Bin quantile regression analysis of i-Tree Eco-B, C, and D outputs for most important input variables.
| Module | Output variable Y | Input variable X | Regression equation | Regression form | Adjusted R2 |
|---|---|---|---|---|---|
| Eco-B | Isoprene | Leaf biomass | Y = 0.16 + 1.32X – 0.18X2 | Concave | 0.99 |
| Eco-B | Isoprene | Temperature | Y = −0.45 + 0.82X + 0.49X2 | Convex | 0.96 |
| Eco-B | Isoprene | PAR | Y = 0.94X | Linear | 0.87 |
| Eco-B | Isoprene | CLE | Y = 0.95X | Linear | 0.87 |
| Eco-B | Monoterpenes | Leaf biomass | Y = 0.34 + 1.66X – 0.38X2 | Concave | 1.00 |
| Eco-B | Monoterpenes | Temperature | Y = −0.35 + 0.89X + 0.39X2 | Convex | 0.99 |
| Eco-B | Monoterpenes | CLE | Y = 0.89X | Linear | 0.74 |
| Eco-C | Carbon storage | DBH | Y = −0.18 + 0.65X + 0.2X2 | Convex | 0.99 |
| Eco-C | Carbon gross sequestration | DBH | Y = 0.99X | Linear | 0.98 |
| Eco-C | Carbon gross sequestration | Condition | Y = 0.91X | Linear | 0.78 |
| Eco-C | Carbon gross sequestration | CLE | Y = 0.82X | Linear | 0.59 |
| Eco-D | Vd,NO2 | PAR | Y = 0.42 + 1.148X – 0.467X2 | Concave | 0.94 |
| Eco-D | Vd,NO2 | Relative humidity | Y = 0.77X | Linear | 0.55 |
| Eco-D | Vd,NO2 | LAI | Y = 0.99X | Linear | 0.98 |
| Eco-D | Vd,NO2 | Temperature | Y = 0.2 + 0.97X – 0.22X2 | Concave | 0.96 |
| Eco-D | Vd,SO2 | PAR | Y = 0.35 + 1.15X – 0.39X2 | Concave | 0.99 |
| Eco-D | Vd,SO2 | Relative humidity | Y = 0.86X | Linear | 0.71 |
| Eco-D | Vd,SO2 | Temperature | Y = 0.15 + 0.98X – 0.16X2 | Concave | 0.98 |
| Eco-D | Vd,SO2 | LAI | Y = 0.975X | Linear | 0.95 |
| Eco-D | Vd,O3 | PAR | Y = 0.37 + 1.16X – 0.41X2 | Concave | 0.98 |
| Eco-D | Vd,O3 | Relative humidity | Y = 0.85X | Linear | 0.69 |
| Eco-D | Vd,O3 | LAI | Y = 0.9775X | Linear | 0.95 |
| Eco-D | Vd,O3 | Temperature | Y = 0.15 + 0.98X – 0.17X2 | Concave | 0.98 |