A multivariate approach to synthetize large amount of connectivity matrices for management decisions: Application to oyster population restocking in the pearl farming context of Tuamotu Archipelago semi-closed atolls

Abstract

In applied ecology, numerical biophysical modelling allows running numerous simulations of spatial connectivity between source and destination locations. To characterize population connectivity, larval dispersal and resulting connectivity matrices can be computed for various forcing conditions of wind, density of spawners, or pelagic larval durations. Here, we investigate a methodology to synthetize meaningfully all numerical experiments performed for three atoll lagoons in the Tuamotu Archipelago pearl farming context. The objective is to identify the best restocking locations that consistently maximize the spread of pearl oyster larval dispersal, considering all forcing conditions. A multivariate generic approach is used to process and synthesize time-series of connectivity matrices and identify afterward with contextual criteria the spawning locations that match a variety of specific connectivity, logistical and ecological criteria. Similar synthesis of large volume of connectivity matrices will likely gain momentum considering the increasing use of numerical models for applied science and population management.

Keywords: Aquaculture; Biophysical modelling; Decision support tools; Larval dispersal; Neuroscience; Restocking.