Linking models with monitoring data for assessing performance of no-take marine reserves

www.frontiersinecology.org © The Ecological Society of America T number of marine reserves is growing worldwide (Wood et al. 2008), so it is prudent to consider how to assess whether such reserves achieve their goals. The stated goals of marine reserves vary widely, but fundamentally all reserves are designed to achieve some combination of preserving biodiversity and supporting sustainable fisheries (Leslie 2005). Empirical evidence indicates that biomass and biodiversity usually increase inside reserves, but sometimes do not change or even decrease (Lester et al. 2009; Figure 1). As governments consider implementing additional reserves, it bears asking: What causes some reserves to perform well while others do not? Also, how can we assess how well reserves meet specific goals? Note that here we deal primarily with no-take marine reserves, a subset of the broader class of marine protected areas (MPAs; WebPanel 1). The interplay of models and data is a powerful approach for advancing science (Caswell 1988), a capacity that is embodied in adaptive management (Walters 1986). Adaptive management ideally requires ongoing comparison of empirical data to quantitative expectations derived from models (Grafton and Kompas 2005; see Lindenmayer and McCarthy [2006] for a terrestrial example). However, in the case of marine reserves, model development and monitoring data collection have proceeded independently, with the two only rarely integrated (eg Claudet et al. 2010). Although marine reserve models and empirical studies have been reviewed separately with respect to reserve design and general outcomes (Gerber et al. 2003; Lester et al. 2009) and the development of indicators from modeling and empirical results (Pelletier et al. 2008), here we focus on the integration of models and monitoring data. First, we provide a theoretical perspective on reserve goals and factors affecting their achievement. Then we review recent empirical assessments, placing them in the context of theoretical expectations and assumptions. Finally, we identify directions for integrating models and data in the assessment and adaptive management of marine reserves.