Data from: A stochastic model for predicting age and mass at maturity of insects

Variation in age and mass at maturity is commonly observed in populations,
even among individuals with the same genetic and environmental
backgrounds. Accounting for such individual variation with a stochastic
model is important for estimating optimal evolutionary strategies and for
understanding potential trade-offs among life history traits. However,
most studies employ stochastic models that are either phenomenological or
account for variation in only one life history trait. We propose a model
based on the developmental biology of the moth Manduca sexta that accounts
for stochasticity in two key life history traits, age and mass at
maturity. The model is mechanistic, describing feeding behavior and common
insect developmental processes including the degradation of juvenile
hormone prior to molting. We derive a joint probability density function
for the model and explore how the distribution of age and mass at maturity
is affected by different parameter values. We find that the joint
distribution is generally non-normal and highly sensitive to parameter
values. In addition, our model predicts previously observed effects of
temperature change and nutritional quality on the expected values of
insect age and mass. Our results highlight the importance of integrating
multiple sources of stochasticity into life history models.