Theoretical and empirical research has shown that increased variability in demographic rates often results in a decline in the population growth rate. In order to reduce the adverse effects of increased variability, life-history theory predicts that demographic rates that contribute disproportionately to population growth should be buffered against environmental variation. To date, evidence of demographic buffering is still equivocal and limited to analyses on a reduced number of age-classes (e.g. juveniles and adults), and on single sex models. Here we used Bayesian inference models for age-specific survival and fecundity on a long-term dataset of wild mountain gorillas. We used these estimates to parameterize two-sex, age-specific stochastic population projection models that accounted for the yearly covariation between demographic rates. We estimated the sensitivity of the long-run stochastic population growth rate to reductions in survival and fecundity on ages belonging to nine sex-age-classes for survival and three age-classes for female fecundity. We found a statistically significant negative linear relationship between the sensitivities and variances of demographic rates, with strong demographic buffering on young adult female survival and low buffering on older female and silverback survival and female fecundity. We found moderate buffering on all immature stages and on prime-age females. Previous research on long-lived slow species has found high buffering of prime-age female survival and low buffering on immature survival and fecundity. Our results suggest that the moderate buffering of the immature stages can be partially due to the mountain gorilla social system and the relative stability of their environment. Our results provide clear support for the demographic buffering hypothesis and its predicted effects on species at the slow end of the slow-fast life history continuum, but with the surprising outcome of moderate social buffering on the survival of immature stages. We also demonstrate how increasing the number of sex-age-classes can greatly improve the detection of demographic buffering in wild populations.
- demographic buffering
- population dynamics
- sex–age-specific demographic rates