenological responses to the same environmental conditions. In comparison we found no evidence for positive phenological covariation among populations across species aggregated at larger spatial scales. 4. In general we found little evidence for positive phenological covariation between populations of a single species, and in many instances the inter-year variation specific to a population was substantial, consistent with each population responding idiosyncratically to local environmental conditions. Black-legged kittiwake (Rissa tridactyla) was the exception, with populations exhibiting positive covariation in laying dates that decayed with the distance between breeding sites, suggesting that populations may be responding to a similar driver. 5. Our

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.