As discussed above, temporal variation in recruitment has major influences on population dynamics. So far, however, we only considered the 'numerical effects' of recruitment fluctuations. Thus, depending on the suitability of the environmental conditions when a cohort is produced, a variable number of propagules will survive throughout the different recruitment stages. That simple process can generate complex dynamics, especially in populations that are strongly age- or stage-structured. The signature of one major change in the number of recruits from a cohort can last for several years, as cohorts of differing size and quality move through the population structure. In some coral reef fish, the signal of major temporal fluctuations in recruitment can span at least 10 years. Let us take a simple example to illustrate how a marked change of recruitment in a given year may generate delayed cohort effects on age structure, and thereby on demographic processes. Consider a vertebrate population in which all individuals give birth for the first time at age 4, produce two offspring per year between 4 and 8 years of age, then cease reproducing. Assume that the first-year survival is 0.75, the annual survival between 1 and 8 years of age is 0.90, and the annual survival beyond 8 years of age is 0.75. Running a simple pre-breeding Leslie matrix model (i.e., individuals observed just before a new cohort is produced so that all individuals are included from 1 year of age onward) leads to an asymptotic natural rate of increase of 1.15, with a stable age distribution of 56.15% individuals in the pre-reproductive stage, 36.14% in the prime-age stage, and 7.71% in the senior stage. Now let recruitment markedly decrease in a given year so that the first-year survival becomes 0.25 instead of 0.75. After the perturbation in recruitment, the natural rate of increase will decrease to 0.97 and the age structure 1 year later will be shifted toward old individuals with 48.01%, 42.86%, and 8.88% of animals in the pre-reproductive, prime-age, and senior stages, respectively. Four years after the perturbation a reverse trend in age structure would have occurred, with 60.68%, 31%, and 8.32% of animals in the pre-reproductive, prime-age, and senior stages, respectively, illustrating how the adult age structure in a population reflects the recruitment of juveniles some years before. The asymptotic growth rate will not be reached for 8 years after the perturbation. Thus, we can observe cycles in the rate of recruitment generated by the lagged reciprocal effects of recruitment variation on age structure and then of variation in age structure on recruitment. Such delayed numerical effects are pervasive in long-lived species.
Another delayed effect is generated by among-cohort differences in individual quality. Although less often addressed because of the requirement of long-term longitudinal data, such 'quality effects', often in propagule size, have marked effects on population dynamics. High-quality cohorts will thus not only produce more recruits than low-quality cohorts, but they may also produce recruits of higher quality that will reproduce earlier, and will give birth to more offspring of higher quality as compared to low-quality cohorts. These quality effects could potentially lead to multigenerational signatures of variability in recruitment, and deserve much greater attention.
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