Advertisement

Journal of Ornithology

, Volume 161, Issue 1, pp 275–288 | Cite as

Who pays the bill? The effects of altered brood size on parental and nestling physiology

  • Emily Cornelius RuhsEmail author
  • François Vézina
  • Morgan A. Walker
  • William H. Karasov
Original Article

Abstract

Current life history theory suggests that during times of extreme energetic demand, animals may need to trade off physiological capacity of certain functions to maintain other more important biological functions. This might be especially true during reproduction, as parents try to balance their current reproductive demands with the maintenance of themselves and their offspring, while also considering their future fitness. Here, we experimentally manipulated the brood size of black-capped (Poecile atricapillus) and boreal (Poecile hudsonicus) chickadees, giving them  ± 2 nestlings (increased/decreased group) or leaving their nest at the same size (without manipulation; natural comparator group). Parents did not adjust their field metabolic rate to reflect the new brood size; however, nest visitation rate was higher in the decreased group. We found little difference between groups in terms of parental body composition or inflammatory response, with the exception that parents in the decreased group had a higher mass. Nestlings in the increased brood group had lower masses over the course of growth, including right before fledging. The manipulation also appeared to have an impact on tarsus length, but was best explained by a combination of group, species, hatch order and interactions. Nestlings in the decreased group had lower circulating IgY antibodies , but the manipulation had a minimal impact on inflammatory response. We found that, when parents were challenged to work harder, instead of altering aspects of their own physiology, the parents pushed the costs onto their nestlings, resulting in lower quality offspring.

Keywords

Brood manipulation Doubly labeled water Field metabolic rate Nestling Immune function Parent 

Zusammenfassung

Wer zahlt die Zeche? Die Effekte unterschiedlicher Gelegegrößen auf die Physiologie von Eltern und Nestlingen Die aktuelle Life-historie-Theorie besagt, dass in Zeiten extremer energetischer Anforderungen Tiere möglicherweise die physiologischen Leistungsfähigkeit bestimmter Funktionen gegen die von anderen, biologisch wichtigeren Funktionen gegenrechnen und einen Kompromiss finden müssen. Dies könnte vor allem auf die Zeit der Fortpflanzung zutreffen, wenn Eltern versuchen müssen, einen Kompromiss zwischen ihrer eigenen Erhaltung und der ihrer Kinder zu finden, wobei auch deren zukünftige Fitness berücksichtigt werden muss. In unserer Untersuchung manipulierten wir experimentell die Gelegegrößen von Schwarzkopfmeisen (Poecile atricapillus) und Hudsonmeisen (Poecile hudsonicus), indem wir ihnen plus/minus 2 Nestlinge (vergrößerte/verkleinerte Gruppe) gaben oder ihre Nester in der vorgegebenen Gelegegröße beließen (ohne Manipulation; natürliche Vergleichsgruppe). Die Elterntiere passten ihren Grundumsatz nicht an als Antwort auf die die veränderte Gelegegröße, aber die Anzahl der Besuche am Nest war in der verkleinerten Gruppe größer. Wir konnten bei den Eltern keine Unterschiede in der Körperzusammensetzung oder bei Entzündungsreaktionen finden, mit der einen Ausnahme, dass die Elterntiere in der verkleinerten Gruppe eine größere Körpermasse hatten. Die Nestlinge in der verkleinerten Gruppe hatten weniger IgY-Antikörper, aber die Manipulation hatte nur einen minimalen Einfluss auf ihre Entzündungsreaktion. Wir fanden heraus, dass die Eltern, wenn sie gezwungen waren, härter zu arbeiten, die „Kosten“ hierfür ihren Jungen aufbürdeten, statt Parameter ihrer eigenen Physiologie zu verändern, was zu einem Nachwuchs von geringerer Qualität führt.

Notes

Acknowledgements

We would like to thank the Karasov and Vézina laboratory members for edits and laboratory support for this project. We are also grateful to our four field technicians, Sarah Senécal, Cecile Vansteenberghe, Jolanie Roy and Héloïse Albagnac. We would also like to thank Dale Schoeller’s laboratory, especially Timothy Shriver, for the advice and analysis of the DLW samples.

