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Anthropogenic disturbance of wildlife is increasing globally. Generalizing impacts of disturbance to novel situations is challenging, as the tolerance of animals to human activities varies with disturbance frequency (e.g. due to habituation). Few studies have quantified frequency-dependent tolerance, let alone determined how it affects predictions of disturbance impacts when these are extrapolated over large areas. In a comparative study across a gradient of air traffic intensities, we show that birds nearly always fled (80%) if aircraft were rare, while birds rarely responded (7%) if traffic was frequent. When extrapolating site-specific responses to an entire region, accounting for frequency-dependent tolerance dramatically alters the predicted costs of disturbance: the disturbance map homogenizes with fewer hotspots. Quantifying frequency-dependent tolerance has proven challenging, but we propose that (i) ignoring it causes extrapolations of disturbance impacts from single sites to be unreliable, and (ii) it can reconcile published idiosyncratic species- or source-specific disturbance responses., (© 2024 The Author(s). Ecology Letters published by John Wiley & Sons Ltd.)

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)., (Henk-Jan van der Kolk, Peter Desmet, Kees Oosterbeek, Andrew M. Allen, Martin J. Baptist, Roeland A. Bom, Sarah C. Davidson, Jan de Jong, Hans de Kroon, Bert Dijkstra, Rinus Dillerop, Adriaan M. Dokter, Magali Frauendorf, Tanja Milotić, Eldar Rakhimberdiev, Judy Shamoun-Baranes, Geert Spanoghe, Martijn van de Pol, Gunther Van Ryckegem, Joost Vanoverbeke, Eelke Jongejans, Bruno J. Ens.)

Understanding which factors cause populations to decline begins with identifying which parts of the life cycle, and which vital rates, have changed over time. However, in a world where humans are altering the environment both rapidly and in different ways, the demographic causes of decline likely vary over time. Identifying temporal variation in demographic causes of decline is crucial to assure that conservation actions target current and not past threats. However, this has rarely been studied as it requires long time series. Here we investigate how the demography of a long-lived shorebird (the Eurasian Oystercatcher Haematopus ostralegus) has changed in the past four decades, resulting in a shift from stable dynamics to strong declines (-9% per year), and recently back to a modest decline. Since individuals of this species are likely to respond differently to environmental change, we captured individual heterogeneity through three state variables: age, breeding status, and lay date (using integral projection models). Timing of egg-laying explained significant levels of variation in reproduction, with a parabolic relationship of maximal productivity near the average lay date. Reproduction explained most variation in population growth rates, largely due to poor nest success and hatchling survival. However, the demographic causes of decline have also been in flux over the last three decades: hatchling survival was low in the 2000s but improved in the 2010s, while adult survival declined in the 2000s and remains low today. Overall, the joint action of several key demographic variables explain the decline of the oystercatcher, and improvements in a single vital rate cannot halt the decline. Conservations actions will thus need to address threats occurring at different stages of the oystercatcher's life cycle. The dynamic nature of the threat landscape is further supported by the finding that the average individual no longer has the highest performance in the population, and emphasizes how individual heterogeneity in vital rates can play an important role in modulating population growth rates. Our results indicate that understanding population decline in the current era requires disentangling demographic mechanisms, individual variability, and their changes over time., (© 2021 The Authors. Ecology published by Wiley Periodicals LLC on behalf of Ecological Society of America.)

Body condition is an important concept in behaviour, evolution and conservation, commonly used as a proxy of an individual's performance, for example in the assessment of environmental impacts. Although body condition potentially encompasses a wide range of health state dimensions (nutritional, immune or hormonal status), in practice most studies operationalize body condition using a single (univariate) measure, such as fat storage. One reason for excluding additional axes of variation may be that multivariate descriptors of body condition impose statistical and analytical challenges. Structural equation modelling (SEM) is used in many fields to study questions relating multidimensional concepts, and we here explain how SEM is a useful analytical tool to describe the multivariate nature of body condition. In this 'Research Methods Guide' paper, we show how SEM can be used to resolve different challenges in analysing the multivariate nature of body condition, such as (a) variable reduction and conceptualization, (b) specifying the relationship of condition to performance metrics, (c) comparing competing causal hypothesis and (d) including many pathways in a single model to avoid stepwise modelling approaches. We illustrated the use of SEM on a real-world case study and provided R-code of worked examples as a learning tool. We compared the predictive power of SEM with conventional statistical approaches that integrate multiple variables into one condition variable: multiple regression and principal component analyses. We show that model performance on our dataset is higher when using SEM and led to more accurate and precise estimates compared to conventional approaches. We encourage researchers to consider SEM as a flexible framework to describe the multivariate nature of body condition and thus understand how it affects biological processes, thereby improving the value of body condition proxies for predicting organismal performance. Finally, we highlight that it can be useful for other multidimensional ecological concepts as well, such as immunocompetence, oxidative stress and environmental conditions., (© 2021 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.)

