Modeling oil palm monoculture and its associated impacts on land-atmosphere carbon, water and energy fluxes in Indonesia

Tropical forests in South-East Asia (SEA) are essential agents in local and regional climate by recycling water, absorbing/releasing greenhouse gases (GHGs) and transforming energy, and through atmospheric teleconnections they also have potential for mitigating global warming by means of evaporative cooling and carbon sequestration. Land cover changes in SEA tropical regions have been accelerated by drastic economic development and policy reforms in the past 30 years. Land transformation from natural to managed ecosystems such as oil palm plantation might alter the patterns of land-atmosphere energy, water and carbon fluxes and therefore affect local or regional climate due to changed land surface properties. Questions remain about the specific mechanisms and degrees of the effects. This project is designed to characterize quantitatively the effects of Indonesia´s historical and future land use change (LUC) on carbon, water and energy fluxes to the atmosphere using the Community Earth System Model (CESM) and its land component CLM.

This research is aimed to answer two key questions: (i) how does LUC affect carbon (CO2, CH4), energy and water fluxes, and (ii) how sensitive is the current capacity to sequester carbon to further LUCs? Through the combined strength of remote sensing and land surface modelling I will accomplish the following objectives:

• Parameterize CLM and adapt CLM to land-use transformation in Indonesia.
• Model the impacts of historical LUC on carbon, water and energy fluxes to the atmosphere.
• Validate CLM outputs at selected eddy covariance (EC) flux sites (Bariri, Jambi) in Indonesia.
• Projection of the effects of future LUC on carbon, energy and water fluxes and carbon sequestration capacity under five different LUC scenarios.

The parameterization of a new Plant Function Type (PFT) for oil palm and adaptation of tropical forest PFTs for Indonesia, plus their implementation in the modelling of LUC effects in CLM will contribute to the development of the CLM model. After model comparison among sites with uncertainty analysis and generalizability assessment, the implication of CLM may be also up-scaled to larger regions.