Estimating age-dependent survival from age-aggregated ringing data - extending the use of historical records

Jimenez-Munoz, Marina and Cole, Diana J. and Freeman, Stephen N. and Robinson, Robert A. and Baillie, Stephen R. and Matechou, Eleni (2019) Estimating age-dependent survival from age-aggregated ringing data - extending the use of historical records. Ecology and Evolution, 9 (2). pp. 769-779. ISSN 2045-7758. (doi:https://doi.org/10.1002/ece3.4820) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided)

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Abstract

Bird ring-recovery data have been widely used to estimate demographic parameters such as survival probabilities since the mid-twentieth century. However, while the total number of birds ringed each year is usually known, historical information on age at ringing is often not available. A standard ring-recovery model, for which information on age at ringing is required, cannot be used when historical data are incomplete. We develop a new model to estimate agedependent survival probabilities from such historical data when age at ringing is not recorded; we call this the historical data model. This new model provides an extension to the model of Robinson (2010) by estimating the proportion of the ringed birds marked as juveniles as an additional parameter. We conduct a simulation study to examine the performance of the historical data model and compare it with other models including the standard and conditional ringrecovery models. Simulation studies show that the approach of Robinson (2010) can cause bias in parameter estimates. In contrast, the historical data model yields similar parameter estimates to the standard model. Parameter redundancy results show that the newly developed historical data model is comparable to the standard ring-recovery model, in terms of which parameters can be estimated, and has fewer identifiability issues than the conditional model. We illustrate the new proposed model using Blackbird and Sandwich Tern data. The new historical data model allows us to make full use of historical data and estimate the same parameters as the standard model with incomplete data and in doing so, detect potential changes in demographic parameters further back in time.

Item Type: Article
Uncontrolled keywords: conditional model, identifiability, mark-recovery, parameter redundancy, tag-recovery, Thalasseus sandvicensis, Turdus merula
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Faculties > Sciences > School of Mathematics Statistics and Actuarial Science
Depositing User: M. Jimenez-Munoz
Date Deposited: 14 Sep 2018 15:46 UTC
Last Modified: 14 Mar 2019 11:10 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/69108 (The current URI for this page, for reference purposes)
Matechou, Eleni: https://orcid.org/0000-0003-3626-844X
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