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Individual improvements and selective mortality shape lifelong migratory performance

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Abstract

Billions of organisms, from bacteria to humans, migrate each year1 and research on their migration biology is expanding rapidly through ever more sophisticated remote sensing technologies2,3,4. However, little is known about how migratory performance develops through life for any organism. To date, age variation has been almost systematically simplified into a dichotomous comparison between recently born juveniles at their first migration versus adults of unknown age5,6,7. These comparisons have regularly highlighted better migratory performance by adults compared with juveniles6, but it is unknown whether such variation is gradual or abrupt and whether it is driven by improvements within the individual, by selective mortality of poor performers, or both. Here we exploit the opportunity offered by long-term monitoring of individuals through Global Positioning System (GPS) satellite tracking to combine within-individual and cross-sectional data on 364 migration episodes from 92 individuals of a raptorial bird, aged 1–27 years old. We show that the development of migratory behaviour follows a consistent trajectory, more gradual and prolonged than previously appreciated, and that this is promoted by both individual improvements and selective mortality, mainly operating in early life and during the pre-breeding migration. Individuals of different age used different travelling tactics and varied in their ability to exploit tailwinds or to cope with wind drift. All individuals seemed aligned along a race with their contemporary peers, whose outcome was largely determined by the ability to depart early, affecting their subsequent recruitment, reproduction and survival. Understanding how climate change and human action can affect the migration of younger animals may be the key to managing and forecasting the declines of many threatened migrants.

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Figure 1: A river of raptors.
Figure 2: Migration performance across and within individuals.
Figure 3: Age-related changes in average speed, duration and timing of pre-breeding migrations.
Figure 4: Age-related changes in average speed, duration and timing of post-breeding migrations.

Change history

  • 19 November 2014

    A minor change was made to the main text.

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Acknowledgements

We thank F. J. Chicano, F. G. Vilches, J. M. Giralt and M. Anjos for help in the field, I. Afán and D. Aragonés for support with GIS analyses, the personnel of the Reserva Biológica de Doñana for logistical help and accommodation, the LEM-EBD for molecular sexing, and Microwave Telemetry for technical support. Part of the study was funded by Natural Research Ltd and research projects CGL2008-01781, CGL2011-28103 and CGL2012-32544 of the Spanish Ministry of Science and Innovation/Economy and Competitiveness and FEDER funds, 511/2012 of the Spanish Ministry of Agriculture, Food and the Environment (Autonomous Organism of National Parks), JA-58 of the Consejería de Medio Ambiente de la Junta de Andalucía and by the Excellence Projects RNM 1790, RNM 3822 and RNM 7307 of the Junta de Andalucía. R.D.S. was supported by the Juan de la Cierva Programme and by the Severo Ochoa Programme for Centres of Excellence of the Spanish Ministry of Economy and Competitiveness (SEV-2012-0262). J.B. was supported by a Ramón y Cajal contract from the CSIC.

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Contributions

F.S., A.T., L.L.J., J.B. and F.H. conducted fieldwork. F.S., A.T., R.D.S., G.T. and D.P. prepared the database, extracted and processed the environmental data from internet sources and analysed the data. F.S. and F.H. obtained funding. R.D.S., A.T. and F.S. developed the Supplementary Videos. All authors took part in the conceptual planning of the study and in the preparation of the manuscript.

Corresponding author

Correspondence to Fabrizio Sergio.

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The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Mean components of pre-breeding migration.

aj, Migration components varied cross-sectionally with age in timing (a, b), speed of progression (c, d), duration (e, f, g, h), route length (i) and longitudinal position of the route (j). Error bars represent 1 s.e.m.

Extended Data Figure 2 Mean components of post-breeding migration.

aj, Migration components varied cross-sectionally with age in timing (a, b), speed of progression (c, d), duration (e, f, g, h), route length (i) and longitudinal position of the route (j). Error bars represent 1 s.e.m.

Extended Data Table 1 Estimates of pre-breeding and post-breeding migration by 92 individual black kites of Doñana National Park, southwestern Spain
Extended Data Table 2 Summary of main results of the mixed models examining the effects of age and environmental variables on migration components
Extended Data Table 3 Cross-sectional effect of age and environmental variables on migration components in the pre-breeding migration
Extended Data Table 4 Cross-sectional effect of age and environmental variables on migration components in the post-breeding migration
Extended Data Table 5 Longitudinal effect of age, migration timing and environmental variables on migration components in the pre-breeding migration
Extended Data Table 6 Repeatability of migration components for different age classes
Extended Data Table 7 Mixed effects models testing the relationship between migration components and fitness
Extended Data Table 8 Longitudinal effect of age, migration timing and environmental variables on migration components in the post-breeding migration

Related audio

Supplementary information

Video 1: The speed of kites in the pre-breeding migration varied with age and was at the maximum in birds of age 3-6, intermediate for birds above 7 years old and lowest in 1-2 years olds

In this video simulation, individuals of all ages are imposed to depart for migration at the same time. They then travel with a speed proportional to the mean value for their age, class and progress along the average population route (see Methods). Under this scenario of equal departure timings, individuals of 3-6 years of age are the first to arrive to the breeding quarters, followed by kites older than seven years and then by 1-2 years old birds. This pattern changes radically when incorporating differences in timing of departure among age classes (see Supplementary Video 2). (WMV 2802 kb)

Video 2: When incorporating differences in timing of departure among age-classes, older birds always arrived at the breeding quarters before younger ones, independently of differences in speed performance.

In this simulation, differences in the timings of departure among age classes are proportional to the observed mean differences in timing. The birds then travel with a speed proportional to the mean value for their age, class and progress along the average route, as in Supplementary Video 1. Under this scenario, age-differences in departure times are so large that they fully dictate the order of arrival and older birds always arrive earlier than younger ones. Therefore, the higher speed of 3-6 years olds, shown in Supplementary Video 1, is swamped by the capability to depart early, which is typical of older, more experienced individuals. Note that the migration speeds in Video 1 and 2 have been arranged so that, in both cases, the overall video-duration is 50 seconds, while the relationship between migratory speed and the time lags in sequential departures are always proportional to their observed averages. (WMV 2755 kb)

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Sergio, F., Tanferna, A., De Stephanis, R. et al. Individual improvements and selective mortality shape lifelong migratory performance. Nature 515, 410–413 (2014). https://doi.org/10.1038/nature13696

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