- Project Description
- Global demand for edible oils and biofuel has stimulated a rapid agribusiness expansion particularly in palm oil. Since 1990s, Indonesia’s oil palm plantation area increased over 7-fold. As a result, Indonesia now dominates global palm oil export markets. Indonesian Borneo (Kalimantan) is the primary region of current and future plantation expansion. Since 1993, West Kalimantan province is undergoing an extensive forest-agricultural transition with a 40-fold increase (3.7 M ha) in plantation area. Occupying >35% of W.
Kalimantan’s lowlands, land conversion for plantations is the major cause of deforestation and fires generating carbon emissions. With such rapid plantation development, we urgently require studies on oil palm’s effects on fire vulnerability, ecosystem services, and, in particular, rural agrarian communities.
Across Borneo, diverse ethnic communities employ forest product collection, agroforestry, rain-fed “swidden” rice farming with cash income generating activities. Despite centuries long residency, villages do not have formal land tenure nor delineated community lands. Plantation leases (10,000-100,000 ha) are allocated without recognition of villages’ usufructuary rights. Officials assert plantations are established only on “degraded lands”, yet oil palm areas are primarily community-managed lands, logged forests and/or peat with high C stocks. Reducing Emissions from avoided Deforestation and Degradation initiatives provide Indonesia with financial resources to support REDD implementation. With REDD’s promise of C investments that also will “alleviate poverty” and protect biodiversity, oil palm’s contradictory practices require critical examination.
Given local-global factors influencing Bornean plantations, we propose to examine socio-economic and political drivers affecting agribusiness practices and their impacts on rural communities, land use and ecosystems. Our overarching objective is to assess costs and benefits of plantations to diverse constituencies. We seek to: 1) discern the relative importance of drivers affecting plantations and to assess REDD’s potential to alter these drivers; 2) estimate historic and possible future impacts of plantations on ecosystems services - especially C dynamics - through 2020; and, 3) uncover rural agrarian household and community responses to such change and how they alter their livelihood and land use.
With Indonesia’s complex district-level “governance” yet national regulatory control, we apply nested-scale analyses in: i) two focal districts with extensive oil palm, national parks, peat forest and REDD pilot sites; ii) W. Kalimantan (147,000 km2) and, iii) Borneo (780,000 km2). Long-term iterative studies within focal sites generate: 1) valuable insights into dynamic factors that alter land use with field validation; and, 2) “baselines” of communities’ livelihood practices before plantation arrival. Through participatory land use mapping, repeated household interviews with local valuation of trade-offs, we assess livelihood change and project effects of land scarcity with plantation development. With multi-sensor satellite and radar imagery (e.g. Quickbird, Landsat ETM+, MODIS, PALSAR, ENVISAT) combined with diverse modeling and classification approaches (e.g. eCognition, Dynamica Ego, Agent-Based Models), we will develop and validate several local-to-regional socio-economic and ecological scenarios of land use change. A distinctive contribution - critical for REDD - is our refined land use transitions with Tier II-III above- and below ground carbon budgets (e.g. regrowth) for 8-10 land use/cover types (e.g. secondary forests by age, degradation, logging history, heath/peat swamp phasic zones). To evaluate cultural and demographic change across communities, social network analysis is used to assess non-local labor and rural-urban migration. Through such efforts, we aim to produce several useful products for diverse applications and user groups.
Project PI: Lisa Curran/Stanford University
473 Via Ortega, Room 373
Stanford, CA 94305-2034
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