Modelling potential growth of forest restoration options in Indonesia

Potential growth of secondary forest and tree species typology were assessed using biophysical productivity model developed by IIASA's Agriculture, Forestry, and Ecosystems Services Group. The methodology involved the integration of random forest algorithm, ground data, remote sensing products, soil properties, and literature on yield tables (more detailed methodology publication in preparation). To calibrate the model, the MODIS NPP dataset was adjusted using forest biomass and land cover maps. The model utilized ERA5-Land monthly averaged meteorological data from 2006 to 2015, with a resolution of 0.1° x 0.1°, in addition to soil properties, land cover, and elevation. This comprehensive approach allowed for the determination of spatially explicit site index values for plantations, secondary forests, and primary forests. The resulting productivity information are reflected in growth curves for both fast and slow-growing commercial species as well as native tree species. The parametrization of Chapman-Richards growth curves was conducted using data from representative tree species available in the literature. In the case of peatland areas, potential growth are also modelled using water regime scenarios provided by IIASA's EPIC model, offering insights into different implications of the potentially varying water table conditions in peatland.Funding acknowledgment: This work was supported by the RESTORE+ project (www.restoreplus.org), which is part of the International Climate Initiative (IKI), supported by the Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection (BMUV) based on a decision adopted by the German Bundestag