Author contributions

ECR co-designed the experiment, conducted the experiment and analysis and wrote the manuscript. FV co-designed the experiment, helped with data collection and helped write and provided edits to the manuscript. MW helped with data collection, data analysis and provided edits to the manuscript. WHK co-designed the experiment, helped with laboratory and statistical analysis and writing the manuscript.

Supplementary material

10336_2019_1715_MOESM1_ESM.docx (525 kb)
Supplementary material 1 (DOCX 524 kb)

References

  1. Akaike H (1974) A new look at statistical model identification. IEE Trans Autom Control 19:716–723Google Scholar
  2. Amat JA (2007) Energetic and developmental costs of mounting an immune response in greenfinches (Carduelis chloris). Ecol Res 22:282–287Google Scholar
  3. Ardia DR (2005) Individual quality mediates trade-offs between reproductive effort and immune function in tree swallows. J Anim Ecol 74:517–524Google Scholar
  4. Ardia DR, Schat KA, Winkler DW (2003) Reproductive effort reduces long-term immune function in breeding tree swallows (Tachycineta bicolor). Proc R Soc Lond B 270:1679–1683Google Scholar
  5. Arnold T (2010) Uninformative parameters and model selection using Akaike’s Information Criterion. J Wildl Manag 74:1175–1178Google Scholar
  6. Bartón K (2014) R package “MuMIn”: multi-model inference (version 1.10. 5). http://CRAN.R-project.org/package=MuMIn
  7. Bates D, Maechler M, Bolker B, Walker S (2015) Fitting linear mixed-effects models using lme4. J Stat Softw 67(1):1–48.  https://doi.org/10.18637/jss.v067.i01 CrossRefGoogle Scholar
  8. Bridge E, Bonter D (2011) A low-cost radio frequency identification device for ornithological research. J Field Ornithol 82:52–59Google Scholar
  9. Burnham KP, Anderson DR (eds) (2004) Model selection and multimodel inference. Springer, New YorkGoogle Scholar
  10. Cornelius EA, Vézina F, Regimbald L, Hallot F, Petit M, Love OP, Karasov WH (2017) Chickadees faced with unpredictable food increase fat reserves but certain components of their immune function decline. Physiol Biochem Zool 90:190–200PubMedGoogle Scholar
  11. Demas G, Greives T, Chester E, French S (2012) The energetics of immunity: mechanisms mediating trade-offs in ecoimmunology. In: Demas G, Nelson RJ (eds) Ecoimmunology. Oxford University Press, New York, pp 259–296Google Scholar
  12. Doherty PF, Williams JB, Grubb TC (2001) Field metabolism and water flux of carolina chickadees during breeding and nonbreeding seasons: a test of the ‘peak-demand’ and ‘reallocation’ hypotheses. Condor 103:370–375Google Scholar
  13. Drent RH, Daan S (1980) The prudent parent: energetic adjustments in avian breeding. Ardea 38–90:225–252Google Scholar
  14. Elliott KH, Le Vaillant M, Kato A, Gaston AJ, Ropert-Coudert Y, Hare JF, Speakman JR, Croll D (2014) Age-related variation in energy expenditure in a long-lived bird within the envelope of an energy ceiling. J Anim Ecol 83:136–146PubMedGoogle Scholar
  15. Ellis HI, Jehl JR (1991) Total body water and body composition in phalaropes and other birds. Physiol Zool 64:973–984Google Scholar
  16. Emlen ST, Wrege PH, Demong NJ, Hegner RE (1991) Flexible growth rates in nestling White-fronted bee-eaters: a possible adaptation to short-term food shortage. Condor 93:591–597Google Scholar
  17. Fassbinder-Orth CA, Wilcoxen TE, Tran T, Boughton RK, Fair JM, Hofmeister EK, Grindstaff JL, Owen JC (2016) Immunoglobulin detection in wild birds: effectiveness of three secondary anti-avian IgY antibodies in direct ELISAs in 41 avian species. Methods Ecol Evol 7:1174–1181PubMedPubMedCentralGoogle Scholar
  18. Fowler MA, Williams TD (2017) A physiological signature of the cost of reproduction associated with parental care. Am Nat 6:762–773Google Scholar
