Estimation of CO₂ flux components over northern hemisphere forest ecosystems by using random forest method through...

Modeling CO₂ flux components is an important task in ecosystem analysis and terrestrial studies. Net ecosystem exchange (NEE), ecosystem respiration (R), and gross primary production (GPP) are three CO₂ flux components. Despite the ecosystem land cover characteristics, climatic factors can make considerable impact on quantity and mechanism of these components. Nevertheless, such climatic factors are not available in most of the areas, especially in developing regions. Therefore, obtaining the models that can exempt using locally recorded variables would be of great importance. A modeling study was carried out here to simulate CO₂ flux components using soft computing-based random forest (RF) model in both local and external (spatial) scales, assessed by k-fold validation procedure. Data from 11 sites located in three forest ecosystems, e.g. deciduous broad leaf (DBF), evergreen needle leaf (ENF), and mixed forest (MF), were used to simulate the flux components. The obtained results showed that the temperature-related parameters (e.g., air and soil temperature, vapor pressure deficit) along with the net radiation play key role in determining the flux components in all studied ecosystems. It was confirmed that a chronologic scan of the available patterns is needed for a thorough assessment of the performance accuracy of the local models. The external models provided promising results when compared with the locally trained models. This is a very great step forward in estimating CO₂ flux components under data scarcity conditions.