Pardon, L., Bessou, C., Nelson, P., Caliman, J., Marichal, R., Dubos, B., Ollivier, J., and Gabrielle, B. (2015) Modelling the nitrogen balance of tropical perennial crops: state of the art and challenges for oil palm plantations. In: Abstracts from the 25th Annual Meeting of the Society of Environmental Toxicology and Chemistry. WE324. pp. 399-400. From: SETAC Europe 2015: 25th Annual Meeting of the Society of Environmental Toxicology and Chemistry: environmental protection in a multi-stressed world, 3-7 May 2015, Barcelona, Spain.

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Abstract

While a number of models exist to estimate nitrogen (N) losses from agricultural fields, they mostly pertain to temperate climate conditions and annual crops. Few models are available for tropical crops [1], [2], and even fewer for perennial crops [3], [4]. The lack of robust N-flux inventories is particularly critical for LCA of perennial and tropical crops. Oil palm is the most rapidly expanding tropical perennial crop, which raises environmental concerns. Beside land-use change and peatland, oil palm agricultural production impacts the environment mainly through the use of synthetic fertilisers, notably nitrogen [5], [6]. The latter is associated with pollution risks of ground and surface water, and emissions of greenhouse gases. Accurate estimation of N losses is critical to assess the environmental impacts of palm plantations. In this study, we reviewed currently-available models for oil palm cultivation, and appraised their capacity to assess the N balances of oil palm agro-ecosystems. We identified various operational and process-based models that could be applied to oil palm, although most of them were not specifically adapted for tropical perennial crops. To our knowledge, APSIM is the only available process-based model of oil palm cultivation that includes N losses [7], but the accuracy of its N loss estimates was untested. Other means of assessment were based on statistical models [8]–[10] or other approaches [11]–[13]. Nitrogen balance assessments have shown important uncertainties (Figure). Estimates of N20 and NO3 - rely on very uncertain and sensitive parameters, such as the clay content for instance with the SQCB-NO3 model [13]. These uncertainties are due to a lack of understanding of processes. In particular, it is difficult to study and understand N dynamics over the whole lifespan of oil palm crops (20-25 years) and to account for varying agricultural practices. Adequate data to characterise various cropping systems is often lacking. Further research is required to develop a procedure that provides a robust assessment of the environmental impact of N management in oil palm cultivation. Particularly, this procedure should have the capacity to account for a range of soils, climates, and management practices over the whole cycle. One track to be pursued is the development of an agro-ecological indicator based on Indigo concept [14], [15]. Such an indicator could help to reduce uncertainties in LCA of tropical perennial crops.

Research Statement

Research Background	Oil palm is an important and expanding crop. One of the key factors influencing environemntal impact of the crop is nitrogen cycling and management. Modelling tools are necessary to assess the impacts and possible changes in management to eliminate or minimise adverse environmental impacts.
Research Contribution	The research identified the modelling tools that may be used for oil palm. It assessed their potential utility and limitations.
Research Significance	With the assessment provided here it is now possible to choose the most effective modelling tools for evaluating options for limiting adverse environmental impacts of oil palm cultivation.
Item ID:	41389
Item Type:	Conference Item (Abstract / Summary)
ISSN:	2309-8031
Date Deposited:	29 Feb 2016 03:29
FoR Codes:	07 AGRICULTURAL AND VETERINARY SCIENCES > 0701 Agriculture, Land and Farm Management > 070101 Agricultural Land Management @ 50% 07 AGRICULTURAL AND VETERINARY SCIENCES > 0701 Agriculture, Land and Farm Management > 070105 Agricultural Systems Analysis and Modelling @ 50%
SEO Codes:	96 ENVIRONMENT > 9609 Land and Water Management > 960904 Farmland, Arable Cropland and Permanent Cropland Land Management @ 40% 82 PLANT PRODUCTION AND PLANT PRIMARY PRODUCTS > 8203 Industrial Crops > 820399 Industrial Crops not elsewhere classified @ 40% 82 PLANT PRODUCTION AND PLANT PRIMARY PRODUCTS > 8298 Environmentally Sustainable Plant Production > 829802 Management of Greenhouse Gas Emissions from Plant Production @ 20%
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