Estimating age when multiple sources of data are available and traditional aging techniques are not practical.

Estimating age from recapture data: integrating incremental growth measures with ancillary data to infer age-at-length

Mitchell J. Eaton and William A. Link

Ecological Applications 21:2487–2497.  Volume 21, Issue 7 (October 2011) 

For answering ecological questions, modeling population demographics, and managing exploited or threatened species estimation of age of individuals in wild populations is of paramount importance. Determining age through the use of growth annuli and growth models are in vogue.

The researcher say many species either do not exhibit physical characteristics useful for independent age validation or are too rare to justify sacrificing a large number of individuals to establish the relationship between size and age.

Many Length-at-age models used in fisheries overlook variation in growth rates of individuals and consider growth parameters as population parameters. More recent models of this genre have taken advantage of hierarchical structuring of parameters and Bayesian inference methods to allow for variation among individuals as functions of environmental covariates or individual-specific random effects.

In this paper the researchers describe hierarchical models in which growth curves vary as individual-specific stochastic processes. They demonstrate how these models can be fit using capture–recapture data for animals of unknown age along with data for animals of known age.

The researchers say they combined these independent data sources in a Bayesian analysis, distinguishing natural variation (among and within individuals) from measurement error. They illustrate using data for African dwarf crocodiles, comparing von Bertalanffy and logistic growth models.

The researchers describe hierarchical models in which growth curves vary as individual-specific stochastic processes, and they show how these models can be fit using capture–recapture data for animals of unknown age along with data for animals of known age. The von Bertalanffy was much better supported than the logistic growth model and predicted that dwarf crocodiles grow from 19.4 cm total length at birth to 32.9 cm in the first year and 45.3 cm by the end of their second year. Based on the minimum size of females observed with hatchlings, the researchers estimated reproductive maturity to be at nine years.

The analysis provides the means of predicting crocodile age, from a single measurement of head length.

The researchers contend that these size benchmarks represent thresholds for important demographic parameters; improved estimates of age, therefore, will increase the precision of population projection models. They say the modeling approach that they present can be applied to other species and offers significant advantages when multiple sources of data are available and traditional aging techniques are not practical.