Decadal increase in vessel interactions by a scavenging pelagic seabird across the North Atlantic.

Fisheries waste is used by many seabirds as a supplementary source of food,1 but interacting with fishing vessels to obtain this resource puts birds at risk of entanglement in fishing gear and mortality.2 As a result, bycatch is one of the leading contributors to seabird decline worldwide,3 and this risk may increase over time as birds increasingly associate fishing vessels with food. Light-level geolocators mounted on seabirds can detect light emitted from vessels at night year-round.4 We used a 16-year time series of geolocator data from 296 northern fulmars (Fulmarus glacialis) breeding at temperate and arctic colonies to investigate trends of nocturnal vessel interactions in this scavenging pelagic seabird. Vessel attendance has progressively increased over the study period despite no corresponding increase in the number of vessels or availability of discards over the same time frame. Fulmars are highly mobile generalist surface feeders,5 so this may signal a reduction in available prey biomass in the upper water column, leading to increased reliance on anthropogenic food subsidies6 and increased risk of bycatch mortality in already threatened seabird populations. Individuals were consistent in the extent to which they interacted with vessels, as shown in other species,7 suggesting that population-level increases may be due to a higher proportion of fulmars following vessels rather than changes at an individual level. Higher encounter rates were correlated with lower time spent foraging and a geographically restricted overwintering distribution, suggesting an energetic advantage for these scavenging strategists compared with foraging for natural prey.

Persistent pollutants in fresh and abandoned eggs of Common Tern (Sterna hirundo) and Arctic Tern (Sterna paradisaea) in Ireland.

Higher levels of persistent pollutants (Σ16PCB, Σ6PBDE, ΣHCH, ΣDDT, ΣCHL) were detected in fresh eggs of Common Terns Sterna hirundo from Rockabill Island near Dublin (Ireland's industrialised capital city) compared to Common and Arctic Terns S. paradisaea from Ireland's west coast. Intra-clutch variation of pollutant levels in Common Terns was shown to be low, providing further evidence that random sampling of one egg may be an appropriate sampling strategy. Significant differences in pollutant concentrations were detected between fresh and abandoned eggs on Rockabill. However, abandoned eggs can still provide a useful approximation of pollutants in bird eggs if non-destructive sampling is preferred. Levels of p,p' -DDE in tern eggs have decreased over time according to this study, in concurrence with worldwide trends. Results in this study fall below toxicological thresholds for birds and OSPARs EcoQO thresholds set for Common Tern eggs, except for mercury and HCH in the west coast.

Ecological insights from three decades of animal movement tracking across a changing Arctic.

The Arctic is entering a new ecological state, with alarming consequences for humanity. Animal-borne sensors offer a window into these changes. Although substantial animal tracking data from the Arctic and subarctic exist, most are difficult to discover and access. Here, we present the new Arctic Animal Movement Archive (AAMA), a growing collection of more than 200 standardized terrestrial and marine animal tracking studies from 1991 to the present. The AAMA supports public data discovery, preserves fundamental baseline data for the future, and facilitates efficient, collaborative data analysis. With AAMA-based case studies, we document climatic influences on the migration phenology of eagles, geographic differences in the adaptive response of caribou reproductive phenology to climate change, and species-specific changes in terrestrial mammal movement rates in response to increasing temperature.

Temperature and precipitation at migratory grounds influence demographic trends of an Arctic-breeding bird.

Anthropogenic climate disruption, including temperature and precipitation regime shifts, has been linked to animal population declines since the mid-20th century. However, some species, such as Arctic-breeding geese, have thrived during this period. An increased understanding of how climate disruption might link to demographic rates in thriving species is an important perspective in quantifying the impact of anthropogenic climate disruption on the global state of nature. The Greenland barnacle goose (Branta leucopsis) population has increased tenfold in abundance since the mid-20th century. A concurrent weather regime shift towards warmer, wetter conditions occurred throughout its range in Greenland (breeding), Ireland and Scotland (wintering) and Iceland (spring and autumn staging). The aim of this study was to determine the relationship between weather and demographic rates of Greenland barnacle geese to discern the role of climate shifts in the population trend. We quantified the relationship between temperature and precipitation and Greenland barnacle goose survival and productivity over a 50 year period from 1968 to 2018. We detected significant positive relationships between warmer, wetter conditions on the Icelandic spring staging grounds and survival. We also detected contrasting relationships between warmer, wetter conditions during autumn staging and survival and productivity, with warm, dry conditions being the most favourable for productivity. Survival increased in the latter part of the study period, supporting the possibility that spring weather regime shifts contributed to the increasing population trend. This may be related to improved forage resources, as warming air temperatures have been shown to improve survival rates in several other Arctic and northern terrestrial herbivorous species through indirect bottom-up effects on forage availability.

Author Correction: Stochastic simulations reveal few green wave surfing populations among spring migrating herbivorous waterfowl.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Stochastic simulations reveal few green wave surfing populations among spring migrating herbivorous waterfowl.

Tracking seasonally changing resources is regarded as a widespread proximate mechanism underpinning animal migration. Migrating herbivores, for example, are hypothesized to track seasonal foliage dynamics over large spatial scales. Previous investigations of this green wave hypothesis involved few species and limited geographical extent, and used conventional correlation that cannot disentangle alternative correlated effects. Here, we introduce stochastic simulations to test this hypothesis using 222 individual spring migration episodes of 14 populations of ten species of geese, swans and dabbling ducks throughout Europe, East Asia, and North America. We find that the green wave cannot be considered a ubiquitous driver of herbivorous waterfowl spring migration, as it explains observed migration patterns of only a few grazing populations in specific regions. We suggest that ecological barriers and particularly human disturbance likely constrain the capacity of herbivorous waterfowl to track the green wave in some regions, highlighting key challenges in conserving migratory birds.

