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Timing of spring departure of long distance migrants correlates with previous year's conditions at their breeding site.

Françoise AmélineauNicolas DelbartPhilipp SchwemmerRiho MarjaJérôme FortStefan GartheJaanus EltsPhilippe DelaportePierre RousseauFrançoise DuraffourPierrick Bocher
Published in: Biology letters (2021)
Precise timing of migration is crucial for animals targeting seasonal resources at locations encountered across their annual cycle. Upon departure, long-distance migrants need to anticipate unknown environmental conditions at their arrival site, and they do so with their internal annual clock. Here, we tested the hypothesis that long-distance migrants synchronize their circannual clock according to the phenology of their environment during the breeding season and therefore adjust their spring departure date according to the conditions encountered at their breeding site the year before. To this end, we used tracking data of Eurasian curlews from different locations and combined movement data with satellite-extracted green-up dates at their breeding site. The spring departure date was better explained by green-up date of the previous year, while arrival date at the breeding site was better explained by latitude and longitude of the breeding site, suggesting that other factors impacted migration timing en route. On a broader temporal scale, our results suggest that long-distance migrants may be able to adjust their migration timing to advancing spring dates in the context of climate change.
Keyphrases
  • climate change
  • electronic health record
  • big data
  • machine learning
  • risk assessment
  • deep learning
  • cancer therapy