Can Life History Predict the Effect of Demographic Stochasticity on Extinction Risk?

TL;DR

This study models how different life histories influence the impact of demographic stochasticity on extinction risk, revealing key traits that affect population vulnerability.

Contribution

It provides a comprehensive analysis linking life history traits to demographic stochasticity effects, enhancing understanding of extinction risks in small populations.

Findings

Extinction risk increases with fecundity and decreases with higher age of maturation.

Adult survival affects extinction risk differently depending on age of maturation.

Juvenile survival contributes most to demographic variance in most life histories.

Abstract

Demographic stochasticity is important in determining extinction risks of small populations, but it is largely unknown how its effect depends on the life histories of species. We modeled effects of demographic stochasticity on extinction risk in a broad range of generalized life histories, using matrix models and branching processes. Extinction risks of life histories varied greatly in their sensitivity to demographic stochasticity. Comparing life histories, extinction risk generally increased with increasing fecundity and decreased with higher ages of maturation. Effects of adult survival depended on age of maturation. At lower ages of maturation, extinction risk peaked at intermediate levels of adult survival, but it increased along with adult survival at higher ages of maturation. These differences were largely explained by differences in sensitivities of population growth to perturbations of life-history traits. Juvenile survival rate contributed most to total demographic variance in the majority of life histories. Our general results confirmed earlier findings, suggesting that empirical patterns can be explained by a relatively simple model. Thus, basic life history information can be used to assign life-history-specific sensitivity to demographic stochasticity. This is of great value when assessing the vulnerability of small populations.