Differences in tail feather growth rate in storm-petrels breeding in the Northern and Southern hemisphere: a ptilochronological approach

Anne Ausems , Katarzyna Wojczulanis-Jakubas , Dariusz Jakubas

Abstract

Moulting and breeding are costly stages in the avian annual cycle and may impose trade-offs in energy allocation between both stages or in their timing. Here, we compared feather growth rates (FGR) of rectrices in adults between two pairs of small pelagic Procellariiformes species differing in moult-breeding strategies: the European storm-petrelHydrobates pelagicusand Leach’s storm-petrelOceanodroma leucorhoabreeding in the Northern Hemisphere (Faroe Islands), showing moult-breeding overlap in tail feathers; and the Wilson’s storm-petrelOceanites oceanicusand black-bellied storm-petrelFregetta tropica, breeding in the Southern Hemisphere (South Shetlands), temporally separating moult and breeding. We used ptilochronology (i.e., feather growth bar width) to reconstruct FGR reflecting relative energy availability during moult. Based on previous research, we expected positive correlations between feather length (FL) and FGR. Additionally, we expected to find differences in FGR relative to FL between the moult-breeding strategies, where a relatively higher FGR to FL indicates a higher energy availability for moult. To investigate if energy availability during moult in the studied species is similar to species from other avian orders, we used FGR and FL found in literature (n = 164) and this study. We fitted a phylogenetic generalized least squares (PGLS) model to FGR with FL, group (i.e., Procellariiformes vs. non-Procellariiformes) and the interaction FL * group as predictors. As it has been suggested that Procellariiformes may form two growth bars per 24 h, we fitted the same model but with doubled FGR for Procellariiformes (PGLSadj). The group term was significant in the PGLS model, but was not in the PGLSadj model, confirming this suggestion. Individually predicted FGR by the PGLSadj model based on FL, showed that the Southern species have a significantly higher FGR relative to FL compared to the Northern species. Additionally, we found no correlation between FL and FGR in the Northern species, and a positive correlation between FL and FGR in the Southern species, suggesting differences in the trade-off between feather growth and size between species from both hemispheres. The observed differences between the Northern and Southern species may be caused by different moult-breeding strategies. The Southern species may have had more energy available for moult as they are free from breeding duties during moult, while the Northern species may have had less free energy due to a trade-off in energy allocation between breeding and moulting. Our study shows how different moult-breeding strategies may affect relative nutritional condition or energy allocation during moult of migratory pelagic seabirds.
Author Anne Ausems (FB/DVEZ)
Anne Ausems,,
- Department of Vertebrate Ecology and Zoology
, Katarzyna Wojczulanis-Jakubas (FB/DVEZ)
Katarzyna Wojczulanis-Jakubas,,
- Department of Vertebrate Ecology and Zoology
, Dariusz Jakubas (FB/DVEZ)
Dariusz Jakubas,,
- Department of Vertebrate Ecology and Zoology
Journal seriesPeerJ, ISSN 2167-8359, (N/A 100 pkt)
Issue year2019
Vol7
Pages1-22
Publication size in sheets1.05
Article numbere7807
Keywords in Englishptilochronology, storm-petrels, growth bar width, moult-breeding overlap, feathergrowth rate
ASJC Classification2700 General Medicine; 1100 General Agricultural and Biological Sciences; 1300 General Biochemistry, Genetics and Molecular Biology; 2800 General Neuroscience
DOIDOI:10.7717/peerj.7807
URL https://doi.org/10.7717/peerj.7807
Languageen angielski
LicenseJournal (articles only); published final; Uznanie Autorstwa (CC-BY); with publication
Score (nominal)100
Score sourcejournalList
ScoreMinisterial score = 100.0, 28-01-2020, ArticleFromJournal
Publication indicators WoS Citations = 0.000; Scopus SNIP (Source Normalised Impact per Paper): 2016 = 0.865; WoS Impact Factor: 2018 = 2.353 (2) - 2018=2.700 (5)
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