Inbreeding and loss of genetic diversity are believed to reduce the ability of natural populations to cope with disease, presenting important implications for the conservation of small, bottlenecked populations. This prediction has been shown experimentally in Drosophila populations (reduced resistance in inbred lines) and in house finches (genetically-diverse individuals showed stronger immune responses and less severe infection). However, few studies have identified the effect of inbreeding on immune function in free-living populations. A recent study demonstrated reduced immunocompetence in a severely bottlenecked robin population in comparison to their out-bred source. Whilst there is little doubt that inbred populations are more likely to be susceptible to disease, it is remains unclear where, when and to what extent this occurs within populations. This project will examine interactions between immune function and inbreeding in two bottlenecked bird species, where level of inbreeding and known extent of pathogenic infection vary between individuals. In avian field studies, immune function in birds has most commonly been measured using the Phytohaemaglutinin (PHA) skin test. PHA response has been shown to be significantly reduced in a severely bottlenecked robin population and to be significantly elevated in hybridised versus pure-bred parakeets. The technique has recently been histologically validated in birds. This project will measure individual levels of immunocompetence amongst two endemic bird species whose restored populations have been intensively-monitored for the past 25 years. The endangered Mauritius parakeet (Psittacula echo) and endangered Mauritius pink pigeon (Columba mayeri) have both experienced a severe population bottleneck over the past 30 years. Long-term management has produced detailed pedigree records and complete life histories for all individuals since the bottleneck. Both bottlenecked populations are infected with introduced pathogens. The Mauritius parakeet suffered a recent outbreak of Psittacene Beak and Feather Virus (PBFV). The pink pigeon is host to two blood pathogens; Trichomonas gallinae and Leucocytozoon marchouxi, whose prevalence has been intensively monitored. PBFV was introduced by feral ringneck parakeets and T. Gallinae/L. Marchouxi by feral ground dove populations on Mauritius. Genetic and pedigree information has confirmed considerable variation in inbreeding within each endangered bird population. Sympatric populations of the introduced Indian ringneck parakeet and barred ground dove will provide out-bred 'control' populations. Each population is closely monitored each year as part of the ongoing recovery programme. Field aviaries on Mauritius will enable replicate measurement of an individuals' immunocompetence across breeding and non-breeding seasons and provide estimates of heritability of immune response. Existing studies assume low immunocompetence to reflect reduced resistance to infection. However, on Mauritius, immunocompetence can be re-measured in free-living infected birds to evaluate change in immune function as infection progresses. The project will use confirmed pedigrees to identify individual inbreeding coefficients; validate measures of immunocompetence for known inbreeding coefficients and observed level of infection in the free-living populations to identify interactions between inbreeding and immune function. Genetically confirmed pedigrees already exist for the Mauritius parakeet population, and pigeon pedigrees will be confirmed using archived samples. Immunocompetence will be measured in ~180 birds from each of the four populations using the PHA skin test and hemolysis-haemagglutination assays. PHA methods will be calibrated in captivity before use on free-living populations. General linear models will identify effects of inbreeding on immunocompetence from effects of inbreeding on immunocompetence from effects of season/life-history.

Conservation monitoring schemes are constrained by time and cost and as such study design needs to be optimised to make the most of these available resources. Removal studies are conducted to protect target species from sites planned for development and the aim of such sampling is to capture and remove the entire population. Typically the studies are designed in an ad-hoc way with some repeated surveys on a single day, and some with simply daily visits. Sampling of sites is often avoided when weather conditions are considered not favourable. Removed species are trans-located to other habitats considered suitable for the specific species. However, measures to determine whether such translocations, and related re-introduction programmes have been successful are currently lacking. Developing robust approaches for both removal and re-introduction programmes will allow resources to be allocated optimally to ensure monitoring can be carried out for a sufficient period of time, to minimise the risk to the species under study. This project will develop new statistical approaches to make the most of the information available from removal and re-introduction data. The types of data which can be collected on animal populations are wide-ranging - for example, simple population counts, presence/absence data, presence only data, batch-marked data, and capture-recapture data. The difficulty and survey intensity required to collect these data will also depend on the associated skill set of data collector as well as the resources available to the team or individual responsible for designing the scheme. As well as proposing optimal study design for removal count data, the project will also address how to optimise study design if multiple types of data are collected simultaneously on a population. Further, we will explore how populations could be monitored with multiple types of data collection to better determine how successfully the population has established itself following some form of intervention (such as trans-location of individuals or re-introducing a previously locally extinct species back into an area). When fitting models to data it is possible to consider different structures to the model, for example to account for time-variation within detectability of the species, and therefore a model selection procedure needs to be implemented to select the structure of the model that best represents the observed data. Current approaches require an understanding of the statistical procedures implemented within this model selection step, however the methodological developments proposed within this project are aimed at a user-base who may have no such knowledge. Therefore within the project we will investigate the development of an automated procedure which will both select a best model(s) out of the models considered for the data set and will also assess how well the model(s) fits the observed data. A best candidate model may in fact fit the observed data very poorly and therefore this check of model fit is crucial if the results of the model will be used to make management decisions as otherwise erroneous conclusions could be drawn. Software with a graphical-user-interface will be developed to make the statistical developments accessible to those with no programming experience. The software will be web-based which will overcome operating system compatibility issues and user-manuals and tutorials will be produced to help end-users to make the most of the software's capabilities.