Carbon (C) flux between forest ecosystems and the atmosphere is an important ecosystem C cycling component. Modeling C flux plays a critical role in assessing both C cycles and budgets. This study aimed to determine important non-redundant input variables to quantify C flux and to develop a new application of a genetic neural network (GNN) model that accurately simulates C flux. Four input variables (atmospheric CO2 concentration, air temperature, photosynthetically active radiation (PAR), and relative humidity) were fixed, whereas three additi...
