Background
In-flight conditions are hypothesized to influence the timing and success of long-distance migration. Wind assistance and thermal uplift are thought to reduce the energetic costs of flight, humidity, air pressure and temperature may affect the migrants’ water balance, and clouds may impede navigation. Recent advances in animal-borne long-distance tracking enable evaluating the importance of these factors in determining animals’ flight altitude.
Methods
Here we determine the effects of wind, humidity, temperature, cloud cover, and altitude (as proxy for climbing costs and air pressure) on flight altitude selection of two long-distance migratory shorebirds, far eastern curlew (Numenius madagascariensis) and whimbrel (Numenius phaeopus). To reveal the predominant drivers of flight altitude selection during migration we compared the atmospheric conditions at the altitude the birds were found flying with conditions elsewhere in the air column using conditional logistic mixed effect models.
Results
Our results demonstrate that despite occasional high-altitude migrations (up to 5550 m above ground level), our study species typically forego flying at high altitudes, limiting climbing costs and potentially alleviating water loss and facilitating navigation. While mainly preferring migrating at low altitude, notably in combination with low air temperature, the birds also preferred flying with wind support to likely reduce flight costs. They avoided clouds, perhaps to help navigation or to reduce the risks from adverse weather.
Conclusions
We conclude that the primary determinant of avian migrant’s flight altitude selection is a preference for low altitude, with wind support as an important secondary factor. Our approach and findings can assist in predicting climate change effects on migration and in mitigating bird strikes with air traffic, wind farms, power lines, and other human-made structures.
Migratory connectivity describes the extent to which migratory species' populations are connected throughout the annual cycle. While recognized as critical for understanding the population dynamics of migratory species and conserving them, empirical evidence of links between migratory connectivity and population dynamics are uncommon. We analyzed associations between spatiotemporal connectivity and differential population trends in a declining and endangered migratory shorebird, the far eastern curlew (Numenius madagascariensis), with multiyear tracking data from across the Australian nonbreeding grounds. We found evidence of temporal and spatial segregation during migration and breeding: curlew from southeast Australia initiated northward migration earlier, arrived at breeding sites earlier, and bred at lower latitudes than curlew from northwest Australia. Analysis of land modification intensity revealed that populations from southeast Australia face greater human impacts compared to those from northwest Australia at both the breeding and nonbreeding grounds, a pattern that aligns with steeper population declines in southeast Australia. This alignment between migratory † Clive D. T. Minton was deceased.
Animal tolerance towards humans can be a key factor facilitating wildlife–human coexistence, yet traits predicting its direction and magnitude across tropical animals are poorly known. Using 10,249 observations for 842 bird species inhabiting open tropical ecosystems in Africa, South America, and Australia, we find that avian tolerance towards humans was lower (i.e., escape distance was longer) in rural rather than urban populations and in populations exposed to lower human disturbance (measured as human footprint index). In addition, larger species and species with larger clutches and enhanced flight ability are less tolerant to human approaches and escape distances increase when birds were approached during the wet season compared to the dry season and from longer starting distances. Identification of key factors affecting animal tolerance towards humans across large spatial and taxonomic scales may help us to better understand and predict the patterns of species distributions in the Anthropocene.
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