Team Members:
Person Name | Person role on project | Affiliation |
---|---|---|
Laixiang Sun | Principal Investigator | University of Maryland, College Park, College Park, United States |
Matthew Hansen | Co-Investigator | University of Maryland, College Park, College Park, United States |
Günther Fischer | Collaborator | International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria |
Yu XIN | Collaborator | University of Maryland at College Park, College Park, USA |
Palm oil is currently the most consumed edible oil in the world. According to USDA, the worldwide production of palm oil has increased from 15 million tons in 1995 to 63 million tons in 2016. Indonesia and Malaysia have been the biggest suppliers of palm oil since 1966, with the dominant share of 85% in 2016. The plantation of oil palm (monoculture or mixed) amounts to 14 million ha in Indonesia and 7 million ha in Malaysia, which account for 62% and 84% of the total plantation areas in each of these two countries, respectively. The FAO land-cover data show that more than 55% of oil palm expansion during 1990-2005 in these two countries occurred at the expense of natural forests, and the remaining occurred mainly at the expense of existing agricultural land. In an increasingly health-conscious world, global demand for palm oil is bound to increase in the near future as consumers shift towards consumption of vegetable oils containing low trans-fat. An additional driving force for rising demand on global palm oil market is the growing bio-fuel blending demand posed by climate change concerns. A 2015 study of Grand View Research Inc. indicates that the global palm oil market demand is likely to increase to 128 million tons in 2022, with an annual growth rate of 7.5%. The above discussion indicates that there are tough challenges for policymakers and other stakeholders to balance the increased palm oil production in the tropics with the growing concerns on food security, tropical forest protection, and emission from deforestation. To effectively deal with these challenges, we need to have accurate answers to the following questions: (1) What are the spatial and temporal patterns of the oil palm expansion into primary forest in the past? (2) How have the interactions of physical and socioeconomic forces shaped the observed patterns of oil palm plantation? (3) What will be the survival probability of each grid-cell of existing primary forest in the near future?
To answer these research questions, this project is designed around four major objectives: (a) Identify the spatial and temporal patterns of the oil palm expansion into primary forest and other agricultural land in Indonesia and Malaysia. (b) Improve the global agro-ecological zones model GAEZ v4 to produce 1x1km potential yield maps of palm oil and other major agricultural crops for Indonesia and Malaysia, and estimate the annual potential economic benefit of palm oil production and alternative cropping at the 1x1km grid-cell level. (c) Establish an econometric model to quantify the responsiveness of oil palm plantation to the export quantities and prices of oil palm products over the period of 1990-2015, and construct a dynamic recursive model to predict, in a spatially explicit way, future patterns of oil palm plantation as driven by rising international demand, up to 2050. (d) Employ the Cox proportional hazard model (CPHM) to estimate the probabilistic relationship between oil palm expansion into primary forest and international palm oil demands as well as local socioeconomic conditions, and predict the likelihood of oil palm expansion into primary forest across space and over time based on the CPHM-enabled dynamic recursive model. The primary outcomes of this project will be consolidated information and analytical results about the physical and socioeconomic driving forces of oil palm expansion, dynamic relationship between the observed patterns of oil palm plantation and the spatial and temporal variation in the benefits and costs of converting forest to oil palm plantation, and future patterns of oil palm plantation as driven by rising international demand. In addition, our modeling analysis will be able to quantify the competition between palm oil production and traditional food production, thus the extent to which oil palm expansion leads to increased food costs at the subnational level.