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Environmental Impacts of Tropical Soybean and Palm Oil Crops

Summary and Keywords

Oil crops play a critical role in global food and energy systems. Since these crops have high oil content, they provide cooking oils for human consumption, biofuels for energy, feed for animals, and ingredients in beauty products and industrial processes. In 2014, oil crops occupied about 20% of crop harvested area worldwide. While small-scale oil crop production for subsistence or local consumption continues in certain regions, global demand for these versatile crops has led to substantial expansion of oil crop agriculture destined for export or urban markets. This expansion and subsequent cultivation has diverse effects on the environment, including loss of forests, savannas, and grasslands, greenhouse gas emissions, regional climate change, biodiversity decline, fire, and altered water quality and hydrology. Oil palm in Southeast Asia and soybean in South America have been identified as major proximate causes of tropical deforestation and environmental degradation. Stringent conservation policies and yield increases are thought to be critical to reducing rates of soybean and oil palm expansion into natural ecosystems. However, the higher profits that often accompany greater yields may encourage further expansion, while policies that restrict oil crop expansion in one region may generate secondary “spillover” effects on other crops and regions. Due to these complex feedbacks, ensuring a sustainable supply of oil crop products to meet global demand remains a major challenge for agricultural companies, farmers, governments, and civil society.

Keywords: oil palm, oilseed, South America, Southeast Asia, land use change, deforestation, conservation, water, climate change, commodity


Oil crops, valued for their oils and amino acids, and are quite diverse. They range from annual crops such as sunflowers, to legumes such as peanuts and soybeans, to perennials including oil palm and olives. During the late 20th and early 21st centuries, the oil crop sector expanded rapidly, with particularly high growth rates in oil palm and soybean markets. Harvested area for these two crops increased by 3–6% per yr-1 from 2000 to 2014 (Figure 1), compared to substantially slower growth rates among other major oil crops (FAO, 2016). Future growth in the global area of all crops, projected to range from 2 to 10 million km2 (Tilman, Balzer, Hill, & Befort, 2011), is expected given increasing demand for food, feed, and biofuels from a growing and increasingly urban and wealthy world population (Hertel, 2011). These newly wealthy are expected to demand more calories, especially as cooking oils (Kearney, 2010).

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Figure 1. Soybean and oil palm total global harvested area from 1990 to 2014 (FAO, 2016).

Oil palm and soybean are demanded by global markets due to their versatility as precursors to or sources of diverse products including vegetable oils and fats, packaged foods, animal feeds, soaps, biofuels, and chemicals used in industrial processes. Palm oil is especially desirable because it is one of the few vegetable fats that is semi-solid at room temperature (Klonoff, 2007). Termed the “oil crop revolution,” expansion of oil palm and soybean is considered distinct from the Green Revolution because it has occurred mainly within rainfed regions in the tropics and primarily serves export markets (Byerlee, Falcon, & Naylor, 2016). Expansion into tropical forests and carbon-rich peat soils, development of genetically modified soybean varieties resistant to herbicides, and land tenure conflicts with local communities have spurred substantial concern over the impacts of these crops on the environment and society (McCarthy, Vel, & Afiff, 2012; Oliveira & Hecht, 2016). This article reviews trends in expansion of soybean and oil palm within tropical regions, the environmental impacts of production of these crops, and policies and practices that may mitigate these negative environmental outcomes.

Soybean Production and Demand

Soybean (Glycine max) is an annual legume native to East Asia that is widely believed to have been domesticated from wild soybean (Glycine soja) in China around 6,000 to 9,000 years ago (Sedivy, Wu, & Hanzawa, 2017). Soybean cultivars have since been adapted to many latitudes, including temperate to equatorial regions. Although considered an oil crop, the bean contains more protein (40%) than oil (20%). Thus, the major use of soybean is as animal feed, especially for pork and chicken production, which nearly quadrupled between 1990 and 2010 (FAO, 2016). For instance, Brazil’s burgeoning chicken industry is a major driver of demand in South America (Garrett & Rausch, 2016). Global demand has supported high soybean prices despite soybean area expansion, fueling continuing soybean plantings throughout the tropics. While the United States has been the global leader in soybean production since the mid-20th century, in 2014 Brazil, Argentina, and India together contained more than 50% of global soybean harvested area, and have experienced rapid expansion in harvested area (5% to 9% yr-1 from 2000 to 2014) compared to the United States (just 1% over the same period) (Figure 2) (FAO, 2016). China is the fourth largest producer of soy, but the country’s soybean harvested area has declined since around 2010 (FAO, 2016; Hairong, Yiyuan, & Bun, 2016).

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Figure 2. Soybean and oil palm harvested area and yield in year 2014 (FAO, 2016), across the nine leading countries (in terms of harvested area) and the rest of the world (ROW).

Land preparation for soybean production involves commercial timber removal if such trees are present, followed by cutting, leveling, and/or burning of remaining vegetation. Land is often graded to improve water distribution and ploughed to loosen the soil. In the initial years of soybean planting, nitrogen-fixing inoculants are often added to ensure that new soybean plants develop nodules to support these symbiotic bacteria (Hungria & Vargas, 2000). Thus, soybean requires low or zero inputs of N fertilizer but high levels of P and K. For instance, nutrient-poor soils of the Brazilian Cerrado require more than 80 kg ha-1 (Garrett et al., 2013b). To avoid soybean rust (Phakopsora sp.), a major threat to soybean production in South America, most Brazilian states have developed mandatory “soybean free” sanitation periods in the three months prior to the first planting to reduce the risk of the rust surviving in the field. While this sanitation period has reduced rust occurrence, heavy application of fungicides needed to prevent the disease costs the industry roughly US$2 billion each year (Godoy et al., 2016). Other major threats to soybean include cyst nematodes that attack soybean roots and aphids that eat soybean leaves. Typically, herbicides are applied before soybean seeds are sown to eliminate and retard any weed growth, while insecticides and fungicides are applied to leaves as needed. Conservation tillage is prevalent in South America but comprises less than 30% of the cropland area in United States, and conventional tillage is common elsewhere (Carvalho et al., 2013; Derpsch, Friedrich, Kassam, & Li, 2010).

Soybean is typically grown either in a continuous sequence or in a rotation with other crops (e.g., corn or wheat). In regions with warm temperatures and sufficient water inputs throughout the year (e.g., the humid tropics), this rotation occurs intra-annually, and farmers may grow soybean twice or even three times each year as a food crop or for seeds. In temperate and dry climates, rotation occurs over multiple years. As an annual crop, the exact timing of soybean planting and harvest depends on weather patterns. For example, in the northern United States, soybean is planted after the snow melts, while in the center-west of Brazil production begins at the onset of the rainy season. Due to these dependencies, soybean is vulnerable to changes in climate including those that alter the timing of precipitation (Cohn, VanWey, Spera, & Mustard, 2016). Soybean yields increase with warmer temperatures until about 30°C, after which they decline rapidly (Schlenker & Roberts, 2009).

In South America, soybean has been planted in the Atlantic Forest and Pampas grassland ecosystems, including parts of Argentina, Brazil, and Paraguay, since the early 1900s (Oliveira, 2016). Soybean area expanded rapidly across the Brazilian Cerrado savanna in the 1960s and 1970s as a result of heavy governmental investment leading to the development of new soybean cultivars and modernization of the farming sector (Spehar, 1995). Expansion in the Cerrado continues at a breakneck pace, particularly in the Brazilian states of Maranhão, Piauìí, Tocantins, and Bahia (Gibbs et al., 2015; Noojipady et al., 2017a; Spera et al., 2016). In the early 2000s, changes in technology and capital inflows in the Cerrado catalyzed development in the Amazon humid tropical forest (Morton et al., 2006). Since the introduction of several environmental governance mechanisms (State and Corporate Environmental Governance section), expansion of soybean area into these humid forests slowed after 2006 (Macedo et al., 2012; Nepstad et al., 2014). Nevertheless, during the 2000s, soybean area continued to expand into forests in the Bolivian Amazon and Chaco and Chiquitano regions of Argentina, Bolivia, and Paraguay (Gasparri, Grau, & Angonese, 2013).

