Noise and determinism in synchronized sheep dynamics
B. T. Grenfell (),
K. Wilson,
B. F. Finkenstädt,
T. N. Coulson,
S. Murray,
S. D. Albon,
J. M. Pemberton,
T. H. Clutton-Brock and
M. J. Crawley
Additional contact information
B. T. Grenfell: University of Cambridge
K. Wilson: University of Stirling
B. F. Finkenstädt: University of Cambridge
T. N. Coulson: Institute of Zoology, Zoological Society of London
S. Murray: Scottish Natural Heritage
S. D. Albon: Institute of Terrestrial Ecology, Hill of Brathens
J. M. Pemberton: Institute of Cell, Animal and Population Biology, University of Edinburgh
T. H. Clutton-Brock: University of Cambridge
M. J. Crawley: Imperial College
Nature, 1998, vol. 394, issue 6694, 674-677
Abstract:
Abstract A major debate in ecology concerns the relative importance of intrinsic factors and extrinsic environmental variations in determining population size fluctuations1,2,3,4,5,6. Spatial correlation of fluctuations in different populations caused by synchronous environmental shocks2,7,8 is a powerful tool for quantifying the impact of environmental variations on population dynamics8,9. However, interpretation of synchrony is often complicated by migration between populations8,10. Here we address this issue by using time series from sheep populations on two islands in the St Kilda archipelago11,12,13. Fluctuations in the sizes of the two populations are remarkably synchronized over a 40-year period. A nonlinear time-series model shows that a high and frequent degree of environmental correlation is required to achieve this level of synchrony. The model indicates that if there were less environmental correlation, population dynamics would be much less synchronous than is observed. This is because of a threshold effect that is dependent on population size; the threshold magnifies random differences between populations. A refined model showsthat part of the required environmental synchronicity can be accounted for by large-scale weather variations. These results underline the importance of understanding the interaction between intrinsic and extrinsic influences on population dynamics14.
Date: 1998
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DOI: 10.1038/29291
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