GPS tracking data of Eurasian oystercatchers (Haematopusostralegus) from the Netherlands and Belgium.

We describe six datasets that contain GPS and accelerometer data of 202 Eurasian oystercatchers (Haematopusostralegus) spanning the period 2008-2021. Birds were equipped with GPS trackers in breeding and wintering areas in the Netherlands and Belgium. We used GPS trackers from the University of Amsterdam Bird Tracking System (UvA-BiTS) for several study purposes, including the study of space use during the breeding season, habitat use and foraging behaviour in the winter season, and impacts of human disturbance. To enable broader usage, all data have now been made open access. Combined, the datasets contain 6.0 million GPS positions, 164 million acceleration measurements and 7.0 million classified behaviour events (i.e., flying, walking, foraging, preening, and inactive). The datasets are deposited on the research repository Zenodo, but are also accessible on Movebank and as down-sampled occurrence datasets on the Global Biodiversity Information Facility (GBIF) and Ocean Biodiversity Information System (OBIS).

Habitat selection can reduce effects of extreme climatic events in a long-lived shorebird.

Changes in the frequency of extreme climatic events (ECEs) can have profound impacts on individual fitness by degrading habitat quality. Organisms may respond to such changes through habitat selection, favouring those areas less affected by ECEs; however, documenting habitat selection in response to ECEs is difficult in the wild due to the rarity of such events and the long-term biological data required. Sea level rise and changing weather patterns over the past decades have led to an increase in the frequency of coastal flooding events, with serious consequences for ground nesting shorebirds. Shorebirds therefore present a useful natural study system to understand habitat selection as a response to ECEs. We used a 32-year study of the Eurasian oystercatcher (Haematopus ostralegus) to investigate whether habitat selection can lead to an increase in nest elevation and minimize the impacts of coastal flooding. The mean nest elevation of H. ostralegus has increased during the last three decades. We hypothesized that this change has been driven by changes in H. ostralegus territory settlement patterns over time. We compared various possible habitat selection cues to understand what information H. ostralegus might use to inform territory settlement. There was a clear relationship between elevation and territory settlement in H. ostralegus. In early years, settlements were more likely at low elevations but in more recent years the likelihood of settlement was similar between high and low elevation areas. Territory settlement was associated with conspecific fledgling output and conspecific density. Settlement was more likely in areas of high density and areas with high fledgling output. This study shows that habitat selection can minimize the effects of increasingly frequent ECEs. However, it seems unlikely that the changes we observe will fully alleviate the consequences of anthropogenic climate change. Rates of nest elevation increase were insufficient to track current increases in maximum high tide (0.5 vs. 0.8 cm/year). Furthermore, habitat selection cues that rely on information from previous breeding seasons (e.g. conspecific fledgling output) may become ineffective as ECEs become more frequent and environmental predictability is diminished.

No phenotypic plasticity in nest-site selection in response to extreme flooding events.

Phenotypic plasticity is a crucial mechanism for responding to changes in climatic means, yet we know little about its role in responding to extreme climatic events (ECEs). ECEs may lack the reliable cues necessary for phenotypic plasticity to evolve; however, this has not been empirically tested. We investigated whether behavioural plasticity in nest-site selection allows a long-lived shorebird (Haematopus ostralegus) to respond to flooding. We collected longitudinal nest elevation data on individuals over two decades, during which time flooding events have become increasingly frequent. We found no evidence that individuals learn from flooding experiences, showing nest elevation change consistent with random nest-site selection. There was also no evidence of phenotypic plasticity in response to potential environmental cues (lunar nodal cycle and water height). A small number of individuals, those nesting near an artificial sea wall, did show an increase in nest elevation over time; however, there is no conclusive evidence this occurred in response to ECEs. Our study population showed no behavioural plasticity in response to changing ECE patterns. More research is needed to determine whether this pattern is consistent across species and types of ECEs. If so, ECEs may pose a major challenge to the resilience of wild populations.This article is part of the themed issue 'Behavioural, ecological and evolutionary responses to extreme climatic events'.

