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Fostering a climate-smart intensification for oil palm

Nature Sustainability volume 4, pages 595–601 (2021)Cite this article

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Abstract

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.

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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 (www.yieldgap.org). Source data are provided with this paper.

References

  1. Pirker, J., Mosnier, A., Kraxner, F., Havlík, P. & Obersteiner, M. What are the limits to oil palm expansion? Glob. Environ. Change 40, 73–81 (2016).

    Article  Google Scholar 

  2. Bonan, G. B. Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320, 1444–1449 (2008).

    Article  CAS  Google Scholar 

  3. Colchester, M. et al. Justice in the Forest (CIFOR, 2006).

  4. Johnson, C. N. et al. Biodiversity losses and conservation responses in the Anthropocene. Science 356, 270–275 (2017).

    Article  CAS  Google Scholar 

  5. Seymour, F. & Harris, N. L. Reducing tropical deforestation. Science 365, 756–757 (2019).

    Article  CAS  Google Scholar 

  6. First Nationally Determined Contribution Submitted to UNFCCC (Republic of Indonesia, 2016).

  7. FAOSTAT (FAO, accessed 1 March 2020); http://www.fao.org/faostat/en/#data

  8. Austin, K. G., Schwantes, A., Gu, Y. & Kasibhatla, P. S. What causes deforestation in Indonesia? Environ. Res. Lett. 14, 024007 (2019).

  9. Tree Crop Estate Statistics of Indonesia 2017–2019 (Directorate General of Estate Crops, 2019).

  10. Woittiez, L. S., van Wijk, M. T., Slingerland, M., van Noordwijk, M. & Giller, K. E. Yield gaps in oil palm: a quantitative review of contributing factors. Eur. J. Agron. 83, 57–77 (2017).

    Article  Google Scholar 

  11. Wilcove, D. S., Giam, X., Edwards, D. P., Fisher, B. & Koh, L. P. Navjot’s nightmare revisited: logging, agriculture, and biodiversity in Southeast Asia. Trends Ecol. Evol. 28, 531–540 (2013).

    Article  Google Scholar 

  12. Curtis, P. G., Slay, C. M., Harris, N. L., Tyukavina, A. & Hansen, M. C. Classifying drivers of global forest loss. Science 361, 1108–1111 (2018).

    Article  CAS  Google Scholar 

  13. Gaveau, D. L. A. et al. Rapid conversions and avoided deforestation: Examining four decades of industrial plantation expansion in Borneo. Sci. Rep. 6, 32017 (2016).

    Article  CAS  Google Scholar 

  14. Srinivas, A. & Koh, L. P. Oil palm expansion drives avifaunal decline in the Pucallpa region of Peruvian Amazonia. Glob. Ecol. Conserv. 7, 183–200 (2016).

    Article  Google Scholar 

  15. Byerlee, D., Stevenson, J. & Villoria, N. Does intensification slow crop land expansion or encourage deforestation? Glob. Food Sec. 3, 92–98 (2014).

    Article  Google Scholar 

  16. Cassman, K. G. Ecological intensification of cereal production systems: Yield potential, soil quality, and precision agriculture. Proc. Natl Acad. Sci. USA 96, 5952–5959 (1999).

    Article  CAS  Google Scholar 

  17. Cassman, K. G. & Grassini, P. A global perspective on sustainable intensification research. Nat. Sustain. 3, 262–268 (2020).

    Article  Google Scholar 

  18. Tilman, D., Cassman, K. G., Matson, P. A., Naylor, R. & Polasky, S. Agricultural sustainability and intensive production practices. Nature 418, 671–677 (2002).

    Article  CAS  Google Scholar 

  19. Statistics Indonesia (BPS, accessed 1 March 2020); https://www.bps.go.id

  20. Jelsma, I., Schoneveld, G. C., Zoomers, A. & van Westen, A. C. M. Unpacking Indonesia’s independent oil palm smallholders: an actor-disaggregated approach to identifying environmental and social performance challenges. Land Use Policy 69, 281–297 (2017).

    Article  Google Scholar 

  21. Roadmap for the National Oil Palm Industry Towards 2045 (Indonesian cross-ministry team and oil palm institutions and local associations, 2019).

  22. The Palm Oil Dilemma: Policy Tensions Among Higher Productivity, Rising Demand, and Deforestation (IFPRI, 2019).

  23. OECD-FAO Agricultural Outlook 2020–2029 (OECD, 2020).

  24. Lobell, D. B., Cassman, K. G. & Field, C. B. Crop yield gaps: their importance, magnitudes, and causes. Annu. Rev. Environ. Resour. 34, 179–204 (2009).

    Article  Google Scholar 

  25. Hoffmann, M. P. et al. Yield gap analysis in oil palm: framework development and application in commercial operations in Southeast Asia. Agric. Syst. 151, 12–19 (2017).

    Article  Google Scholar 

  26. Molenaar, J. W., Persch-Orth, M., Taylor, C. & Harms, J. Diagnostic Study on Indonesia Oil Palm Smallholders: Developing a Better Understanding of their Performance and Potential (IFC, 2013).

