Abstract

Scientific information to properly manage resources, improve sustainability of exploited ecosystems and conserve biodiversity will never be sufficient to provide a ‘how-to’ user manual for managers and conservation agencies. Yet, scientists must still provide guidelines to preserve the ecosystem services on which life depends and help us navigate a path away from collapse. Facing the impossibility of managing data-poor coastal fisheries using traditional fisheries protocols and recognizing the limitations of ‘resource-focus’ approaches, which disregard the wider ecosystem implications of fisheries and the human dimensions of sustainability, scientists and practitioners have turned to more integrated and holistic approaches. The implementation of Marine Protected Areas (MPAs) and Ecosystem Based Management (EBM) plans have been endorsed by the scientific community and are prioritized. Here, we highlight two persistently overlooked or under-appreciated aspects in the zonation design, the monitoring programs, and EBM and MPA effectiveness assessments. Using the Galápagos Marine Reserve Management Plan (GMRMP) as example we illustrate the need to include: (1) basic principles of dispersal and connectivity in spatial planning and EBM in general and (2) multi-species models to assess ecosystem-wide consequences of management policies, i.e. adaptive monitoring. On one hand, well-developed metapopulatiton theory, advanced oceanographic modeling, and global hydrographic information make it possible to consider connectivity in spatial management and we show why it is urgent to include time-varying metapopulation dynamics if we are to sustainably exploit coastal marine ecosystems, including the Galapagos Marine Reserve. On the other hand, attributing biodiversity changes to policy cannot be done without species interaction models that anticipate the propagation of effects through the ecological web. We suggest that quantitative, bioenergetic multi-species models, parameterized following basic allometric principles can be used in a qualitative manner to simulate management scenarios and identify the species that can be most affected by spatial management decisions.

Full Text
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