An assessment of high carbon stock and high conservation value approaches to sustainable oil palm cultivation in Gabon

Industrial-scale oil palm cultivation is rapidly expanding in Gabon, where it has the potential to drive economic growth, but also threatens forest, biodiversity and carbon resources. The Gabonese government is promoting an ambitious agricultural expansion strategy, while simultaneously committing to minimize negative environmental impacts of oil palm agriculture. This study estimates the extent and location of suitable land for oil palm cultivation in Gabon, based on an analysis of recent trends in plantation permitting. We use the resulting suitability map to evaluate two proposed approaches to minimizing negative environmental impacts: a High Carbon Stock (HCS) approach, which emphasizes forest protection and climate change mitigation, and a High Conservation Value (HCV) approach, which focuses on safeguarding biodiversity and ecosystems. We quantify the forest area, carbon stock, and biodiversity resources protected under each approach, using newly developed maps of priority species distributions and forest biomass for Gabon. We find 2.7–3.9 Mha of suitable or moderately suitable land that avoid HCS areas, 4.4 million hectares (Mha) that avoid HCV areas, and 1.2–1.7 Mha that avoid both. This suggests that Gabon's oil palm production target could likely be met without compromising important ecosystem services, if appropriate safeguards are put in place. Our analysis improves understanding of suitability for oil palm in Gabon, determines how conservation strategies align with national targets for oil palm production, and informs national land use planning

Effects of Demand-Side Restrictions on High-Deforestation Palm Oil in Europe on Deforestation and Emissions in Indonesia

13-C-AJFF-PU-29, 36This is an open access article under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) license https://creativecommons.org/licenses/by/4.0/. Please cite this article as:Jonah Busch et al 2022 Environ. Res. Lett. 17 014035. https://doi.org/10.1088/1748-9326/ac435eDemand-side restrictions on high-deforestation commodities are expanding as a climate policy, but their impact on reducing tropical deforestation and emissions has yet to be quantified. Here we model the effects of demand-side restrictions on high-deforestation palm oil in Europe on deforestation and emissions in Indonesia. We do so by integrating a model of global trade with a spatially explicit model of land-use change in Indonesia. We estimate a European ban on high-deforestation palm oil from 2000 to 2015 would have led to a 8.9% global price premium on low-deforestation palm oil, resulting in 21 374 ha yr 121 (1.60%) less deforestation and 21.1 million tCO2 yr 121 (1.91%) less emissions from deforestation in Indonesia relative to what occurred. A hypothetical Indonesia-wide carbon price would have achieved equivalent emission reductions at $0.81/tCO2. Impacts of a ban are small because: 52% of Europe\u2019s imports of high-deforestation palm oil would have shifted to non-participating countries; the price elasticity of supply of high-deforestation oil palm cropland is small (0.13); and conversion to oil palm was responsible for only 32% of deforestation in Indonesia. If demand-side restrictions succeed in substantially reducing deforestation, it is likely to be through non-price pathways

What causes deforestation in Indonesia?

We investigate the causes of deforestation in Indonesia, a country with one of the highest rates of primary natural forest loss in the tropics, annually between 2001 and 2016. We use high spatial resolution imagery made available on Google Earth to characterize the land cover types following a random selection of deforestation events, drawn from the Global Forest Change dataset. Notorious in the region, large-scale oil palm and timber plantations together contributed more than two-fifths of nationwide deforestation over our study period, with a peak in late aughts followed by a notable decline up to 2016. Conversion of forests to grasslands, which comprised an average of one-fifth of national deforestation, rose sharply in dominance in years following periods of considerable fire activity, particularly in 2016. Small-scale agriculture and small-scale plantations also contributed one-fifth of nationwide forest loss and were the dominant drivers of loss outside the major islands of Indonesia. Although relatively small contributors to total deforestation, logging roads were responsible for a declining share of deforestation, and mining activities were responsible for an increasing share, over the study period. Direct drivers of deforestation in Indonesia are thus spatially and temporally dynamic, suggesting the need for forest conservation policy responses tailored at the subnational level, and new methods for monitoring the causes of deforestation over time

Effects of demand-side restrictions on high-deforestation palm oil in Europe on deforestation and emissions in Indonesia

Demand-side restrictions on high-deforestation commodities are expanding as a climate policy, but their impact on reducing tropical deforestation and emissions has yet to be quantified. Here we model the effects of demand-side restrictions on high-deforestation palm oil in Europe on deforestation and emissions in Indonesia. We do so by integrating a model of global trade with a spatially explicit model of land-use change in Indonesia. We estimate a European ban on high-deforestation palm oil from 2000 to 2015 would have led to a 8.9% global price premium on low-deforestation palm oil, resulting in 21 374 ha yr(-1) (1.60%) less deforestation and 21.1 million tCO(2) yr(-1) (1.91%) less emissions from deforestation in Indonesia relative to what occurred. A hypothetical Indonesia-wide carbon price would have achieved equivalent emission reductions at $0.81/tCO(2). Impacts of a ban are small because: 52% of Europe's imports of high-deforestation palm oil would have shifted to non-participating countries; the price elasticity of supply of high-deforestation oil palm cropland is small (0.13); and conversion to oil palm was responsible for only 32% of deforestation in Indonesia. If demand-side restrictions succeed in substantially reducing deforestation, it is likely to be through non-price pathways

Impacts of current and projected oil palm plantation expansion on air quality over Southeast Asia