These patterns of expansion were influenced by myriad factors including macroeconomic context (e.g., export taxes, exchange rates), government investments (e.g., tax breaks, subsidized credit), climate change in the form of changing precipitation, and technological change (e.g., new cultivars, no-till planting) (Hecht & Mann, 2008; Hillman & Faminow, 1987; Oliveira, Costa, Soares, & Coe, 2013). Tele-couplings with other regions and agricultural commodities were also critical (Gasparri & Waroux, 2015; Liu et al., 2013). For instance, in the United States soybean production declined as a result of biofuels policies that incentivized farmers to plant more corn (Gelfand et al., 2011), driving up soybean prices and likely stimulating soybean expansion in other world regions (Laurance, 2007; Searchinger et al., 2008). Since 1990 demand growth in China has been by far the largest driver of soybean expansion in South America (Oliveira & Schneider, 2016).

Soybean yields vary greatly across major global soybean production regions. Although yields vary substantially within countries, in 2014, Indian soybean farms achieved the lowest average yields (1.0 ton ha-1), while the United States had the highest yields (3.2 tons ha-1) (FAO, 2016). Argentina, Brazil, and Paraguay all had similar and relatively high yields (2.8–2.9 tons ha-1), while yields in China fell somewhere in the middle (1.8 tons ha-1) (FAO, 2016). Yields have been increasing rapidly in Brazil, Argentina, the United States, and parts of India, suggesting potential for further yield advances in these regions (Figure 3) (Ray, Mueller, West, & Foley, 2013).

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Figure 3. Soybean and oil palm fresh fruit bunch average global yields from 1990 to 2014 (FAO, 2016).

Soybean production in South America occurs on thousands of individual farms ranging from 50 to more than 10,000 hectares (Figure 4) (IBGE, 2006; Leguizamón, 2014). Despite a wide range of farm sizes, technology is largely similar across farms, with equally high P and K fertilizer application rates and similar cultivars (Garrett & Rausch, 2016). Most production is grown with commercial rather than subsistence farming systems and farmers typically sell beans either to a trader or a farmers’ cooperative, who then sells the beans to food and energy manufacturers (Garrett et al., 2013b). In some cases, farmers sell directly to local biodiesel or livestock production facilities. In other parts of the world such as India and China, farm sizes are smaller and soybean may be produced for local human consumption (Garrett et al., 2016).

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Figure 4. Soybean farm in Mato Grosso, Brazil. (Credit line: Rachael Garrett).

Oil Palm Production and Demand

Oil palm (Elaeis guineensis) in a perennial palm that originated in West Africa, where it has been an important resource for the last 5,000 years (Sowunmi, 1999). Oil palm trees produce both palm kernels and palm oil. Palm kernels are mainly destined for animal feed and industrial products, while about 75% of palm oil is used for food (Byerlee et al., 2016). Bleached and deodorized palm oil is the primary source of cooking oil for much of Asia, including Indonesia and India (FAO, 2016), and makes up a substantial portion of edible oil consumption in Europe and China. In 2013 India, Indonesia, the European Union, and China consumed more than 50% of the world’s palm oil (FAO, 2016).

The palm thrives in locations with consistently high rainfall (more than 2 m yr-1), warm mean annual temperatures (20–32°C), and high solar radiation (Corley & Tinker, 2003). Thus, oil palm’s most suitable habitat is humid lowland tropical forests near the equator. In West Africa, oil palm is traditionally grown in groves that range from semi-wild patches in secondary forest to more managed areas in and around villages (Gerritsma & Wessel, 1997). Oil palm was first commercially cultivated in Indonesia starting in 1911. Since that time, Southeast Asia has evolved into a hotspot of palm oil production, with Indonesia and Malaysia supplying more than 80% of all palm oil in 2014 (Figure 2) (FAO, 2016). Unlike traditional oil palm cultivation in Africa, oil palm in Southeast Asia is typically grown in monotypic stands planted with high-yielding varieties (Barcelos et al., 2015). Here, most production occurs on industrial-scale plantation estates held by large companies that average around 10,000 hectares per plantation (Figure 5) (Carlson et al., 2013). Smallholders also cultivate oil palm, and hold around 40% of all oil palm lands in Indonesia, 13% in Malaysia, and more than 70% in Thailand and Papua New Guinea (Colchester et al., 2011). While smallholders may either be associated with a corporate estate or function as independent growers, even independent smallholders frequently hold contracts with particular mills or middlemen who buy their fresh fruit bunches (McCarthy & Zen, 2016).

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Figure 5. Oil palm plantation in West Kalimantan, Indonesia. (Credit line: Kimberly Carlson).

In industrial-scale plantations, land preparation for initial oil palm planting involves removal of commercial timber, cutting and sometimes burning of existing vegetation, stacking residues in rows, and construction of drainage canals, roads, and other infrastructure to allow for efficient fruit harvest. Seed germination is conducted in highly controlled conditions, and germinated seeds are then planted in polyethylene bags in a nursery. After one to two years in the nursery, seedlings are permanently transplanted to the plantation. Leguminous cover crops are typically used in young oil palm stands to improve soil quality and prevent erosion. Throughout the oil palm life cycle, pesticides, herbicides, and fertilizers (e.g., compound NPK) are applied as needed to control weeds and pests, and to maintain plant productivity (Corley & Tinker, 2003). At the age of around three years, harvest of fresh fruit bunches begins. These fruits are used for their oily outer layer (mesocarp, which produces palm oil) and their oil-rich palm kernel (endosperm). Fresh fruit bunches are manually harvested and then transported to a nearby mill, where they are processed into crude palm oil (CPO) and palm kernels. Oil palm fruits degrade quickly after harvesting, and must be processed to CPO as soon as possible (e.g., less than 24 hours) after harvest to maintain high oil quality. Most commercially grown oil palm has an economic lifespan of about 25 to 30 years, after which time it is replanted. Re-planting decisions depend on the current price of palm oil and other economic factors. Some plantations in Malaysia have successfully been replanted three times (Basiron, 2007). One of the greatest barriers to continued cultivation over multiple rotations is Ganoderma boninense, a fungus that leads to basal stem rot and palm depth, which may be enhanced if dead oil palm stems are left on the plantation rather than burned or removed (Susanto, Sudharto, & Purba, 2005). After processing at the mill, CPO and palm kernels are transported to regional domestic or international processing facilities, where they are converted to myriad food and non-food products.

While Indonesia and Malaysia have established themselves as leaders in oil palm production, tropical regions outside of Southeast Asia have also experienced growth in the oil palm sector. In the Americas, Peru and Guatemala have the world’s fastest-expanding oil palm areas, with approximately 25% annual growth rates in harvested area from 2010 to 2014 (FAO, 2016). Although Brazil’s climate and topography are deemed suitable for high-yield oil palm production (Butler & Laurance, 2009; Pirker, Mosnier, Kraxner, Havlík, & Obersteiner, 2016; Vijay, Pimm, Jenkins, & Smith, 2016), most of the country’s oil palm is produced in just one state, Pará, with additional small-scale cultivation for local use by Afro-Brazilian communities in northeast Brazil. Oil palm is also present and expanding in Colombia, Ecuador, Mexico, and Costa Rica, which all have annual 2010 to 2014 harvested area growth rates of 9% or greater (FAO, 2016). While African countries remain important producers of palm oil especially for local markets, the region contributed only 6% of global production increases from 2000 to 2013, and African oil palm yields are substantially lower than in other major palm-producing regions (FAO, 2016; Ordway, Asner, & Lambin, 2017). However, Africa is predicted to become a new frontier of industrial oil palm expansion due to rural labor and land availability (Côte d’Ivoire et al., 2016).

