Oil palm plantations have caused approximately 135,000 km2 of forest loss across Southeast Asia, Africa, and South America. While Southeast Asia has the largest extent of plantations, oil palm is expanding across the tropics, with plantation area doubling in the Brazilian Amazon between 2004 and 2010. Although oil palm plantations have caused substantial deforestation, these areas may also increase terrestrial carbon storage when planted in deforested areas, and initial investments in fertilizer and high yield varieties can reduce deforestation pressure on the surrounding forest, improve economic livelihoods and reduce emissions from non-renewable energy sources.
Two models of oil palm cultivation characterize expansion in the Brazilian Amazon, associated with the size of the landholding and initial capital investments. Large areas of cultivation, in which initial capital investments are higher, typically benefit from higher productivity per unit area, resulting in less deforestation pressure on the surrounding forest. Smallholder production is typically less efficient, but may also be associated with less deforestation because these plantations are more likely to occupy areas that were deforested for another purpose such as cropland or pasture. The yield per unit area and the fraction of cultivation area converted directly from forest are two important indicators of the effects of oil palm cultivation on forest loss and economic livelihoods. This study will map the expansion of oil palm in the Brazilian Amazon and compare these data with official statistics on oil palm cultivation area and yield to answer the following research questions:
What fraction of oil palm cultivation in the Amazon comes from deforested areas currently and historically? Has this fraction changed in response to the Program for Sustainable Production of Palm Oil in 2010 and changes in the Forest Code in 2012?
Is palm oil production lower per unit area in municipalities with a greater proportion of smallholder plantations? If so, is this due to variation in suitability for cultivation or differences in initial investments?
Has the proportion of large- and smallholder oil palm cultivation changed in response to greater incentives for smallholders and a reduction in available area suitable for industrial operations?
This study will use remotely sensed data to map the expansion of oil palm in the Brazilian Amazon from 2000 to the present. Methods for automated mapping of oil palm in Southeast Asia will be modified for this study, as previous mapping of oil palm in the region has required substantial user input. The length of time between deforestation and oil palm cultivation will be established to estimate what fraction of oil palm cultivation has been the direct cause of deforestation. Plantation sizes will be determined using an object-based classification, and the fraction of large- and smallholder plantations will be compared with official statistics on palm oil production to determine if municipalities dominated by smallholder plantations are less productive than those with larger, more industrialized operations. Changes in the fraction of smallholder plantations will be compared with the changes in government incentives for palm oil production and the Forest Code (Villela et al. 2014).
Training and Skills
CENTA students are required to complete 45 days training throughout their PhD including a 10 day placement. In the first year, students will be trained as a single cohort on environmental science, research methods and core skills. Throughout the PhD, training will progress from core skills sets to master classes specific to CENTA research themes.
This project will support the development of skills in remote sensing using optical and radar data and geospatial analysis to support sustainable development in areas of high deforestation risk. Fieldwork in selected plantations will inform the analysis of remotely sensed data for inferring and predicting palm oil yield from different types of cultivation. The student will gain skills in written communication through papers published in international scientific peer-reviewed journals, and oral communication through regular presentations and participation in conferences and meetings with project partners and stakeholders.
Year 1: Review of available field based observations and remotely sensed data. Development of a field plan to visit selected plantation areas in conjunction with project partners at SEED and Geospatial Insight. Field data collection at the end of year 1.
Year 2: Incorporation of field-based and remotely sensed data to analyse production efficiency in oil palm cultivation areas of different types. Publication of first paper. Three months working at SEED International.
Year 3: Three months working at Geospatial Insight. Completion of write up and publication of second and third papers, attendance at RSPSoc conference.
Partners and collaboration (including CASE)
Dr Barrett and Prof Page currently supervise CENTA PhD students, and the student will benefit from working with a non-governmental organization, SEED, and an industrial CASE partner, GI. SEED is an environment and development consultancy, focused on the interface of policy and science. GI is a provider of earth observation research, currently involved in the development of methods for detection of oil palm in Southeast Asia directly relevant to this project. SEED and GI are interested in combining field-based observation and remotely sensed data to monitor the expansion of oil palm and associated variability in production efficiency and human wellbeing.
Dr Kirsten Barrett, email@example.com
University of Leicester, UK