Table 2.
Linear regression modeling of variation versus input biomass and mean relative abundance. Summary of the linear regression model (a) and predicted variation values for a subset of 16S rRNA gene copies/microliter and mean relative abundance values (b)
| a. Model | Estimate | Standard error | t value | p value | ||
| (Intercept) | 1.43238 | 0.12556 | 11.408 | < 2.2E−16 | ||
| log10 copies/microliter | − 0.2816 | 0.04905 | − 5.741 | 6.93E−8 | ||
| log10 mean relative abundance | − 0.54936 | 0.06927 | − 7.931 | 1.13E−12 | ||
| Residual standard error | 0.5196 | |||||
| Multiple R-squared | 0.4496 | |||||
| Adjusted R-squared | 0.4407 | |||||
| F statistic | 50.25 on DF (2123) | |||||
| b. Prediction | Mean relative abundance (%) | |||||
| Copies/microliter | 1 | 5 | 10 | 25 | 50 | |
| Low biomass | 10 | 0.5723 | 1.7313 | 2.7888 | 5.2376 | 8.4370 |
| Medium biomass | 1000 | 0.2865 | 0.8668 | 1.3963 | 2.6224 | 4.2242 |
| High biomass | 100,000 | 0.1435 | 0.4340 | 0.6991 | 1.3130 | 2.1150 |