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Understanding the effectiveness of marine protected areas using genetic connectivity patterns and Lagrangian simulations

August 5, 2013

Aim: To explore the patterns of connectivity between marine protected areas (MPAs) and neighbouring non-protected areas and the scale at which the benefits of MPAs are expected using the white sea bream as model species.

Location: Marine protected area of Torre Guaceto (TGMPA, Italy) in the south Adriatic Sea.

Methods: A multidisciplinary approach was used combining (1) a genetic survey using 12 highly informative microsatellite loci of samples collected within the MPA and in several locations up to 100 km from the MPA; and (2) larval trajectories using Lagrangian simulations based on an oceanographical model of the region that includes specific data on early life-history traits. Both genetic and simulation studies were temporarily replicated during two consecutive years.

Results: The overall genetic homogeneity observed indicates that the TGMPA is not isolated and that there is genetic connectivity among locations across a scale of at least ~200 km. A high degree of connectivity between the TGMPA and neighbouring areas is in agreement with Lagrangian simulations, which indicate that white sea bream larvae can be transported over large distances up to about 300 km. Trajectories released from the TGMPA showed that on average, 12.75% of the larvae remains within the TGMPA, while the rest travel south towards non-protected areas.

Main conclusions: Our findings highlight the potential benefits of effectively enforced MPAs for neighbouring or relatively distant non-protected fishing areas and the potential connection with other MPAs at regional scale. Combining genetics and modelling can provide a general framework to investigate the role of connectivity in MPA design that can be easily extended to other species and geographical areas.

Pujolar J M, Schiavina M, Di Franco A, Melià P, Guidetti P, Gatto M, De Leo G A, Zane L, 2013, Understanding the effectiveness of marine protected areas using genetic connectivity patterns and Lagrangian simulations, Diversity and Distributions, 1-12, doi:10.1111/ddi.12114. Article.


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