  19. Hawley DM, DuRant SE, Wilson AF, Adelman JS, Hopkins WA (2012) Additive metabolic costs of thermoregulation and pathogen infection. Funct Ecol 26:701–710Google Scholar
  20. Hegemann A, Matson KD, Versteegh MA, Tieleman BI (2012) Wild skylarks seasonally modulate energy budgets but maintain energetically costly inflammatory immune responses throughout the annual cycle. PLoS One 7:e36358PubMedPubMedCentralGoogle Scholar
  21. Hegner RE, Wingfield JC (1987) Effects of brood-size manipulations on parental investment, breeding success, and reproductive endocrinology of house sparrows. Auk 104:470–480Google Scholar
  22. Hõrak P, Ots I, Murumägi A (1998) Haematological health state indices of reproducing Great Tits: a response to brood size manipulation. Funct Ecol 12:750–756Google Scholar
  23. Ilmonen P, Hasselquist D, Langefors Å, Wiehn J (2003) Stress, immunocompetence and leukocyte profiles of pied flycatchers in relation to brood size manipulation. Oecologia 136:148–154PubMedGoogle Scholar
  24. Karasov WH, Brittingham MC, Temple SA (1992) Daily energy and expenditure by black-capped chickadees (Parus atricapillus) in winter. The Auk 109:393–395Google Scholar
  25. Ketterson VN, Thompson CF (2012) Current ornithology. Springer Science and Business Media, BerlinGoogle Scholar
  26. Killpack TL, Karasov WH (2012) Ontogeny of adaptive antibody response to a model antigen in captive altricial Zebra finches. PLoS One 7:e47294PubMedPubMedCentralGoogle Scholar
  27. Killpack TL, Carrel E, Karasov WH (2015) Impacts of Short-Term Food Restriction on Immune Development in Altricial House Sparrow Nestlings. Physiol Biochem Zool 88:195–207PubMedGoogle Scholar
  28. King MO, Swanson DL (2013) Activation of the immune system incurs energetic costs but has no effect on the thermogenic performance of House sparrows during acute cold challenge. J Exp Biol 216:2097–2102PubMedGoogle Scholar
  29. Knowles SCL, Nakagawa S, Sheldon BC (2009) Elevated reproductive effort increases blood parasitaemia and decreases immune function in birds: a meta-regression approach. Funct Ecol 23:405–415Google Scholar
  30. Konarzewski M, Kowalczyk J, Swierubska T, Lewonczuk B (1996) Effect of short-term feed restriction, realimentation and overfeeding on growth of song thrush (Turdus philomelos) nestlings. Funct Ecol 10:97–105Google Scholar
  31. Krams I, Vrublevska J, Cirule D, Kivleniece I, Krama T, Rantala MJ, Sild E, Hõrak P (2012) Heterophil/lymphocyte ratios predict the magnitude of humoral immune response to a novel antigen in great tits (Parus major). Comp Biochem Physiol A 161:422–428Google Scholar
  32. Lee KA (2006) Linking immune defenses and life history at the levels of the individual and the species. Integr Comp Biol 46:1000–1015PubMedGoogle Scholar
  33. Lenth RV (2016) Least-squares means: the R Package lsmeans. J Stat Softw 69(1):1–33.  https://doi.org/10.18637/jss.v069.i01 CrossRefGoogle Scholar
  34. Lochmiller RL, Deerenberg C (2000) Trade-offs in evolutionary immunology: just what is the cost of immunity? Oikos 88:87–98Google Scholar
  35. Martin TE (1987) Food as a limit on breeding birds: a life-history perspective. Annu Rev Ecol Evol Syst 18:453–487Google Scholar
  36. Nagy KA (1983) The doubly labeled water (3HH18O) method: a guide to its use. UCLA Publication no 12–1417. UCLA, Los Angeles, CAGoogle Scholar
  37. Nilsson JA (2002) Metabolic consequences of hard work. Proc R Soc B 269:1735–1739PubMedGoogle Scholar
  38. Nordling D, Andersson M, Zohari S, Gustafsson L (1998) Reproductive effort reduces specific immune response and parasite resistance. Proc R Soc 265:1291–1298Google Scholar
  39. Olsen J, Tucker AD (2003) A brood-size manipulation experiment with Peregrine Falcons, Falco peregrinus, near Canberra. Emu - Austral Ornithol 103:127–132Google Scholar
  40. Owen-Ashley NT, Wingfield JC (2007) Acute phase responses of passerine birds: characterization and seasonal variation. J Ornithol 148:583–591Google Scholar
