Published May 23, 2023 | Version v1
Dataset Open

Dataset for yield and carbon sequestration of main tree crops in Indonesia

  • 1. World Agroforestry (ICRAF), Indonesia
  • 2. International Institute for Applied Systems Analysis

Description

Biophysical productivity of production systems involving oil palm, rubber, cacao, coffee and coconut on mineral soil using the WaNuLCAS model developed by ICRAF. The WaNuLCAS model (van Noordwijk and Lusiana 1999; van Noordwijk et al., 2011) is a generic tree-crop growth model for a wide range of agroforestry systems that considers both aboveground (light) and belowground (soil, water, and nutrients). Yield and carbon sequestration calculation of the corresponding production systems in peatland were developed using a hybrid approach through adjusting results for mineral soil production system with productivity gaps identified through literature review. Finally, land suitability and statistical data analyses were conducted to estimate productivity of sago and pineapple.

The dataset cover current practices and potential management improvements of tree crops cultivation that can increase the benefits to people’s livelihood while contributing to climate change mitigation and biodiversity. Results from this study, in combination with other tree-growth and forest regrowth related information, will provide a comprehensive overview on ecological and economic impact of restoration interventions ranging from improved management to ecological restoration. This dataset was created as a part of the RESTORE+ project. The details are described in a separate document (see https://doi.org/10.5281/zenodo.7937135).

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

treecrop_productivity_long.csv

Files (105.9 MB)

Name Size Download all
md5:44822bfbfba64d7d90ea5f90e000b486
11.8 kB Download
md5:8707b2e735dfe968430fac4b505b89ae
66.4 MB Preview Download
md5:40a4c49926a41ea65577ebd20acfae32
39.5 MB Download