Riverine Barriers as Obstacles to Dispersal in Amazonian Birds
Notice bibliographique
Résumé
Amazonian rivers represent known barriers for avian dispersal, reducing gene flow and enhancing differentiation. Despite the importance of rivers in the avian evolutionary process, we have made only minor advances in understanding the limitations imposed by rivers on flying birds. To fill that gap, we conducted dispersal-challenge experiments over water, assessing the flying capabilities of 84 tropical bird species of 22 different avian families. We mist-netted and released 484 birds from a stationary boat on the Rio Branco, northern Amazonia, at increasing distances from the shore, including 249 individuals at 100; 219 at 200; 8 at 300; and 5 at 400 m. A successful trial was represented by a bird reaching the riverbank, whereas a failure would refer to birds not reaching the shore and landing on the water, when they were rescued by our team. Our main goal was to understand if the outcome in the experiments could be predicted by (i) phylogenetic constraints, (ii) morphology (body mass and wing shape), (iii) flight speed, (iv) ecological preferences (stratum, habitat, and river-island specialization), and (v) psychological reluctance to fly. Nearly two thirds of the individuals (332) were successful in reaching the riverbank, whereas 152 failed. We found significant differences among lineages. Whereas seven avian families succeeded in all of the trials, two families (antbirds and wrens) were particularly bad dispersers (<40% success). The hand-wing index (HWI) was the single most powerful predictor of trial success. Flying speed was also a significant predictor of success. Overall, ecological attributes had a low explanatory power. Only forest stratum preference had a significant, although weak, effect on dispersal ability: canopy- and ground-dwellers performed better than understory birds. However, we found no effect of habitat preference or river-island specialization on dispersal ability. Our speed estimates for 64 bird species are among the first produced for the tropics and suggest slower flying speeds than those reported from temperate migratory birds. Although birds showed behavioral differences when presented with the opportunity to fly away from the boat, we found no evidence that their reluctance to fly could predict the outcome in the experiments. This represents the first experimental study evaluating the riverine effect through dispersal ability of Amazonian birds, providing important insights to better understand dispersal limitations provided by riverine barriers.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».