design methodology
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The Evidence Based Decision Making (EBDM) paradigm encourages managers to base their decisions on the strongest available evidence, but it has been criticized for placing too much emphasis on the choice of study design method without considering the types of questions that are being addressed as well as other relevant factors such as how well a study is implemented. Here we review the objectives of Australia’s Marine Park network, and identify the types of questions and data analysis that would address these objectives. Critically, we consider how the design of a monitoring program influences our ability to adequately answer these questions, using the strength of evidence hierarchy from the EBDM paradigm to assess the adequacy of different design strategies and other sources of information. It is important for conservation managers to recognize that the types of questions monitoring programs are able to answer depends on how they are designed and how the collected data are analyzed. The socio-political process that dictates where protected areas are placed typically excludes the strongest types of evidence, Random Controlled Trials (RCTs), for certain questions. Evidence bases that are stronger than ones commonly employed to date, however, could be used to provide a causal inference, including for those questions where RCTs are excluded, but only if appropriate designs such as cohort or case-control studies are used, and supported where relevant by appropriate sample frames. Randomized, spatially balanced sampling, together with careful selection of control sites, and more extensive use of propensity scores and structured elicitation of expert judgment, are also practical ways to improve the evidence base for answering the questions that underlie marine park objectives and motivate long-term monitoring programs. <b>Citation:</b> Hayes KR, Hosack GR, Lawrence E, Hedge P, Barrett NS, Przeslawski R, Caley MJ and Foster SD (2019) Designing Monitoring Programs for Marine Protected Areas Within an Evidence Based Decision Making Paradigm.<i> Front. Mar. Sci</i>. 6:746. doi: 10.3389/fmars.2019.00746