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opencc-zeroNov 2023View details →

Social behavior among nocturnally migrating birds revealed by automated moonwatching

Migrating birds often fly in group formations during the daytime; whereas at night, it is generally presumed that they fly singly. However, it is difficult to quantify group behavior during nocturnal migration as there are few means of directly observing interactions among individuals. We employed an automated form of moonwatching to estimate percentages of birds that appear to migrate in groups during the night within the Central Flyway of North America. We compared percentages of birds in groups across the spring and fall and examined overnight temporal patterns of group behavior. We found groups were rare in both seasons, never exceeding 10% of birds observed, and were almost nonexistent during the fall. We also observed an overnight pattern of group behavior in the spring wherein groups were more commonly detected early in the night and again just before migration activity ceased. This finding may be related to changes in species composition of migrants throughout the night, or alternatively it suggests that group formation may be associated with flocking activity on the ground as groups are most prevalent when birds begin and end a night of migration.

opencc-zeroJan 2024View details →

Energetic trade-offs in migration decision-making, reproductive effort, and subsequent parental care in a long-distance migratory bird

Migratory species trade-off long-distance movement with survival and reproduction, but the spatiotemporal scales at which these decisions occur is relatively unknown. Technological and statistical advances allow fine-scale study of animal decision-making, improving our understanding of possible causes and therefore conservation management. We quantified effects of reproductive preparation during spring migration on subsequent breeding outcomes, breeding outcomes on autumn migration characteristics, and autumn migration characteristics on subsequent parental survival in Greenland white-fronted geese (Anser albifrons flavirostris). These are long-distance migratory birds with a ~50% population decline from 1999 to 2022. We deployed GPS-acceleration devices on adult females to quantify up to five years of individual decision-making throughout the annual cycle. Weather and habitat-use affected time spent feeding and overall dynamic body acceleration (i.e., energy expenditure) during spring and autumn. Geese that expended less energy and fed longer during spring were more likely to successfully reproduce. Geese with offspring expended more energy and fed for less time during autumn, potentially representing adverse fitness consequences of breeding. These behavioural comparisons among Greenland white-fronted geese improve our understanding of fitness trade-offs underlying abundance. We provide a reproducible framework for full annual cycle modelling using location and behaviour data, applicable to similarly studied migratory animals.

opencc-zeroMar 2024View details →

Data from: Early-life variation in migration is subject to strong fluctuating survival selection in a partially migratory bird

Population dynamic and eco-evolutionary responses to environmental variation and change fundamentally depend on combinations of within- and among-cohort variation in phenotypic expression of key life-history traits, and on corresponding variation in selection on those traits. Specifically, in partially migratory populations, spatio-seasonal dynamics depend on the degree of adaptive phenotypic expression of seasonal migration versus residence, where more individuals migrate when selection favours migration. Opportunity for adaptive (or, conversely, maladaptive) expression could be particularly substantial in early life, through initial development of migration versus residence. However, within- and among-cohort dynamics of early-life migration, and of associated survival selection, have not been quantified in any system, preventing any inference on adaptive early-life expression. Such analyses have been precluded because data on seasonal movements and survival of sufficient young individuals, across multiple cohorts, have not been collected. We undertook extensive year-round field resightings of 9,359 colour-ringed juvenile European Shags (Gulosus aristotelis) from 11 successive cohorts in a partially-migratory population. We fitted advanced Bayesian multi-state capture-mark-recapture models to quantify early-life variation in migration versus residence and associated survival across short temporal occasions through each cohort's first year from fledging, thereby quantifying the degree of adaptive phenotypic expression of migration within and across years. All cohorts were highly partially migratory, but the degree and timing of migration varied considerably within and among cohorts. Episodes of strong survival selection on migration versus residence occurred both on short timeframes within years, and cumulatively across whole years, generating instances of instantaneous and cumulative net selection that would be obscured at coarser temporal resolutions. Further, the magnitude and direction of selection varied among years, generating strong fluctuating survival selection on early-life migration across cohorts, as rarely evidenced in nature. Yet, the degree of migration did not strongly covary with the direction of selection, indicating limited early-life adaptive phenotypic expression. These results reveal how dynamic early-life expression and selection on a key life-history trait, seasonal migration, can emerge across seasonal, annual, and multi-year timeframes, yet be substantially decoupled. This restricts the potential for adaptive phenotypic, micro-evolutionary, and population dynamic responses to changing seasonal environments.

opencc-by-4.0Jun 2009View details →

Fig. 1 in Infestation With Ixodes Ricinus Ticks On Migrating Passerine Birds In Lithuania And Norway

