Modelling potential nitrogen losses in oil palm plantations with IN-Palm, an agri-environmental indicator

Pardon Lénaïc, Bockstaller Christian, Marichal Raphaël, Ribka Sionita T., Nelson Paul N., Gabrielle Benoît, Laclau Jean-Paul, Caliman Jean-Pierre, Bessou Cécile. 2016. Modelling potential nitrogen losses in oil palm plantations with IN-Palm, an agri-environmental indicator. In : Proceedings of the 8th International Congress on Environmental Modelling and Software. Sauvage, S. (ed.), Sánchez-Pérez, J.M. (ed.), Rizzoli, A.E. (ed.). Toulouse : Université de Toulouse, pp. 445-452., 5 vol (1335 p.) ISBN 978-88-9035-745-9 International Congress on Environmental Modelling and Sofware (iEMSs 2016). 8, Toulouse, France, 10 July 2016/14 July 2016.

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Abstract : Oil palm cultivation area is expected to increase until at least 2050. This expansion raises environmental concerns, not only regarding land-use change and its consequences, but also concerning potential impacts of losses of nitrogen such as ammonia volatilisation, nitrous oxide emission and nitrate leaching and runoff. The prerequisite to any work on the reduction of losses and identification of best practices is the development of an assessment tool. However, the available knowledge regarding nitrogen losses is limited for oil palm, which leads to high uncertainty in environmental assessment. In this context, we chose to develop an agri-environmental indicator, IN-Palm, which aims at estimating the risk of nitrogen losses in oil palm plantations, using the INDIGO® method. This kind of operational model is built to assess environmental risks as well as being used as a decision support tool. The development of indicators is particularly relevant in such contexts of data scarcity, as it allows for harnessing the most of readily accessible data from a whole range of sources, i.e. measured or modelled, qualitative or quantitative, empirical or expert knowledge. We adapted the indicator to characteristics of the oil palm system, such as the tropical climate, the long growth cycle of about 25 years and the high production of biomass. We designed it to be easily implementable with available data on climate and soil conditions, and sensitive to practices such as fertiliser application (type, rate and timing), legume cover establishment, and residue management. Future work will include a sensitivity analysis, a validation against experimental data of losses in Sumatra, and a validation by end-users in a plantation in Sumatra.

Classification Agris : F01 - Crop husbandry
U10 - Mathematical and statistical methods
P01 - Nature conservation and land resources
P33 - Soil chemistry and physics
P35 - Soil fertility
P36 - Soil erosion, conservation and reclamation

Auteurs et affiliations

  • Pardon Lénaïc, CIRAD-PERSYST-UPR Systèmes de pérennes (FRA)
  • Bockstaller Christian, INRA (FRA)
  • Marichal Raphaël, CIRAD-PERSYST-UPR Systèmes de pérennes (IDN)
  • Ribka Sionita T., SMART Research Institute (IDN)
  • Nelson Paul N., James Cook University (AUS)
  • Gabrielle Benoît, AgroParisTech (FRA)
  • Laclau Jean-Paul, CIRAD-PERSYST-UMR Eco&Sols (FRA) ORCID: 0000-0002-2506-214X
  • Caliman Jean-Pierre
  • Bessou Cécile, CIRAD-PERSYST-UPR Systèmes de pérennes (FRA) ORCID: 0000-0001-6686-8468

Source : Cirad-Agritrop (

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