Modelling differences in angler choice behaviour with advanced discrete choice models

Abstract

New Zealand is internationally renowned for having some of the finest and most challenging trout fishing in the world. However, due to continuing development and angling pressure many fishing sites are showing signs of environmental degradation and over fishing. This trend is almost certain to continue into the future given continued population and economic growth. Understanding the determinants of site choice, preference heterogeneity and anglers’ substitution patterns is fundamentally important to fishery managers who have the difficult task of maintaining quality angling experiences on a number of fishing sites, managing angling pressure and maintaining license sales.

Recent advances in simulation techniques and computational power have improved the capability of discrete choice models to reveal preference heterogeneity and complex substitution patterns among individuals. This thesis applies and evaluates a number of state-of-the-art discrete choice models to study angler site choice in New Zealand. Recreation specialisation theory is integrated into the analysis to enhance the behavioural representation of the statistical models.

A suite of models is presented throughout the empirical portion of this thesis. These models demonstrate different ways and degrees of explaining preference heterogeneity as well as identifying anglers’ substitution patterns. The results show that North Canterbury anglers’ preferences vary considerably. Resource disturbances such as riparian margin erosion, reduced water visibility and declines in catch rates can cause significant declines in angler use of affected sites, and at the same time non-proportional increases in the use of unaffected sites. Recreation specialisation is found to be closely related to the types of fishing site conditions, experiences and regulations preferred by anglers. Anglers’ preference intensities for fishing site attributes, such as catch rates, vary across different types of fishing sites. This location specific preference heterogeneity is found to be related to specialisation. Overall, the empirical findings indicate that conventional approaches to modelling angler site choice which do not incorporate a strong understanding of angler preference heterogeneity can lead to poorly representative models and suboptimal management and policy outcomes.