Oil palm has high caloric yields, which are substantially greater than soybean and other leading oil crops (Carlson et al., 2017). While profits from oil palm production vary widely based on the location, cost of land, type of production, global market price, and other variables, these high yields contribute to a large profit margin for producers (Byerlee et al., 2016). Yet, static oil palm yields, which have averaged around three tons CPO ha-1 yr-1 since the mid-2000s (Figure 3) (Woittiez, van Wijk, Slingerland, van Noordwijk, & Giller, 2017) are a major challenge to the oil palm industry. Yields vary widely across countries and producers. For instance, in 2013 Malaysia had yields of around 4.2–4.5 tons ha-1 yr-1, while Ghana’s yields were around 0.30–1.1 tons ha-1 yr-1 (Woittiez et al., 2017). These average yields stand in contrast to observed maximum yields of 10 tons ha-1 yr-1, and estimated yield potentials of 11–18 tons ha-1 yr-1 (Barcelos et al., 2015). Oil palm’s long breeding cycle (10–12 years) and large land requirements for field trials mean that development of high yield varieties is slower than that for annual crops such as corn and soybean (Singh et al., 2013). With the sequencing of the oil palm genome completed in 2013 (Singh et al., 2013), major yield improvements are expected. Long-term future yield improvements are likely to come from advancements in propagation technologies that would allow for production of planting material from high yield individuals, changes in oil palm architecture to allow for more efficient harvesting, and reduction of post-harvest losses during transport and storage. In the near-term, providing smallholder farmers with access to high quality planting material, fertilizers, and other inputs used in commercial plantations, and training on best management practices, is likely to produce the greatest gains in oil palm yields, with possible co-benefits for human livelihoods through higher farm incomes (Woittiez et al., 2017).

Environmental Impacts of Production

Oil palm and soybean share prominence as rapidly growing edible oil commodities that are linked to deforestation. One report suggested that oil palm and soybean together were responsible for around 10% of tropical deforestation from 2000 to 2012 (Henders, Persson, & Kastner, 2015). This measure excludes indirect land use change, such as soybean expansion into pasture and subsequent displacement of deforestation for cattle production into the Amazon forest (Arima, Richards, Walker, & Caldas, 2011; Lapola et al., 2010; Macedo et al., 2012). Thus, oil palm and soybean have also been targets of non-governmental organization campaigns that vilified their production in tropical regions (Walker, Patel, Davies, Milledge, & Hulse, 2013). Campaigns have focused on how expansion has destroyed tropical forests, reduced biodiversity and harmed endangered species, contributed to greenhouse gas (GHG) emissions and climate change, and marginalized local communities. A large literature has developed around these and less “news-worthy” but nevertheless substantial and complex effects of soybean and oil palm expansion and cultivation on the natural environment and human well-being (Brando, Coe, DeFries, & Azevedo, 2013; Goldsmith & Cohn, 2017; McCarthy et al., 2012). This section reviews these documented impacts and identifies uncertainties and future research questions and needs. The analysis relies largely on comparisons between intact or relatively undisturbed tropical forests and soybean farms and oil palm plantations, because most research has focused on such contrasts rather than on comparisons between human-dominated land uses.

Natural Ecosystem Loss

Sources of land for commodity crop expansion are determined by a complex set of biophysical, socioeconomic, and political factors that vary widely across commodities and regions (Meyfroidt et al., 2014). A common framing for environmental concerns regarding oil palm and soybean expansion is the conversion of humid tropical forests to these commodity crops. While both commodities have been major proximate causes of tropical forest loss at specific times and places, land covers converted to oil palm and soybean vary widely across space and time.

In the early 2000s, soybean expansion was identified as a major and direct cause of deforestation in the Brazilian Amazon. Estimates suggest that around 25% to 30% of all soybean expansion occurred directly through forest clearing (Gibbs et al., 2015; Macedo et al., 2012; Morton et al., 2006). At this time, Brazil had the highest absolute tropical forest loss of any country (Hansen et al., 2013). In response to these high deforestation rates, in the mid-2000s the Brazilian government established several new policies to reduce deforestation, followed by the introduction of voluntary commitments by major soybean traders to not source products from land that had been deforested after July 2006, an intervention known as the “Soybean Moratorium” (Gibbs et al., 2015). Combined with a reduction in soybean profitability, these restrictions on forest conversion led to a sharp decline in forest clearing for soybean production (Nepstad et al., 2014). Since 2006, most deforestation in the humid Amazon has been linked to expansion of cattle pasture (Macedo et al., 2012), although soybean encroachment into pasturelands is considered to be an indirect driver of this deforestation (Arima et al., 2011; Barona, Ramankutty, Hyman, & Coomes, 2010).

Compared to the Brazilian Amazon, restrictions on natural ecosystem clearing tend to be lower in other parts of South America, including the Cerrado savanna of Brazil and the Gran Chaco dry forests of Bolivia, Paraguay, Brazil, and Argentina (Garrett et al., 2016; le Polain de Waroux, Garrett, Heilmayr, & Lambin, 2016). In these regions, soybean has continued to clear natural ecosystems (Figure 6) (Grau, Aide, & Gasparri, 2005; le Polain de Waroux et al., 2016; Noojipady et al., 2017a). For instance, around 21% of crop expansion in the Brazilian Cerrado biome from 2003 to 2013 was sourced from forests or woodlands, rather than pasture (Noojipady et al., 2017a). Under projected demand for soybean and other commodities, combined with a continuation of “business as usual” protections for these ecosystems, a third of the remaining Cerrado vegetation is anticipated to be cleared by 2050 (Strassburg et al., 2017). Soybean is also expanding into natural ecosystems other world regions including the prairies of the United States (Wright & Wimberly, 2013) and Southern Africa’s dry forests and savannas (Gasparri et al., 2016).

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Figure 6. Deforestation from expansion of oil palm in Indonesia’s Papua Province (A/B, 2001–2017) and soybean in Paraguay (C/D, 2013–2015). Imagery was taken by Landsat 7 (A) and Landsat 8 (B-C) satellites, and is displayed as SWIR-NIR-Red = red-green-blue.

Deforestation in Southeast Asia, the center of global oil palm production, has increased since the early 2000s (Figure 6) (Hansen et al., 2013; Margono et al., 2012). Several studies have examined the role of oil palm plantation expansion in this forest loss. In Borneo, Gaveau et al. (2016) found that from 1973 to 2015, industrial plantations, including oil palm plantations, expanded into areas that had recently been old-growth forest at a rate of 60% in Malaysia and 15% in Indonesia. Austin et al. (2017) reported that the percentage of new large-scale oil palm expansion clearing forests in Indonesia decreased from 54% in the late 1990s to just 18% from 2010 to 2015. An Indonesian-wide study suggested that oil palm contributed to about 15% of all forest loss from 2000 to 2010 (Abood, Lee, Burivalova, Garcia-Ulloa, & Koh, 2014). Less work has quantified the relative contributions of different actors engaged in deforestation. While several datasets of industrial-scale palm oil are now available (Austin et al., 2017; Carlson et al., 2013; Gaveau et al., 2016; Gunarso, Hartoyo, Agus, & Killeen, 2013; Petersen et al., 2016), mapping smallholder oil palm plantations is far more challenging because these farms are small in size (e.g., 1–2 hectares) and may be mixed with non-oil palm crops in agroforestry systems. In Sumatra, Lee et al. (2014) attributed around 11% of 2000 to 2010 forest loss in Sumatra to smallholdings, with the remainder of deforestation occurring within concessions held by private corporations and the government. Outside of Southeast Asia, the degree of oil palm expansion into forests has generally been much lower (Vijay et al., 2016). For instance, Furumo and Aide (2017) found that 79% of oil palm expansion in Latin America replaced “previously intervened lands,” especially pasturelands.


