Combining capture-recapture data and known ages allows estimation of age-dependent survival rates.

Tomas Bird,Jarod Lyon,Zeb Tonkin,Michael Mccarthy,Charles Todd,Simon Wotherspoon

doi:10.1002/ece3.4633

Abstract

In many animal populations, demographic parameters such as survival and recruitment vary markedly with age, as do parameters related to sampling, such as capture probability. Failing to account for such variation can result in biased estimates of population‐level rates. However, estimating age‐dependent survival rates can be challenging because ages of individuals are rarely known unless tagging is done at birth. For many species, it is possible to infer age based on size. In capture–recapture studies of such species, it is possible to use a growth model to infer the age at first capture of individuals. We show how to build estimates of age‐dependent survival into a capture–mark–recapture model based on data obtained in a capture–recapture study. We first show how estimates of age based on length increments closely match those based on definitive aging methods. In simulated analyses, we show that both individual ages and age‐dependent survival rates estimated from simulated data closely match true values. With our approach, we are able to estimate the age‐specific apparent survival rates of Murray and trout cod in the Murray River, Australia. Our model structure provides a flexible framework within which to investigate various aspects of how survival varies with age and will have extensions within a wide range of ecological studies of animals where age can be estimated based on size.

Highlights

Characterizing individual variability in population dynamic rates is an important consideration in ecological studies
We show how assuming that individual growth follows a well‐ defined trajectory, such as the von Bertalanffy (VBF) growth function (Von Bertalanffy, 1957), allows us to estimate age at first capture based on estimated growth parameters, meaning that all subsequent ages are known
For both trout cod (Figure 2) and Murray cod (Figure 3), the model based on CMR data alone had 95% Bayesian credible intervals that in some cases did not overlap with known ages

Summary

| INTRODUCTION

Characterizing individual variability in population dynamic rates is an important consideration in ecological studies. We show how assuming that individual growth follows a well‐ defined trajectory, such as the von Bertalanffy (VBF) growth function (Von Bertalanffy, 1957), allows us to estimate age at first capture based on estimated growth parameters, meaning that all subsequent ages are known. By incorporating this model for age at first capture into a multistate Cormack–Jolly–Seber (CJS) model, it is possible to estimate survival at age for the remainder of the study. We show how it is possible to recover age‐depen‐ dent survival and capture rates using both the Murray River and simulated datasets

| METHODS

| DISCUSSION