Over recent decades oil palm plantations have rapidly expanded across Southeast Asia (SEA). According to the United Nations, oil palm production in SEA increased by a factor of 3 from 1995 to 2010. We investigate the impacts of current (2010) and near-term future (2020) projected oil palm expansion in SEA on surface–atmosphere exchange and the resulting air quality in the region. For this purpose, we use satellite data, high-resolution land maps, and the chemical transport model GEOS-Chem. Relative to a no oil palm plantation scenario (∼ 1990), overall simulated isoprene emissions in the region increased by 13 % due to oil palm plantations in 2010 and a further 11 % in the near-term future. In addition, the expansion of palm plantations leads to local increases in ozone deposition velocities of up to 20 %. The net result of these changes is that oil palm expansion in SEA increases surface O₃ by up to 3.5 ppbv over dense urban regions, and in the near-term future could rise more than 4.5 ppbv above baseline levels. Biogenic secondary organic aerosol loadings also increase by up to 1 µg m⁻³ due to oil palm expansion, and could increase by a further 2.5 µg m⁻³ in the near-term future. Our analysis indicates that while the impact of recent oil palm expansion on air quality in the region has been significant, the retrieval error and sensitivity of the current constellation of satellite measurements limit our ability to observe these impacts from space. Oil palm expansion is likely to continue to degrade air quality in the region in the coming decade and hinder efforts to achieve air quality regulations in major urban areas such as Kuala Lumpur and Singapore.National Science Foundation (U.S.) (AGS- 1238109

Reconciling Oil Palm Expansion and Climate Change Mitigation in Kalimantan, Indonesia

<div><p>Our society faces the pressing challenge of increasing agricultural production while minimizing negative consequences on ecosystems and the global climate. Indonesia, which has pledged to reduce greenhouse gas (GHG) emissions from deforestation while doubling production of several major agricultural commodities, exemplifies this challenge. Here we focus on palm oil, the world’s most abundant vegetable oil and a commodity that has contributed significantly to Indonesia’s economy. Most oil palm expansion in the country has occurred at the expense of forests, resulting in significant GHG emissions. We examine the extent to which land management policies can resolve the apparently conflicting goals of oil palm expansion and GHG mitigation in Kalimantan, a major oil palm growing region of Indonesia. Using a logistic regression model to predict the locations of new oil palm between 2010 and 2020 we evaluate the impacts of six alternative policy scenarios on future emissions. We estimate net emissions of 128.4–211.4 MtCO₂ yr^-1 under <i>business as usual</i> expansion of oil palm plantations. The impact of diverting new plantations to low carbon stock land depends on the design of the policy. We estimate that emissions can be reduced by 9-10% by extending the current moratorium on new concessions in primary forests and peat lands, 35% by limiting expansion on all peat and forestlands, 46% by limiting expansion to areas with moderate carbon stocks, and 55–60% by limiting expansion to areas with low carbon stocks. Our results suggest that these policies would reduce oil palm profits only moderately but would vary greatly in terms of cost-effectiveness of emissions reductions. We conclude that a carefully designed and implemented oil palm expansion plan can contribute significantly towards Indonesia’s national emissions mitigation goal, while allowing oil palm area to double.</p></div

What Is Threatening Forests in Protected Areas? A Global Assessment of Deforestation in Protected Areas, 2001–2018

The protection of forests is crucial to providing important ecosystem services, such as supplying clean air and water, safeguarding critical habitats for biodiversity, and reducing global greenhouse gas emissions. Despite this importance, global forest loss has steadily increased in recent decades. Protected Areas (PAs) currently account for almost 15% of Earth&rsquo;s terrestrial surface and protect 5% of global tree cover and were developed as a principal approach to limit the impact of anthropogenic activities on natural, intact ecosystems and habitats. We assess global trends in forest loss inside and outside of PAs, and land cover following this forest loss, using a global map of tree cover loss and global maps of land cover. While forests in PAs experience loss at lower rates than non-protected forests, we find that the temporal trend of forest loss in PAs is markedly similar to that of all forest loss globally. We find that forest loss in PAs is most commonly&mdash;and increasingly&mdash;followed by shrubland, a broad category that could represent re-growing forest, agricultural fallows, or pasture lands in some regional contexts. Anthropogenic forest loss for agriculture is common in some regions, particularly in the global tropics, while wildfires, pests, and storm blowdown are a significant and consistent cause of forest loss in more northern latitudes, such as the United States, Canada, and Russia. Our study describes a process for screening tree cover loss and agriculture expansion taking place within PAs, and identification of priority targets for further site-specific assessments of threats to PAs. We illustrate an approach for more detailed assessment of forest loss in four case study PAs in Brazil, Indonesia, Democratic Republic of Congo, and the United States

Average propensity scores within areas of predicted expansion.

<p>The ratio of change in average propensity score to emissions reductions is calculated as the difference between the average propensity score relative to the BAU scenario divided by the difference between the average CO₂ emissions relative to the BAU scenario.</p><p>* Negative value results from an estimate increase in GHG emissions in the permit constrained scenario when area increases to 3.6 Mha. Uncertainty estimates include 95% confidence intervals derived from bootstrapping.</p><p>Average propensity scores within areas of predicted expansion.</p

Probability of Oil Palm Plantation Expansion in Kalimantan under six alternative expansion scenarios.

<p>Probability of Oil Palm Plantation Expansion in Kalimantan under six alternative expansion scenarios.</p