Embedding predictive tools into marine environmental management policy and legislation
Start date: 1 June 2015
Marine environmental protection has shown a marked change from behavioural regulation to policy and legislation designed to directly protect ecosystem biodiversity, function and services. However, the effectiveness of such policies and legislation are difficult to interpret without regular monitoring, and (at least in the absence of additional legislation) damage to an ecosystem must occur before preventative action can be taken. Here we present a tool based on Bayesian belief networks for predicting the effects of various activities on marine communities which 1) provides information at the level of detail required by most policy and legislation worldwide; 2) can be developed and parameterised by any existing data and expert opinion; 3) is intuitive to use, and management scenarios can be explored independently by scientists, policy makers, enforcers and stakeholders; 4) provides accurate and robust predictions of marine systems, including at the ecological community level. We propose that more effective marine environmental management can be obtained by embedding the use of such predictive tools into the direct protection policy and legislation which exists or is being developed at present.