Table 7.
Variable | SLOW | Substrate degradation rate | FAST | ||||||
---|---|---|---|---|---|---|---|---|---|
MOD | |||||||||
FS | |||||||||
0.0 | 0.5 | 1.0 | 0.0 | 0.5 | 1.0 | 0.0 | 0.5 | 1.0 | |
Mean observed | 2.6 | 2.6 | 2.6 | 2.6 | 2.6 | 2.6 | 2.6 | 2.6 | 2.6 |
Mean predicted | 1.9 | 1.7 | 1.6 | 1.9 | 1.8 | 1.6 | 1.9 | 1.7 | 1.6 |
Mean bias | −0.6 | −0.8 | −1.0 | −0.7 | −0.8 | −1.0 | −0.7 | −0.8 | −1.0 |
Relative prediction error1 | 45.2 | 49.0 | 53.4 | 45.1 | 48.7 | 52.7 | 45.3 | 48.7 | 52.8 |
Error decomposition: | |||||||||
% bias | 30.4 | 43.2 | 54.0 | 31.3 | 43.0 | 53.1 | 32.1 | 43.5 | 53.3 |
% slope | 0.8 | 0.5 | 0.7 | 1.2 | 0.9 | 1.1 | 1.2 | 1.0 | 1.2 |
% random | 60.8 | 52.1 | 44.3 | 61.3 | 53.1 | 45.5 | 61.1 | 53.0 | 45.4 |
R22 | 0.02 | 0.01 | 0.01 | 0.01 | 0.00 | 0.00 | 0.01 | 0.01 | 0.00 |
CCC3 | −0.04 | −0.02 | 0.00 | −0.03 | −0.01 | 0.00 | −0.03 | −0.01 | −0.01 |
RSR4 | 1.2 | 1.3 | 1.5 | 1.2 | 1.3 | 1.4 | 1.2 | 1.3 | 1.4 |
N = 20.
1RPE = (Root mean square prediction error RMSPE/mean observed) × 100 (a smaller value is better).
2 R 2 of the regression predicted vs. observed.
3Lin’s concordance correlation coefficient (closer to 1 is better).
4Ratio of RMSPE to standard deviation of observed values: <0.5, very good prediction; 0.5–0.75, good prediction; 0.75–1, moderate prediction; and >1.0, model needs improvement.