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Incorporating individual heterogeneity into mark-recapture models

Ford, JH 2013 , 'Incorporating individual heterogeneity into mark-recapture models', PhD thesis, University of Tasmania.

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Mark-recapture analysis is a fundamental tool for understanding populations,
since it allows the estimation of demographic parameters, such as
survival, movement and reproduction, which can be used to infer population
status and predict dynamics. As individuals in wild populations do not
all behave in the same way, a challenge is presented in the collection and
analysis of these data. Within a natural population, animals may exhibit
substantial individual variation which can manifest through these demographic
parameters. Inherent individual dierences in movement and behavior
can introduce bias into mark-recapture estimates (most notoriously,
of population size), and are often of considerable interest in their own right.
There has been much focus in mark-recapture research on the development
of methods to account for individual heterogeneity, yet easily applied,
accurate methods are still lacking. The most natural, but computationally
complex, approach for modeling individual heterogeneity assumes a continuous
distribution using random eects. This method introduces the complexity
of solving for the individual random eects which has been a stumbling
block of much work in the mark-recapture eld. The focus of this thesis is
the development of methods to better estimate individual heterogeneity in
mark-recapture data. In chapter 1 I introduce the concepts arising in this thesis and briey
outline techniques for modeling individual heterogeneity. Chapter 2 explores
the population consequences of individual heterogeneity in spatial use in the
context of a marine protected area. Using population projections, I explore
the population consequences of individual heterogeneity in proportion of
time spent inside a marine protected area. The projections indicate that
individual heterogeneity in spatial use and site delity could have important
implications under certain conditions for the dynamics of populations
managed using marine protected areas. In several scenarios, high individual
heterogeneity resulted in larger population size and positive population trajectories,
compared to decline and eventual extinction with low individual
heterogeneity in site delity.
I then present three novel statistical approaches for handling individual
heterogeneity using random effects. The rst, developed in chapter 3, is an
approach using Laplace approximation with Gaussian random efects, implemented
in the language Automatic Dierentiation Model Builder (ADMB).
In chapter 4 I develop a Markov chain Monte Carlo sampling framework with
a parametric distribution for the individual heterogeneity. This is extended
in chapter 5 to incorporate the non-parametric Dirichlet process prior. The
natural subgroups often seen in mark-recapture studies, and the complexity
of real mark-recapture data means that parametric and discrete style models
can be insucient. Non-parametric models avoid these often restrictive assumptions.
The Dirichlet process prior is a flexible extension to a parametric
model as it avoids assumptions about the functional form of the distribution,
and it extends discrete style models to the infinite limit by avoiding
any prespecications about the number of groups. Each of these methods
was tested using simulated data. In each case the simulation studies demonstrated accurate estimation of true parameter values with random effects.
In the case of the Dirichlet process, the simulation studies were used to explore
the ability and limits of the Dirichlet process in identifying multiple
behavioural modes.
The methods are applied to data for up to 1100 individually identified North Atlantic humpback whales, where an unseen individual may be
present but not seen, temporarily absent, or dead. There was some evidence
of individual heterogeneity in site fedelity and multimodality in the
probability of observation.

Item Type: Thesis - PhD
Authors/Creators:Ford, JH
Keywords: hidden Marker model, individual heterogenity, mark re-capture, random effects, ADMB, MCMC, North Atlantic humpback whale.
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