Abstract:
The estimation of population size is important in studying population dynamics (Kingsland
1995, Turchin 2003), in calculating effective population sizes in studies of evolutionary
dynamics (Nunney and Elam 1994, Frankham 1995), in estimating the sex-ratio of
populations (Clutton-Brock 1986, Clutton-Brock and Iason 1986), and in monitoring the
status of populations which are at risk of extinction (Jones et al. 2013). The estimation of
population size in the wild can be challenging as animals may range over vast, inaccessible
areas and individuals may not be easily detectable. Social species may present an additional
challenge as individuals belonging to different social groups may have varying detectability
(Cubaynes et al. 2010), especially if these groups have changing compositions over short time
periods. While capture-recapture models have been widely used, and progressively refined, in
order to estimate the population sizes of animals in the wild (Seber 1982, Williams et al.
2002, Amstrup et al. 2005), these models do not explicitly consider sociality as a factor that
can affect population estimates. Therefore, in this thesis, I examine whether the current
statistical methods of population size estimation give unbiased estimates for populations
exhibiting different kinds of social structures. Using individual-based simulations, I also
explore the effect of population densities, trap densities (sampling intensity), sampling scale,
and trap spatial arrangement or distribution on the efficacy of two commonly used markrecapture
estimators, POPAN and Robust Design with heterogeneity.
