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Title: Statistical development of ecological removal models
Author: Zhou, Ming
ISNI:       0000 0004 7655 9089
Awarding Body: University of Kent
Current Institution: University of Kent
Date of Award: 2018
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Removal sampling is commonly used to estimate abundance of populations in which captured individuals are permanently removed from a study area. The classic removal model (Moran, 1951) assumes a constant capture probability and all animals are available for detection throughout the study, which results in a simple geometric decline of counts of removed individuals over time. However, the real data collected from some species exhibit unexpected fluctuations in the number of captured animals. The work in this thesis is driven by real data on common lizards, Zootoca vivipara and great crested newts, Triturus cristatus, where existing approaches may give rise to misleading conclusions. When modelling removal data it is crucial to account for imperfect availability in the population, as individuals could sometimes temporarily become undetectable at study area, or emerge from an area outside the study. This thesis deals with three aspects of removal modelling: (i) We develop a robust design multievent removal modelling (RMER framework) which allows considerable flexibility in estimating temporary emigration as well as capture probability and the size of populations. We also consider the effect of sparse data and investigate the use of modelling different sources of data in conjunction with the removal data (Besbeas et al, 2002). (ii) The estimation of temporary emigration or population renewal for removal data relies on the use of the robust design (Zhou et al. 2018). However, there are many removal data which lack the robust design structure. Motivated by the analysis of a data set of common lizards collected under standard sampling protocol, we develop and evaluate the use of penalised maximum likelihood estimation to allow populations to be open to new individuals via birth/arrival for data sets without the robust design. (iii) We use four criteria to explore study design aspects of removal data with the robust design, including the trade-off in survey effort allocation between primary periods and secondary periods for a fixed level of total sampling effort. The models we propose can account for temporary emigration or new arrivals of individuals during removal sampling and represent a step forward with respect to current modelling approaches and will guide wildlife management.
Supervisor: McCrea, Rachel ; Matechou, Eleni ; Cole, Diana Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available