Most population models for plants are structured exclusively by size or stage. However, the assumption that age can be safely ignored has not been rigorously tested. We used an unprecedented data set on age-specific demography of 21 populations of perennial grasses representing 17 species from western North America to evaluate the consequences of incorporating age into size-structured models and to determine when age-structure can alter model behavior. Specifically, we addressed the following three questions: 1) Based on an information-theoretic approach, how frequently do the best statistical models for survival and growth include age? 2) How large are the differences in the projections of population models that include age-structure compared to projections of models based on size-structure alone? 3) What diagnostic metrics predict the population-level consequences of age-structure?
Results/Conclusions
The best statistical models included both size and age for 16 of the 21 populations for the growth function, and 20 of 21 populations for the survival function. Density-dependent integral projection models showed that the inclusion of age had strong effects on equilibrium cover for some species but not others. The population consequences of incorporating age were best predicted by the shape of a species' survival curve: Equilibrium cover was most sensitive to inclusion of age-structure for species with very hollow (Type III) survivorship curves. Our results will help population modelers determine when age-structure can be safely ignored and when it must be modeled explicitly.