Genetic effect of domestication selective pressures on Pacific oyster at larval stage

Among bivalve species, the Pacific oyster, Crassostrea gigas, is the most economically important bivalve production over the world. Today, C. gigas is subject to an important production effort that leads to an intensive artificial selection. Larval stage is relatively unknown, specifically in a domestication context. Genetic consequence of artificial selection is still at a preliminary study. We aimed to tackle the consequence of inconscient domestication on the variance reproductive success focusing on larval stage, keystone of the life cycle. We studied two kinds of specific selective processes that common hatchery rearing practices exert : the effect of discarding the smallest larvae on genetic diversity and the artificial environment rearing effect via the temperature providing a contrast resembling wild versus hatchery conditions (20 and 26°C). In order to monitor the effect of the selection of fast growing larvae by sieving, growth variability and genetic diversity in a larval population descended from a factorial breeding was studied. We used a mixed-family approach to reduce potentially confounding environmental biais. The retrospective assignment of individuals to family groups has been performed using a three microsatellite markers set. Two different rearing were carried out in parallel. For three (replicates) 50-l tanks, the smallest larvae were progressively discarded by selective sieving, whereas for the three others no selective sieving was performed. The intensity of selective sieving was adjusted so as to discard 50% of the larvae over the whole rearing period in a progressive manner. As soon as the larvae reached the pediveliger stage, ready to settle larvae were sampled for genetic analysis. Regarding the artificial environment rearing effect via the temperature, we used a similar mixed-family approach. The progeny from a factorial breeding design was divided as follows: three (replicates) 50-l tanks were dedicaced to a rearing at 26°C versus 20°C for three others 50-l tanks. The whole size variability was preserved for this experiment. Individual growth measurements for larvae genetically identified have been performed at days 22 and 30 after fertilization for both conditions. In a same way, we collected individual measurements for genotyped juvenile oysters (80 days after fertilization). At a phenotypic scale, relative survival and settlement success for larvae with sieving were higher. Sieving appears as a time-saving process associated with a better relative survival ratio. But in the same time, our results confirm that a significant genetic variability exist for early developmental traits in the Pacific oyster. This is congruent with the results already obtained that investigated genetic variability and genetic correlations in early life-history traits of Crassostrea gigas. Discarding around 50% of the smallest larvae can lead to significant selection at the larval stage.

Probabilistic approach of water residence time and connectivity using Markov Chains with application to tidal embayments

Markov Chain analysis was recently proposed to assess the time scales and preferential pathways into biological or physical networks by computing residence time, first passage time, rates of transfer between nodes and number of passages in a node. We propose to adapt an algorithm already published for simple systems to physical systems described with a high resolution hydrodynamic model. The method is applied to bays and estuaries on the Eastern Coast of Canada for their interest in shellfish aquaculture. Current velocities have been computed by using a 2 dimensional grid of elements and circulation patterns were summarized by averaging Eulerian flows between adjacent elements. Flows and volumes allow computing probabilities of transition between elements and to assess the average time needed by virtual particles to move from one element to another, the rate of transfer between two elements, and the average residence time of each system. We also combined transfer rates and times to assess the main pathways of virtual particles released in farmed areas and the potential influence of farmed areas on other areas. We suggest that Markov chain is complementary to other sets of ecological indicators proposed to analyse the interactions between farmed areas - e.g. depletion index, carrying capacity assessment. Markov Chain has several advantages with respect to the estimation of connectivity between pair of sites. It makes possible to estimate transfer rates and times at once in a very quick and efficient way, without the need to perform long term simulations of particle or tracer concentration.