Computer-based simulation models of changes occurring within crop population when subjected to agents of phenotypic change, have been developed for use on commonly available personal computer equipment. As an underlying developmental principle, the models have been designed as general-case, mechanistic, stochastic models, in contrast to the predominantly empirically-derived, system-specific, deterministic (predictive) models currently available. A modelling methodology has evolved, to develop portable simulation models, written in high-level, general purpose code, allowing for use, modification and continued development by biologists with little requirement for computer programming expertise. The initial subject of these modelling activities was the simulation of the effects of selection and other agents of genetic change in crop populations, resulting in the computer model, PSELECT. Output from PSELECT, specifically phenotypic and genotypic response to phenotypic truncation selection, conformed to expectation, as defined by results from established analogue modelling work. Validation of the model by comparison of output with the results from an experimental-scale plant breeding exercise was less conclusive, and, owing to the fact that the genetic basis of the phenotypic characters used in the selection programme was insufficiently defined, the validation exercise provided only broad qualitative agreement with the model output. By virtue of the predominantly subjective nature of plant breeding programmes, the development of PSELECT resulted in a model of theoretical interest, but with little current practical application. Modelling techniques from the development of the PSELECT model were applied to the simulation of plant disease epidemics, where the modelled system is well characterised, and simulation modelling is an area of active research. The model SATSUMA, simulating the spatial and temporal development of diseases within crop populations, was developed. The model generates output which conforms to current epidemiological theory, and is compatible with contemporary methods of temporal and spatial analysis of crop disease epidemics. Temporal disease progress in the simulations was accurately described by variations of a generalised logistic model. Analysis of the spatial pattern of simulated epidemics by frequency distribution fitting or distance class methods was found to give good qualitative agreement with observed biological systems.

Agricultural policy analysis can be visualised as a multiple objective hierarchical optimisation problem whereby sequential non-cooperative interactions between policy makers and farmers take place. The objectives and choices of policy makers will almost always diverge from the objectives and choices of farmers. This thesis shows how multi-objective genetic algorithms (MOGA) in conjunction with mathematical programming can be used for solving this type of problem. A positive mathematical programming (PMP) model is developed to capture the production choices of farmers, and its objective function parameters are estimated using the method of generalised maximum entropy. The PMP model is nested in, and controlled by, a MOGA which captures the process of multi-objective optimisation of policy decisions. The approach is illustrated using a case study taken from Scottish agricultural systems, where several socio-economic and environmental objectives for policy making are considered. Five types of policy instruments are examined: the current single payment scheme, a multi-payment scheme based on land use, an input taxation, a regulatory scheme and, a combination of the last three. For a selection of scenarios alternative Pareto-optimal solutions are discovered and tradeoffs between policy objectives are presented along with their associated production patterns. Two lines of conclusions are drawn: (1) the performance of the method suggests that it is well suited to dealing with real world applications of policy optimisation and, (2) the current agricultural policy may be sub-optimal in relation to most of the policy objectives examined; more effective policies are possible for Scottish agriculture.

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Humans have been farming plants and animals for over 10,000 years. Meat, grain, medicinal ingredients, fabrics and cloths can all be produced efficiently and cheaply on farms or synthesised. If there is plentiful supply then why does the wildlife trade continue to threaten populations of our remaining natural environments? Clearly the available products do not present an appropriate substitute for the wild product given their prices, attributes or availability. Farming the desired species is therefore an intuitively neat solution to trade issues facing some species. However, I argue and present data to support that argument, that farming is not a panacea for wildlife trade problems. This thesis begins by outlining a theoretical framework around the impact which farming might have upon the poaching of species from the wild. Once the pre-requisites for a successful farming policy to protect wild populations were identified the thesis began to test these for existing trades. Chapters 2 and 3 quantitatively examine the substitutability of wild and farmed products with data from the Atlantic salmon (Salmo sa/ar) market in the UK and the bear bile (Ursus spp.) markets in China. Chapter 3 examines demand for wildlife derived pharmaceuticals by examining the health seeking behaviour in a dual system of traditional Chinese and western medicines. The fifth chapter estimates the total size of the market for wild bear bile after 3 decades of competition from legal farmed bile. The thesis then tests the assumption that competition from the farmed alternative will significantly diminish the incentive to hunt bears for bile by interviewing rural Cambodians. The last two chapters represent methodological work incidental to the core work of this thesis. A novel method to measuring attitudes was developed (and used in chapter 5) to measure moral attitudes towards bear bile use. Finally a method for measuring the marginal value of small changes in available habitat was developed and published during the course of this thesis.

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