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Spatial synchronization of vole population dynamics by predatory birds

Author

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  • Rolf A. Ims

    (University of Oslo PO Box 1050 Blindern
    NINA, Polar Environment Centre)

  • Harry P. Andreassen

    (University of Oslo PO Box 1050 Blindern)

Abstract

Northern vole populations exhibit large-scale, spatially synchronous population dynamics1,2. Such cases of population synchrony provide excellent opportunities for distinguishing between local intrinsic and regional extrinsic mechanisms of population regulation3. Analyses of large-scale survey data and theoretical modelling4,5,6 have indicated several plausible synchronizing mechanisms. It is difficult, however, to determine the most important one without detailed data on local demographic processes3,7. Here we combine results from two field studies in southeastern Norway—one identifies local demographic mechanisms and landscape-level annual synchrony among 28 enclosed experimental populations and the other examines region-level multi-annual synchrony in open natural populations. Despite fences eliminating predatory mammals and vole dispersal, the growth rates of the experimental populations were synchronized and moreover, perfectly linked with vole abundance in the region. The fates of 481 radio-marked voles showed that bird predation was the synchronizing mechanism. A higher frequency of risky dispersal movements in slowly growing populations appeared to accelerate predation rate. Thus, dispersal may induce a feedback-loop between predation and population growth that enhances synchrony.

Suggested Citation

  • Rolf A. Ims & Harry P. Andreassen, 2000. "Spatial synchronization of vole population dynamics by predatory birds," Nature, Nature, vol. 408(6809), pages 194-196, November.
    • Handle: RePEc:nat:nature:v:408:y:2000:i:6809:d:10.1038_35041562
    DOI: 10.1038/35041562
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    Cited by:

    1. Gao, Meng & Li, Wenlong & Li, Zizhen & Dai, Huawei & Liu, Hongtao, 2007. "Spatial synchrony in host–parasitoid populations," Ecological Modelling, Elsevier, vol. 204(1), pages 29-39.
    2. Engen, Steinar, 2017. "Spatial synchrony and harvesting in fluctuating populations:Relaxing the small noise assumption," Theoretical Population Biology, Elsevier, vol. 116(C), pages 18-26.
    3. Donadello, Carlotta & Nguyen, Thi Nhu Thao & Razafison, Ulrich, 2021. "On the mathematical modeling of vole populations spatial dynamics via transport equations on a graph," Applied Mathematics and Computation, Elsevier, vol. 396(C).
    4. Upadhyay, Ranjit Kumar & Rai, Vikas, 2009. "Complex dynamics and synchronization in two non-identical chaotic ecological systems," Chaos, Solitons & Fractals, Elsevier, vol. 40(5), pages 2233-2241.
    5. Bagchi, Dweepabiswa & Arumugam, Ramesh & Chandrasekar, V.K. & Senthilkumar, D.V., 2022. "Metacommunity stability and persistence for predation turnoff in selective patches," Ecological Modelling, Elsevier, vol. 470(C).
    6. Marilleau, Nicolas & Lang, Christophe & Giraudoux, Patrick, 2018. "Coupling agent-based with equation-based models to study spatially explicit megapopulation dynamics," Ecological Modelling, Elsevier, vol. 384(C), pages 34-42.
    7. Saitoh, Takashi & Cohen, Joel E., 2018. "Environmental variability and density dependence in the temporal Taylor’s law," Ecological Modelling, Elsevier, vol. 387(C), pages 134-143.
    8. Hugues Santin-Janin & Bernard Hugueny & Philippe Aubry & David Fouchet & Olivier Gimenez & Dominique Pontier, 2014. "Accounting for Sampling Error When Inferring Population Synchrony from Time-Series Data: A Bayesian State-Space Modelling Approach with Applications," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-12, January.

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