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Effects of developmental conditions on growth, stress and telomeres in black-legged kittiwake chicks.

Published on Jul 1, 2017in Molecular Ecology5.86
· DOI :10.1111/mec.14121
Rebecca C. Young9
Estimated H-index: 9
(UNAM: National Autonomous University of Mexico),
Jorg Welcker19
Estimated H-index: 19
(UAF: University of Alaska Fairbanks)
+ 5 AuthorsAlexander S. Kitaysky33
Estimated H-index: 33
(UAF: University of Alaska Fairbanks)
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Abstract
Early-life conditions can drive ageing patterns and life history strategies throughout the lifespan. Certain social, genetic and nutritional developmental conditions are more likely to produce high-quality offspring: those with good likelihood of recruitment and productivity. Here, we call such conditions "favoured states" and explore their relationship with physiological variables during development in a long-lived seabird, the black-legged kittiwake (Rissa tridactyla). Two favoured states were experimentally generated by manipulation of food availability and brood size, while hatching order and sex were also explored as naturally generating favoured states. Thus, the favoured states we explored were high food availability, lower levels of sibling competition, hatching first and male sex. We tested the effects of favoured developmental conditions on growth, stress, telomere length (a molecular marker associated with lifespan) and nestling survival. Generation of favoured states through manipulation of both the nutritional and social environments furthered our understanding of their relative contributions to development and phenotype: increased food availability led to larger body size, reduced stress and higher antioxidant status, while lower sibling competition (social environment) led to lower telomere loss and longer telomere lengths in fledglings. Telomere length predicted nestling survival, and wing growth was also positively correlated with telomere length, supporting the idea that telomeres may indicate individual quality, mediated by favoured states.
  • References (78)
  • Citations (9)
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References78
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#2Julio Blas (CSIC: Spanish National Research Council)H-Index: 26
Last.Fabrizio Sergio (CSIC: Spanish National Research Council)H-Index: 32
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#1John R. Speakman (CAS: Chinese Academy of Sciences)H-Index: 78
#2Jonathan D. Blount (University of Exeter)H-Index: 37
Last.Michael Briga (UG: University of Groningen)H-Index: 10
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#1Simone Vincenzi (Polytechnic University of Milan)H-Index: 17
#2Scott A. Hatch (USGS: United States Geological Survey)H-Index: 29
Last.Alexander S. Kitaysky (UAF: University of Alaska Fairbanks)H-Index: 33
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#1Joacim Näslund (University of Gothenburg)H-Index: 12
#2Angela Pauliny (University of Gothenburg)H-Index: 9
Last.Jörgen I. Johnsson (University of Gothenburg)H-Index: 38
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#1Norith Eckbo (University of Oslo)H-Index: 2
#2Céline Le Bohec (UDS: University of Strasbourg)H-Index: 6
Last.Katrine Borgå (University of Oslo)H-Index: 29
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#1Allison Injaian (UC Davis: University of California, Davis)H-Index: 4
#2Paulina L. González-Gómez (UC Davis: University of California, Davis)H-Index: 8
Last.John C. Wingfield (UC Davis: University of California, Davis)H-Index: 108
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#1Andrea S. Grunst (ISU: Indiana State University)H-Index: 7
#2Melissa L. Grunst (ISU: Indiana State University)H-Index: 7
Last.Elaina M. Tuttle (ISU: Indiana State University)H-Index: 17
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#1Beate A. Apfelbeck (Glas.: University of Glasgow)H-Index: 9
#2Mark F. Haussmann (Bucknell University)H-Index: 25
Last.Barbara Helm (Glas.: University of Glasgow)H-Index: 27
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#1Nicola Saino (University of Milan)H-Index: 53
#2Roberto Ambrosini (University of Milano-Bicocca)H-Index: 22
Last.Marco Parolini (University of Milan)H-Index: 23
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#1Jelle J. Boonekamp (UG: University of Groningen)H-Index: 8
#2Christina Bauch (UG: University of Groningen)H-Index: 9
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