Placing wind turbines within large migration flyways, such as the North Sea basin, can contribute to the decline of vulnerable migratory bird populations by increasing mortality through collisions. Curtailment of wind turbines limited to short periods with intense migration can minimize these negative impacts, and near-term bird migration forecasts can inform such decisions. Although near-term forecasts are usually created with long-term datasets, the pace of environmental alteration due to wind energy calls for urgent development of conservation measures that rely on existing data, even when it does not have long temporal coverage. Here, we use five years of tracking bird radar data collected off the western Dutch coast, weather, and phenological variables to develop seasonal near-term forecasts of low-altitude nocturnal bird migration over the southern North Sea. Overall, the models explained 71% of the variance and correctly predicted migration intensity above or below a threshold for intense hourly migration in more than 80% of hours in both seasons. However, the percentage of correctly predicted intense migration hours (top 5% of hours with the most intense migration) was low, likely due to the short-term dataset and their rare occurrence. We, therefore, advise careful consideration of a curtailment threshold to achieve optimal results. Synthesis and applications: Near-term forecasts of migration fluxes evaluated against measurements can be used to define curtailment thresholds for offshore wind energy. We show that to minimize collision risk for 50% of migrants, if predicted correctly, curtailments should be applied during 18 hours in spring and 26 in autumn in the focal year of model assessments, resulting in an estimated annual wind energy loss of 0.12%. Drawing from the Dutch curtailment framework, which pioneered the 'international first' offshore curtailment, we argue that using forecasts developed from limited temporal datasets alongside expert insight and data-driven policies can expedite conservation efforts in a rapidly changing world. This approach is particularly valuable in light of increasing interannual variability in weather conditions.

Migrant bird populations often show substantial variation in route choice and timing. Determining whether this population-level variation is driven by between-individual differences and/or flexibility within individuals is key to identifying drivers of migration patterns. ‘Repeatability’ (R, the proportion of population-level variation attributable to between-individual variation) has become a central metric for the relative consistency of individual behaviour. Individual repeatability in migratory route choice and timing is often reported to vary between seasonal and regional contexts and may also differ between demographic groups (e.g. sexes), but interpreting repeatability requires careful consideration of the underlying changes in between- and within-individual variation. We GPS-tracked repeat migrations for eight male and five female Eleonora’s falcons Falco eleonorae and quantified the magnitude of within- and between-individual variation and the individual repeatability of their seasonal routes and timing at 100km intervals all across Africa. We did this across both sexes and then separately for males and females. We found greater between-individual variation in spring routes, albeit with substantial regional fluctuations in both seasons. The greatest between-individual variation in routes occurred during the spring desert-crossing, but this coincided with high within-individual variation, and thus only low repeatability of route choice. Route repeatability instead peaked (R = 0.6–0.8) through the Horn of Africa in spring and during the rainforest-crossing in autumn. Variation and repeatability of timing were stable across regions, with generally higher between-individual variation and repeatability in spring. Sex-specific analyses suggest males exhibit higher route repeatability, while females exhibit stronger seasonal contrasts in timing repeatability. Such sex differences were unexpected, but overall, between-individual variation and repeatability in routes and timings appear greater where environmental and annual cycle constraints are weaker. Route repeatability is especially high where falcons show fidelity to stop-over sites, or individual barrier-crossing preferences. Individual routines may be acquired through early-life exploration-refinement.

1. Aircraft collisions with birds span the entire history of human aviation, including fatal collisions during some of the first powered human flights. Much effort has been expended to reduce such collisions, but increased knowledge about bird movements and species occurrence could dramatically improve decision support and proactive measures to reduce them. Migratory movements of birds pose a unique, often overlooked, threat to aviation that is particularly difficult for individual airports to monitor and predict: the occurrence of birds vary extensively in space and time at the local scales of airport responses. 2. We use two publicly available datasets, radar data from the US NEXRAD network characterizing migration movements and eBird data collected by citizen scientists to map bird movements and species composition with low human effort expenditures but high temporal and spatial resolution relative to other large scale bird survey methods. As a test case we compare these results from weather radar distributions and eBird species composition with detailed bird strike records from three major New York airports. 3. We show that weather radar based estimates of migration intensity can accurately predict probability of bird strikes, with 80% of the variation in bird strikes across the year explained by the average amount of migratory movements captured on weather radar. We also show that eBird based estimates of species occurrence can, using species’ body mass and flocking propensity, accurately predict when most damaging strikes occur. 4. Synthesis and applications: Our results highlight the power of federating datasets with movement and distribution data for developing better and more taxonomically and ecologically tuned models of likelihood of strikes occurring and severity of strikes. By better understanding when, and where, different species occur, airports across the world can predict seasonal periods of collision risks with greater temporal and spatial resolution; such predictions include potential to predict when the most severe and damaging strikes may occur.

