Suitability of the boreal ecosystem simulator (BEPS) model for estimating gross primary productivity in hemi-boreal upland pine forest

Gross Primary Productivity (GPP) is the core component of the terrestrial and global carbon cycle and Earth’s climate research. In this study, GPP estimation was performed with the Boreal Ecosystem Productivity Simulator (BEPS) model to check its performance for hemi-boreal forests on the example of the Soontaga area in Estonia. The model was run by using a combination of remote sensing (leaf area index (LAI), clumping index) and meteorological data inputs (air temperature, global radiation, air humidity, precipitation and wind speed). The results were validated against GPP derived from the available flux tower measurements. The spatial representativeness of the site was evaluated using multiple spatial thresholds (500 m–2 km), as well. We found that the BEPS model can track the GPP changes with the season and inter-annual variation very well in a coniferous hemi-boreal forest, given that good quality input data are provided.