An Empirical Model of Gross Primary Productivity (GPP) and Relations between GPP and Its Driving Factors, Biogenic Volatile Organic Compounds in a Subtropical Conifer Plantation in China

Measurements of net ecosystem exchange (NEE), solar global radiation, photosynthetically active radiation (PAR) and meteorological parameters were carried out on a subtropical conifer plantation in China from 2013 to 2016. These observations used develop evaluate an empirical model gross primary production (GPP) (EMGPP) with 3-factor 2-factor models. Using model, the simulated hourly GPP values consistent relative bias 9.96% normalized mean square error 0.07 mg CO2 m−2 s−1 for scattering factor S/Q (S Q are diffuse radiation) < 0.5 15.52% 0.15 ≥ 0.5. Validations EMGPP hourly, daily, monthly, annual showed that both models can accurately capture diurnal, seasonal interannual variations GPP, but most overestimated observed value. When is not available, be used. The using was applied simulate under all sky conditions 2013–2016, estimated reasonable agreement measured systematic overestimations 31% 29% 41% amounts, respectively. sensitivity test demonstrated more sensitive changes PAR than water vapor at low S/Q, high S/Q. revealed some mechanisms its related processes, including relationships between PAR, vapor, which good other studies. An based energy balance better describe multiple interactions driving factors (PAR, S/Q). ratio emissions biogenic volatile organic compounds (BVOCs) clearly varied forests different climate zones.