Hampered performance of migratory swans: intra- and inter-seasonal effects of avian influenza virus.

The extent to which animal migrations shape parasite transmission networks is critically dependent on a migrant's ability to tolerate infection and migrate successfully. Yet, sub-lethal effects of parasites can be intensified through periods of increased physiological stress. Long-distance migrants may, therefore, be especially susceptible to negative effects of parasitic infection. Although a handful of studies have investigated the short-term, transmission-relevant behaviors of wild birds infected with low-pathogenic avian influenza viruses (LPAIV), the ecological consequences of LPAIV for the hosts themselves remain largely unknown. Here, we assessed the potential effects of naturally-acquired LPAIV infections in Bewick's swans, a long-distance migratory species that experiences relatively low incidence of LPAIV infection during early winter. We monitored both foraging and movement behavior in the winter of infection, as well as subsequent breeding behavior and inter-annual resighting probability over 3 years. Incorporating data on infection history we hypothesized that any effects would be most apparent in naïve individuals experiencing their first LPAIV infection. Indeed, significant effects of infection were only seen in birds that were infected but lacked antibodies indicative of prior infection. Swans that were infected but had survived a previous infection were indistinguishable from uninfected birds in each of the ecological performance metrics. Despite showing reduced foraging rates, individuals in the naïve-infected category had similar accumulated body stores to re-infected and uninfected individuals prior to departure on spring migration, possibly as a result of having higher scaled mass at the time of infection. And yet individuals in the naïve-infected category were unlikely to be resighted 1 year after infection, with 6 out of 7 individuals that never resighted again compared to 20 out of 63 uninfected individuals and 5 out of 12 individuals in the re-infected category. Collectively, our findings indicate that acute and superficially harmless infection with LPAIV may have indirect effects on individual performance and recruitment in migratory Bewick's swans. Our results also highlight the potential for infection history to play an important role in shaping ecological constraints throughout the annual cycle.

Optimizing acceleration-based ethograms: the use of variable-time versus fixed-time segmentation.

BACKGROUND: Animal-borne accelerometers measure body orientation and movement and can thus be used to classify animal behaviour. To univocally and automatically analyse the large volume of data generated, we need classification models. An important step in the process of classification is the segmentation of acceleration data, i.e. the assignment of the boundaries between different behavioural classes in a time series. So far, analysts have worked with fixed-time segments, but this may weaken the strength of the derived classification models because transitions of behaviour do not necessarily coincide with boundaries of the segments. Here we develop random forest automated supervised classification models either built on variable-time segments generated with a so-called 'change-point model', or on fixed-time segments, and compare for eight behavioural classes the classification performance. The approach makes use of acceleration data measured in eight free-ranging crab plovers Dromas ardeola. RESULTS: Useful classification was achieved by both the variable-time and fixed-time approach for flying (89% vs. 91%, respectively), walking (88% vs. 87%) and body care (68% vs. 72%). By using the variable-time segment approach, significant gains in classification performance were obtained for inactive behaviours (95% vs. 92%) and for two major foraging activities, i.e. handling (84% vs. 77%) and searching (78% vs. 67%). Attacking a prey and pecking were never accurately classified by either method. CONCLUSION: Acceleration-based behavioural classification can be optimized using a variable-time segmentation approach. After implementing variable-time segments to our sample data, we achieved useful levels of classification performance for almost all behavioural classes. This enables behaviour, including motion, to be set in known spatial contexts, and the measurement of behavioural time-budgets of free-living birds with unprecedented coverage and precision. The methods developed here can be easily adopted in other studies, but we emphasize that for each species and set of questions, the presented string of work steps should be run through.

From sensor data to animal behaviour: an oystercatcher example.

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.

Poor environmental tracking can make extinction risk insensitive to the colour of environmental noise.

