ESTIMATION OF GROWTH AND MORTALITY PARAMETERS FROM SIZE FREQUENCY-DISTRIBUTIONS LACKING AGE PATTERNS - THE RED-SEA URCHIN (STRONGYLOCENTROTUS-FRANCISCANUS) AS AN EXAMPLE

We present a maximum likelihood procedure for estimating population gr owth and mortality parameters by simultaneously analysing size frequen cy and growth increment data. The model uses von Bertalanffy growth wi th variability among individuals in the two parameters that determine growth rate, and size-dependent mortality. Analyzing growth increments together with size frequencies reduces the statistical confounding of the natural mortality rate with von Bertalanffy's K parameter. We ass ume steady-state (constant recruitment) conditions for the size distri butions; hence the method does not depend on age modes in the distribu tion. We evaluate the bias and precision of estimates obtained for gro wth-dominated distributions typical of the red sea urchin (Strongyloce ntrotus franciscanus) in northern California, although the method and its evaluation could be applied as easily to mortality-dominated or bi modal distributions. The method provides good estimates with sample si zes as low as 200 individuals in a size distribution and 30 growth inc rements. Results are robust to random variability in recruitment, meas urement error, and sampling selectivity up to the size where about one third of the distribution is affected. Estimation of the fishing mort ality rate could require size distributions from both an unharvested a nd a harvested population; Estimates of growth and mortality rates dep end critically on reliable growth data.