Fig. 1 Molecular taxonomical identification of the I. ricinus by PCR assay. Lines 1 and 15 – 50 bp marker; Line 2 –negative control; Lines 2-13 –positive results: amplified 150 bp specific fragment for I. ricinus; Line 14 – positive control of I. ricinus (150 bp)

opencc-by-4.0Nov 2024View details →

Supplementary material for "In-flight reactions of nocturnally migrating birds to winds"

Abstract Available knowledge on in-flight reactions of nocturnal bird migrants to winds is reviewed, with emphasis on the challenging topographical and meteorological conditions in Western Europe, and differences from the situation in North America discussed. Conclusions drawn are used for a new approach: using individual radar tracks of nocturnal migrants (mainly passerines) as well as winds measured at their flight altitudes, we defined the basic direction (BD=average flight direction of all migrants tracked under negligible wind influence) as a reference. For two altitudinal zones above a radar site near Nuremberg, we modelled the deviations of tracks and headings from BD for increasing wind from six 60° sectors. A comparison of birds’ air speeds Va with winds from four 90°-sectors confirmed that Va increased with opposing winds from ~11 to 13 (14) m/s; a similar increase occurred with side winds. An expected, slight decrease of Va with increasing following winds was only indicated for high-flying, not for low-flying birds. A predicted increase in average Va due to decreasing air density with increasing height was not observed; possible explanations (birds climbing to high altitudes in following, but not in strong opposing winds) are discussed. Over the whole autumn migration season, headings were concentrated in a sector of ±30° around 230° in both altitudinal zones. Prevailing winds from 230 to 320° (SW–NW, i.e. opposing from right) led to widely scattered tracks primarily between 190° and 270°, but additional ones in the SE sector (mainly 100°–170°). The analysis of tracks and headings relative to BD revealed the following features. (1) Overcompensation was frequently observed at low wind speeds (<3 m/s); (2) under all wind conditions, but particularly with opposing winds and at low flight levels, tracks were widely scattered, including birds deviating more than 90° from BD. (3) Under opposing and side winds from the right compensatory efforts led to partial drift compensation up to wind speeds of ~8–10 m/s. Because efforts to compensate drift dwindled with increasing wind speeds, birds were fully drifted. Many even shifted their heading to due south and, hence, overdrifted. (4) Opposing and side winds from the left induced partial compensation at low flight levels and full drift above 1500 m asl. (5) The lateral components of the rare and weak following winds led to tracks close to expected minimal drift (without important compensation needed). In general, migrants compensated less for deviations by wind force than expected. The tendency of birds to maintain headings close to BD under opposing winds was so strong that many individuals continued migration with minimal progress over ground or even with retrograde migration as an extreme. On the other hand, there was an omnipresent fraction of birds with tracks far from seasonally favourable directions, including reverse migration.

opencc-by-4.0Mar 2020View details →

Fig. 4 in Autumn Migration Of Birds Over Polonyna Borzhava (Ukrainian Carpathians)

Fig. 4. Distribution of the passage flow of most numerous species of birds (%) migrating over Polonyna Borzhava and their main migration directions.

opencc-by-4.0Mar 2020View details →

Fig. 3 in Autumn Migration Of Birds Over Polonyna Borzhava (Ukrainian Carpathians)

Fig. 3. Dynamics of passage intensity in some common bird species across Polonyna Borzhava in autumn 2018.

opencc-by-4.0Nov 2021View details →

Migrating birds real flight V-formation spatial configuration.

Bird real flight V-formation dataset: Arbitrary (pixel) coordinates of migrating birds, probably Geese, flying in V-formation. Photo is taken in an angle so their formation data is only a cross-section in 3-D perspective but with entire pack. However, despite this limitation this V-formation configuration provides a quantitative data for the understanding for the spatial properties, i.e., V-shape characteristics. There are 95 birds in total including the lead bird. Lower V-arm is denoted with tags dXX has 51 birds and upper V-arm is denoted by tags uXX has 43 birds. Lead bird has two entries d00 and u00 for consistency. Annotated image provides boxes and labels. The data is given under bird_arbitrary_coordinates as pixel location on the plane with tags. In coordinate annotation head of the bird is taken as a refrence point.

opencc-by-4.0Mar 2020View details →

Рис. 5. Passage height preferences (M, ± SD) of birds migrating over Polonyna Borzhava mountain ridge in autumn 2018. in Autumn Migration Of Birds Over Polonyna Borzhava (Ukrainian Carpathians)

Рис. 5. Passage height preferences (M, ± SD) of birds migrating over Polonyna Borzhava mountain ridge in autumn 2018.