  27. The Future of Food and Agriculture: Trends and Challenges (FAO, 2017).

  28. Hoffmann, M. P. et al. Simulating potential growth and yield of oil palm (Elaeis guineensis) with PALMSIM: model description, evaluation and application. Agric. Syst. 131, 1–10 (2014).

    Article  Google Scholar 

  29. Euler, M., Hoffmann, M. P., Fathoni, Z. & Schwarze, S. Exploring yield gaps in smallholder oil palm production systems in eastern Sumatra, Indonesia. Agric. Syst. 146, 111–119 (2016).

    Article  Google Scholar 

  30. Soliman, T., Lim, F. K. S. S., Lee, J. S. H. H. & Carrasco, L. R. Closing oil palm yield gaps among Indonesian smallholders through industry schemes, pruning, weeding and improved seeds. R. Soc. Open Sci. 3, 160292 (2016).

    Article  CAS  Google Scholar 

  31. Grassini, P. et al. How good is good enough? Data requirements for reliable crop yield simulations and yield-gap analysis. Field Crop. Res. 177, 49–63 (2015).

    Article  Google Scholar 

  32. Tilman, D. et al. Future threats to biodiversity and pathways to their prevention. Nature 546, 73–81 (2017).

    Article  CAS  Google Scholar 

  33. Mitchard, E. T. A. The tropical forest carbon cycle and climate change. Nature 559, 527–534 (2018).

    Article  CAS  Google Scholar 

  34. Zabel, F. et al. Global impacts of future cropland expansion and intensification on agricultural markets and biodiversity. Nat. Commun. 10, 2844 (2019).

    Article  CAS  Google Scholar 

  35. Barlow, J. et al. The future of hyperdiverse tropical ecosystems. Nature 559, 517–526 (2018).

    Article  CAS  Google Scholar 

  36. Indonesia. Second Biennial Update Report. Under the United Nations Framework Convention on Climate Change (Directorate General of Climate Change, Ministry of Environment and Forestry, 2018).

  37. Rhebergen, T. et al. Closing yield gaps in oil palm production systems in Ghana through best management practices. Eur. J. Agron. 115, 126011 (2020).

    Article  Google Scholar 

  38. Woittiez, L. S., Slingerland, M., Rafik, R. & Giller, K. E. Nutritional imbalance in smallholder oil palm plantations in Indonesia. Nutr. Cycl. Agroecosyst. 111, 73–86 (2018).

    Article  Google Scholar 

  39. Corley, R. H. V. & Lee, C. H. The physiological basis for genetic improvement of oil palm in Malaysia. Euphytica 60, 179–184 (1992).

    Article  Google Scholar 

  40. Jelsma, I., Woittiez, L. S., Ollivier, J. & Dharmawan, A. H. Do wealthy farmers implement better agricultural practices? An assessment of implementation of Good Agricultural Practices among different types of independent oil palm smallholders in Riau, Indonesia. Agric. Syst. 170, 63–76 (2019).

    Article  Google Scholar 

  41. Deininger, K. Challenges posed by the new wave of farmland investment. J. Peasant Stud. 38, 217–247 (2011).

    Article  Google Scholar 

  42. Agricultural Innovation Systems: An Investment Sourcebook (The World Bank, 2012).

  43. Cock, J. et al. Learning from commercial crop performance: oil palm yield response to management under well-defined growing conditions. Agric. Syst. 149, 99–111 (2016).

    Article  Google Scholar 

  44. Jelsma, I., Slingerland, M., Giller, K. E. & Bijman, J. Collective action in a smallholder oil palm production system in Indonesia: the key to sustainable and inclusive smallholder palm oil? J. Rural Stud. 54, 198–210 (2017).

    Article  Google Scholar 

  45. Carlson, K. M. et al. Effect of oil palm sustainability certification on deforestation and fire in Indonesia. Proc. Natl Acad. Sci. USA 115, 121–126 (2018).

    Article  CAS  Google Scholar 

  46. Sahide, M. A. K. & Giessen, L. The fragmented land use administration in Indonesia: analysing bureaucratic responsibilities influencing tropical rainforest transformation systems. Land Use Policy 43, 96–110 (2015).

    Article  Google Scholar 

  47. Presidential Instruction no. 5 (President of the Replublic of Indonesia, 2019).

  48. REDD+ (UNFCCC, accessed 1 March 2020); https://redd.unfccc.int

  49. Evans, L. T. Crop Evolution, Adaptation and Yield (Cambridge Univ. Press, 1993).

  50. van Ittersum, M. K. et al. Yield gap analysis with local to global relevance—A review. F. Crop. Res. 143, 4–17 (2013).

    Article  Google Scholar 

  51. Fairhurst, T. H. & Griffiths, W. Oil Palm: Best Management Practices for Yield Intensification (International Plant Nutrition Institute, Southeast Asia Program, 2015).

  52. Global Yield Gap Atlas (University of Nebraska, Wageningen University, accessed 1 March 2020); https://www.yieldgap.org

  53. Hekman, W., Slingerland, M. A., van den Beuken, R., Gerrie, V. & Grassini, P. Estimating yield gaps in oil palm in Indonesia using PALMSIM to inform policy on the scope of intensification. In International Oil Palm Conference (IOPC) (2018).

