Population Ecology

, Volume 56, Issue 3, pp 551–553 | Cite as

Covariation between mean vole density and variability drives the numerical response of storks to vole prey

  • Frédéric Barraquand
  • Jan Hušek
Notes and Comments


Hušek et al. (Popul Ecol 55:363–375, 2013) showed that the numerical response of storks to vole prey was stronger in regions where variability in vole density was higher. This finding is, at first sight, in contradiction with the predictions of life-history theory in stochastic environments. Since the stork productivity-vole density relationship is concave, theory predicts a negative association between the temporal variability in vole density and stork productivity. Here, we illustrate this negative effect of vole variability on stork productivity with a simple mathematical model relating expected stork productivity to vole dynamics. When comparing model simulations to the observed mean density and variability of thirteen Czech and Polish vole populations, we find that the observed positive effect of vole variability on stork numerical response is most likely due to an unusual positive correlation between mean and variability of vole density.


Coefficient of variation (CV) Jensen’s inequality Life history Population cycles Taylor’s law 



We thank Emil Tkadlec for providing us with vole data and comments on the manuscript. John-André Henden, David N. Koons, an anonymous reviewer and the editor provided useful feedback. JH was supported by the BEcoDyn project at Hedmark University College. FB’s postdoc was financed by the ECOCYCLES BiodivERsA project.


  1. Barraquand F, Yoccoz NG (2013) When can environmental variability benefit population growth? Counterintuitive effects of nonlinearities in vital rates. Theor Popul Biol 89:1–11PubMedCrossRefGoogle Scholar
  2. Barraquand F, Høye TT, Henden JA, Yoccoz NG, Gilg O, Schmidt NM, Sittler B, Ims RA (2014) Demographic responses of a site-faithful and territorial predator to its fluctuating prey: long-tailed skuas and arctic lemmings. J Anim Ecol 83:375–387CrossRefGoogle Scholar
  3. Brommer JE (2000) The evolution of fitness in life history theory. Biol Rev 75:377–404PubMedCrossRefGoogle Scholar
  4. García-Carreras B, Reuman DC (2013) Are changes in the mean or variability of climate signals more important for long-term stochastic growth rate? PLoS One 8:e63974PubMedCentralPubMedCrossRefGoogle Scholar
  5. Henden JA, Bårdsen BJ, Yoccoz NG, Ims RA (2008) Impacts of differential prey dynamics on the potential recovery of endangered arctic fox populations. J Appl Ecol 45:1086–1093Google Scholar
  6. Hušek J, Adamík P, Albrecht T, Cepák J, Kania W, Mikolášková E, Tkadlec E, Stenseth NC (2013) Cyclicity and variability in prey dynamics strengthens predator numerical response: the effects of vole fluctuations on white stork productivity. Popul Ecol 55:363–375CrossRefGoogle Scholar
  7. Kilpatrick AM, Ives AR (2003) Species interactions can explain Taylor’s power law for ecological time series. Nature 422:65–68PubMedCrossRefGoogle Scholar
  8. Koons DN, Pavard S, Baudisch A, Metcalf JE (2009) Is life-history buffering or lability adaptive in stochastic environments? Oikos 118:972–980CrossRefGoogle Scholar
  9. Krebs CJ (2013) Population fluctuations in rodents. University of Chicago Press, ChicagoCrossRefGoogle Scholar
  10. Linnerud M, Sæther BE, Grøtan V, Engen S, Noble DG, Freckleton RP (2013) Interspecific differences in stochastic population dynamics explains variation in Taylor’s temporal power law. Oikos 122:1207–1216CrossRefGoogle Scholar
  11. McArdle BH, Gaston KJ (1995) The temporal variability of densities: back to basics. Oikos 74:165–171CrossRefGoogle Scholar
  12. Pásztor L, Kisdi É, Meszena G (2000) Jensen’s inequality and optimal life history strategies in stochastic environments. Trends Ecol Evol 15:117–118PubMedCrossRefGoogle Scholar
  13. Schaub M, Pradel R, Lebreton JD (2004) Is the reintroduced white stork (Ciconia ciconia) population in Switzerland self-sustainable? Biol Conserv 119:105–114CrossRefGoogle Scholar
  14. Schaub M, Kania W, Köppen U (2005) Variation of primary production during winter induces synchrony in survival rates in migratory white storks Ciconia ciconia. J Anim Ecol 74:656–666CrossRefGoogle Scholar
  15. Tkadlec E, Zbořil J, Losík J, Gregor P, Lisická L (2006) Winter climate and plant productivity predict abundances of small herbivores in central Europe. Clim Res 32:99–108CrossRefGoogle Scholar

Copyright information

© The Society of Population Ecology and Springer Japan 2014

Authors and Affiliations

  1. 1.The Northern Populations and Ecosystems Group, Department of Arctic and Marine BiologyUniversity of TromsøTromsøNorway
  2. 2.Faculty of Applied Ecology and Agricultural SciencesHedmark University CollegeKoppangNorway

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