ESTIMATING GROWTH AND MORTALITY IN STAGE-STRUCTURED POPULATIONS

This paper presents a practical numerical method for separating and es timating growth and mortality coefficients in stage-or size-structured populations using only observations of the relative or absolute abund ance of each stage. The method involves writing a system of linear ord inary differential equations (ODEs) modelling the rate of change of ab undance. The solution of the differential system can be numerically ap proximated using standard (e.g. sixth-order Runge-Kutta-Felhberg) meth ods. An optimization problem whose solutions yield 'optimal' coefficie nts for a given model is formulated. The ODE numerical integration tec hnique can then be employed to furnish required function and gradient information to the optimization algorithm. The data-fitting software p ackage ODRPACK is then successfully employed to estimate optimal coeff icients for the ODE population model. Simulation experiments with four -and eight-stage model populations illustrate that the method results in the successful estimation of coefficients of mortality and growth f rom abundance data.