Conversion of natural vegetation to commodity crops usually leads to biodiversity declines, and under certain conditions may lead to species extinctions. Since tropical forests harbor high numbers of species (“richness”), as well as endemic species at high risk of extinction (Gardner et al., 2009; Spahni et al., 2011), tropical deforestation is of particular concern. Pesticide and herbicide use associated with intensive crop production may also affect biodiversity (Schiesari et al., 2013). While a large literature on interactions between oil palm agriculture and biodiversity has emerged, and research in the Amazon region has generated significant advances in understanding biodiversity persistence in fragmented tropical landscapes (Barlow et al., 2007; Moura et al., 2013; Peres et al., 2010), almost no work has specifically addressed how soybean agriculture affects biodiversity. Thus, this section focuses on oil palm.

Oil palm plantations hold less than half as many vertebrate species as primary forests and have lower species richness than logged or secondary forests (Fitzherbert et al., 2008), although plantation species richness and abundance may remain high for some taxa (Foster et al., 2011). Conversion of forest to oil palm reduces functional diversity (Edwards, Edwards, Hamer, & Davies, 2013), which is likely to affect the ecosystem services provided by plantations. The relative effects of oil palm development on biodiversity are dependent on the land cover present before conversation to oil palm. Oil palm plantations in Malaysian Borneo retained less functional biodiversity than logged forests (Edwards et al., 2013). Work in Colombia indicates that oil palm plantations retain significantly greater biodiversity across multiple taxa than cattle pastures, which suggests that conversion of certain land cover types to oil palm may benefit biodiversity (Gilroy et al., 2015). In Southeast Asia, much oil palm development occurs at the expense of jungle rubber and community agroforests (Carlson et al., 2012). While rubber stand management practices—expected to affect biodiversity in rubber stands—vary widely, several studies suggest that rubber supports at least as much species richness as oil palm plantations for taxa including bats, primates, birds, and ants (Fitzherbert et al., 2008; Peh et al., 2006; Room, 1975).

The spatial configuration of commodity crop expansion and natural ecosystem retention has important implications for biodiversity (Chaplin-Kramer et al., 2015). Work in both Southeast Asia and Amazonia suggests that landscape configurations that maintain large contiguous tracts of forest, rather than small patches or narrow riparian areas, have the greatest biodiversity benefits (Edwards et al., 2010; Lees & Peres, 2008; Lucey et al., 2016). While riparian corridors and other connected forest fragments may support habitat connectivity, research in Malaysia indicates few spillovers of rainforest-dependent species to surrounding oil palm areas (Gray, Simmons, Fayle, Mann, & Slade, 2016; Lucey et al., 2016). Thus, conservation of large connected forest patches appears most critical for biodiversity. Some authors have suggested that “intelligent manipulation” of habitat complexity in and around oil palm plantations may also benefit agro-ecological function (Foster et al., 2011). Specifically, maintaining biodiverse forest fragments near oil palm plantations may lead to higher yields, potentially due to the biological control benefits of these non-oil palm lands (Gérard et al., 2017; Nurdiansyah, Denmead, Clough, Wiegand, & Tscharntke, 2016). The critically endangered orangutan (Pongo sp.), endemic to Borneo and Sumatra, has been the focus of much conflict between the oil palm industry and conservationists. While deforestation and poaching have led to sharp orangutan population declines (Gaveau et al., 2009; Wich et al., 2016), these primates have been observed traveling through and nesting within mature oil palm plantations near remnant forest patches (Ancrenaz et al., 2015), adding further evidence to support efforts to maintain forest fragments in and around plantations. Ongoing experiments that manipulate cropland-forest landscapes to assess ecosystem function within these matrices are critical to inform corporate and government policies that shape the configuration and balance of forest and non-forest lands (Fayle et al., 2015).


Land cover change and agricultural production can affect climate through biogeochemical (e.g., GHG emissions) or biophysical (e.g., albedo, evaporation) effects. Globally, agriculture is estimated to contribute about 20% to 30% of total GHG emissions, if upstream and downstream emissions, such as fertilizer manufacture, food waste, and transport to markets are considered (Vermeulen, Campbell, & Ingram, 2012). These emissions contribute to GHG concentrations in the atmosphere, which lead to global warming, ocean acidification, and climate change.

The expansion of croplands into humid tropical forests is associated with a large net flux of carbon to the atmosphere due to the loss of vegetative carbon and soil carbon, and several groups have estimated these emissions across regions of soy and oil palm expansion (Table 1). As described in the Natural Ecosystem Loss section, direct expansion of soybean into Amazon forests has declined substantially since the early 2000s, and is therefore associated with relatively small direction GHG emissions. In the Brazilian Cerrado, where clearing for soybean expansion has been a leading cause of deforestation (Morton et al., 2016; Spera et al., 2016), cropland expansion from 2003 to 2013 totaled more than 90,000 km2, and was associated with average forest carbon emissions of 59 Tg CO2 yr-1 (Noojipady et al., 2017a). In the Chaco, where soybean is a leading crop driving agricultural expansion, Baumann et al. (2017) estimated net biomass emissions of 27–39 Tg CO2 yr-1 from conversion of approximately 30,000 km2 of forest and grazing land to cropland from 2001 to 2013. They also found 21 Tg CO2 yr-1 emissions from soils over the same period.

Table 1. Carbon Dioxide Emissions from Oil Palm and Soybean Expansion



Time Period


Converted Area (km2 yr-1)

Emissions (Tg CO2 yr-1)








Noojipady et al., 2017b







Baumann et al., 2017







Baumann et al., 2017

Oil Palm






Carlson et al., 2013

Oil Palm

Indonesia, Papua New Guinea, Malaysia





Agus et al., 2013

Industrial oil palm plantation expansion in Southeast Asia has led to massive carbon emissions from the clearance of humid tropical forests. Yet, conversion of pasturelands, croplands, and what some call “degraded” lands to oil palm may lead to net carbon sequestration because oil palm itself stores substantial carbon. In Indonesian Borneo, Carlson et al. (2013) reported that 23,380 km2 of oil palm expansion from 2000 to 2010 generated 92 Tg CO2 yr-1 of net carbon emissions associated with, including loss of biomass carbon from land clearing and sequestration in palm oil plantations. Agus et al. (2013) use a similar methodology to estimate net carbon emissions across Indonesia, Papua New Guinea, and Malaysia of 109 Tg CO2 yr-1 from 2000 to 2010 (59,400 km2 oil palm expansion).

While the effects of conversion from natural vegetation to oil palm and soybean on live vegetation carbon are relatively straightforward to measure, and will likely become more accurate with the use of direct measurements of forest structure enabled by advanced remote sensing techniques (e.g., airborne light detection and ranging), measuring soil carbon fluxes soil carbon stocks is more complex. Soil carbon stocks depend on relative changes in soil carbon inputs (e.g., agricultural residues) and losses (e.g., erosion), which change over time and depend on management practices (e.g., tillage, oil palm frond recycling) and initial conditions (e.g., land cover). Measuring these fluxes is experimentally challenging (Crow et al., 2016), and comparisons between land covers often rely on space-for-time substitutions.

Thus, the effects of oil palm and soybean expansion on soil carbon are highly context-dependent and somewhat unclear. Oil palm plantations have very high rates of net primary production, yet much of this carbon is harvested in the form of fresh fruit bunches rather than recycled to the soil (Kotowska, Leuschner, Triadiati, & Hertel, 2016) and erosional carbon losses are substantial (Guillaume, Damris, & Kuzyakov, 2015). A large pantropical study sampling to 3 m soil depth found that deforestation for oil palm plantations led to a 45% reduction in soil organic carbon (van Straaten et al., 2015). However, several studies in South America and Southeast Asia that sampled to 0.3 m depth suggest carbon neutrality or even net sequestration upon conversion of forest or grassland to oil palm (Frazão, Paustian, Pellegrino Cerri, & Cerri, 2013; Goodrick et al., 2015; Khasanah, van Noordwijk, Ningsih, & Rahayu, 2015). Yet, these studies only sampled surface soils, and may have missed changes in carbon dynamics in deeper soils that could substantially affect soil carbon balance (Don, Schumacher, & Freibauer, 2011). Research in Brazil indicates that relative to other land covers including forest, savanna, and pasture vegetation, full tillage soybean systems have reduced carbon storage, but that the use of no-till planting and rotations with grazed pastures and forages may increase soil carbon stocks relative to continuous tillage monocultures (Garrett et al., 2017; Maia, Ogle, Cerri, & Cerri, 2010; Miranda, Carmo, Couto, & Camargo, 2016; Silva Figueira, Davidson, Nagy, Riskin, & Martinelli, 2016). While Cerrado soils contain significant amounts of carbon, conversion to intensive agriculture such as no-till soybean appears to have a relatively small effect on these soil carbon stocks (Batlle-Bayer, Batjes, & Bindraban, 2010). However, soil carbon estimates for different tillage regimes vary widely due to differences in soil carbon measurement and co-management factors.

