New approach to identifying the drivers of regulation compliance using multivariate behavioural models

Abstract

Non-compliance with fishing regulations can undermine management effectiveness. Previou bivariate approaches were unable to untangle the complex mix of factors that may influenc fishers' compliance decisions, including enforcement, moral norms, perceive legitimacy of regulations and the behaviour of others. We compared seven multivariat behavioural models of fisher compliance decisions using structural equation modeling. A online survey of over 300 recreational fishers tested the ability of each model to best predic their compliance with two fishing regulations (daily and size limits). The best fitting mode for both regulations was composed solely of psycho-social factors, with social norms havin the greatest influence on fishers' compliance behaviour. Fishers' attitude also directl affected compliance with size limit, but to a lesser extent. On the basis of these findings, w suggest behavioural interventions to target social norms instead of increasing enforcemen for the focal regulations in the recreational blue cod fishery in the Marlborough Sounds New Zealand. These interventions could include articles in local newspapers and fishin magazines highlighting the extent of regulation compliance as well as using respected loca fishers to emphasize the benefits of compliance through public meetings or letters to th editor. Our methodological approach can be broadly applied by natural resource manager as an effective tool to identify drivers of compliance that can then guide the design of intervention to decrease illegal resource use.