Local biodiversity trends over time are likely to be decoupled from global trends, as local processes may compensate or counteract global change. We analyze 161 long-term biological time series (15-91 years) collected across Europe, using a comprehensive dataset comprising ~6,200 marine, freshwater and terrestrial taxa. We test whether (i) local long-term biodiversity trends are consistent among biogeoregions, realms and taxonomic groups, and (ii) changes in biodiversity correlate with regional climate and local conditions. Our results reveal that local trends of abundance, richness and diversity differ among biogeoregions, realms and taxonomic groups, demonstrating that biodiversity changes at local scale are often complex and cannot be easily generalized. However, we find increases in richness and abundance with increasing temperature and naturalness as well as a clear spatial pattern in changes in community composition (i.e. temporal taxonomic turnover) in most biogeoregions of Northern and Eastern Europe.

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., (© 2019 The Authors. Journal of Animal Ecology © 2019 British Ecological Society.)

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., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Arctic amplification, the accelerated climate warming in the polar regions, is causing a more rapid advancement of the onset of spring in the Arctic than in temperate regions. Consequently, the arrival of many migratory birds in the Arctic is thought to become increasingly mismatched with the onset of local spring, consequently reducing individual fitness and potentially even population levels. We used a dynamic state variable model to study whether Arctic long-distance migrants can advance their migratory schedules under climate warming scenarios which include Arctic amplification, and whether such an advancement is constrained by fuel accumulation or the ability to anticipate climatic changes. Our model predicts that barnacle geese Branta leucopsis suffer from considerably reduced reproductive success with increasing Arctic amplification through mistimed arrival, when they cannot anticipate a more rapid progress of Arctic spring from their wintering grounds. When geese are able to anticipate a more rapid progress of Arctic spring, they are predicted to advance their spring arrival under Arctic amplification up to 44 days without any reproductive costs in terms of optimal condition or timing of breeding. Negative effects of mistimed arrival on reproduction are predicted to be somewhat mitigated by increasing summer length under warming in the Arctic, as late arriving geese can still breed successfully. We conclude that adaptation to Arctic amplification may rather be constrained by the (un)predictability of changes in the Arctic spring than by the time available for fuel accumulation. Social migrants like geese tend to have a high behavioural plasticity regarding stopover site choice and migration schedule, giving them the potential to adapt to future climate changes on their flyway., (© 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.)

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'., (© 2017 The Author(s).)

The behavioural rhythms of organisms are thought to be under strong selection, influenced by the rhythmicity of the environment. Such behavioural rhythms are well studied in isolated individuals under laboratory conditions, but free-living individuals have to temporally synchronize their activities with those of others, including potential mates, competitors, prey and predators. Individuals can temporally segregate their daily activities (for example, prey avoiding predators, subordinates avoiding dominants) or synchronize their activities (for example, group foraging, communal defence, pairs reproducing or caring for offspring). The behavioural rhythms that emerge from such social synchronization and the underlying evolutionary and ecological drivers that shape them remain poorly understood. Here we investigate these rhythms in the context of biparental care, a particularly sensitive phase of social synchronization where pair members potentially compromise their individual rhythms. Using data from 729 nests of 91 populations of 32 biparentally incubating shorebird species, where parents synchronize to achieve continuous coverage of developing eggs, we report remarkable within- and between-species diversity in incubation rhythms. Between species, the median length of one parent's incubation bout varied from 1-19 h, whereas period length-the time in which a parent's probability to incubate cycles once between its highest and lowest value-varied from 6-43 h. The length of incubation bouts was unrelated to variables reflecting energetic demands, but species relying on crypsis (the ability to avoid detection by other animals) had longer incubation bouts than those that are readily visible or who actively protect their nest against predators. Rhythms entrainable to the 24-h light-dark cycle were less prevalent at high latitudes and absent in 18 species. Our results indicate that even under similar environmental conditions and despite 24-h environmental cues, social synchronization can generate far more diverse behavioural rhythms than expected from studies of individuals in captivity. The risk of predation, not the risk of starvation, may be a key factor underlying the diversity in these rhythms.

