72 



principal component explained 18.3% of the variance and was 

 significantly correlated with TSI(AVG) (r = 0.648, p < 0.001, n = 29) 

 and pH (r = 0.499, p = 0.006, n = 29). The second principal component 

 explained 10.3% of the variance in the diatom assemblages and was 

 not significantly correlated with any of the environmental or 

 macrophyte variables. The third principal component explained 9.9% 

 of the variance in the diatom assemblages. This component had a 

 significant negative correlation with floating-leaved biomass (r = - 

 0.536, p = 0.010, n = 22), and a positive correlation with pH (r = 

 0.400, p = 0.032, n = 29) and shoreline length. Scores obtained for 

 survey lakes using eigenvectors of the third principal component 

 (Table 8) were used to construct the following model: 



floating-leaved biomass = 2.419 - 0.750(PRIN3) 3.1 



R2 = 0.287, p = 0.010, n = 22 

 where PRIN3 is the sum of the products between eigenvectors and 

 sedimentary concentrations of the 47 diatom groups. 

 The majority of the taxa in Table 8 that show large, positive 

 eigenvectors (e.g. Fragilaria construens, F. pinnata, Navicula 

 lanceolata, N. pupula and vars., A^. radiosa and vars., A^. cuspidata, 

 Nitzschia amphibia, N. capitellata, Cocconeis placentula var. lineata), 

 have a periphytic life form. Many of the taxa with smaller, negative 

 eigenvectors {e.g. Asterionella spp., Aulacoseira islandica, 

 Cyclostephanos dubius, Fragilaria crotonensis) have a euplanktonic 

 life form. It appears that samples with large numbers of periphytic 

 diatoms and few planktonic diatoms would have large values of 

 PRIN3, and it would be reasonable to expect that large PRIN3 values 

 would be associated with greater floating-leaved biomass. Equation 



