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.
Subscribe to Journal
Get full journal access for 1 year
only $3.90 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
Murdoch, W. W. Population regulation in theory and practice. Ecology 75, 271–287 (1994)
den Boer, P. J. & Reddingius, J. Regulation and Stabilization Paradigms in Population Ecology (Chapman & Hall, London, 1996)
Shenk, T. M., White, G. C. & Burnham, K. P. Sampling-variance effects on detecting density dependence from temporal trends in natural populations. Ecol. Monogr. 68, 445–463 (1998)
Murray, B. G. Can the population regulation controversy be buried and forgotten? Oikos 84, 148–152 (1999)
Turchin, P. Population regulation: a synthetic view. Oikos 84, 153–159 (1999)
Berryman, A. A., Lima Arce, M. & Hawkins, B. A. Population regulation, emergent properties, and a requiem for density dependence. Oikos 99, 600–606 (2002)
Hsiesh, C.-h. et al. Fishing elevates the variability in the abundance of exploited species. Nature 443, 859–862 (2006)
Sæther, B.-E., Engen, S., Islam, A., McCleery, R. & Perrins, C. Environmental stochasticity and extinction risk in a population of a small songbird, the great tit. Am. Nat. 151, 441–450 (1998)
Lande, R., Engen, S. & Sæther, B.-E. Stochastic Population Dynamics in Ecology and Conservation (Oxford Univ. Press, Oxford, 2003)
Drake, J. M. Density-dependent demographic variation determines extinction rate of experimental populations. PLoS Biol. 3, 1300–1304 (2005)
Wolda, H. & Dennis, B. Density dependence tests, are they? Oecologia 95, 581–591 (1993)
Godfray, H. C. L. & Hassell, M. P. Long time series reveal density dependence. Nature 359, 673–674 (1992)
Myers, R. A. Stock and recruitment: generalizations about maximum reproductive rate, density dependence, and variability using meta-analytic approaches. ICES J. Mar. Sci. 58, 937–951 (2001)
Sale, P. F. & Tolimieri, N. Density dependence at some time and place? Oecologia 124, 166–171 (2000)
Myers, R. A. & Cadigan, N. G. Density-dependent juvenile mortality in marine demersal fish. Can. J. Fish. Aquat. Sci. 50, 1576–1590 (1993)
Deriso, R. B. Harvesting strategies and parameter estimation for an age-structured model. Can. J. Fish. Aquat. Sci. 37, 268–282 (1980)
Schnute, J. A general theory for analysis of catch and effort data. Can. J. Fish. Aquat. Sci. 42, 414–429 (1985)
Harvey, A. C. Estimating regression models with multiplicative heteroscedasticity. Econometrica 44, 461–465 (1976)
Mertz, G. & Myers, R. A. Estimating the predictability of recruitment. Fish. Bull. 93, 657–665 (1995)
Myers, R. A. & Cadigan, N. G. Is juvenile natural mortality in marine demersal fish variable? Can. J. Fish. Aquat. Sci. 50, 1591–1598 (1993)
Mertz, G. & Myers, R. A. Match/mismatch predictions of spawning duration versus recruitment variability. Fish. Oceanogr. 3, 236–245 (1994)
May, R. M. C. Stability and Complexity in Model Ecosystems Ch. 2 (Princeton Univ. Press, Princeton, 1973)
Myers, R. A., Barrowman, N. J., Hutchings, J. A. & Rosenberg, A. A. Population dynamics of exploited fish stocks at low population levels. Science 269, 1106–1108 (1995)
Walters, C. & Kitchell, J. F. Cultivation/depensation effects on juvenile survival and recruitment: implications for the theory of fishing. Can. J. Fish. Aquat. Sci. 58, 39–50 (2001)
Leigh, E. G. The average lifetime of a population in a varying environment. J. Theor. Biol. 90, 213–239 (1981)
Rosenberg, A. A. et al. The history of ocean resources: modeling cod biomass using historical records. Front. Ecol. Environ. 3, 78–84 (2005)
Hutchings, J. A. & Myers, R. A. The effect of age on the seasonality of maturation and spawning of Atlantic cod, Gadus morhua. Can. J. Fish. Aquat. Sci. 50, 2468–2474 (1993)
Peterman, R. M. Form of random variation in salmon smolt-to-adult relations and its influence on production estimates. Can. J. Fish. Aquat. Sci. 38, 1113–1119 (1981)
Myers, R. A., Bridson, J. & Barrowman, N. J. Summary of worldwide stock and recruitment data. Can. Tech. Rep. Fish. Aquat. Sci. 2024, 1–327 (1995)
Hassell, M. P., Latto, J. & May, R. M. Seeing the wood for the tree: detecting density dependence from existing life-table studies. J. Anim. Ecol. 58, 883–892 (1989)
Mertz, G. & Myers, R. A. Influence of fecundity on recruitment variability of marine fish. Can. J. Fish. Aquat. Sci. 53, 1618–1625 (1996)
Manly, B. F. Stage-structured Populations: Sampling, Analysis and Simulation (Chapman and Hall, London, 1990)
Stuart, A. & Ord, J. K. Kendall’s Advanced Theory of Statistics Vol. 1 Distribution Theory (Oxford Univ. Press, New York, 1987)
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)
About this article
Cite this article
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
Highlighting growth regulation processes in fish populations by a simplex simulation approach: application to Merluccius hubbsi stocks in the Southwestern Atlantic
ICES Journal of Marine Science (2020)
Advances in Water Resources (2020)
Dynamic spawning patterns in the California market squid ( Doryteuthis opalescens ) inferred through paralarval observation in the Southern California Bight, 2012–2019
Marine Ecology (2020)
Estuarine, Coastal and Shelf Science (2020)
Disentangling the influence of fishing, demography, and environment on population dynamics of Iberian Peninsula waters fish stocks
ICES Journal of Marine Science (2020)