On their migratory journeys, terrestrial birds can come across large inhospitable areas with limited opportunities to rest and refuel. Flight over these areas poses a risk especially when wind conditions en route are adverse, in which case inhospitable areas can act as an ecological barrier for terrestrial migrants. Thus, within the East-Atlantic flyway, the North Sea can function as an ecological barrier. The main aim of this study was to shed light on seasonal patterns of bird migration in the southern North Sea and determine whether departure decisions on nights of intense migration were related to increased wind assistance. We measured migration characteristics with a radar that was located 18 km off the NW Dutch coast and used simulation models to infer potential departure locations of birds on nights with intense nocturnal bird migration. We calculated headings, track directions, airspeeds, groundspeeds on weak and intense migration nights in both seasons and compared speeds between seasons. Moreover, we tested if departure decisions on intense migration nights were associated with supportive winds. Our results reveal that on the intense migration nights in spring, the mean heading was towards E, and birds departed predominantly from the UK. On intense migration nights in autumn, the majority of birds departed from Denmark, Germany and north of the Netherlands with the mean heading towards SW. Prevailing winds from WSW at departure were supportive of a direct crossing of the North Sea in spring. However, in autumn winds were generally not supportive, which is why many birds exploited positive wind assistance which occurred on intense migration nights. This implies that the seasonal wind regimes over the North Sea alter its migratory dynamics which is reflected in headings, timing and intensity of migration.

1. Large-scale environmental forces can influence biodiversity at different levels of biological organization. Climate, in particular, is often associated to species distributions and diversity gradients. However, its mechanistic link to population dynamics is still poorly understood. 2. Here, we unraveled the full mechanistic path by which a climatic driver, the Atlantic trade winds, determines the viability of a bird population. 3. We monitored the breeding population of Eleonora’s falcons in the Canary Islands for over a decade (2007-2017) and integrated different methods and data to reconstruct how the availability of their prey (migratory birds) is regulated by trade winds. We tracked foraging movements of breeding adults using GPS, monitored departure of migratory birds using weather radar, and simulated their migration trajectories using an individual-based, spatially explicit model. 4. We demonstrate that regional easterly winds regulate the flux of migratory birds that is available to hunting falcons, determining food availability for their chicks and consequent breeding success. By reconstructing how migratory birds are pushed towards the Canary Islands by trade winds, we explain most of the variation (up to 86%) in annual productivity for over a decade. 5. This study unequivocally illustrates how a climatic driver can influence local-scale demographic processes, while providing novel evidence of wind as a major determinant of population fitness in a top predator. 06-Jul-2020

GPS-tracking devices have been used in combination with a wide range of additional sensors to study animal behaviour, physiology and interaction with their environment. Tri-axial accelerometers allow researchers to remotely infer the behaviour of individuals, at all places and times. Collection of accelerometer data is relatively cheap in terms of energy usage, but the amount or raw data collected generally requires much storage space and is particularly demanding in terms of energy needed for data transmission. Here we propose compressing the raw ACC data into summary statistics within the tracking device (before transmission) to reduce data size, as a means to overcome limitations in storage and energy capacity. We explored this type of lossy data compression in the accelerometer data of tagged Bewick’s swans (Cygnus columbianus bewickii) collected in spring 2017. By using software settings in which bouts of 2 s of both raw ACC data and summary statistics were collected in parallel but with different bout intervals to keep total data size comparable, we created the opportunity for a direct comparison of time budgets derived by the two data collection methods. We found that the data compression in our case yielded a 6 time reduction in data size per bout, and concurrent, similar decreases in storage and energy use of the device. We show that with the same accuracy of the behavioural classification, the freed memory and energy of the device can be used to increase the monitoring effort, resulting in a more detailed representation of the individuals’ time budget. Rare and/or short behaviours such as daily roost flights, were picked up significantly more when collecting summary statistics instead of raw ACC data (but note differences in sampling rate). Such level of detail can be of essential importance, for instance to make a reliable estimate of the energy budgets of individuals. In conclusion, we argue that this type of lossy data compression can be a well-considered choice in study situations where limitations in energy and storage space of the device pose a problem. Ultimately these developments can allow for long-term and nearly continuous remote-monitoring of the behaviour of free-ranging animals.