opencc-by-4.0May 2022View details →

Nocturnal flight calls dataset: long-term acoustic monitoring of birds migrating at night

General Description: This is a development set used in the experiments in the Ph.D. thesis: "Nowe metody akustycznej identyfikacji ptaków migrujących nocą" ("Novel methods of acoustic identification of birds migrating at night") by Hanna Pamula. The project focuses on the detection (and - partially - classification) of passerine birds' calls from long-term audio recordings collected during bird autumn migration between 2016 and 2019. The dataset consists of >56,5 hours of recordings with annotations of nocturnal flight calls of passerine birds migrating along the Baltic Sea coast, Poland.   Folder Structure Development_Set_3.1.zip |_Development_Set_3.1/     |__Training_Set/             |____*.wav             |____*.txt     |__Validation_Set/             |____*.wav             |____*.txt     |__Testing_Set/             |____*.wav             |____*.txt Training Set: 86 recordings Validation Set: 8 recordings Testing set: 18 recordings (BUT: uploaded 20 recordings, as in the previous version of the dataset - version 3, two additional recordings were used. Then, they were deleted in the final version of development set 3.1. Two additional recordings are: 'BUK5_20161101_002104a and BUK5_20161101_002104b) Names of waveforms and annotations are matching. Waveforms: The whole dataset consists of 114 recordings. One hundred thirteen recordings are about 30 minutes long (29min56s – 29min 59s), one recording is 1min20s. All data were recorded at 44,100 Hz sampling rate, one channel, with SM2 Wildlife Acoustics recorders + SMX-NFC microphone. The recording sessions were performed at night (starting time and date denoted in a file name) on the Baltic Sea coast in Poland (Dąbkowice, near Darłowo). Annotations: Transcriptions were produced using Audacity 2.4.1: https://www.audacityteam.org/ by an experienced birdwatcher, Hanna Pamula. While every effort has been made to ensure the quality and accuracy of the labels, some errors may occur, taking into account the difficulty of nocturnal call recognition and transcription tasks in general. Transcription format: [Starting time (sec)] [Ending time (sec)] [Label] Meaning of the labels: 1. Positive classes – migrating passerine birds: <ul> <li>'s' – song thrush call (Turdus philomelos)</li> <li>'k' – blackbird call (Turdus merula)</li> <li>'d' – redwing call (Turdus iliacus)</li> <li>'r' – robin call (Erithacus rubecula)</li> <li>‘kwiczol’ – fieldfare call (Turdus pilaris)</li> <li>‘skowronek’ – skylark call (Alauda arvensis)</li> <li>Each of the above labels could also have a question mark '?', e.g. 'r?', 'k?' – meaning that it's not a sure label. In a bird call detection task, they are regarded as positive chunks containing bird call(s).</li> <li>'ni' – non identified bird call (distant/quiet/not recognized)</li> </ul> Only the supposed calls of migrating passerine birds were labeled; other sounds of species were ignored (e.g., robin's tik-calling, which can be often heard at dusk, and may be regarded as warning sounds). 2. Negative classes – other marked sound events: <ul> <li>'g' – other bird calls/songs/sounds. Sounds that could confuse the model; for example, sounds of migrating geese, cranes, plovers calls, etc.</li> <li>'gh' – human voices</li> <li>'t' – cracks, clicks, raindrops, other noise</li> <li>‘puszczyk’ – tawny owl voice (Strix aluco)</li> <li>'czapla' – grey heron voice (Ardea cinerea)</li> </ul> Not all occurrences of the negative sounds were labeled – only some chosen examples to represent the possible noises/negative samples. Thus these annotations can't be used for entirely different detection / classification tasks than intended, e.g., detecting migrating cranes or human voices in long-term recordings. 3. Labels to be excluded from analysis: <ul> <li>'???', '??? mysz', '??? high freq' – unknown, not sure if the sound event is a birds' call or not. Uncertainty about belonging to a positive/negative class in the detection task.</li> </ul>

opencc-zeroJun 2024View details →

The diet–intestinal microbiota dynamics and adaptation in an elevational migration bird, the Himalayan bluetail (Tarsiger rufilatus)

