81 



valves of 9 diatom taxonomic groups (Appendix 3.7) that were 

 correlated with floating-leaved biomass in the cluster analysis 

 procedure. All models that resulted from these stepwise attempts 

 demonstrated random errors. Stepwise regression was also 

 performed on the 7 diatom taxa in the annual-accumulation rate 

 cluster analysis that were correlated with floating-leaved biomass. 

 The best model, as indicated by the Cp statistic, included a single 

 diatom taxon, and this model explained only 28.7% of the variance in 

 floating-leaved biomass. 



Better results were obtained by stepwise regression of 12 

 diatom taxonomic groups (Appendix 3.9) that were selected from 

 plots of percentage data for diatom taxa versus floating-leaved 

 biomass. The best model obtained was the following: 



FLOATING = 5.105 - 3.4551oglO(ACHS) - 2.4931oglO(CYMMUEL) 

 + 0.264(CYSTEPDU) - 0.281(S-NAVS) - 3.2971oglO(S- 

 NITZS) 3.5 



R2 = 0.866, p < 0.001, n = 22, adj. R2 = 0.825 



where FLOATING = floating-leaved biomass in kg wet mass m-2 

 ACHS = ACHEX + ACHLIN + ACHLINCU + ACHMIN 

 S-NAVS = NAVGOT + NAVLAN + S-NAVPU + S-NAVRA 

 -hNAVSUBTS 

 NITZS = NITZAM + NITZCAP + NITZFRUS. 



The values for all taxonomic groups, whose acronyms are defined in 



Appendices 1 and 2, are expressed as a percentage of the diatom 



assemblages. This model appeared to have a significant relationship 



with submerged biomass (R2 = 0.502, p = 0.034). Partial correlation 



coefficients showed that floating-leaved biomass was significantly 



correlated with the model (r = 0.882, p < 0.001, n = 22) when the 



