No-take marine reserves can be powerful management tools, but only if they are well designed and effectively managed. We review how ecological guidelines for improving marine reserve design can be adapted based on an area's unique evolutionary, oceanic, and ecological characteristics in the Gulf of California, Mexico. We provide ecological guidelines to maximize benefits for fisheries management, biodiversity conservation and climate change adaptation. These guidelines include: representing 30% of each major habitat (and multiple examples of each) in marine reserves within each of three biogeographic subregions; protecting critical areas in the life cycle of focal species (spawning and nursery areas) and sites with unique biodiversity; and establishing reserves in areas where local threats can be managed effectively. Given that strong, asymmetric oceanic currents reverse direction twice a year, to maximize 123Rev Fish Biol Fisheries (2018) 28:749-776 https://doi.org/10.1007/s11160-018-9529-y( 0123456789().,-volV) (0123456789().,-volV)

The relative importance of environmental and intrinsic controls on recruitment in fishes has been studied for over a century. Despite this, we are not much closer to predicting recruitment. Rather, recent analyses suggest that recruitment is virtually independent of stock size and, instead, seems to occur in distinct environmental regimes. This issue of whether or not recruitment and subsequent production are coupled to stock size is highly relevant to management. Here, we apply empirical dynamical modelling (EDM) to a global database of 185 fish populations to address the questions of whether or not variation in recruitment is (a) predictable and (b) coupled to stock size. We find that a substantial fraction of recruitment variation is predictable using only the observed history of fluctuations (~40% on average). In addition, although recruitment is often coupled to stock size (107 of 185 stocks), stock size alone explains very little of the variation in recruitment; In ~90% of the stocks analysed, EDM forecasts have substantially lower prediction error than models based solely on stock size. We find that predictability varies across taxa and improves with the number of generations that have been sampled. In the light of these results, we suggest that EDM will be of greatest use in managing relatively short‐lived species.

Although it seems obvious that with more data, the predictive capacity of ecological models should improve, a way to demonstrate this fundamental result has not been so obvious. In particular, when the standard models themselves are inadequate (von Bertalanffy, extended Ricker etc.) no additional data will improve performance. By using time series from the Sir Alister Hardy Foundation for Ocean Science Continuous Plankton Recorder, we demonstrate that longterm observations reveal both the prevalence of nonlinear processes in species abundances and an improvement in out-of-sample predictability as the number of observations increase. The empirical results presented here quantitatively demonstrate the importance of long-term temporal data collection programs for improving ecosystem models and forecasts, and to better support environmental management actions.