Migratory birds experience changes in their environment and diet during seasonal migrations, thus requiring interactions between diet and gut microbes. Understanding the co-evolution of the host and gut microbiota is critical for elucidating the rapid adaptations of avian gut microbiota. However, dynamics of gut microbial adaptations concerning elevational migratory behavior, which is prevalent but understudied in montane birds remain poorly understood. We focused on the Himalayan bluetail (Tarsiger rufilatus) in the montane forests of Mt. Gongga to understand the diet-gut microbial adaptations of elevational migratory birds. Our findings indicate that elevational migratory movements can rapidly alter gut microbial composition and function within a month. There was a significant interaction between an animal-based diet and gut microbiota across migration stages, underscoring the importance of diet in shaping microbial communities. Furthermore, the gut microbial composition of T. rufilatus may be potentially altered by high-altitude acclimatization. An increase in fatty acid and amino acid metabolism was observed in response to low temperatures and limited resources, resulting in enhanced energy extraction and nutrient utilization. Moreover, microbial communities in distinct gut segments varied in relative abundance and responses to environmental changes. While the bird jejunum exhibited greater susceptibility to food and environmental fluctuations, there was no significant difference in metabolic capacity among gut segments. This study provides initial evidence of rapid diet-gut microbial changes in distinct gut segments of elevational migratory birds and highlights the importance of seasonal sample collection. Our findings provide a deeper understanding of the unique high-altitude adaptation patterns of the gut microbiota for montane elevational migratory birds.

opencc-by-4.0Jul 2024View details →

Data from: Ontogeny of migration destination, route and timing in a partially migratory bird

Abstract <ol> <li>In migratory animals, the developmental period from inexperienced juveniles to breeding adults could be a key life stage in shaping population migration patterns. Nevertheless, the development of migration routines in early life remains underexplored. While age-related changes in migration routes and timing have been described in obligate migrants, most investigations into the ontogeny of partial migrants only focused on age-dependency of migration as a binary tactic (migrant or resident), and variations in routes and timing among individuals classified as ‘migrants’ is rarely considered. </li> <li>To fill this gap, we study the ontogeny of migration destination, route and timing in a partially migratory red kite (Milvus milvus) population. Using an extensive GPS-tracking dataset (292 fledglings and 38 adults, with 1 – 5 migrations tracked per individual), we studied how 9 different migration characteristics changed with age and breeding status in migrant individuals, many of which become resident later in life.</li> <li>Individuals departed later from and arrived earlier at the breeding areas as they aged, resulting in a gradual prolongation of stay in the breeding area by two months from the first to the fifth migration. Individuals delayed southward migration in the year prior to territory acquirement, and they further delayed it after occupying a territory. Migration routes became more direct with age. Individuals were highly faithful to their wintering site. Migration distance shortened only slightly with age and was more similar among siblings than among unrelated individuals.</li> <li>The large gradual changes in northward and southward migrations suggest a high degree of plasticity in temporal characteristics during the developmental window. However, the high wintering site fidelity points towards large benefits of site familiarity, prompting spatial migratory plasticity to be expressed through a switch to residency. </li> <li>The contrasting patterns of trajectories of age-related changes between spatial and temporal migration characteristics might reflect different mechanisms underlying the expression of plasticity. Investigating such patterns among species along the entire spectrum of migration tactics would enable further understanding of the plastic responses exhibited by migratory species to rapid environmental changes.</li> </ol>

opencc-by-4.0Nov 2022View details →

Figure 3 in Are recaptures of banded birds efficient at detecting altitudinal migrations in the Atlantic Forest?

Figure 3. Schematic illustration of the altitudinal movements recorded on the slope of Núcleo Curucutu by the recapture of individually marked birds. White lines indicate the two lines of mist-nets at each locality. Source: Google Earth Pro (Image Landsat/Copernicus 2015).

Fig. 4 in Characterization of the Plasmodium and Haemoproteus parasite community in temperate-tropical birds during spring migration

Fig. 4. Differences by foraging guild among infected birds in the probability of Haemoproteus versus Plasmodium infection adjusted for the significant predictors in the model. Single asterisks with brackets beneath denote significant differences between categories.

Fig. 3 in Characterization of the Plasmodium and Haemoproteus parasite community in temperate-tropical birds during spring migration

Fig. 3. Differences by wintering ground among infected birds in the probability of Haemoproteus versus Plasmodium infection adjusted for the significant predictors in the model. Single asterisks with brackets beneath denote significant differences between categories.

Fig. 2 in Characterization of the Plasmodium and Haemoproteus parasite community in temperate-tropical birds during spring migration

Fig. 2. Differences by avian family in the probabilities of a) infection versus non-infection with a Haemosporidian parasite and b) among infected birds, the Plasmodium versus Haemoproteus infection adjusted for the significant predictors in the respective models. Single asterisks with brackets beneath denote significant differences between families.

Fig. 1 in Characterization of the Plasmodium and Haemoproteus parasite community in temperate-tropical birds during spring migration

Fig. 1. Location of field site in Clive Runnells Family Mad Island Marsh Preserve in Texas, USA (Image credit: Google Earth).