In addition to emissions upon land conversion to oil palm or soy, both commodities produce ongoing emissions of N2O from nitrification and denitrification in soils associated with N fertilizer application. These emissions are estimated to be relatively lower for soybean in comparison to oil palm. Soybean fixes N and therefore receives low to zero N fertilizer inputs. Global circa 2000 soybean N fertilizer application rate averaged 29 kg ha-1, in comparison to 56 kg ha-1 for oil palm (Gerber et al., 2016; Mueller et al., 2012). Nevertheless, due to soybean’s much larger harvested area, in 2000 soybean cultivation worldwide emitted around 8.4 Tg CO2e yr-1, and oil palm 2.7 Tg CO2e yr-1 (Carlson et al., 2017).

Oil palm cultivation also generates CO2 emissions from draining organic peatland soils in Southeast Asia, and CH4 emissions from decomposition of palm oil mill effluent (POME). Emissions from draining peatlands for industrial-scale oil palm plantations in Indonesia and Malaysia were estimated to total about 172 Tg CO2 yr-1 in 2015 (Miettinen, Hooijer, Vernimmen, Liew, & Page, 2017; Miettinen et al., 2016). Taylor et al. (2014) found that in 2014, POME emissions totaled around 135 Tg CO2e yr-1, and may reach 1% of anthropogenic GHG emissions by 2050 given expected increases in palm oil production. POME also offers an opportunity to generate biogas for energy generation, but by 2014 less than 5% of palm oil mills had adopted technologies to capture methane and use it as energy (Taylor et al., 2014).

Land cover change also has substantial biogeophysical impacts on regional climate (Feddema et al., 2005). The Brazilian Amazon, and by extension soybean, has received much attention when it comes to the biogeophysical impacts of tropical crop production. This research focus grew out of the Large Scale Biosphere-Atmosphere (LBA) Experiment in Amazonia, an international research initiative from 1995 to 2005 led by Brazil. Macro-scale modeling studies indicate that large-scale deforestation in the Amazon causes increased surface temperatures, and decreased precipitation and evaporation (Bonan, 2008; Swann, Longo, Knox, Lee, & Moorcroft, 2015). While mechanisms underlying these responses involve increased albedo, changes in latent/sensible heat flux, and surface roughness, effects vary among agricultural land covers (Sampaio et al., 2007; Silvério et al., 2015). Conversion of forest to soybean appears to have a larger impact on local climate than conversion to pasture, due to the very high albedo of soybean (Costa et al., 2007; Sampaio et al., 2007). However, interactions between patch size, pattern of deforested areas, and total area deforested are complex, and thus deforestation may lead to regional rainfall gains under certain conditions (Da Silva & Avissar, 2006). Additional research is also needed to assess the effects of large-scale oil palm plantation expansion on local climate. Since oil palm is a perennial evergreen crop while soybean is an annual crop (Fan et al., 2015), the effects of oil palm expansion on local climate may be distinct from those of soybean (Lawrence & Vandecar, 2015).

Changes in climate from land conversion to oil crops affect natural ecosystems and human well-being. Some studies suggest that changes in local climate in the Amazon may promote widespread, frequent wildfires and forest dieback to cause a major shift in vegetation (Cochrane & Barber, 2009; Phillips et al., 2009). Climate change from tropical deforestation also has direct impacts on agricultural production. A model of future land use change that links yields to changes in climate indicates that deforestation due to agricultural expansion may reduce soybean yields in the Amazon by up to 25% to 60% by 2050 (Lawrence & Vandecar, 2015; Oliveira et al., 2013). The ability of farmers in the Amazon to grow more than one crop in a single year may be affected by changes in the timing of precipitation (Cohn et al., 2016; Pires et al., 2016). Tropical land cover change may also affect climate and agricultural production outside of the tropics (Lawrence & Vandecar, 2015).

Peatland Drainage

Most oil palm plantations occur in Southeast Asia, a region that also contains extensive deposits of organic soils known as “peatlands.” These peatlands developed due to changes in sea level, and are estimated to store around 11% to 14% of the global carbon soil carbon pool (Page, Rieley, & Banks, 2011b). In their natural waterlogged state, peatlands typically accumulate carbon over time because the rate of decomposition is lower than the rate of organic matter input. In recent years, these carbon rich soils have been drained to support a variety of agricultural and timber activities, including oil palm plantations (Carlson et al., 2013; Carlson et al., 2012; Koh, Miettinen, Liew, & Ghazoul, 2011; Miettinen et al., 2012). Satellite-based estimates suggest that in 2015, about 20% of peatlands in insular Southeast Asia had been converted to oil palm (Miettinen et al., 2016). Oil palm requires root aeration for ideal growth, and therefore these peatlands are drained to depths of between 50 and 100 cm to accommodate the needs of the crop (Carlson, Goodman, & May-Tobin, 2015b). Thus drained, peatlands begin to release their long-stored carbon. While estimates of the net impact of peatland drainage for oil palm on carbon emissions vary widely and losses depend on soil chemistry, drainage depth, fertilizer inputs, and life stage of the plantation, currently available studies suggest that net CO2 emissions are somewhere between 29–81 tons CO2 ha-1 yr-1 (Carlson et al., 2015b; Couwenberg & Hooijer, 2013; Hergoualc’h & Verchot, 2013; Intergovernmental Panel on Climate Change (IPCC), 2013; Page et al., 2011a). Given the wide range of these estimates and the growing need to accurately account for land-based emissions under climate agreements, better understanding of the controls on carbon flux from peatlands is required (Carlson et al., 2015b). In addition to affecting the global climate, peatland drainage also leads to land subsidence and may contribute to eventual flooding and loss of land when combined with sea level rise (Sumarga, Hein, Hooijer, & Vernimmen, 2016; Wösten, Ismail, & vanWijk, 1997). Finally, drained peatlands pose a high risk of fire during droughts (Page et al., 2009).

While researchers and governments are working together to devise solutions to restore peatlands (Graham, Giesen, & Page, 2017), the unique hydrology of large peat domes, combined with the likelihood of fire in drained peat, poses major challenges to restoration efforts. Thus, preventing further development of peatlands is considered to be a more feasible way to prevent the carbon emissions, subsidence, fire risk, and other negative effects associated with peatland use for oil palm (Wijedasa et al., 2017). Much work is still needed to assess the extent and characteristics of peatlands across the tropics, which is a necessary (but insufficient) step toward developing policies that would prevent further draining of these soils for oil palm and other agricultural land uses. Recent research presents promising techniques for predicting the locations of peat deposits, and include modeling approaches, mapping deposits using remotely sensed imagery, and detecting peat drainage canals (Dargie et al., 2017; Gumbricht et al., 2017; Luscombe et al., 2016).


