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Despite the recognised effectiveness of networks of Marine Protected Areas(MPAs) as a biodiversity conservation instrument, nowadays MPA network designfrequently disregards the importance of connectivity patterns. In the case ofsedentary marine populations, connectivity stems not only from the stochasticnature of the physical environment that affects early-life stages dispersal,but also from the spawning stock attributes that affect the reproductive output(e.g., passive eggs and larvae) and its survivorship. Early-life stages arevirtually impossible to track in the ocean. Therefore, numerical ocean currentsimulations coupled to egg and larval Lagrangian transport models remain themost common approach for the assessment of marine larval connectivity. Inferredlarval connectivity may be different depending on the type of connectivityconsidered; consequently, the prioritisation of sites for marine populations'conservation might also differ. Here, we introduce a framework for evaluatingand designing MPA networks based on the identification of connectivity hotspotsusing graph theoretic analysis. We use as a case of study a network ofopen-access areas and MPAs, off Mallorca Island (Spain), and test itseffectiveness for the protection of the painted comber Serranus scriba. Outputsfrom network analysis are used to: (1) identify critical areas for improvingoverall larval connectivity; (2) assess the impact of species' biologicalparameters in network connectivity; and (3) explore alternative MPAconfigurations to improve average network connectivity. Results demonstrate thepotential of graph theory to identify non-trivial egg/larval dispersal patternsand emerging collective properties of the MPA network which are relevant forincreasing protection efficiency.

MPA network design based on graph network theory and emergent properties of larval dispersal