Application of a process-based model for predicting the productivity of Eucalyptus nitens bioenergy plantations in Spain
Gonzales-Garcia, M and Almeida, AC and Hevia, A and Majada, J and Beadle, C, Application of a process-based model for predicting the productivity of Eucalyptus nitens bioenergy plantations in Spain, Global Change Biology. Bioenergy, 8, (1) pp. 194-210. ISSN 1757-1693 (2016) [Non Refereed Article]
The feasibility of using plantation-grown biomass to fuel bioenergy plants is in part dependent on the ability to predict the capacity of surrounding forests to maintain a sustainable supply. In this study, the potential productivity of Eucalyptus nitens (Deane and Maiden) Maiden plantations grown for bioenergy in a region of north-west Spain was quantified using the 3-PG process-based model. The model was calibrated using detailed measurements from five permanent sample plots and validated using data from thirty-five additional permanent sample plots; both sets represented the variability of climate and soils of the region. Plot scale analysis showed that the model was able to reasonably estimate above-ground biomass and water use when compared with the observed data. Using a representative loam soil characteristic, a spatial analysis was then carried out to predict the potential productivity of E. nitens for bioenergy across a potential area for plantation establishment of 2550 km2 and to evaluate different management scenarios related to rotation length and stocking. An increase of only 1.9% in mean annual increment (MAI) of above-ground biomass (WAGB) was found between stockings of 3000 and 5000 trees ha−1; for the lower stocking, MAI of WAGB increased 4% for rotation lengths between 6 and 8 years. Production was reduced by low summer rainfall and to a lesser extent by high summer and low winter temperatures, and vapour pressure deficit. Above-ground biomass production was higher by around 12% when average rather than actual climate data were applied. The information from this study can be used to optimize forest management, determine regional relative potential productivity and contribute to decision-making for bioenergy production from E. nitens plantations in north-west Spain.