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| Content Provider | Springer Nature Link |
|---|---|
| Author | Reynolds, Toby J. King, Ruth Harwood, John Frederiksen, Morten Harris, Michael P. Wanless, Sarah |
| Copyright Year | 2009 |
| Abstract | Integrated data analyses are becoming increasingly common in studies of wild animal populations where two or more separate sources of data contain information about common parameters. These types of analyses provide robust parameter estimates which fully reflect all available information, as well as estimates of parameters that would be unidentifiable in a separate analysis. In this article we present an integrated Bayesian analysis of four long-term datasets (counts, two mark-recapture-recovery time series, and productivity) relating to a colony of common guillemots (Uria aalge) on the Isle of May, southeast Scotland. A complication when considering the dynamics of populations of this kind is the unobservable emigration of immature animals. In the analysis of mark-recapture-recovery data, the rate of emigration is frequently confounded with that of mark loss and it is only possible to estimate the product of these parameters. By combining all available data for the Isle of May guillemots in an integrated population model, we are able to estimate these parameters separately and thus obtain improved estimates of prerecruitment emigration. |
| Starting Page | 411 |
| Ending Page | 431 |
| Page Count | 21 |
| File Format | |
| ISSN | 10857117 |
| Journal | Journal of Agricultural, Biological, and Environmental Statistics |
| Volume Number | 14 |
| Issue Number | 4 |
| e-ISSN | 15372693 |
| Language | English |
| Publisher | Springer-Verlag |
| Publisher Date | 2009-01-01 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Bayesian inference Combined data Common guillemot (Uria aalge) Markov chain Monte Carlo (MCMC) Population dynamics State-space model Statistics for Life Sciences, Medicine, Health Sciences Agriculture Environmental Monitoring/Analysis Biostatistics |
| Content Type | Text |
| Resource Type | Article |
| Subject | Applied Mathematics Statistics and Probability Environmental Science Agricultural and Biological Sciences Statistics, Probability and Uncertainty |
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