eCite Digital Repository

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

Citation

Bird, T and Lyon, J and Wotherspoon, S and Todd, C and Tonkin, Z and McCarthy, M, Combining capture-recapture data and known ages allows estimation of age-dependent survival rates, Ecology and Evolution, 9, (1) pp. 90-99. ISSN 2045-7758 (2019) [Refereed Article]


Preview
PDF
1Mb
  

Copyright Statement

2018 The Authors. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) http://creativecommons.org/licenses/by/4.0/

DOI: 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.

Item Details

Item Type:Refereed Article
Keywords:age, Bayesian, individual growth, otoliths, state-space, survival
Research Division:Biological Sciences
Research Group:Ecology
Research Field:Population Ecology
Objective Division:Environment
Objective Group:Ecosystem Assessment and Management
Objective Field:Ecosystem Assessment and Management of Fresh, Ground and Surface Water Environments
UTAS Author:Wotherspoon, S (Dr Simon Wotherspoon)
ID Code:133810
Year Published:2019
Deposited By:Ecology and Biodiversity
Deposited On:2019-07-11
Last Modified:2019-09-25
Downloads:1 View Download Statistics

Repository Staff Only: item control page