###############################################################

                     #Perform ANOVA on Observed, which effects are significant

                     anova.Observed <-aov( Observed  ~  Depth + source + sample_species, anova_data)

                     summary(anova.Observed)
               Df Sum Sq Mean Sq F value Pr(>F)  
Depth           1   1382    1382   0.370 0.5523  
source          1   1323    1323   0.354 0.5608  
sample_species  2  42699   21349   5.711 0.0143 *
Residuals      15  56078    3739                 
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1


###############################################################

                     #Perform ANOVA on Chao1, which effects are significant

                     anova.Chao1 <-aov( Chao1  ~  Depth + source + sample_species, anova_data)

                     summary(anova.Chao1)
               Df Sum Sq Mean Sq F value Pr(>F)  
Depth           1   1376    1376   0.368 0.5531  
source          1   1323    1323   0.354 0.5608  
sample_species  2  42710   21355   5.712 0.0143 *
Residuals      15  56077    3738                 
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1


###############################################################

                     #Perform ANOVA on Shannon, which effects are significant

                     anova.Shannon <-aov( Shannon  ~  Depth + source + sample_species, anova_data)

                     summary(anova.Shannon)
               Df Sum Sq Mean Sq F value  Pr(>F)   
Depth           1  3.656   3.656   9.631 0.00727 **
source          1  0.553   0.553   1.458 0.24601   
sample_species  2  6.389   3.194   8.415 0.00354 **
Residuals      15  5.694   0.380                   
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1


###############################################################

                     #Perform ANOVA on InvSimpson, which effects are significant

                     anova.InvSimpson <-aov( InvSimpson  ~  Depth + source + sample_species, anova_data)

                     summary(anova.InvSimpson)
               Df Sum Sq Mean Sq F value Pr(>F)  
Depth           1  236.9  236.92   4.325 0.0551 .
source          1   66.1   66.06   1.206 0.2895  
sample_species  2  535.6  267.79   4.888 0.0232 *
Residuals      15  821.7   54.78                 
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1


###############################################################

                     #Perform ANOVA on Pielou, which effects are significant

                     anova.Pielou <-aov( Pielou  ~  Depth + source + sample_species, anova_data)

                     summary(anova.Pielou)
               Df  Sum Sq Mean Sq F value   Pr(>F)    
Depth           1 0.15057 0.15057  25.883 0.000134 ***
source          1 0.01270 0.01270   2.183 0.160265    
sample_species  2 0.10838 0.05419   9.315 0.002345 ** 
Residuals      15 0.08726 0.00582                     
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1