A05 - Optimizing nutrient management in oil palm plantations and upscaling greenhouse gas (GHG) fluxes from plot to a rainforest-transformation landscape


Our project aims:

  1. To investigate whether long-term (four years) management manipulations (reduced versus conventional fertilization rates and weed control) increase nutrient response and retention efficiencies as compared to the short-term (one-year) management effects in a large-scale oil palm plantation.
  2. To conduct a comprehensive analysis of various ecosystem functions of whether reduced management can contribute to a more sustainable oil palm production than conventional management.
  3. To generate a landscape-scale estimate and maps of soil N2O and CH4 fluxes; we will use a landform segmentation approach and the LAPSUS modelling framework.

In Phase 3, we firstly propose to investigate whether long-term (four years) management manipulations (reduced versus conventional fertilization rates and weed control) in a large-scale oil palm plantation increase nutrient response and retention efficiencies as compared to the short-term (one year) treatment effects. We will conduct whole-year measurements of nutrient availability, nutrient leaching losses, and soil greenhouse gas (GHG) fluxes and calculate the nutrient response and retention efficiencies. Together with all other subprojects involved in this oil palm management experiment, we will conduct a comprehensive analysis of various ecosystem functions and services to assess whether reduced management intensity can contribute to a more sustainable oil palm production than conventional management. Secondly, we will upscale the soil GHG fluxes measured in the first and second phases to the landscape level. We will compare a simple ‘measure and multiply’ approach with a ‘landscape segmentation’ approach, in which we incorporate the distal controls of landform shape and position on soil GHG fluxes at the landscape scale. In this approach, we employ landform segmentation to categorize the studied landscapes in phases 1 and 2 into functionally distinct units, based on a detailed digital elevation model (from the LiDAR flight planned for the two landscapes). Our upscaling approaches will also be compared with the upscaling approach using the process-based Community Land Model (A07 Knohl/Veldkamp). To assess the quality of our upscaling methods, we plan to measure soil GHG fluxes and control parameters at a selection of independent sites (included in the scope of the Landscape Assessment), which will be stratified according to distal controllers of soil GHG fluxes: soil texture, land uses and landform. Our proposed works are essential to the overall objectives and research Foci 1-4 of EFForTS.

Trennblatt A05