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Predicting Migratory Survival in a Songbird Hybrid Zone Using Machine Learning.

Sarah A Vastani1, Stephanie A Blain2, Hannah Justen3

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Extrinsic postzygotic isolation, crucial for speciation, was studied in songbird hybrids. Genetic ancestry and migration orientation influenced survival, suggesting hybrids can benefit from admixture.

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Area of Science:

  • Evolutionary Biology
  • Speciation Research
  • Ornithology

Background:

  • Extrinsic postzygotic isolation is key to speciation but hard to prove.
  • Ecological adaptation differences between populations can drive hybrid disadvantage.
  • Seasonal migration differences are hypothesized as isolating barriers in songbird hybrids.

Purpose of the Study:

  • To demonstrate the role of ecologically relevant traits in hybrid fitness.
  • To investigate how genetic, morphological, and behavioral traits affect migratory survival in a songbird hybrid zone.
  • To assess the impact of extrinsic postzygotic isolation on speciation.

Main Methods:

  • Individual radio tracking of songbirds in a hybrid zone.
  • Machine learning, specifically a random forest model, to predict survival.
  • Analysis of genetic ancestry, heterozygosity, morphology, and migratory orientation.

Main Results:

  • A random forest model predicted migratory survival with 72% accuracy.
  • Genetic ancestry, heterozygosity, and fall orientation significantly impacted survival.
  • Non-linear effects were observed, with some hybrid classes showing increased survival.
  • Body condition and study year also influenced survival predictions.

Conclusions:

  • Hybrid class, defined by ancestry and heterozygosity, affects migratory survival.
  • Initial migratory direction is a critical factor in survival.
  • Ecological selection on migration plays a role in speciation, and some hybrids may benefit from admixture.