Generalized model for plantation production of Eucalyptus grandis and hybrids for genotype-site-management applications

The use of process-based modelling of wood production in forest plantation has increased in recent decades amongst researchers and forest companies. Although, such models are used by several plantation researchers and managers, improved options and sensitivity to soil characteristics, genotype, and management options are desirable. A new generation of forest productivity modelling needs to extend previous capabilities and incorporate modern software engineering technologies. Our objective was to develop and evaluate an Agricultural Production Systems sIMulator (APSIM) Next Generation model for simulating the growth of Eucalyptus grandis and hybrids with or of E. globulus and E. urophyylla. The model simulates stem, canopy and root development, resource capture and use (light, water, N), and C and N allocation as mediated by climate, soil, genotype physiological characteristics and management. Tree dimensions (stem diameter, height, volume) are calculated as empirical functions of above-ground biomass. Datasets used for model calibration or independent evaluation were from diverse conditions in Australia (5 sites) and Brazil (13 sites), and at several of these sites there were treatments for fertilizer, irrigation or genotype. For the calibration and evaluation datasets, model performance was very good for above-ground biomass (Nash Sutcliffe Efficiency, NSE = 0.96 and 0.84 respectively). Notwithstanding this general performance, and as an example, local calibration improved performance in one of the independent test datasets, suggesting that applications of the model for specific sites or clones may benefit from parameterization to local conditions. Simulation of management for weed cover, N fertilizer and genotype are also demonstrated. As the model performed well and has high flexibility, it warrants consideration by forest plantation managers and researchers for knowledge synthesis and operational productivity predictions of Eucalyptus and other plantation genotypes.