E

2 4 6 8 10 Clutch size

Figure 5 The strength of density dependence in annual population fluctuations 7 and in the total life history D in relation to (a), (d) generation time T; (b), (e) clutch size; and (c), (f) adult survival rate s of birds.

0.2 0.4 0.6 0.8

IOQiq t life expectancies. In contrast, interspecific differences in avian demographic stochasticity per generation are independent of life-history variation.

Conclusion

Life-history traits show in most taxa a strong pattern of covariation. In many cases, species distribute them along a 'slow-fast' continuum of life-history variation, for which generation time is a useful proxy. These analyses demonstrate clearly how many population dynamical patterns can be explained by the species' location along this continuum.

Figure 6 (a) The residual variance in a first-order process, af, describing environmental stochasticity transient fluctuations in age structure as well as long-term autocorrelations in the environment and (b) in the total residual variance over a period of one generation af T, in relation to generation time T of birds.

variance in population size as in the full model. Theoretical analyses show that variance for this white noise process for species with age at maturity larger than 1 year should be approximately equal to the environmental variance. In our bird data set, log10 a2e was independent of log10 T (Figure 6a). In contrast, there was a highly significant linear increase in log10(a"T) (Figure 6b). Furthermore, the environmental variance for this process per generation (a^T) was closely related to life-history characters, that is, a^T decreased with clutch size, but increased with adult survival rate. This suggests that environmental stochasticity per generation is greater for long-lived species than for species with short

Acknowledgment

This work was supported by the Research Council of Norway (Strategic University Program in Conservation Biology).

See also: Fecundity; Growth Models; Invasive Species; Stability.

Further Reading

Barker R, Fletcher D, and Scofield P (2002) Measuring density dependence in survival from mark-recapture data. Journal of Applied Statistics 29: 305-313.

Caswell H (2001) Matrix Population Models, 2nd edn. Sunderland, MA: Sinauer.

Dennis B, Ponciano JM, Lele SR, Taper ML, and Staples DF (2006) Estimating density dependence, process noise, and observation error. Ecological Monographs 76: 323-341.

Gaillard JM and Yoccoz NG (2003) Temporal variation in survival of mammals: A case of environmental canalization? Ecology 84:3294-3306.

Lande R, Engen S, and S^ther BE (2003) Stochastic Population Dynamics in Ecology and Conservation. Oxford: Oxford University Press.

Lande R, S^ther BE, Engen S, et al. (2002) Estimating density dependence from population time series using demographic theory and life-history data. American Naturalist 159: 321-332.

S^ther B-E and Bakke 0 (2000) Avian life history variation and contribution of demographic traits to the population growth rate. Ecology 81: 642-653.

S^ther B-E, Engen S, Moller AP, et al. (2004) Life-history variation predicts the effects of demographic stochasticity on avian population dynamics. American Naturalist 164: 793-802.

S^ther B-E, Lande R, Engen S, et al. (2005) Generation time and temporal scaling of bird population dynamics. Nature 436: 99-102.

Figure 6 (a) The residual variance in a first-order process, af, describing environmental stochasticity transient fluctuations in age structure as well as long-term autocorrelations in the environment and (b) in the total residual variance over a period of one generation af T, in relation to generation time T of birds.

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