On the use of self-thinning relationships in stocking experiments

Abstract

We present a method for estimating optimal stocking density (OSD), via the analysis of the relationship between yield (biomass, B) and population density ( N) at harvest, using a B- N diagram (BND). This differs from the usual approach in aquaculture, in which yield is expressed as a function of initial population density, and B and N are analysed separately. Both methods allow estimation of OSD. In addition to OSD, however, the BND potentially allows: (1) assessment of the relative importance of competition-dependent and competition-independent mortality factors; (2) estimation of approximate OSD and maximum yield by extrapolation of results from short-term experiments; and (3) indentification of the nature of the factor regulating competition-dependent mortality. We compared the classical and BND methods using data from mussels grown in suspension cultures. The classical approach suggested that OSD was roughly 400 individuals per 30.5 cm of sleeve, that mortality patterns were the same for all stocking densities, and that competition-dependent mortality occurred only at high density. The BN approach suggested that optimal seeding density ranges between 120 and 200 mussels per 30.5 cm of sleeve, which was below the range of initial densities tested. In addition, there was evidence that mortality patterns differed between mussel groups. One group exhibited successively competition-dependent mortality and competition-independent mortality, whereas others exhibited either one type or the other. In an experiment designed to test the effect of spat origin (stock effect) on commercial yield, the classical approach suggested that there were no differences in yield and survival, despite differences in growth rate. The BN approach, however, showed that yield was constrained by self-thinning, not by intrinsic properties of the stocks. Thus the BND invalidated the experiment. The BN approach, unlike the classical approach, yielded results consistent with state-of-the-art commercial practice and general knowledge about the stocks tested.