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Fostering a climate-smart intensification for oil palm


Oil palm production in Indonesia illustrates the intense pressure that exists worldwide to convert natural ecosystems to agricultural production. Oil palm production has increased because of expansion of cultivated area rather than due to average-yield increases. We used a data-rich modelling approach to investigate how intensification on existing plantations could help Indonesia meet palm oil demand while preserving fragile ecosystems. We found that average current yield represents 62% and 53% of the attainable yield in large and smallholder plantations, respectively. Narrowing yield gaps via improved agronomic management, together with a limited expansion that excludes fragile ecosystems, would save 2.6 million hectares of forests and peatlands and avoid 732 MtCO2e compared with following historical trends in yield and land use. Fine-tuning policy to promote intensification, along with investments in agricultural research and development, can help reconcile economic and environmental goals.

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Fig. 1: Yield gaps for oil palm in Indonesia.
Fig. 2: Projected trends in mature oil palm area, average actual yield, and production in Indonesia.
Fig. 3: Cumulative land conversion and GWP associated with different scenarios of intensification and land use change.

Data availability

The data on yield potential and yield gaps that support the findings of this study are publicly available via the Global Yield Gap Atlas website ( Source data are provided with this paper.


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We are thankful to the personnel at the former International Plant Nutrition Institute (South East Asia Office) and a number of private plantation companies (SMART PT, Asian Agri, Lonsum and Wilmar) for providing productivity and management data from a number of well-managed blocks across the Indonesian archipelago for model calibration and testing. We are also grateful to large plantations and smallholder farmers’ associations, non-governmental organizations and the Research Center for Climate Change at Universitas Indonesia (RCCC-UI) for their support to the project and useful discussions. We also thank J. Matthews (formerly R&D Head at PT Bumitama Gunajava Agro) and T. Fairhurst (Tropical Crops Consultants Limited) for useful feedback at many stages of this project. This project was funded by the Norwegian Ministry of Foreign Affairs (grant INS-19/0007 to P.G.), with some additional funding from the Global Engagement Office at the Institute of Agriculture and Natural Resources, University of Nebraska-Lincoln.

Author information




P.G., M.A.S., S.R., F.A., T.O. and T.F. conceived the project. F.H., I.P., D.K.G.P. and Y.L.L. collected the data. W.H. and R.v.d.B. ran the model simulations. P.G., J.P.M., F.A., J.F.A., A.C., J.I.R.E., C.R.D. and H.S. analysed the data. P.G. and J.P.M. wrote the manuscript with input from all authors.

Corresponding author

Correspondence to Patricio Grassini.

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Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Sustainability thanks Wan Yee Lam, Ana Meijide and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Water-limited yield potential (Yw), attainable yield (Yatt), and average actual oil palm yield (Ya).

The Yatt is calculated as 70% of Yw. The exploitable yield gap (arrow) is calculated as the difference between Yatt and Ya.

Extended Data Fig. 2 Scheme illustrating the methodology used to build the yield gap atlas for oil palm in mineral soils in Indonesia.

Yields are expressed as fresh fruit bunches (FFB) per hectare per year. Yatt: attainable yield.

Extended Data Fig. 3 Selected 22 sites (yellow circles) and associated buffer zones (polygons with red borders).

Note that buffers’ borders are irregular as they were clipped by the borders of the climate zone where each buffer is located. Mature oil palm area located in mineral soils is shown in green. Lines show administrative boundaries. Details on each specific buffer are shown in Extended Data Table 1. Inset shows the location of the study area within Indonesia.

Extended Data Fig. 4 Scheme illustrating estimation of water-limited yield potential using different sets of weather data to account for variation in water-limited yield potential at a given plant age due to weather variation.

Separate sets of simulations were started at different years, filling the missing years at the end with the early years of the weather file if needed.

Extended Data Fig. 5 Scheme showing estimation of the exploitable yield gap for large plantations and smallholders.

Water-limited yield potential (Yw; blue solid line), attainable yield (Yatt; green solid line), average actual yields (solid triangles), and exploitable yield gaps (red arrows) are shown. The Yatt was estimated as 70% of Yw at a given age.

Extended Data Fig. 6 Projected trends in accumulated land use change and associated global warming potential (GWP).

Accumulated high- and low-carbon land converted for oil palm production (a, b) and associated accumulated GWP (c) during the study period (2018–2035) for three scenarios: (i) business as usual (BAU), with historical trends in area and yield remaining unchanged in the future; (ii) intensification (INT), with complete closure of the exploitable yield gap in current plantation area in mineral soils and without physical expansion of oil palm area; and (iii) intensification plus target expansion (INT-TE), with partial closure of exploitable yield gap and oil palm area expansion into low-carbon land. Source data

Extended Data Fig. 7 Comparison of simulated and measured water-limited yield potential and attainable yield.

In the case of water-limited yield potential (Yw), simulated values correspond to those derived from crop modelling in this study (see Extended Data Table 1) while published data (PD) correspond to highest recorded yields in plantations located in Southeast Asia as reported in the oil palm literature (see Supplementary Information, Section IIa). In the case of attainable yield (Yatt), values were estimated as 70% of simulated Yw in this study (see Extended Data Table 1) while large plantation (LP) values were derived from long-term yield records from 14 well-managed commercial blocks in Indonesia as provided by a number of private large plantations companies, including the four blocks used for calibration. Boxes indicate the 25th and 75th percentiles, whiskers represent the 10th and 90th percentiles, and means are shown with crosses. Also shown is the sample size (n), statistical significance for the differences and degrees of freedom (d.f.) for the comparison between the values reported in this study versus those reported in the literature (left) or provided by large plantations (right) using unpaired two-tailed Student’s t-test. All variables were normally distributed (D’Agostino’s test; p > 0.30). Source data

Extended Data Fig. 8 Global warming potential (GWP) associated with different scenarios of intensification and land use change and different assumptions in relation to changes in soil organic carbon (SOC) in mineral soils.

The GWP during the study period (2018–2035) was estimated for three scenarios and two different assumptions in relation to SOC changes in mineral soils after land conversion for oil palm cultivation: (i) no change in SOC following Khasanah et al.59 and (ii) 40% decline in SOC in the topsoil after conversion of primary or secondary forest for oil palm cultivation following van Straaten et al.60. For the latter, we assumed no change in SOC in mineral soils when non-forest land is converted for oil palm cultivation; hence, GWP in the other two scenarios (INT and INT-TE) remained unchanged. Dashed portion of the bar indicates the increase in GWP as a result of including changes in SOC in mineral soils when forest is converted for oil palm cultivation. We note that GHG emissions derived from peat decomposition are accounted for in the calculation of GWP, regardless the assumption on SOC changes in mineral soils. Source data

Supplementary information

Supplementary Information

Supplementary text and Tables 1–3.

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Source Data Fig. 1

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Source Data Fig. 2

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Source Data Fig. 3

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Source Data Extended Data Fig. 6

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Source Data Extended Data Fig. 7

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Source Data Extended Data Fig. 8

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Monzon, J.P., Slingerland, M.A., Rahutomo, S. et al. Fostering a climate-smart intensification for oil palm. Nat Sustain (2021).

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