Inference From Gene to Population: Propagating Uncertainty In Estimates of Population Characteristics Through Ecological Scales

A current trend in population biology is the increasing realisation of the effect of individual
variability on some of the big patterns of population dynamics. Simultaneously, the field of
population genetics continues to develop a sophisticated theoretical basis for the inference of
large-scale population dynamics from information derived from the smallest ecological unit,
that of the gene.

This thesis aims to contribute to the synthesis of these two fields by outlining a series of
novel methods that can be used in the scaling up of genetic information to individual dynamics,
and, eventually, to inference of patterns of the population. A critical feature of the methods
described here is the preservation and propagation of uncertainty in estimates at each stage of
the analysis. The thesis begins by introducing an estimation procedure for the calculation of
allele frequencies when observation error means that frequencies cannot be directly observed.
Genotyping errors can also prove troublesome in the field of parentage analysis, the basis of
many models of inference of population-level processes. Any assignment errors made at this
stage can be disastrous for any inference build upon these assignments. I describe a novel
method of conducting parentage analysis, extend these methods for a series of common marker
types and arbitrary ploidy, and show how uncertainty in parentage allocations can be propagated
robustly to further stages of analysis.

I review a set of new methods that may prove useful for the fitting of individual-based models
to real data. I describe how these methods can be applied in the context of individual-based
modelling and describe an extension of the methods to efficiently handle common data used to
parametrise individual-based models. I discuss that individual-based models may provide a key
bridging discipline between the field of traditional population ecology and population genetics.

Finally, I describe a method to use information on dispersal collected at the individual-level
to inform population-level estimate of immigration and emigration rates of spatially-explicit
models of population dynamics.