Estimating population size and hidden demographic parameters with state-space modelling

Tavecchia, Giacomo and Besbeas, Panagiotis and Coulson, Tim and Morgan, Byron J. T. and Clutton-Brock, Tim H. (2009) Estimating population size and hidden demographic parameters with state-space modelling. American Naturalist, 173 (6). pp. 722-733. ISSN 0003-0147 . (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)

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Recent research has shown how process variability and measurement error in ecological time series can be separated using state-space modeling techniques to combine individual-based data with population counts. We extend the current maximum likelihood approaches to allow the incorporation of sex-and age-dependent counts and provide an application to data from a population of Soay sheep living on the St. Kilda archipelago. We then empirically evaluate the performance and potential of the method by sequentially omitting portions of the data available. We show that the use of multivariate time series extends the power of the state-space modeling approach. The variance of measurement error was found to be smaller for males and the sex ratio of lambs to be skewed toward females and constant over time. Our results indicated that demographic parameters estimated using state-space modeling without relevant individual-based data were in close agreement with those obtained from mark-recapture-recovery analyses alone. Similarly, estimates of population size obtained when the corresponding count observations were unavailable were close to those from the entire data set. We conclude that the approach illustrated here has great potential for estimating hidden demographic parameters, planning studies on population monitoring, and estimating both historical and future population size.

Item Type: Article
Uncontrolled keywords: fecundity; hidden parameters; population dynamics; Soay sheep; state-space modeling; survival
Subjects: Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics
Q Science > QL Zoology
Divisions: Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science
Depositing User: Byron Morgan
Date Deposited: 25 Sep 2009 08:15
Last Modified: 09 May 2014 10:28
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