Open access Journal
Evaluating the feasibility of oil palm agroforestry in Harapan Rainforest, Jambi, Indonesia
Forest and Society · Vol. 5 No. 2 (2021) · pp. 458–477
- ISSN
- 2549-4333, 2549-4724
- Published
- 2021-09-05
- Publisher
- Forestry Faculty, Universitas Hasanuddin
- Language
- en
Abstract
About 2.5 million hectares of a total of 15 million hectares of oil palm plantation in Indonesia are planted in, or conflict with, the forest zone. Oil palm plantations face a conflict between socio-economic and ecological issues. This study was conducted in the Harapan Rainforest, Jambi to evaluate the potential of oil palm-based agroforestry to reconcile economic and ecological interests, by considering socio-economic and financial feasibility as well as biodiversity and land cover. The financial feasibility of oil palm agroforestry is compared to oil palm monoculture, employing a discounted cash flow approach using three indicators: net present value (NPV), benefit-cost ratio (BCR), and internal rate of return (IRR). Two ecological indicators—biodiversity and land cover—are evaluated in an experimental plot of oil palm agroforestry in Jambi. This study indicates that the NPV, BCR, and IRR of oil palm monoculture are IDR 62,644,836 (US$ 4,476.84), 1.39, and 20.77%, respectively, while the oil palm agroforestry planted in the experimental plot potentially generates much better values of financial indicators with NPV, BCR, and IRR being IDR 209,221,212 (US$ 14,951.76), 1.79, and 24.42%, respectively. Besides evaluating financial feasibility, we also found that the reviewed current studies indicate that the oil palm agroforestry provides positive ecological impacts, such as increased forest land cover, invertebrate fauna, and bird diversity.
Keywords
Collaboration network of the authors
38 authors · 112 co-authorship links · 38 across different organisations
Hover or tap a name to highlight its co-authors. Double-click to open the author's page.
- IPB University
- Ministry of Environment and Forestry, Republic of Indonesia
- Seoul National University
- University of Leeds
- Wageningen University & Research
- Bandung Institute of Technology
- University of Bengkulu
- Other organisations
- Affiliation unknown
- Different organisations
- Same organisation
- Affiliation unknown
- Thicker line = more joint articles · bigger circle = more articles
Show as table
| Co-author | Organisation | Joint articles |
|---|---|---|
| Annuri Rossita | IPB University | 2 |
| Lars Hein | Wageningen University & Research | 2 |
| Akhmad Riqqi | Bandung Institute of Technology | 2 |
| Dudung Darusman | IPB University | 1 |
| Gusti Hardiansyah | Affiliation unknown | 1 |
| Cecep Kusmana | Affiliation unknown | 1 |
| Muhammad Sheriffdeen | IPB University | 1 |
| Perdinan Perdinan | IPB University | 1 |
| Monica Di Gregorio | University of Leeds | 1 |
| Hariadi Kartodihardjo | IPB University | 1 |
| Handian Purwawangsa | IPB University | 1 |
| Ernan Rustiadi | IPB University | 1 |
| Lala Mulyowibowo Kolopaking | IPB University | 1 |
| Septri Widiono | University of Bengkulu | 1 |
| Ekawati Sri Wahyuni | IPB University | 1 |
| Rhett D. Harisson | Affiliation unknown | 1 |
| Suryanto Suryanto | IPB University | 1 |
| Suria Darma Tarigan | IPB University | 1 |
| Iskandar Zulkarnaen Siregar | IPB University | 1 |
| Irdika Mansur | IPB University | 1 |
| Ishak Yassir | Ministry of Environment and Forestry, Republic of Indonesia | 1 |
| Mangarah Silalahi | IPB University | 1 |
| Agus Wahyudi | Ministry of Environment and Forestry, Republic of Indonesia | 1 |
| Lutfy Abdulah | National Research and Innovation Agency | 1 |
| Soni Trison | Affiliation unknown | 1 |
| Ary Widiyanto | Affiliation unknown | 1 |
| Subarudi | Affiliation unknown | 1 |
| Andrea Emma Pravitasari | IPB University | 1 |
| Rina Mardiana | IPB University | 1 |
| Dwi Suprastyo | Affiliation unknown | 1 |
| Hadi Susilo Arifin | Affiliation unknown | 1 |
| Ni Made Santi | Affiliation unknown | 1 |
Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.