Look at the time: diel variation in the flight initiation distance of a nectarivorous bird

  • Stephen M. FergusonEmail author
  • Lauren N. Gilson
  • Philip W. Bateman
Original Article


When approached by a predator, foraging animals should adjust escape behavior based on their current energetic status to minimize opportunity costs (foraging time) and maximize the chance of escape. Animals should therefore be more reluctant to leave a foraging patch when their energy reserves are low and should flee using low-energy escape tactics, but be quicker to flee and use the best escape tactic when satiated. Nectarivorous birds have little capacity for energy storage; thus, they should be particularly sensitive to variation in nutritional status throughout the day. We tested whether New Holland honeyeaters (Phylidonyris novaehollandiae) alter their antipredator behavior by testing whether flight initiation distance (FID—the distance at which an individual flees from an approaching predator) and escape tactic (hopping or flying) vary over the course of the day. Honeyeater FID was shortest in the morning, following the overnight fast, and longest at midday. In the evening, though FID tended to shorten, responses were more variable overall, likely due to individual variation in foraging success. In the morning, honeyeaters were equally likely to hop or fly when approached, but increasingly favored flight as the day progressed. These results suggest a strong link between individual energetic condition and antipredator responses. We suggest that time of day is a useful and important variable influencing escape behavior, the potential effects of which should be more consistently considered as a covariate in the widely used FID protocol.

Significance statement

Diel variation in internal and external conditions can alter behavioral responses. In this study, we observed antipredator response behaviors in foraging New Holland honeyeaters, small passerines sensitive to changes in energy status throughout the day. We found that honeyeaters allowed researchers to approach more closely in the morning and evening before fleeing and escaped by flying more often than hopping as the day progressed. Our results suggest that antipredator behaviors are sensitive to current energy status and impending energy needs. In addition, we show that time of day is an important consideration in the experimental design and statistical analysis of behavior studies.


Antipredator behavior Escape strategy FID Foraging Time of day 



Thanks go to the BEERS group of Curtin and Murdoch Universities for discussion during analyses. Thanks also to Bill Cooper and Blake Jones for their helpful suggestions on earlier versions of this manuscript. We thank our anonymous reviewers who also made important contributions.

Funding information

SMF was supported by an Endeavor Research Fellowship from the Australia Department of Education and Training.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflicts of interest.

Ethical approval

All applicable Australia and Western Australia laws were followed during the course of this study. The Curtin University Animal Ethics Committee approved all experimental methods (ARE2017-17).

Supplementary material

265_2019_2757_MOESM1_ESM.docx (65 kb)
ESM 1 (DOCX 64 kb)


