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Animal-borne sensors enable researchers to remotely track animals, their physiological state and body movements. Accelerometers, for example, have been used in several studies to measure body movement, posture, and energy expenditure, although predominantly in marine animals. In many studies, behaviour is often inferred from expert interpretation of sensor data and not validated with direct observations of the animal. The aim of this study was to derive models that could be used to classify oystercatcher (Haematopus ostralegus) behaviour based on sensor data. We measured the location, speed, and tri-axial acceleration of three oystercatchers using a flexible GPS tracking system and conducted simultaneous visual observations of the behaviour of these birds in their natural environment. We then used these data to develop three supervised classification trees of behaviour and finally applied one of the models to calculate time-activity budgets. The model based on accelerometer data developed to classify three behaviours (fly, terrestrial locomotion, and no movement) was much more accurate (cross-validation error = 0.14) than the model based on GPS-speed alone (cross-validation error = 0.35). The most parsimonious acceleration model designed to classify eight behaviours could distinguish five: fly, forage, body care, stand, and sit (cross-validation error = 0.28); other behaviours that were observed, such as aggression or handling of prey, could not be distinguished. Model limitations and potential improvements are discussed. The workflow design presented in this study can facilitate model development, be adapted to a wide range of species, and together with the appropriate measurements, can foster the study of behaviour and habitat use of free living animals throughout their annual routine.

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Climate warming challenges animals to advance their timing of reproduction [1], but many animals appear to be unable to advance at the same rate as their food species [2, 3]. As a result, mismatches can arise between the moment of largest food requirements for their offspring and peak food availability [4-6], with important fitness consequences [7]. For long-distance migrants, adjustment of phenology to climate warming may be hampered by their inability to predict the optimal timing of arrival at the breeding grounds from their wintering grounds [8]. Arrival can be advanced if birds accelerate migration by reducing time on stopover sites [9, 10], but a recent study suggests that most long-distance migrants are on too tight a schedule to do so [11]. This may be different for capital-breeding migrants, which use stopovers not only to fuel migration but also to acquire body stores needed for reproduction [12-14]. By combining multiple years of tracking and reproduction data, we show that a long-distance migratory bird (the barnacle goose, Branta leucopsis) accelerates its 3,000 km spring migration to advance arrival on its rapidly warming Arctic breeding grounds. As egg laying has advanced much less than arrival, they still encounter a phenological mismatch that reduces offspring survival. A shift toward using more local resources for reproduction suggests that geese first need to refuel body stores at the breeding grounds after accelerated migration. Although flexibility in body store use allows migrants to accelerate migration, this cannot solve the time constraint they are facing under climate warming.

Migrating birds are believed to minimize the time spent on migration rather than energy. Birds seem to maximize migration speed in different ways as a noteworthy variation in migration strategies exists. We studied migration strategies of a flight mode and feeding generalist, the Lesser Black-backed Gull Larus fuscus, using GPS-based satellite telemetry. We expected the gulls to achieve very high overall migration speeds by traveling via the shortest direct route, traveling during a large part of the day and night, and making few and short stopovers. Fourteen individuals were tracked between the Dutch breeding colony and the wintering sites in England, southern Europe and northwest Africa. The gulls did not travel via the shortest possible route but made substantial detours by their tendency to follow coasts. Although the gulls traveled during most of the day, and sometimes during the night, they did not achieve long daily distances (177 and 176 km/day in autumn and spring, respectively), which is explained by the gulls stopping frequently on travel days to forage. Furthermore, due to frequent and long migratory stopovers, their overall migration speed was among the lowest recorded for migratory birds (44 and 98 km/day, in autumn and spring, respectively). A possible explanation for the unexpected frequent stopovers and low migration speeds is that gulls do not minimize the duration of migration but rather minimize the costs of migration. Energy rather than time might be important for short-distance migrating birds, resulting in very different migration strategies compared with long-distance migrants.

The nighttime sky is increasingly illuminated by artificial light sources. Although this ecological light pollution is damaging ecosystems throughout the world, the topic has received relatively little attention. Many nocturnally migrating birds die or lose a large amount of their energy reserves during migration as a result of encountering artificial light sources. This happens, for instance, in the North Sea, where large numbers of nocturnally migrating birds are attracted to the many offshore platforms. Our aim is to develop bird-friendly artificial lighting that meets human demands for safety but does not attract and disorient birds. Our current working hypothesis is that artificial light interferes with the magnetic compass of the birds, one of several orientation mechanisms and especially important during overcast nights. Laboratory experiments have shown the magnetic compass to be wavelength dependent: migratory birds require light from the blue-green part of the spectrum for magnetic compass orientation, whereas red light (visible long-wavelength) disrupts magnetic orientation. We designed a field study to test if and how changing light color influenced migrating birds under field conditions. We found that nocturnally migrating birds were disoriented and attracted by red and white light (containing visible long-wavelength radiation), whereas they were clearly less disoriented by blue and green light (containing less or no visible longwavelength radiation). This was especially the case on overcast nights. Our results clearly open perspective for the development of bird-friendly artificial lighting by manipulating wavelength characteristics. Preliminary results with an experimentally developed bird-friendly light source on an offshore platform are promising. What needs to be investigated is the impact of bird-friendly light on other organisms than birds.

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