Fire may be used to convert woody vegetation to soybean farms and oil palm plantations and during ongoing management of oil palm plantations. Use of fire in land clearance is beneficial for cultivation because it releases nutrients to the soil and reduces or eliminates the need for manual removal of woody debris, which can be costly (Simorangkir, 2007). Croplands also affect fire dynamics off-site and indirectly, through edge effects and impacts on local climate as described in the “Climate” section. In both the Amazon and Southeast Asia, fire incidence is linked to El Niño Southern Oscillation (ENSO) events when cold sea surface temperatures surround Indonesia and warm waters occur in the eastern Pacific Ocean. Interactions between oil crop-driven land use and land cover change, crop management, and regional precipitation have resulted in years with severe burning events in both South America and Southeast Asia (Alencar, Nepstad, & Diaz, 2006; Aragao et al., 2008; Field et al., 2009).

The use of fire is ubiquitous in soybean expansion in South America (DeFries et al., 2008; Malhi et al., 2008). Emissions of particulate matter from these fires have substantial negative impacts on human health. Deforestation fires contributed almost 3,000 annual premature deaths in South America from 2002 to 2011 (Reddington et al., 2015). Such emissions also contribute to global warming (DeFries et al., 2008). Forests near soybean fields may be drier and more susceptible to fire (Balch et al., 2015), and understory fire can promote invasion of grasses into forests (D’Antonio & Vitousek, 1992; Silvério et al., 2013). In the early 2000s in Amazonia, more than 40% of all fires detected using the MODIS satellite sensors were associated with deforestation, some of which was due to soybean expansion directly into forests (Morton et al., 2008; Morton et al., 2006). While the occurrence of fire has declined in Brazil and across much of South America since the mid-2000s, fire rates remain strongly associated with deforestation, including clearing for pasture and agriculture including soybean (Chen et al., 2013; Reddington et al., 2015).

Burning for oil palm expansion and within established plantations in Indonesia has captured global attention and is used in civil society campaigns against palm oil companies (Greenpeace, 2016; Simons, 1998). Beyond their association with ENSO events, fires in Kalimantan and Sumatra are linked to positive Indian Ocean Dipole (IOD) events, when western Indian Ocean waters are anomalously warm (Field et al., 2009). During ENSO and/or IOD events, the region receives little to no rainfall for multiple consecutive months, which increases the flammability of fuel sources by reducing their moisture content (Cochrane, 2003). Indonesia experienced major fire events in 1997 and 1998, 2006, and 2015, all related to ENSO and/or IOD (Chen, Lin, Yu, & Lo, 2016; Field et al., 2016; van der Werf et al., 2008). Burning of aboveground biomass and peat substrate releases large quantities of CO2 into the atmosphere (van der Werf et al., 2008; Yin et al., 2016), which contributes to global warming. Toxic smoke and haze from these fires affects the local environment and the larger region including Singapore and Peninsular Malaysia (Lee et al., 2016). One model estimated that the 2015 event led to more than 100,000 excess deaths in Indonesia, Malaysia, and Singapore (Koplitz et al., 2016). Moreover, re-distribution of nutrients via biomass burning may affect nutrient-limited ecosystems such as peatlands (Ponette-González et al., 2016). Some evidence suggests that even in non-ENSO years, short-lived droughts and associated fires can generate substantial smoke and haze episodes (Gaveau et al., 2014).

After the 1997 and 1998 fires, the oil palm industry in Indonesia was implicated as a major source of fire ignitions (Dauvergne, 1998). Oil palm plantations are indeed one source of fire ignitions and emissions, although their contribution varies across time, administrative boundaries, and ecosystems (Cattau et al., 2016; Marlier et al., 2015; Noojipady et al., 2017b; Ponette-González et al., 2016). For instance, Marlier et al. (2015) found that oil palm concessions in Kalimantan contributed about 18% of total PM2.5 fire emissions in 2006 and covered 16% of land area; in contrast, oil palm concessions in Sumatra accounted for just 4% of these emissions and covered 7% of the land area. In a peatland area of Central Kalimantan, Cattau et al. (2016) found that while ignition density of fires within oil palm plantations was similar to ignition density in non-forest areas, only about 10% of fires escaped from oil palm plantations.

The use of fire for forest clearing is prohibited under Indonesian law (Herawati & Santoso, 2011), and many larger oil palm companies now claim to use zero-burn methods when clearing and planting (Padfield et al., 2016). Nevertheless, fire is still used by many growers during oil palm development and cultivation, including to clear vegetation for initial planting, to remove ground cover and manage for pests during cultivation, and to sterilize organic materials before replanting to avoid harmful pests. Accidental fires also occur within plantations and can destroy mature palms, new plantings, and peat soil substrate. Therefore, companies and landholders take measures to prevent fires within their planted areas. As described in the Peatland Drainage section, drainage of peatlands for plantation development is another risk factor, as dry peatlands contain substantial amounts of combustible organic matter (Page et al., 2009). While Indonesia signed the 2002 Association of Southeast Asian Nations (ASEAN) Agreement on Transboundary Haze in 2014, the catastrophic fire and haze event of 2015 suggests that the country still lacked the capacity to effectively prevent and control fires. The oil palm industry faces government-levied fines, prosecution, loss of market share, and reputational risk from burning, which land users must balance against the potential economic benefits of fire use (Chisholm, Wijedasa, & Swinfield, 2016; Dauvergne, 1998; Lee et al., 2016; Simorangkir, 2007).

Hydrology and Water Quality

Expansion and cultivation of oil palm and soybean have important effects on water quality, which is mediated by water flux into and out of croplands. Conversion of tropical forest to agriculture tends to increase total stream water discharge, largely due to reduction in evapotranspiration from vegetation loss (Bruijnzeel, 2004). As a result, in the Brazilian Amazon, soybean watersheds have three to four times greater mean water yields than forested watersheds (Dias, Macedo, Costa, Coe, & Neill, 2015; Hayhoe et al., 2011; Riskin et al., 2017). Moreover, water export from soybean watersheds in the Amazon had greater seasonal variability in comparison with forests, likely because trees can access water stored in deep soil during dry periods, while soybean plants only have access to shallow soil water (Hayhoe et al., 2011). In Peninsular Malaysia, deforestation for oil palm plantation development led to an increase in water export over the short term, although as plantations matured this effect attenuated (Department of Irrigation and Drainage, 1989). Few other field-based investigations have examined the impacts of oil palm plantation development—including replanting and regrowth—on stream water fluxes, a clear avenue for future research (Comte et al., 2012). Differences in streamflow due to land use change will likely affect downstream ecosystems and communities, potentially through flooding and more variable water availability. Increased streamflow variability in the Amazon may alter the viability and life span of existing and planned hydroelectric dams (Castello & Macedo, 2015; Finer & Jenkins, 2012; Lima et al., 2014).

One of the most consistently reported impacts of soybean and oil palm agricultural land use on aquatic ecosystems is stream warming. Streams draining soybean farms and oil palm plantations in the humid tropics are 3–4°C warmer than those draining similar forested areas (Carlson et al., 2014; Luke et al., 2016; Macedo et al., 2013). Loss of riparian vegetation that shaded streams, and land surface warming in the cropland itself, are implicated in these temperature increases. While the effects of stream warming on aquatic ecosystem function remain understudied, this warming combined with predicted temperature increases due to climate change are likely to alter stream processes including metabolism, fish survival, and stream susceptibility to invasion (Kaushal et al., 2010).

Stream sediment yields increase with forest conversion to agriculture (Douglas, 1999; Hunter & Walton, 2008). For instance, in Indonesian Borneo, sediment export from a recently cleared oil palm plantation (<3 year old palms) was significantly greater than from nearby forests (Carlson et al., 2014). After agricultural development, sediment dynamics depend on management and biogeophysical factors. Due to introduction of glyphosate-resistant soybean varieties, soybean fields in Brazil are frequently prepared using no-till techniques, reducing soil disturbance and potential sediment and nutrient export (Riskin et al., 2017). Intercropping with corn, and use of cover crops with no-till practices, helps retain soils and reduce runoff from soybean fields during the off-season (Merten, Araújo, Biscaia, Barbosa, & Conte, 2015). Oil palm’s perennial nature means that soil disturbance around palms is typically low except during initial planting and replanting activities, although dense road networks in commercial plantations—required to harvest fresh fruit bunches and maintain palms—are a major source of sediment to streams (Carlson et al., 2014). While sediment concentrations measured in streams draining soybean fields in Brazil were similar to those in forests (Riskin et al., 2017), mature oil palm plantations had greater sediment concentration and yield than forested areas (Carlson et al., 2014; Nainar, Bidin, Walsh, Ewers, & Reynolds, 2017). Elevated sediment export implies loss of soil and nutrients, which can reduce agricultural productivity. Moreover, sediments can accumulate in streambeds and behind impoundments, affecting stream morphology and navigability, and the viability of dams (Clark, 1985). Finally, sediments may affect coastal ecosystems, coral reefs, and stream biota via smothering and light attenuation (Tulloch et al., 2016).

