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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