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Conditional modelling of ring-recovery data

McCrea, Rachel S., Morgan, Byron J. T., Brown, Daniel I., Robinson, Rob A. (2012) Conditional modelling of ring-recovery data. Methods in Ecology and Evolution, 3 (5). pp. 823-831. ISSN 2041-210X. (doi:10.1111/j.2041-210X.2012.00226.x) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:32846)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1111/j.2041-210X.2012.00226.x

Abstract

1. Ring-recovery data can be used to obtain estimates of survival probability which is a key demo-

data is needed when cohort numbers are unavailable or unreliable. It is often necessary to include in

result in biased estimates of annual survival.

sions to be drawn regarding the effects of climate change.

and propose and investigate a range of alternative procedures.

is a scaled-logistic model, and it is shown to provide a unifying analysis of several data sets collected

insights and avenues for ecological research. The wider performance of this model is evaluated

5. In this study, we propose a new scaled-logistic model for the analysis of ring-recovery data with-

is shown to perform well in simulation studies and for both a single real data set and several real

that currently do not incorporate such reporting probabilities. Alternative models are shown to

possess undesirable features.

Item Type: Article
DOI/Identification number: 10.1111/j.2041-210X.2012.00226.x
Uncontrolled keywords: blackbird, declining recovery probability, grey heron, logistic models, song thrush, time segmentation, wren
Subjects: Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics
Q Science > QH Natural history > QH541 Ecology
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
Depositing User: Byron Morgan
Date Deposited: 09 Jan 2013 16:26 UTC
Last Modified: 16 Feb 2021 12:43 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/32846 (The current URI for this page, for reference purposes)
McCrea, Rachel S.: https://orcid.org/0000-0002-3813-5328
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