Studies reporting nutrient export from soybean and oil palm croplands to streams note few if any changes in stream nutrient concentrations in commodity dominated watersheds. In Indonesia, Comte et al. (2015) reported that due to oil palm’s high nutrient uptake, appropriate fertilization practices at the study site, and high dilution of nutrients, mature oil palm plantations did not contribute to stream eutrophication. Luke et al. (2016) found that streams draining oil palm watersheds had higher nitrate and lower phosphate levels than forested watersheds. Yet, they noted that these nutrient concentrations were well below pollution thresholds. In the Brazilian Amazon, Neill et al. (2013) found no differences in concentrations of nitrate and phosphate between forest and soybean streams, due to soil chemical properties that lead to rapid binding of P into forms that are not readily available to plants and retard the rate of N loss. Similarly, Riskin et al. (2017) reported that solute concentrations for major nutrients (N, P, K) remained similar across forest and soybean streams in the Brazilian Amazon. Nevertheless, studies on the nutrient impacts of soybean production in the Amazon are limited to a few isolated study sites, and the long-term impacts of high fertilizer P inputs remain poorly understood. Maintenance of riparian buffers, often in accordance with local laws and regulations, is expected to mitigate increases in temperature and sediment and nutrient input to streams (Carlson et al., 2015a). These buffers shade streams and reduce sediment and nutrient inputs.

In addition to the effects of agricultural land use on water, processing of oil palm may also impact water quality. Fresh fruit bunches are converted to crude palm oil in mills located in or near oil palm plantations. This process releases POME, an acidic wastewater that contains high levels of oil and grease, nutrients, and other pollutants (Poh, Yong, & Chong, 2010). When released into water bodies, POME is quickly decomposed, leading to oxygen depletion and negative impacts on biota and malodorous emissions from anaerobic decomposition. In the 1970s, discharge of POME by palm oil mills was a leading source of pollution in Malaysia. The Malaysian government, through regulations levied on the palm oil industry (Department of Environment, 2010), incentivized development of wastewater treatment systems including anaerobic digestion tanks and ponds, along with alternative uses for POME such as fertilizer, that substantially reduced this problem (Vincent, 1993). Commercial oil palm growers follow industry standards for POME treatment by installing anaerobic digesters at their mills, and must abide by often strict requirements for minimum water quality standards in their discharges to water bodies. Moreover, as ponding systems to treat POME generate high levels of methane emissions, some mills have developed methane capture systems in order to take advantage of this energy source (Taylor et al., 2014). However, small artisanal mills that are commonly used in Africa are still problematic, since they are largely unregulated and discharge wastes directly to nearby environments (Kim, Kim, Madhavan, & Suarez, 2013; Nkongho, Nchanji, Tataw, & Levang, 2014).

Genetic Modification

The vast majority of the soybean produced in North and South America is genetically modified (GM) (Garrett et al., 2013a). However, GM soybean cultivars are not currently permitted for use in China or India (Wong & Chan, 2016). In contrast, no GM oil palm varieties are commercially produced. Starting in the mid-1990s, herbicide tolerant soybean—adapted for application of glyphosate, a broad-spectrum herbicide—became commercially available. A review of the impacts of herbicide resistance on yields indicates that herbicide resistant soybean tends to have yields that are similar to or greater than conventional varieties due to improved weed control (National Academies of Sciences, 2017). If producers apply recommended levels of herbicide, use of GM soybean may reduce the number and toxicity of herbicides applied in soybean fields (Qaim & Traxler, 2005), although total herbicide application has not declined with use of GM soybean (National Academies of Sciences, 2017).

Still, GM crops present several environmental risks. Continuous application of a single herbicide without other methods of weed control may result in increasing prevalence of weed species that are not sensitive to the herbicide applied, and a reduction in beneficial plants (National Academies of Sciences, 2017; Pleasants & Oberhauser, 2013). Moreover, weed resistance to glyphosate has become increasingly common around the world (Heap, 2014), and scientific understanding of the best methods to delay evolution of weed resistance is still limited (National Academies of Sciences, 2017). Due in part to uncertainty about the long-term environmental impacts of GM crops, cultivation and consumption of GM soybean remains highly controversial.

Opportunities and Challenges

Given these often large tradeoffs between commodity crop production and natural ecosystem function (West et al., 2014), and the highly complex multi-scalar dynamics of the global food system, ensuring sustainable agricultural production and food security are grand challenges of the 21st century (Foley et al., 2011). As globally traded, rapidly expanding crops with major environmental impacts and clear economic benefits to producing and importing countries, oil palm and soybean exemplify these challenges. This section briefly outlines recent successes and key barriers to effectively addressing the negative environmental impacts of soybean and oil palm production. Here, broader scale state and corporate governance efforts and unanticipated spillover effects from effective policy implementation, rather than farm or plantation level dynamics, are considered.

State and Corporate Environmental Governance

Many undesirable environmental outcomes including biodiversity loss, GHG emissions, and water quality degradation occur upon conversion of natural ecosystems to commodity crops. In response to these issues, and international and/or civil society pressure and incentives, many governments and corporations have developed policies that aim to reduce expansion of oil palm and soybean into tropical forests, woodlands, savannas, and grasslands.

State-led policy mixes can be highly effective at reducing commodity crop deforestation especially when they combine multiple synergistic policies and conditions (Lambin & Meyfroidt, 2011; Nolte, de Waroux, Munger, Reis, & Lambin, 2017). For instance, Brazil has undertaken a multi-pronged Plan for the Prevention and Control of Deforestation in the Amazon that includes protected area expansion, restrictions on agricultural credit in locations with high deforestation rates, and greater enforcement of requirements that landowners maintain a portion of their property in natural vegetation (e.g., 80% in the Amazon). Enforcement of these conservation policies relies on several complementary interventions, including the creation of a rural land registry, remotely sensed maps of forest loss to identify properties out of compliance with deforestation regulations, and restrictions on credit for landholders who deforested illegally (le Polain de Waroux et al., 2017; Nepstad et al., 2014). As discussed in the Natural Ecosystem Loss section, deforestation for soybean in the Brazilian Amazon declined sharply in the mid-2000s, a dynamic that is strongly linked to the synergy between these government policies and the introduction of voluntary efforts by traders and processers not to source soybeans from farms deforested after July 2006 (Gibbs et al., 2015; Nepstad et al., 2014). However, deforestation rates increased from 2015 to 2016, potentially due to changes in environmental governance, macroeconomic drivers, and climatic conditions that promote fire (Tollefson, 2016).

In contrast, Indonesia’s efforts to reduce deforestation from commodity crop expansion have led to few quantifiable changes in forest loss rates. In 2011 the president of Indonesia placed a moratorium on the allocation of licenses for new concessions on land designated as primary forest or peatland (Sloan, 2014). Concurrently, however, the government enacted policies encouraging development of all lands, including forests, within allocated concessions (Republic of Indonesia, 2014), and continues to maintain an attitude of secrecy around datasets of leased lands (Sloan, 2014). Enforcement of environmental regulations in the plantation sector remains problematic (McCarthy & Zen, 2010; Obidzinski, Andriani, Komarudin, & Andrianto, 2012). Indonesia experienced steadily increasing deforestation rates from 2000 to a maximum in 2012, the year after the moratorium was put into place (Hansen et al., 2013; Margono et al., 2012), and more recent measures suggest near-peak deforestation rates in 2014 and 2015 (Wijaya, Juliane, Firmansyah, & Payne, 2017).

