Is my marine park achieving its conservation goal? A straightforward analytical approach to help managers address this question

There is an increasing demand that managers of marine parks quantitatively demonstrate the achievement of their conservation goals. Monitoring is one tool that can help with this. One component of monitoring that is challenging for managers is the statistical treatment of monitoring data. Commonly used approaches, such as null hypothesis tests, are conceptually challenging and operationally complex, potentially leading to wrong conclusions and poor decisions. A more straightforward approach is parameter estimation with confidence intervals. Parameter estimation focuses on estimating the size of change or difference (an ‘effect size’) in a response variable and comparing this with a pre-defined effect size called a management threshold. Confidence intervals indicate the level of precision in estimates of change, which make for more balanced conclusions. Parameter estimation is also conducive to graphing, which can facilitate interpretation and communication to non-scientists. In this paper, I demonstrate three examples of parameter estimation and discuss their relative strengths and weaknesses. By presenting these examples, I hope to encourage managers to adopt statistical approaches that allow them to quantify environmental change in a way that will contribute to defensible conclusions, facilitate timely decision making and be understood by stakeholders.