Quantifying nitrogen losses in oil palm plantations: models and challenges
2016
Pardon, Lénaïc | Bessou, Cécile | Saint-Geours, Nathalie | Gabrielle, Benoit | Khasanah, Ni'Matul | Caliman, Jean-Pierre | Nelson, Paul N. | Performance des systèmes de culture des plantes pérennes (UPR Système de pérennes) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad) | College of Science and Engineering ; James Cook University (JCU) | CEEI CAP ALPHA, Centre Européen d'Entreprises et d'Innovation ; ITK | Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS) ; Institut National de la Recherche Agronomique (INRA)-AgroParisTech | Université Paris-Saclay | Southeast Asia Regional Programme ; World Agroforestry Centre | SMART agribusiness and food [Jakarta] (SMART)
Oil palm is the most rapidly expanding tropical perennial crop. Its cultivation raises environmental concerns,notably related to the use of nitrogen (N) fertilisers and the associated pollution and greenhouse gas emissions. While numerous and diverse models exist to estimate N losses from agriculture, very few are currently available for tropical perennial crops. Moreover, there is a lack of critical analysis of their performance in the specific context of tropical perennial cropping systems. We assessed the capacity of 11 models and 29 sub-models to estimate N losses in a typical oil palm plantation over a 25-year growth cycle, through leaching and runoff, and emissions of NH3, N2, N2O, and NOx . Estimates of total N losses were very variable, ranging from 21 to 139 kg Nha 1 yr 1. On average, 31% of the losses occurred during the first 3 years of the cycle. Nitrate leaching accounted for about 80% of the losses. A comprehensive Morris sensitivity analysis showed the most influential variables to be soil clay content, rooting depth, and oil palm N uptake.We also compared model estimates with published field measurements. Many challenges remain in modelling processes related to the peculiarities of perennial tropicalcrop systems such as oil palm more accurately.
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