  54. Austin, K. G. et al. Shifting patterns of oil palm driven deforestation in Indonesia and implications for zero-deforestation commitments. Land Use Policy 69, 41–48 (2017).

    Article  Google Scholar 

  55. Land Cover Data (Ministry of Environment and Forestry, Indonesia, accessed 1 March 2020).

  56. Searchinger, T. et al. Use of U.S. croplands for biofuels increases greenhouse gases through emissions from land-use change. Science 319, 1238–1240 (2008).

    Article  CAS  Google Scholar 

  57. National Forest References Emission Level for Deforestations and Forest Degradation (Ministry of Environment and Forestry, Indonesia, 2016).

  58. Khasanah, N., van Noordwijk, M., Ningsih, H. & Wich, S. Aboveground carbon stocks in oil palm plantations and the threshold for carbon-neutral vegetation conversion on mineral soils. Cogent Environ. Sci. 1, 1119964 (2015).

    Article  CAS  Google Scholar 

  59. Khasanah, N., van Noordwijk, M., Ningsih, H. & Rahayu, S. Carbon neutral? No change in mineral soil carbon stock under oil palm plantations derived from forest or non-forest in Indonesia. Agric. Ecosyst. Environ. 211, 195–206 (2015).

    Article  Google Scholar 

  60. van Straaten, O. et al. Conversion of lowland tropical forests to tree cash crop plantations loses up to one-half of stored soil organic carbon. Proc. Natl Acad. Sci. USA 112, 9956–9960 (2015).

    Article  CAS  Google Scholar 

  61. Quezada, J. C., Etter, A., Ghazoul, J., Buttler, A. & Guillaume, T. Carbon neutral expansion of oil palm plantations in the Neotropics. Sci. Adv. 5, eaaw4418 (2019).

    Article  CAS  Google Scholar 

  62. Harsono, S. S., Prochnow, A., Grundmann, P., Hansen, A. & Hallmann, C. Energy balances and greenhouse gas emissions of palm oil biodiesel in Indonesia. GCB Bioenergy 4, 213–228 (2012).

    Article  CAS  Google Scholar 

  63. Archer, S. A., Murphy, R. J. & Steinberger-Wilckens, R. Methodological analysis of palm oil biodiesel life cycle studies. Renew. Sustain. Energy Rev. 94, 694–704 (2018).

    Article  Google Scholar 

  64. Brentrup, F., Lammel, J., Stephani, T. & Christensen, B. Updated carbon footprint values for mineral fertilizer from different world regions. In 11th International Conference on Life Cycle Assessment of Food 2018 (LCA Food) (2018).

  65. Lim, Y. L. et al. An update on oil palm nutrient budgets. In International Oil Palm Conference (IOPC) (2018).

  66. Tiemann, T. T. et al. Feeding the palm: a review of oil palm nutrition. Adv. Agron. 152, 149–243 (2018).

    Article  Google Scholar 

  67. Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (eds Calvo Buendia, E. et al.) (IPCC, 2019).

  68. Caliman, J. P. N-Fertiliser losses quantification in term of N2O emission and NH3 volatilisation. In Oil Palm Best Practices Workshop (MOSTA, 2019).

  69. Meijide, A. et al. Measured greenhouse gas budgets challenge emission savings from palm-oil biodiesel. Nat. Commun. 11, 1089 (2020).

    Article  CAS  Google Scholar 

  70. Hassler, E., Corre, M. D., Kurniawan, S. & Veldkamp, E. Soil nitrogen oxide fluxes from lowland forests converted to smallholder rubber and oil palm plantations in Sumatra, Indonesia. Biogeosciences 14, 2781–2798 (2017).

    Article  CAS  Google Scholar 

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Acknowledgements

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.

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Authors and Affiliations

  1. Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE, USA

    Juan P. Monzon, José F. Andrade, Antoine Couëdel, Juan I. Rattalino Edreira, Christopher R. Donough, Hendra Sugianto, Ya Li Lim, Thomas Farrell & Patricio Grassini

  2. National Scientific and Technical Research Council (CONICET), Balcarce, Argentina

    Juan P. Monzon

  3. Wageningen University and Research, Wageningen, The Netherlands

    Maja A. Slingerland, Willem Hekman & Rob van den Beuken

  4. Indonesian Oil Palm Research Institute (IOPRI), Medan, Indonesia

    Suroso Rahutomo, Fandi Hidayat & Iput Pradiko

  5. Indonesian Agency for Agricultural Research and Development (IAARD), Bogor, Indonesia

    Fahmuddin Agus & Dwi K. G. Purwantomo

  6. African Plant Nutrition Institute (APNI), Benguérir, Morocco

    Thomas Oberthür

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  1. Juan P. Monzon
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Contributions

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.

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Correspondence to Patricio Grassini.

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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.

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Supplementary information

Supplementary Information

Supplementary text and Tables 1–3.

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Source Data Fig. 1

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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 4, 595–601 (2021). https://doi.org/10.1038/s41893-021-00700-y

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