  1. Blamires SJ (1999) Factors influencing the escape response of an arboreal agamid lizard of tropical Australia (Lophognathus temporalis) in an urban environment. Can J Zool 77:1998–2003. CrossRefGoogle Scholar
  2. Blumstein DT (2003) Flight-initiation distance in birds is dependent on intruder starting distance. J Wildl Manag 67:852–857CrossRefGoogle Scholar
  3. Blumstein DT, Samia DSM, Stankowich T, Cooper WE Jr (2015) Best practice for the study of escape behavior. In: Cooper WE Jr, Blumstein DT (eds) Escaping from predators: an integrative view of escape decisions. Cambridge University Press, Cambridge, pp 407–419CrossRefGoogle Scholar
  4. Bulova SJ (1994) Ecological correlates of population and individual variation in antipredator behavior of two species of desert lizards. Copeia 1994:980–992CrossRefGoogle Scholar
  5. Cleasby IR, Nakagawa S (2011) Neglected biological patterns in the residuals: a behavioural ecologist’s guide to co-operating with heteroscedasticity. Behav Ecol Sociobiol 65:2361–2372. CrossRefGoogle Scholar
  6. Collins BG (1985) Energetics of foraging and resource selection by honeyeaters in forest and woodland habitats of Western Australia. New Zeal J Zool 12:577–587. CrossRefGoogle Scholar
  7. Collins BG, Clow H (1978) Feeding behaviour and energetics of the western spinebill, Canthorhynchus superciliosis (Aves: Meliphagidae). Aust J Zool 26:269–277. CrossRefGoogle Scholar
  8. Collins BG, Morellini PC (1979) The influence of nectar concentration and time of day upon energy intake and expenditure by the singing honeyeater, Meliphaga virescens. Physiol Zool 52:165–175CrossRefGoogle Scholar
  9. Collins BG, Cary G, Packard G (1980) Energy assimilation, expenditure and storage by the brown honeyeater, Lichmera indistincta. J Comp Physiol B 137:157–163. CrossRefGoogle Scholar
  10. Collins BG, Walsh M, Grey J (2008) Floral development and breeding systems of Dryandra sessilis and Grevillea wilsonii (Proteaceae). Aust J Bot 56:119–130. CrossRefGoogle Scholar
  11. Cooper WE Jr, Blumstein DT (2015) Escaping from predators: an integrative view of escape decisions. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  12. Cooper WE Jr, Frederick WG (2007) Optimal flight initiation distance. J Theor Biol 244:59–67. CrossRefPubMedGoogle Scholar
  13. Cooper WE Jr, Frederick WG (2010) Predator lethality, optimal escape behavior, and autotomy. Behav Ecol 21:91–96. CrossRefGoogle Scholar
  14. Dumont F, Pasquaretta C, Réale D, Bogliani G, von Hardenberg A (2012) Flight initiation distance and starting distance: biological effect or mathematical artefact? Ethology 118:1051–1062. CrossRefGoogle Scholar
  15. Engqvist L (2005) The mistreatment of covariate interaction terms in linear model analyses of behavioural and evolutionary ecology studies. Anim Behav 70:967–971. CrossRefGoogle Scholar
  16. Guay P-J, van Dongen WFD, Robinson RW, Blumstein DT, Weston MA (2016) AvianBuffer : an interactive tool for characterising and managing wildlife fear responses. Ambio 45:841–851. CrossRefPubMedPubMedCentralGoogle Scholar
  17. Hurlbert SH (1984) Pseudoreplication and the design of ecological field experiments. Ecol Monogr 54:187–211. CrossRefGoogle Scholar
  18. Kohler A, Verburgt L, Nicolson SW (2006) Short-term energy regulation of whitebellied sunbirds (Nectarinia talatala): effects of food concentration on feeding frequency and duration. J Exp Biol 209:2880–2887. CrossRefPubMedGoogle Scholar
  19. Kroodsma DE (1989) Suggested experimental designs for song playbacks. Anim Behav 37:600–609. CrossRefGoogle Scholar
  20. Lattanzio MS (2014) Temporal and ontogenetic variation in the escape response of Ameiva festiva (squamata: Teiidae). Phyllomedusa 13:17–27. CrossRefGoogle Scholar
  21. Livezey KB, Blumstein DT (2016) “Shortest-distance” method is more accurate than conventional method in estimating flight initiation distances for close, perched birds. J Ornithol 157:923–925. CrossRefGoogle Scholar
  22. Long JS, Ervin LH (2000) Using heteroscedasticity consistent standard errors in the linear regression model. Am Stat 54:217–224. CrossRefGoogle Scholar
  23. MacKinnon JG, White H (1985) Some heteroskedasticity-consistent covariance matrix estimators with improved finite sample properties. J Econ 29:305–325CrossRefGoogle Scholar
  24. McFadden D (1974) Conditional logit analysis of qualitative choice behavior. Academic Press, New YorkGoogle Scholar
  25. McFarland DC (1986) Determinants of feeding territory size in the New Holland honeyeater Phylidonyris novaehollandiae. Emu 86:180–185. CrossRefGoogle Scholar
  26. Møller AP (2010) Up, up, and away: relative importance of horizontal and vertical escape from predators for survival and senescence. J Evol Biol 23:1689–1698. CrossRefPubMedGoogle Scholar
  27. Newman AEM, Hess H, Woodworth BK, Norris DR (2017) Time as tyrant: the minute, hour and day make a difference for corticosterone concentrations in wild nestlings. Gen Comp Endocrinol 250:80–84. CrossRefPubMedGoogle Scholar
  28. Nicolson SW, Fleming PA (2003) Nectar as food for birds: the physiological consequences of drinking dilute sugar solutions. Plant Syst Evol 238:139–153. CrossRefGoogle Scholar
  29. Nowicki S (1983) Flock-specific recognition of chickadee calls. Behav Ecol Sociobiol 12:317–320. CrossRefGoogle Scholar
  30. Paton DC (1982) The diet of the New Holland honey eater, Phylidonyris novaehollandiae. Aust J Ecol 7:279–298. CrossRefGoogle Scholar
  31. Pyke GH (1981) Honeyeater foraging: a test of optimal foraging theory. Anim Behav 29:878–888. CrossRefGoogle Scholar
  32. R Core Team (2019) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria Google Scholar
  33. Rodriguez-Prieto I, Fernández-Juricic E, Martín J (2008) To run or to fly: low cost versus low risk escape strategies in blackbirds. Behaviour 145:1125–1138. CrossRefGoogle Scholar
  34. Rosenthal R (1979) The file drawer problem and tolerance for null results. Psychol Bull 86:638–641. CrossRefGoogle Scholar
  35. Samia DSM, Blumstein DT (2014) Phi index: a new metric to test the flush early and avoid the rush hypothesis. PLoS One 9:e113134. CrossRefPubMedPubMedCentralGoogle Scholar
  36. Shy E, Morton ES (1986) The role of distance, familiarity, and time of day in Carolina wrens responses to conspecific songs. Behav Ecol Sociobiol 19:393–400CrossRefGoogle Scholar
  37. Small TW, Bebus SE, Bridge ES, Elderbrock EK, Ferguson SM, Jones BC, Schoech SJ (2017) Stress-responsiveness influences baseline glucocorticoid levels: revisiting the under 3 min sampling rule. Gen Comp Endocrinol 247:152–165. CrossRefPubMedGoogle Scholar
  38. Stankowich T, Blumstein DT (2005) Fear in animals: a meta-analysis and review of risk assessment. Proc R Soc Lond B 272:2627–2634. CrossRefGoogle Scholar
  39. Weston MA, McLeod EM, Blumstein DT, Guay P-J (2012) A review of fl ight-initiation distances and their application to managing disturbance to Australian birds. Emu 112:269–286CrossRefGoogle Scholar
  40. Ydenberg RC, Dill LM (1986) The economics of fleeing from predators. Adv Study Behav 16:229–249. CrossRefGoogle Scholar
  41. Zeileis A, Hothorn T (2002) Diagnostic checking in regression relationships. R News 2:7–10Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Molecular and Life SciencesCurtin UniversityPerthAustralia
  2. 2.Department of BiologyKalamazoo CollegeKalamazooUSA

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