The aerosphere is utilized by billions of birds, moving for different reasons and from short to great distances spanning tens of thousands of kilometres. The aerosphere, however, is also utilized by aviation which leads to increasing conflicts in and around airfields as well as en-route. Collisions between birds and aircraft cost billions of euros annually and, in some cases, result in the loss of human lives. Simultaneously, aviation has diverse negative impacts on wildlife. During avian migration, due to the sheer numbers of birds in the air, the risk of bird strikes becomes particularly acute for low-flying aircraft, especially during military training flights. Over the last few decades, air forces across Europe and the Middle East have been developing solutions that integrate ecological research and aviation policy to reduce mutual negative interactions between birds and aircraft. In this paper we (1) provide a brief overview of the systems currently used in military aviation to monitor bird migration movements in the aerosphere, (2) provide a brief overview of the impact of bird strikes on military low-level operations, and (3) estimate the effectiveness of migration monitoring systems in bird strike avoidance. We compare systems from the Netherlands, Belgium, Germany, Poland and Israel, which are all areas that Palearctic migrants cross twice a year in huge numbers. We show that the en-route bird strikes have decreased considerably in countries where avoidance systems have been implemented, and that consequently bird strikes are on average 45% less frequent in countries with implemented avoidance systems in place. We conclude by showing the roles of operational weather radar networks, forecast models and international and interdisciplinary collaboration to create safer skies for aviation and birds.

The extraordinary adaptations of birds to contend with atmospheric conditions during their migratory flights have captivated ecologists for decades. During the 21st century technological advances have sparked a revival of research into the influence of weather on migrating birds. Using biologging technology, flight behaviour is measured across entire flyways, weather radar networks quantify large-scale migratory fluxes, citizen scientists gather observations of migrant birds and mechanistic models are used to simulate migration in dynamic aerial environments. In this review, we first introduce the most relevant microscale, mesoscale and synoptic scale atmospheric phenomena from the point of view of a migrating bird. We then provide an overview of the individual responses of migrant birds (when, where and how to fly) in relation to these phenomena. We explore the cumulative impact of individual responses to weather during migration, and the consequences thereof for populations and migratory systems. In general, individual birds seem to have a much more flexible response to weather than previously thought, but we also note similarities in migratory behaviour across taxa. We propose various avenues for future research through which we expect to derive more fundamental insights into the influence of weather on the evolution of migratory behaviour and the life-history, population dynamics and species distributions of migrant birds.

Avian migrants often make substantial detours between their seasonal destinations. It is likely some species do this to make the most of predictable wind regimes along their respective flyways. We test this hypothesis by studying orientation behaviour of a long-distance soaring migrant in relation to prevailing winds along the East Atlantic Flyway. We tracked 62 migratory journeys of 12 adult European Honey Buzzards Pernis apivorus with GPS loggers. Hourly fixes were annotated with local wind vectors from a global atmospheric model to determine orientation behaviours with respect to the buzzards’ seasonal goal destinations. This enabled us to determine hot spots where buzzards overdrifted and overcompensated for side winds. We then determined whether winds along the buzzards’ detours differed from winds prevailing elsewhere in the flyway. Honey Buzzards cross western Africa using different routes in autumn and spring. In autumn, they overcompensated for westward winds to circumvent the Atlas Mountains on the eastern side and then overdrifted with south-westward winds while crossing the Sahara. In spring, however, they frequently overcompensated for eastward winds to initiate a westward detour at the start of their journey. They later overdrifted with side winds north-westward over the Sahel and north-eastward over the Sahara, avoiding adverse winds over the central Sahara. We conclude that Honey Buzzards make seasonal detours to utilize more supportive winds further en route and thereby expend less energy while crossing the desert. Lifelong tracking studies will be helpful to elucidate how honey buzzards and other migrants learn complex routes to exploit atmospheric circulation patterns from local to synoptic scales.

Wind energy generation is increasing globally, and associated environmental impacts must be considered. The risk of seabirds colliding with offshore wind turbines is influenced by flight height, and flight height data usually come from observers on boats, making estimates in daylight in fine weather. GPS tracking provides an alternative and generates flight height information in a range of conditions, but the raw data have associated error. Here, we present a novel analytical solution for accommodating GPS error. We use Bayesian state-space models to describe the flight height distributions and the error in altitude measured by GPS for lesser black-backed gulls and great skuas, tracked throughout the breeding season. We also examine how location and light levels influence flight height. Lesser black-backed gulls flew lower by night than by day, indicating that this species would be less likely to encounter turbine blades at night, when birds’ ability to detect and avoid them might be reduced. Gulls flew highest over land and lowest near the coast. For great skuas, no significant relationships were found between flight height, time of day and location. We consider four ‘collision risk windows’, corresponding to the airspace swept by rotor blades for different offshore wind turbine designs. We found the highest proportion of birds at risk for a 22–250 m turbine (up to 9% for great skuas and 34% for lesser black-backed gulls) and the lowest for a 30–258 m turbine. Our results suggest lesser black-backed gulls are at greater risk of collision than great skuas, especially by day. Synthesis and applications. Our novel modelling approach is an effective way of resolving the error associated with GPS tracking data. We demonstrate its use on GPS measurements of altitude, generating important information on how breeding seabirds use their environment. This approach and the associated data also provide information to improve avian collision risk assessments for offshore wind farms. Our modelling approach could be applied to other GPS data sets to help manage the ecological needs of seabirds and other species at a time when the pressures on the marine environment are growing.