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Here, we developed a biophysical, individual-based larval dispersal model to assess the effect of oceanographic variability and biological traits (i.e., larval diel vertical migration (DVM) and temperature-dependent larval development (PLD)) on recruitment success, dispersal distance, and alongshore connectivity patterns. We selected two species exploited by the Chilean artisanal fisheries: Loxechinus albus (20 days PLD) and Fissurella latimarginata (5 days PLD).

A sensitivity analysis was used to examine the effect of intrinsic (DVM and PLD) and extrinsic processes (release depth, latitude, and timing). Release location and timing of release explained respectively (a) 24.30 and 5.54% (F. latimarginata) and 34.8 and 4.19% (L. albus) of the variability observed in recruitment success and (b) 23.80 and 6.94% (F. latimarginata) and 26.10 and 19.60% (L. albus) of the variability observed in dispersal distance.

Most recruitment to local populations was allochthonous, presenting low levels of self-recruitment and local retention, including species with short PLD. Similar geographic patterns of source and destination strengths were observed in both species, showing a geographic mosaic of source and sink populations with relatively higher importance towards the northern region of the study area. Our findings allow us to identify primary determinants of recruitment success and dispersal distance for two important exploited species in Chile.

• Offline particle (larvae) tracking and statistics were conducted using a customized version of the open source modeling tool ICHTHYOP (Lett et al. 2008) (http://www.ichthyop.org/) on the hydrographic fields produced by the HYCOM model described above.
• We used a reflective boundary condition at the coast and applied a filter to remove particles that stopped moving for more than 1.5 consecutive days, which were considered beached.
• This filter ensured that larval transport had occurred before tallying onshore recruitment. To establish the appropriate number of particles to be released, we performed repeated trials increasing release numbers (1,000, 5,000, 10,000, 15,000, 20,000, 50,000 and 100,000) and looked for the point at which these statistics stabilized (Brickman & Smith 2002).