STAGE DURATION ESTIMATION FOR CALANUS POPULATIONS, A MODELING STUDY

Citation
Cb. Miller et Ks. Tande, STAGE DURATION ESTIMATION FOR CALANUS POPULATIONS, A MODELING STUDY, Marine ecology. Progress series, 102(1-2), 1993, pp. 15-34
Citations number
58
Categorie Soggetti
Marine & Freshwater Biology",Ecology
ISSN journal
01718630
Volume
102
Issue
1-2
Year of publication
1993
Pages
15 - 34
Database
ISI
SICI code
0171-8630(1993)102:1-2<15:SDEFCP>2.0.ZU;2-L
Abstract
Population dynamics of Calanus finmarchicus have been modelled using v ery finely divided representation of the stock according to age-within -stage, in the manner of models developed by C. S. Davis, A. Sciandra, F. Carlotti and others. A key assumption of the model is that develop ment rate is relatively insensitive to food-limitation, so that stage duration can be represented by a temperature function alone. We used t he Belehradek function for this purpose, noting that better data are n eeded for fitting its parameters. The model closely simulates the timi ng of stage progression and relative stage abundances of C. finmarchic us in the Malangen fjord system (northern Norway) during the winter-sp ring generation. The model is sensitive to the resolution of the age-w ithin-stage division, but it is fully stable at 0.5 h increments. Modi fications of the model simulated several methods for field estimation of stage duration in Calanus (or other highly seasonal copepod populat ions). A method based on changes in stage proportions (the 'Heinle gra ph' method) is biased by confounding of the effects of developmental p rogress and mortality on stage proportions. However, the model shows t hat the bias is mild and the method gives useful estimates of stage du ration. Simulation of a method based on molting rate determinations (' Kimmerer experiments') showed its unsuitability for highly seasonal st ocks in which stage composition is changing rapidly. Differences in C. finmarchicus survivorship schedules between constant and continuously increasing temperatures were simulated, showing that such differences in pattern are critical to annual survival and stock production. Simp le methods for fitting mortality rates to data using the model were ex tremely sensitive to sampling noise. More complex methods may succeed but remain to be developed.