Model for growth and survival of mussels Mytilus edulis reared in Prince Edward Island, Canada

Abstract

Mathematical models of commercially important species enable one to integrate the diversity of information on these species, understand mechanisms responsible for observed population dynamics, and assess management scenarios. We present a population model for blue mussels Mytilus edulis grown in suspended culture in 2 bays in Prince Edward Island, Canada. The model incorporates a number of ecological processes, namely allometric growth of individual mussels, temperature-dependent growth rates (based on the Lassiter-Kearns equation), and survival of mussels based on self-thinning. Analysis of our model suggests that the optimal temperature for mussel growth is 15.8°C. Also, survival does not depend on site or year, indicating that self-thinning is probably due to competition for space rather than food or other site-specific conditions. Based on sensitivity analyses, growth predictions are robust to changes in parameter values, while survival predictions are quite sensitive to changes in the strength of the effect of initial mussel density and of self-thinning. Evaluation of management scenarios over one grow-out period indicates that date of deployment strongly affects time for seeds to reach commercial size. Optimal initial mussel density depends on whether one wants to maximise the proportion of mussels surviving to harvest or the number of mussels available at harvest; this decision depends on whether seed availability or lease area is limiting.

Body size, population density and factors regulating suspension-cultured blue mussel (Mytilusspp.) populations

“…The effective-density method was developed for the analysis of an intertidal tunicate (Guiñez and Castilla 2001). The multilayer method was applied to suspensiongrown mussels (Lachance-Bernard et al 2010) and provided estimates of the 3-D ST exponent which are consistent with the present study i.e., that ST in suspension-grown mussels is driven by spatial constraints (see also Lauzon-Guay et al 2006). This conclusion clearly diverges from that of Filgueira et al (2008), who reported FST in suspension-grown mussels using the effective-density method.…”

“…They found β = [−0.557, −0.423], suggesting that ST was driven by competition for space. Lauzon-Guay et al (2006), using a population model of growth and survival of mussels cultured on long lines in two estuaries of Prince Edward Island, Canada, also concluded that mussel population density was regulated by spatial constraints. Although these studies were based on different numerical methods, all involved similar mussel species grown in suspension (Mytilus edulis, M. galloprovincialis and M. trossulus).…”

Effects of temperature on energetics and the growth pattern of benthic octopuses

“…We used the metric of 'elasticity', in which the effect of proportional (rather than absolute) perturbations on a given output quantity are evaluated (Caswell 2001). Elasticity is defined as: (13) where S P (%) is the elasticity of the output quantity to a given % increase in parameter P, x 0 is the output of the original model and x P is the output of the model modified for parameter P (Barbeau & Caswell 1999, Lauzon-Guay et al 2006. Elasticities of B* (critical transition weight) and t* (critical transition age) to independent perturbations of d ƒ , T ƒopt , ƒ opt , p 1 , a 2 , b 2 , p 2 , d, T opt and m opt were calculated at 2 levels of parameter change, namely at 1 and 5%.…”

Hierarchical structure of bivalve culture systems and optimal stocking density

“…3 in AlunnoBruscia et al 2000;e.g., Figs. 5 and 7 in Fréchette et al 2000; but see Lauzon-Guay et al 2006). A further example of ambient conditions being reflected in stocking experiments is found in mussel rafts (provided that the conventional a = 0.05 significance level is used instead of a = 0.01, as used by Fuentes et al 2000).…”