Track-while-scan bird radars are widely used in ornithological studies, but often the precise detection capabilities of these systems are unknown. Quantification of radar performance is essential to avoid observational biases, which requires practical methods for validating a radar's detection capability in specific field settings. In this study a method to quantify the detection capability of a bird radar is presented, as well a demonstration of this method in a case study. By time-referencing line-transect surveys, visually identified birds were automatically linked to individual tracks using their transect crossing time. Detection probabilities were determined as the fraction of the total set of visual observations that could be linked to radar tracks. To avoid ambiguities in assigning radar tracks to visual observations, the observer's accuracy in determining a bird's transect crossing time was taken into account. The accuracy was determined by examining the effect of a time lag applied to the visual observations on the number of matches found with radar tracks. Effects of flight altitude, distance, surface substrate and species size on the detection probability by the radar were quantified in a marine intertidal study area. Detection probability varied strongly with all these factors, as well as species-specific flight behaviour. The effective detection range for single birds flying at low altitude for an X-band marine radar based system was estimated at ~1.5 km. Within this range the fraction of individual flying birds that were detected by the radar was 0.50 ± 0.06 with a detection bias towards higher flight altitudes, larger birds and high tide situations. Besides radar validation, which we consider essential when quantification of bird numbers is important, our method of linking radar tracks to ground-truthed field observations can facilitate species-specific studies using surveillance radars. The methodology may prove equally useful for optimising tracking algorithms.

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.

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.

Migrants, such as birds or representatives of other taxa, usually make use of several stopover sites to cover the distance between their site of origin and destination. Potentially, multiple routes exist, but often little is known about the causes and consequences of alternative migration routes. Apart from their geographical distribution, the suitability of potential sites might play an important role in the animals' decisions for a particular itinerary. We used an optimal-migration model to test three nonmutually exclusive hypotheses leading to variations in the spring migration routes of a subspecies of Red Knot, Calidris canutus islandica, which migrates from wintering grounds in Western Europe to breeding grounds in Greenland and the Canadian Arctic: the breeding location hypothesis, the energy budget hypothesis, and the predation risk hypothesis. Varying only breeding location, the model predicted that birds breeding in the Canadian Arctic and on West Greenland stop over on Iceland, whereas birds breeding in East and Northeast Greenland migrate via northern Norway, a prediction that is supported by empirical findings. Energy budgets on stopover sites had a strong influence on the choice of route and staging times. Varying foraging-intensity and mass-dependent predation risk prompted the birds to use less risky sites, if possible. The effect of simultaneous changes in the energy budget and predation risk strongly depended on the site where these occurred. Our findings provide potential explanations for the observations that C. canutus islandica uses a diverse array of migration routes. Scrutinizing the three alternative driving forces for the choice of migratory routes awaits further, specific data collection in rapidly developing fields of research (e.g., predation risk assessment, GPS tracking). Generally, the type of modeling presented here may not only highlight alternative explanations, but also direct follow-up empirical research.

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 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.

As field determinations take much effort, it would be useful to be able to predict easily the coefficients describing the functional response of free-living predators, the function relating food intake rate to the abundance of food organisms in the environment. As a means easily to parameterise an individual-based model of shorebird Charadriiformes populations, we attempted this for shorebirds eating macro-invertebrates. Intake rate is measured as the ash-free dry mass (AFDM) per second of active foraging; i.e. excluding time spent on digestive pauses and other activities, such as preening. The present and previous studies show that the general shape of the functional response in shorebirds eating approximately the same size of prey across the full range of prey density is a decelerating rise to a plateau, thus approximating the Holling type II ('disc equation') formulation. But field studies confirmed that the asymptote was not set by handling time, as assumed by the disc equation, because only about half the foraging time was spent in successfully or unsuccessfully attacking and handling prey, the rest being devoted to searching.A review of 30 functional responses showed that intake rate in free-living shorebirds varied independently of prey density over a wide range, with the asymptote being reached at very low prey densities (<150/m-2). Accordingly, most of the many studies of shorebird intake rate have probably been conducted at or near the asymptote of the functional response, suggesting that equations that predict intake rate should also predict the asymptote.A multivariate analysis of 468 'spot' estimates of intake rates from 26 shorebirds identified ten variables, representing prey and shorebird characteristics, that accounted for 81% of the variance in logarithm-transformed intake rate. But four-variables accounted for almost as much (77.3%), these being bird size, prey size, whether the bird was an oystercatcher Haematopus ostralegus eating mussels Mytilus edulis, or breeding. The four variable equation under-predicted, on average, the observed 30 estimates of the asymptote by 11.6%, but this discrepancy was reduced to 0.2% when two suspect estimates from one early study in the 1960s were removed. The equation therefore predicted the observed asymptote very successfully in 93% of cases. We conclude that the asymptote can be reliably predicted from just four easily measured variables. Indeed, if the birds are not breeding and are not oystercatchers eating mussels, reliable predictions can be obtained using just two variables, bird and prey sizes. A multivariate analysis of 23 estimates of the half-asymptote constant suggested they were smaller when prey were small but greater when the birds were large, especially in oystercatchers. The resulting equation could be used to predict the half-asymptote constant, but its predictive power has yet to be tested. As well as predicting the asymptote of the functional response, the equations will enable research workers engaged in many areas of shorebird ecology and behaviour to estimate intake rate without the need for conventional time-consuming field studies, including species for which it has not yet proved possible to measure intake rate in the field.