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The detrimental effects of inbreeding are well known, and they have been shown to be associated with lower levels of reproductive success, higher levels of parasitism and differences in disease susceptibility. To better understand large fitness differences between morphs in the colour polymorphic common buzzard, Buteo buteo, we investigated differences in the levels of internal relatedness between morphs. As the common buzzard mating system is non-random and the light and dark morph individuals are less abundant than the intermediates, it could be the case the extreme colour morph individuals are more inbred. However, no differences were found in levels of inbreeding. In birds, the physiological and behavioural consequences of colour polymorphisms are not widely known. Here we used an experiment to investigate the effect of this melanin-based polymorphism on nest defence behaviour in the common buzzard. Among males, light morphs were found to be significantly more aggressive to a perceived threat of nest predation than either intermediate or darkly coloured birds, while there was a non-significant tendency for the reverse among females. The level of aggression observed for each member of a pair was independent of the level of aggression shown by the other member. These results illustrate that polymorphisms can be associated with alternative reproductive tactics in birds, and suggest a possible link between the biochemistry of melanin production and individual behaviour. For most species living in seasonal environments, timing is an important determinant of the success of a breeding attempt. Individuals also face a trade off between current and future reproduction. Here we investigated whether colour morphs differed in their timing of breeding. Light-light and dark-dark pairs were found to breed earlier than the population mean, with light-dark pairs fledging chicks slightly later. Differences in reproductive strategies between morphs may account for the observed differences.

This thesis presents a structural model of one aspect of science, the theory-driven discovery of empirical laws, in terms of the knowledge structures and reasoning processes that it involves; and describes a machine learning system designed to embody the major features of the model, called OZ, which is designed to investigate the transport properties of an unknown membrane separating two solutions. Inductive data-driven discovery is an important process in science, but takes place within very tightly constrained limits defined by theoretical reasoning. An explicit specification of the possible search space for a law is a law framework; this takes the form of a law with some undetermined parameters. Inductive law discovery is the search for the values of these free parameters. According to the model informal qualitative models (IQMs) describing the essential structural features of a physical system are used to guide the selection of appropriate variables for scientific law discovery, and the selection of an appropriate mathematical function for a law. Our analysis differs from previous work in machine discovery in stressing the importance of models of internal structure in scientific discovery. OZ comprises a domain independent control structure and a set of domain independent procedures, plus a set of domain dependent heuristics for the membrane properties domain. It constructs a set of candidate IQMs for the unknown membrane, and designs goal-directed experiments to determine which IQM is the right one, generating and testing qualitative predictions about the patterns to be expected in numerical data. When it has identified a single model as correct, it constructs law frameworks for possible laws describing the transport properties of the membrane, then designs different experiments to gather data to supply to an inductive law discovery function, which looks for a law of the type specified by each law framework.