Table 6 Regression results of multi− factor liner model between daily carbon flux (NEE, ER and GPP) and environmental variables and LAI, selected according to significant level p < 0.01
From: Drivers of carbon flux in drip irrigation maize fields in northwest China
Carbon flux | Year | Multi− factor liner model | R2 | p |
|---|---|---|---|---|
NEE | 2014 | NEE = − 0.02Rn − 0.05Ta − 24.87SWC − 1.50LAI + 8.03 | 0.73 |  < 0.01 |
2015 | NEE = − 0.04Rn − 0.05Ta − 1.83LAI + 7.29 | 0.78 |  < 0.01 | |
2016 | NEE = − 0.03Rn − 0.30Ta − 1.17VPD − 10.19SWC − 0.41LAI + 10.22 | 0.72 |  < 0.01 | |
2017 | NEE = − 0.03Rn − 0.07Ta − 0.44VPD − 1.42LAI + 5.07 | 0.74 |  < 0.01 | |
2018 | NEE = − 0.01Rn − 0.24Ta + 3.44SWC − 1.22LAI + 5.59 | 0.76 |  < 0.01 | |
Total | NEE = − 1.03LAI − 0.029Rn − 1.67Ta − 0.03IP + 5.72SWC | 0.79 |  < 0.01 | |
ER | 2014 | ER = 0.01Rn + 0.06Ta + 10.06SWC + 0.54LAI − 1.50 | 0.79 |  < 0.01 |
2015 | ER = 0.004Rn + 0.27Ta + 1.60VPD + 3.36SWC + 0.85LAI − 4.38 | 0.78 |  < 0.01 | |
2016 | ER = 0.003Rn + 0.47Ta − 2.09VPD − 0.09LAI − 1.16 | 0.76 |  < 0.01 | |
2017 | ER = − 0.002Rn + 0.23Ta + 0.03VPD + 1.15SWC + 0.83LAI − 1.32 | 0.90 |  < 0.01 | |
2018 | ER = 0.002Rn + 0.09Ta − 0.74SWC + 0.87LAI + 0.77 | 0.89 |  < 0.01 | |
Total | ER = 0.52LAI + 0.17Ta + 0.01Rn + 5.04SWC | 0.71 |  < 0.01 | |
GPP | 2014 | GPP = − 0.01Rn + 0.04Ta + 17.39SWC + 2.69LAI − 3.36 | 0.85 |  < 0.01 |
2015 | GPP = 0.05Rn + 0.53Ta − 34.61SWC + 2.70LAI − 6.04 | 0.90 |  < 0.01 | |
2016 | GPP = 0.04Rn + 0.77Ta − 1.91VPD + 8.70SWC + 0.33LAI − 11.09 | 0.70 |  < 0.01 | |
2017 | GPP = 0.02Rn + 0.29Ta + 0.45VPD + 2.26LAI − 6.10 | 0.86 |  < 0.01 | |
2018 | GPP = 0.02Rn + 0.33Ta − 4.17SWC + 2.09LAI − 4.82 | 0.89 |  < 0.01 | |
Total | GPP = 1.54LAI + 0.03Rn + 0.34Ta + 0.02IP | 0.89 |  < 0.01 |