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

Jimenez-Munoz, Marina, Cole, Diana J., Freeman, Stephen N., Robinson, Robert A., Baillie, Stephen R., 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:10.1002/ece3.4820) (KAR id:69108)

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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
DOI/Identification number: 10.1002/ece3.4820
Uncontrolled keywords: conditional model, identifiability, mark-recovery, parameter redundancy, tag-recovery, Thalasseus sandvicensis, Turdus merula
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
Depositing User: M. Jimenez-Munoz
Date Deposited: 14 Sep 2018 15:46 UTC
Last Modified: 09 Jan 2024 13:08 UTC
Resource URI: (The current URI for this page, for reference purposes)

University of Kent Author Information

Jimenez-Munoz, Marina.

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Cole, Diana J..

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Matechou, Eleni.

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