4.7 Article

Larval Fish Swimming Behavior Alters Dispersal Patterns From Marine Protected Areas in the North-Western Mediterranean Sea

期刊

FRONTIERS IN MARINE SCIENCE
卷 5, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fmars.2018.00097

关键词

fish larvae; behavior; swimming; connectivity; dispersal; mediterranean sea; marine protected areas; modeling

资金

  1. Partner University Fund
  2. National Science Foundation [1260424]
  3. French Ministry of Education and Research [247/2012]
  4. Division Of Ocean Sciences
  5. Directorate For Geosciences [1260424] Funding Source: National Science Foundation

向作者/读者索取更多资源

Most demersal fishes undergo a dispersal phase as larvae, which strongly influences the connectivity among adult populations and, consequently, their genetic structure and replenishment opportunities. Because this phase is difficult to observe directly, it is frequently simulated through numerical models, most of which consider larvae as passive or only vertically migrating. However, in several locations, including the Mediterranean Sea, many species have been shown to swim fast and orient. Here we use a Lagrangian model to study connectivity patterns among three Mediterranean Marine Protected Areas (MPAs) and compare simulations in which virtual larvae are passive to simulations in which oriented swimming is implemented. The parameterization of behavior is based on observations for two groups of species of the family Sparidae: species with small larvae (i.e., 9-11 mm), displaying a maximum swimming speed of 6cm s(-1) and a pelagic larval duration of 13-19 days (e.g., Diplodus annularis L., Oblade melanura L.) and species with large larvae (i.e., 14-16 mm), displaying a maximum swimming speed of 10 cm s(-1) and a PLD of 28-38 days (e.g., Spondyliosoma cantharus L.). Including larval behavior in the model (i) increased the overall proportion of successful settlers, (ii) enhanced self-recruitment within the MPAs, but also (iii) increased the intensity, and (iv) widened the export of eggs and larvae (recruitment subsidy) from the MPAs; overall, it significantly changed connectivity patterns. These results highlight the need to gather the observational data that are required to correctly parameterize connectivity models.

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