A state-space modelling approach to population size estimation
Mazzetta, Chiara, Morgan, Byron J. T., 1946- and Coulson, Tim (2010) A state-space modelling approach to population size estimation. Working Paper. University of Warwick. Centre for Research in Statistical Methodology, Coventry.
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We consider populations of wild animals that are closely monitored over time, by being recaptured on multiple occasions, until finally recovered dead or lost to follow up. We propose a state-space formulation that enables us to estimate, simultaneously: time-varying size, demographic composition and geographical dispersal of an open population. Simulations show that our method is robust to low proportions of monitored individuals. Parameters are estimated with MCMC methods within a fully Bayesian approach and our model is applied to a real population for which we are able to provide new results.
|Item Type:||Working or Discussion Paper (Working Paper)|
|Subjects:||Q Science > QA Mathematics
Q Science > QL Zoology
|Divisions:||Faculty of Science > Statistics|
|Library of Congress Subject Headings (LCSH):||Animal populations -- Statistical methods, Animal populations -- Mathematical models, State-space methods|
|Series Name:||Working papers|
|Publisher:||University of Warwick. Centre for Research in Statistical Methodology|
|Place of Publication:||Coventry|
|Number of Pages:||27|
|Status:||Not Peer Reviewed|
|Access rights to Published version:||Open Access|
|Funder:||Engineering and Physical Sciences Research Council (EPSRC), University of Warwick. Centre for Research in Statistical Methodology|
|References:||Barry, S. C., Brooks, S. P., Catchpole, E. A. & Morgan, B. J. T. (2003). The analysis of ring-recovery data using random effects. Biometrics 59, 54–65. Basu, S. & Ebrahimi, N. (2001). Bayesian capture-recapture methods for error detection and estimation of population size: Heterogeneity and dependence. Biometrika 87, 269– 279. Besbeas, P., Freeman, S. N. & Morgan, B. J. T. (2002). Integrating mark-recapture- recovery and census data to estimate animal abundance and demographic parameters. Biometrics 58, 540–547. Borchers, D. & Efford, M. (2008). Spatially explicit maximum likelihood methods for capture recapture studies. Biometrics 64, 377–385. Brooks, S. P. & Gelman, A. (1998). General methods for monitoring convergence of iterative simulations. Journal of Computational and Graphical Statistics 7, 434–455. Brooks, S. P., King, R. & Morgan, B. J. T. (2004). A Bayesian approach to combining animal abundance and demographic data. Animal Biodiversity and Conservation 27, 515–529. Casteldine, B. J. (1981). A Bayesian analysis of multiple-recapture sampling for a closed population. Biometrika 67, 197–210. Catchpole, E. A., Freeman, S. N., Morgan, B. J. T. & Harris, M. P. (1998). Integrated recovery/recapture data analysis. Biometrics 54, 33–46. Catchpole, E. A., Freeman, S. N., Morgan, B. J. T. & Nash, W. J. (2001). Abalone I: Analyzing mark-recapture-recovery data incorporating growth and delayed recovery. Biometrics 57, 469–477. Catchpole, E. A., Morgan, B. J. T., Coulson, T., Freeman, S. N. & Albon, S. D. (2000). Factors influencing Soay sheep survival. Journal of the Royal Statistical Society Series C (Applied Statistics) 49, 453–472. Chao, A., Chu, W. & Hsu, C. H. (2000). Capture-recapture when time and behavioral response affect capture probabilities. Biometrics 56, 427. Clutton-Brock, T. H. & Pemberton, J. M. (2004). Soay Sheep: Dynamics and Selection in an Island Population. Cambridge: Cambridge University Press. Coulson, T., A, C. E., Albon, S. D., Morgan, B. J. T., Pemberton, J. M., Clutton-Brock, T. H., J, C. M. & Grenfell, B. T. (2001). Age, sex, density, winter weather, and population crashes in soay sheep. Science 292, 1528–1531. Dorazio, R. M., Mukherjee, B., Zhang, L., Ghosh, M., Jelks, H. L. & Jordan, F. (2008). Modeling unobserved sources of heterogeneity in animal abundance using a Dirichlet process prior. Biometrics 64, 635–644. Dorazio, R. M. & Royle, J. (2003). Mixture models for estimating the size of a closed population when capture rates vary among individuals. Biometrics 59, 351–364. Gelman, A., Roberts, G. O. & Gilks, W. R. (1996). Efficient Metropolis jumping rules. In BAYESIAN STATISTICS 5, J. M. Bernardo, J. O. Berger, A. P. Dawid & A. F. M. Smith, eds. Oxford: OUP, pp. 599–607. Gelman, A. & Rubin, D. (1992). Inference from iterative simulation using multiple se- quences. Statistical Science 7, 457–511. George, E. I. & Robert, C. P. (1992). Capture-recapture estimation via Gibbs sampling. Biometrika 79, 677–683. Jamieson, L. E. & Brooks, S. P. (2004). Density dependence in North American ducks. Animal Biodiversity and Conservation 27, 113–128. King, R. & Brooks, S. P. (2008). On the Bayesian estimation of a closed population size in the presence of heterogeneity and model uncertainty. Biometrics 64, 816–824. King, R., Brooks, S. P., Morgan, B. J. T. & Coulson, T. (2006). Factors influencing Soay sheep survival: A Bayesian analysis. Biometrics 62, 211–220. Madigan, D. & York, J. C. (1997). Bayesian methods for estimation of the size of a closed population. Biometrika 84, 19–31. Mazzetta, C., Brooks, S. P. & Freeman, S. N. (2007). On smoothing trends in popu- lation index modeling. Biometrics 63, 1007–1014. Morgan, B. J. T. & Ridout, M. S. (2008). A new mixture model for capture heterogeneity. Journal of the Royal Statistical Society Series C (Applied Statistics) 57, 433–446. Newman, K. B., Fern´andez, C., Thomas, L. & Buckland, S. T. (2009). Monte Carlo inference for state space models of wild animal populations. Biometrics 65, 572–583. Otis, D., Burnham, K., White, G. & Anderson, D. (1978). Statistical inference from capture data on closed animal populations. Wildlife Monographs 62, 1–135. Pledger, S. (2000). Unified maximum likelihood estimates for closed capture-recapture models using mixtures. Biometrics 56, 434–442. Tardella, L. (2002). A new Bayesian method for nonparametric capture-recapture models in presence of heterogeneity. Biometrika 89, 807–817. Thomas, L., Buckland, S. T., Newman, K. B. & Harwood, J. (2005). A unified frame- work for modelling wildlife population dynamics. Australian and New Zealand Journal of Statistics 47, 19–34. West, M. & Harrison, J. (1997). Bayesian Forecasting and Dynamic Models. New York: Springer.|
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