In oil palm and soybean supply chains, large multinational trading companies wield considerable power, creating new opportunities to impose environmental restrictions on producers outside of or in addition to state channels. These nodes of power are viewed by environmental NGOs as “leverage points” for generating on-the-ground changes in environmental practices, particularly in regions where state efforts and capacity to promote conservation are limited (Newton, Agrawal, & Wollenberg, 2013). Of 566 companies tracked by Forest Trends’ Supply Change initiative in 2016, 66% have made some level of commitment to sustainable sourcing or no deforestation supply chains (McCarthy & Zen, 2016). Especially in the oil palm sector, some corporations are applying third-party sustainability certification systems to avoid natural ecosystem conversion. In 2014 about 20% of all global palm oil was certified by the Roundtable on Sustainable Palm Oil (RSPO), but less than 1 percent of soybean was certified by the Round Table on Responsible Soy (RTRS) (Garrett et al., 2016). Certified producers must conform to set of principles and criteria, including the protection of primary forests and High Conservation Value (HCV) areas. During the certification process, HCVs are identified and mapped by auditors, and if a plantation or farm remains certified, these HCVs should be protected. RTRS and RSPO certification systems also address other environmental concerns, ranging from water quality to compliance with local laws and regulations. NGOs and industry representatives claim that certification can boost yields due to its focus on best management practices (Levin et al., 2012).

Spillover Effects

Even when state regulations or voluntary efforts are effective in reducing deforestation for the target crop in a specific region, these policies may generate secondary “spillover” effects that challenge their overall effectiveness. First, regulations restricting expansion may incentivize investments in non-land inputs (e.g., fertilizers, seeds, machinery) and lead to improved yields. If these investments are costly, this may spare land locally. However, if improved yields are generated by a technological change that reduces the costs of non-land inputs, intensification may actually lead to increased expansion into natural systems due to higher profitability, the rebound effect known as “Jevon’s Paradox” (Angelsen, 2010; Burney, Davis, & Lobell, 2010).

Second, if investments needed to improve yields within the region where the policy is applied are too costly, policy implementation could lead to the displacement or “leakage” of land use change to another location, commodity, activity, or actor (Boucher & Elias, 2013; Meyfroidt et al., 2014). Leakage may span scales from highly local (e.g., a household shifting its labor from land clearing for crops to cattle in response to a policy encouraging no further crop expansion) (Delacote & Angelsen, 2015) to international (e.g., substitutions in land use across countries as the result of a policy change in one country) (Searchinger et al., 2008). Leakage has been hypothesized through retrospective modeling in the oil palm sector (Busch et al., 2015). Work on the cattle sector in the South American Chaco suggests that leakage may occur in regions with lower enforcement and fewer regulations governing forest land clearing (i.e., “deforestation havens”) (le Polain de Waroux et al., 2016). Nevertheless, evidence of wide-scale leakage from increases in conservation restrictions in the Brazilian Amazon to less regulated regions of South America remains limited (le Polain de Waroux et al., 2017; le Polain de Waroux et al., 2016) and displacement of demand remains challenging to measure empirically.

Third, policies that single out a specific crop or land use may lead to indirect land use change. In Brazil, policies supporting ethanol production led to increases in sugarcane planted area, which may have displaced soybean production into regions with native vegetation (Lapola et al., 2010). In much of South America the dynamics of soybean expansion are tightly linked with cattle ranching, such that soybean generally expands onto existing pastures and pushes the cattle frontier further into the forest (Arima et al., 2011; Barona et al., 2010; Gasparri & Waroux, 2015).

In sum, when conservation policies result in yield increases, they may help “spare” land for nature and biodiversity by meeting commodity demand using a smaller amount of land (Phalan, Onial, Balmford, & Green, 2011). Evidence suggests that historical yield improvements have led to substantial land sparing globally (Burney et al., 2010). However, the overall impacts depend on the costs of these yield increases, feedbacks with global demand, differences in the stringency of conservation policies across regions, the ease with which actors and capital can move between regions, and the abundance of suitable alternative land for production (Atmadja & Verchot, 2012).


Oil palm and soybean systems share several commonalities regarding their environmental impacts in the tropics. While oil palm has been associated with direct forest clearing in Southeast Asia, soybean contributes to deforestation indirectly via linkages with cattle ranching in South America. Natural ecosystem clearing leads to large carbon emissions from live biomass associated with land clearing, while effects on soil carbon sequestration are highly dependent on management practices, preceding land use, and environmental conditions. Oil palm plantations harbor significantly less biodiversity than surrounding forests, and the same is true for soybean farms. Changes in water flux and increases in stream warming are common across both oil palm and soybean systems, although there is less evidence that these land uses affect stream nutrient concentrations. Soybean in South America and oil palm in Southeast Asia are associated with fire, which generates smoke that contributes to human mortality. Oil palm is also linked to peatland drainage, which generates GHG emissions and land subsidence. As a perennial tree crop, it is likely that oil palm’s effects on local climate are low in comparison to soybean, although this is a clear avenue for future research. The long-term impacts of genetically modified soybean in South America remain largely unknown, but weed resistance to glyphosate is an issue of increasing concern.

Oil crops will continue to be demanded by a growing and more affluent global population. Given the interconnected nature of the global land system, simply avoiding new plantings of crops such as oil palm and soybean that are environmentally harmful is unfeasible. This approach is unlikely to reduce the environmental impact of agriculture, because demand will likely be met by in other world regions or by expansion of other crops (Carrasco, Larrosa, Milner-Gulland, & Edwards, 2014; Villoria, Golub, Byerlee, & Stevenson, 2013). Instead, diverse and creative approaches that mitigate the impacts of oil crops on the environment, while being appropriate for local socioeconomic objectives, are required.

To better inform policies and practices that promote oil crop production with fewer negative environmental impacts, this literature review reveals several needed directions for future studies. For instance, most research to date focuses on contrasts between natural ecosystems and croplands, yet these crops are often developed from other agricultural land uses. Thus, how do non-intact land uses (e.g., soybean versus cattle pasture) differentially affect environmental outcomes? How does an economically viable yet diversified oil crop system compare to prevalent monoculture systems? Several environmental governance efforts, including zero-deforestation commitments by corporations and third-party certification systems, have emerged. How effective are these efforts, and what are the unanticipated spillover effects generated from such policy implementation? Much research focus regarding land use has been on industrial-scale actors, especially in the oil palm sector. What is the role of different actors (e.g., smallholder farmers) in land clearing, and how might environmental governance differentially affect these actors? Addressing these questions will inform effective environmental policy and on-farm practices for soybean and oil palm commodity crop production.

This review also indicates that several farm- or plantation-scale remedies for improving environmental outcomes are available. For soy, no-till cultivation and rotation with grazed forages can have positive effects on soil carbon sequestration and result in reduced erosion rates (Carvalho et al., 2010). In smallholder oil palm areas, large yield gaps may be addressed through access to improved planting material, appropriate fertilizers, and training in best management practices. In soy, production increases will likely rely less on closing yield gaps, and more on expansion that occurs on already-cleared lands such as pasture or other types of cropland. Yield increases achieved through additional inputs of fertilizer, pesticides, and herbicides may spare land for nature at a global level with potential local environmental degradation. Avoiding peatlands in new oil palm plantings and eliminating fire use for land preparation and replanting would reduce GHG emissions and have positive human health outcomes. Changes in water quality and hydrology are more difficult to address but could be partly mitigated by use of riparian buffers. Achieving these farm-level outcomes is likely to require synergistic changes in government and corporate policy to incentivize improved outcomes. To achieve global reductions in deforestation for oil crop expansion, policies that address deforestation must consider spillovers and rebound effects.


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