Forecasting spring from afar? Timing of migration and predictability of phenology along different migration routes of an avian herbivore.

Herbivorous birds are hypothesized to migrate in spring along a seasonal gradient of plant profitability towards their breeding grounds (green wave hypothesis). For Arctic breeding species in particular, following highly profitable food is important, so that they can replenish resources along the way and arrive in optimal body condition to start breeding early. We compared the timing of migratory movements of Arctic breeding geese on different flyways to examine whether flyways differed in the predictability of spring conditions at stopovers and whether this was reflected in the degree to which birds were following the green wave. Barnacle geese (Branta leucopsis) were tracked with solar GPS/ARGOS PTTs from their wintering grounds to breeding sites in Greenland (N = 7), Svalbard (N = 21) and the Barents Sea (N = 12). The numerous stopover sites of all birds were combined into a set of 16 general stopover regions. The predictability of climatic conditions along the flyways was calculated as the correlation and slope between onsets of spring at consecutive stopovers. These values differed between sites, mainly because of the presence or absence of ecological barriers. Goose arrival at stopovers was more closely tied to the local onset of spring when predictability was higher and when geese attempted breeding that year. All birds arrived at early stopovers after the onset of spring and arrived at the breeding grounds before the onset of spring, thus overtaking the green wave. This is in accordance with patterns expected for capital breeders: first, they must come into condition; at intermediate stopovers, arrival with the food quality peak is important to stay in condition, and at the breeding grounds, early arrival is favoured so that hatching of young can coincide with the peak of food quality. Our results suggest that a chain of correlations between climatic conditions at subsequent stopovers enables geese to closely track the green wave. However, the birds' precision of migratory timing seems uninfluenced by ecological barriers, indicating partly fixed migration schedules. These might become non-optimal due to climate warming and preclude accurate timing of long-distance migrants in the future.

Migratory herbivorous waterfowl track satellite-derived green wave index.

Many migrating herbivores rely on plant biomass to fuel their life cycles and have adapted to following changes in plant quality through time. The green wave hypothesis predicts that herbivorous waterfowl will follow the wave of food availability and quality during their spring migration. However, testing this hypothesis is hampered by the large geographical range these birds cover. The satellite-derived normalized difference vegetation index (NDVI) time series is an ideal proxy indicator for the development of plant biomass and quality across a broad spatial area. A derived index, the green wave index (GWI), has been successfully used to link altitudinal and latitudinal migration of mammals to spatio-temporal variations in food quality and quantity. To date, this index has not been used to test the green wave hypothesis for individual avian herbivores. Here, we use the satellite-derived GWI to examine the green wave hypothesis with respect to GPS-tracked individual barnacle geese from three flyway populations (Russian n = 12, Svalbard n = 8, and Greenland n = 7). Data were collected over three years (2008-2010). Our results showed that the Russian and Svalbard barnacle geese followed the middle stage of the green wave (GWI 40-60%), while the Greenland geese followed an earlier stage (GWI 20-40%). Despite these differences among geese populations, the phase of vegetation greenness encountered by the GPS-tracked geese was close to the 50% GWI (i.e. the assumed date of peak nitrogen concentration), thereby implying that barnacle geese track high quality food during their spring migration. To our knowledge, this is the first time that the migration of individual avian herbivores has been successfully studied with respect to vegetation phenology using the satellite-derived GWI. Our results offer further support for the green wave hypothesis applying to long-distance migrants on a larger scale.

Flying with the wind: scale dependency of speed and direction measurements in modelling wind support in avian flight.

BACKGROUND: Understanding how environmental conditions, especially wind, influence birds' flight speeds is a prerequisite for understanding many important aspects of bird flight, including optimal migration strategies, navigation, and compensation for wind drift. Recent developments in tracking technology and the increased availability of data on large-scale weather patterns have made it possible to use path annotation to link the location of animals to environmental conditions such as wind speed and direction. However, there are various measures available for describing not only wind conditions but also the bird's flight direction and ground speed, and it is unclear which is best for determining the amount of wind support (the length of the wind vector in a bird's flight direction) and the influence of cross-winds (the length of the wind vector perpendicular to a bird's direction) throughout a bird's journey. RESULTS: We compared relationships between cross-wind, wind support and bird movements, using path annotation derived from two different global weather reanalysis datasets and three different measures of direction and speed calculation for 288 individuals of nine bird species. Wind was a strong predictor of bird ground speed, explaining 10-66% of the variance, depending on species. Models using data from different weather sources gave qualitatively similar results; however, determining flight direction and speed from successive locations, even at short (15 min intervals), was inferior to using instantaneous GPS-based measures of speed and direction. Use of successive location data significantly underestimated the birds' ground and airspeed, and also resulted in mistaken associations between cross-winds, wind support, and their interactive effects, in relation to the birds' onward flight. CONCLUSIONS: Wind has strong effects on bird flight, and combining GPS technology with path annotation of weather variables allows us to quantify these effects for understanding flight behaviour. The potentially strong influence of scaling effects must be considered and implemented in developing sampling regimes and data analysis.