MODELING ZOOPLANKTON POPULATION-DYNAMICS WITH THE EXTENDED KALMAN FILTERING TECHNIQUE

The extended Kalman filter is a mathematical method for simultaneous s tate and parameter estimation, originally developed for use in enginee ring science. We applied the technique for modelling zooplankton popul ation dynamics in nature. We described population dynamics by a stage- classified matrix projection model, where vital rates were allowed to vary between stages and over time. We tested the technique with simula ted rotifer data and with field data of a Filinia longiseta (Rotifera) population from a sewage treatment pond in Hungary. Very quick change s in model parameters were typical for the population examined. Howeve r, the extended Kalman filter was capable of tracking parameter change s in the varying environment. The technique was also effective in filt ering moderate sampling noise. The Kalman filter seems to be a very pr omising method for zooplankton population analysis. (C) 1998 Elsevier Science B.V. All rights reserved.