To understand the processes that regulate the abundance and persistence of wild populations is a fundamental goal of ecology and a prerequisite for the management of living resources. Variable abundance data, however, make the demonstration of regulation processes challenging1,2,3. A previously overlooked aspect in understanding how populations are regulated4,5,6 is the possibility that the pattern of variability—its strength as a function of population size—may be more than ‘noise’, thus revealing much about the characteristics of population regulation. Here we show that patterns in survival variability do provide evidence of regulation through density. Using a large, global compilation of marine, anadromous and freshwater fisheries data, we examine the relationship between the variability of survival and population abundance. The interannual variability in progeny survival increases at low adult abundance in an inversely density-dependent fashion. This pattern is consistent with models in which density dependence enters after the larval stage. The findings are compatible with very simple forms of density dependence: even a linear increase of juvenile mortality with adult density adequately explains the results. The model predictions explain why populations with strong regulation may experience large increases in variability at low densities7. Furthermore, the inverse relationship between survival variability and the strength of density dependence has important consequences for fisheries management and recovery, and population persistence or extinction8,9,10.
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We thank D. Tittensor for comments on the variance derivations and A. Edwards, B. Worm, D. Ricard and C. Barber for comments on the manuscript. This work was funded partly by the Irish government and partly by the European Union, under the National Development Plan 2000–2006, through “Supporting Measures in the Fisheries Sector” (to C.M.).
Author Contributions The original idea for this study was conceived by R.A.M. R.A.M., C.M. and W.B. developed the theoretical models for the variance in survival. C.M. conducted the empirical analyses. All authors contributed to the writing of the manuscript.
All data used are available at the stock-recruitment database http://www.mathstat.dal.ca/~myers/welcome.html.
The file contains Supplementary Methods, Supplementary Figures 1-8 with Legends and Supplementary Table 1. The Supplementary Methods include analytical models for survival variability; delta approximations to survival variability; sensitivity analysis and meta-analytical methods. (PDF 927 kb)
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Minto, C., Myers, R. & Blanchard, W. Survival variability and population density in fish populations. Nature 452, 344–347 (2008). https://doi.org/10.1038/nature06605
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