Published July 5, 2023 | Version v1
Dataset Open

Modelling potential growth of forest restoration options in Indonesia

  • 1. International Institute for Applied Systems Analysis
  • 2. National University of Science and Technology MISiS
  • 3. World Agroforestry (ICRAF)

Description

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.

Notes

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.

Files

Fast_commercial_species.zip

Files (378.3 MB)

Name Size Download all
md5:f3d94ac51e27ac3a35892b863d177858
43.9 MB Preview Download
md5:7ed2b288654b6a1ee9876eabf0982ff0
65.2 MB Preview Download
md5:631e0875b75419a6e1ec8b963cacd48a
91.3 MB Preview Download
md5:28bac44503b33bec2628626594ddab9e
84.9 MB Preview Download
md5:f6c409a0dc677818fe33c9912d3820d9
93.0 MB Preview Download