The relative importance of environmental colour for extinction risk compared with other aspects of environmental noise (mean and interannual variability) is poorly understood. Such knowledge is currently relevant, as climate change can cause the mean, variability and temporal autocorrelation of environmental variables to change. Here, we predict that the extinction risk of a shorebird population increases with the colour of a key environmental variable: winter temperature. However, the effect is weak compared with the impact of changes in the mean and interannual variability of temperature. Extinction risk was largely insensitive to noise colour, because demographic rates are poor in tracking the colour of the environment. We show that three mechanisms-which probably act in many species-can cause poor environmental tracking: (i) demographic rates that depend nonlinearly on environmental variables filter the noise colour, (ii) demographic rates typically depend on several environmental signals that do not change colour synchronously, and (iii) demographic stochasticity whitens the colour of demographic rates at low population size. We argue that the common practice of assuming perfect environmental tracking may result in overemphasizing the importance of noise colour for extinction risk. Consequently, ignoring environmental autocorrelation in population viability analysis could be less problematic than generally thought.

Effects of climate change and variability on population dynamics in a long-lived shorebird.

Climate change affects both the mean and variability of climatic variables, but their relative impact on the dynamics of populations is still largely unexplored. Based on a long-term study of the demography of a declining Eurasian Oystercatcher (Haematopus ostralegus) population, we quantify the effect of changes in mean and variance of winter temperature on different vital rates across the life cycle. Subsequently, we quantify, using stochastic stage-structured models, how changes in the mean and variance of this environmental variable affect important characteristics of the future population dynamics, such as the time to extinction. Local mean winter temperature is predicted to strongly increase, and we show that this is likely to increase the population's persistence time via its positive effects on adult survival that outweigh the negative effects that higher temperatures have on fecundity. Interannual variation in winter temperature is predicted to decrease, which is also likely to increase persistence time via its positive effects on adult survival that outweigh the negative effects that lower temperature variability has on fecundity. Overall, a 0.1 degrees C change in mean temperature is predicted to alter median time to extinction by 1.5 times as many years as would a 0.1 degrees C change in the standard deviation in temperature, suggesting that the dynamics of oystercatchers are more sensitive to changes in the mean than in the interannual variability of this climatic variable. Moreover, as climate models predict larger changes in the mean than in the standard deviation of local winter temperature, the effects of future climatic variability on this population's time to extinction are expected to be overwhelmed by the effects of changes in climatic means. We discuss the mechanisms by which climatic variability can either increase or decrease population viability and how this might depend both on species' life histories and on the vital rates affected. This study illustrates that, for making reliable inferences about population consequences in species in which life history changes with age or stage, it is crucial to investigate the impact of climate change on vital rates across the entire life cycle. Disturbingly, such data are unavailable for most species of conservation concern.

Fluctuating selection and the maintenance of individual and sex-specific diet specialization in free-living oystercatchers.

Fluctuating and disruptive selection are important mechanisms for maintaining intrapopulation trait variation. Nonetheless, few field studies quantify selection pressures over long periods and identify what causes them to fluctuate. Diet specialists in oystercatchers differ in short-term payoffs (intake), but their long-term payoffs are hypothesized to be condition dependent. We test whether phenotypic selection on diet specialization fluctuates between years due to the frequency of specialists, competitor density, prey abundance, and environmental conditions. Short-term payoffs proved to be poor predictors of long-term fitness payoffs of specialization. Sex-differences in diet specialization were maintained by opposing directional fecundity and viability selection between the sexes. Contrasting other studies, selection on individual diet specialization was neither negative frequency- or density-dependent nor dependent on prey abundance. Notwithstanding, viability selection fluctuated strongly (stabilizing<-->disruptive) over the 26-year study period: slightly favoring generalists in most years, but strongly disfavoring generalists in rare harsh winters, suggesting generalists cannot cope with extreme conditions. Although selection fluctuated, mean selection on specialists was weak, which can explain how individual specialization can persist over long periods. Because rare events can dramatically affect long-term selective landscapes, more care should be taken to match the timescale of evolutionary studies to the temporal variability of critical environmental conditions.