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The tag location problem

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Sumner, MD (2011) The tag location problem. PhD thesis, University of Tasmania.

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Abstract

This thesis provides an integrated approach to common problems with location estimation for animal tracking. Many existing techniques confound problems of location accuracy with simplistic track representations and under-utilization of available data. Traditional techniques such as speed ltering and time spent maps are illustrated with a software package developed by the author with examples of location estimates from southern elephant seals. This software enables the application and exploration of various techniques that have previously not been available in a single solution. These include ltering, temporal gridding, projection transformation and GIS integration. A novel Bayesian approach is introduced for the more general problems faced by dierent tagging techniques. This approach integrates all sources of data including movement models, environmental data and prior knowledge. This general framework is illustrated by application to satellite tag data and light-measuring tag data. Examples are used to detail the use of movement models with a powerful track representation model, and the application of raw light data for location estimation. Previously under-utilized sources of data are used to inform location estimates. A method for applying light level geo-location within the framework is presented. This approach provides a primary location estimate for each twilight and utilizes all of the available data from archival tags. These model runs result in very large databases of samples from Markov Chain Monte Carlo (MCMC) simulations and techniques for summarizing these for the variety of analysis outputs are illustrated. This system solves issues of location uncertainty with a full path representation and provides spatial maps of residency for multiple animals. The relation between archival tag data and ocean circulation is used to extend the application of archival tag data for location estimation for diving animals in a manner similar to commonly used SST methods. Diving proles from elephants seals are compared with 4D oceanographic datasets. Older tags are limited by problems with measurement lags for temperature|this problem is addressed with a proxy model for temperature at depth to ocean height. This thesis provides a number of important improvements to the derivation of location from various types of tag data by integrating disparate information sources in a systematic way. Location estimates are produced with inherent quantication of errors. The approach provides the variety of metrics and analysis types required with an extensible software package. These contributions help bridge the divides between various analytic techniques traditionally employed for animal tracking.

Item Type: Thesis (PhD)
Keywords: animal tracking, Bayesian, MCMC, light level geo-location, Argos
Additional Information: Copyright © the Author. Chapter 3 contains published material
Date Deposited: 18 Nov 2011 01:55
Last Modified: 11 Dec 2012 02:36
URI: http://eprints.utas.edu.au/id/eprint/12273
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