  41. Owen-Ashley NT, Turner M, Hahn TP, Wingfield JC (2006) Hormonal, behavioral, and thermoregulatory responses to bacterial lipopolysaccharide in captive and free-living white-crowned sparrows (Zonotrichia leucophrys gambeli). Horm Behav 49:15–29PubMedGoogle Scholar
  42. Perrins C (1965) Population fluctuations and clutch-size in the Great tit, Parus major L. J Anim Ecol 34:601–647Google Scholar
  43. Rofstad G (1986) Growth and morphology of nestling Hooded crows Corvus corone cornix, a sexually dimorphic bird species. J Zool 208:299–323Google Scholar
  44. Saino N, Calza S, Moller AP (1997) Immunocompetence of nestling barn swallows in relation to brood size and parental effort. J Anim Ecol 66:827–836Google Scholar
  45. Santos ESA, Nakagawa S (2012) The costs of parental care: a meta-analysis of the trade-off between parental effort and survival in birds. J Evol Biol 25:1911–1917PubMedGoogle Scholar
  46. Schew W, Ricklefs RE (1998) Developmental plasticity. In: Starck M, Ricklefs RE (eds) Avian growth and development: evolution within the altricial-precocial spectrum. Oxford University Press, Oxford, pp 288–304Google Scholar
  47. Schroeder J, Cleasby I, Dugdale HL, Nakagawa S, Burke T (2013) Social and genetic benefits of parental investment suggest sex differences in selection pressures. J Avian Biol 44:133–140Google Scholar
  48. Sköld-Chiriac S, Nord A, Tobler M, Nilsson J-Å, Hasselquist D (2015) Body temperature changes during simulated bacterial infection in a songbird: fever at night and hypothermia during the day. J Exp Biol 218:2961–2969PubMedGoogle Scholar
  49. Speakman JR (1997) Doubly-labelled water: theory and practice. Springer Academic Publishers, New YorkGoogle Scholar
  50. Svensson E, Råberg L, Koch C, Hasselquist D (1998) Energetic stress, immunosuppression and the costs of an antibody response. Funct Ecol 12:912–919Google Scholar
  51. Tieleman BI, Dijkstra TH, Klasing KC, Visser GH, Williams JB (2008) Effects of experimentally increased costs of activity during reproduction on parental investment and self-maintenance in tropical House wrens. Behav Ecol 19:949–959Google Scholar
  52. Vitousek MN, Jenkins BR, Hubbard JK, Kaiser SA, Safran RJ (2017) An experimental test of the effect of brood size on glucocorticoid responses, parental investment, and offspring phenotype. Gen Comp Endocrinol 247:97–106PubMedGoogle Scholar
  53. Webster MD, Weathers WW (1989) Validation of single-sample doubly labeled water method. Am J Physiol 256:R572–R576PubMedGoogle Scholar
  54. Whitaker S, Fair J (2002) The costs of immunological challenge to developing mountain chickadees, Poecile gambeli, in the wild. Oikos 99:161–165Google Scholar
  55. Wicher KB, Fries E (2006) Haptoglobin, a hemoglobin-binding plasma protein, is present in bony fish and mammals but not in frog and chicken. Proc Natl Acad Sci 103(11):4168–4173PubMedGoogle Scholar
  56. Williams TD, Fowler MA (2015) Individual variation in workload during parental care: can we detect a physiological signature of quality or cost of reproduction? J Ornithol 156:441–451Google Scholar
  57. Wright J, Both C, Cotton PA, Bryant D (1998) Quality vs. quantity: energetic and nutritional trade-offs in parental provisioning strategies. J Anim Ecol 67:620–634Google Scholar

Copyright information

© Deutsche Ornithologen-Gesellschaft e.V. 2019

Authors and Affiliations

  1. 1.Department of Forest and Wildlife EcologyUniversity of Wisconsin-MadisonTampaUSA
  2. 2.Global and Planetary HealthUniversity of South FloridaTampaUSA
  3. 3.Département de biologie, chimie et géographieUniversité du Québec à RimouskiRimouskiCanada
  4. 4.Groupe de recherche sur les environnements nordique BORÉAS, Centre d’études nordiquesCentre de la science de la biodiversité du QuébecMadisonUSA
  5. 5.Department of GeographyUniversity of FloridaTampaUSA

Personalised recommendations