| dc.description.abstract | The significant expansion of agricultural areas in response to rising consumer demand has resulted in the conversion of extensive tropical peat swamp forests into agricultural plantations in Malaysia, leading to substantial emissions of carbon dioxide. Oil palm plantations present in 13 % of former peat swamp forests, however, the accuracy of reported emissions of oil palm plantations remains highly uncertain due to inconsistencies in sampling designs and insufficient quantification of site-specific environmental factors on peat soils. These uncertainties have implications for global emissions estimates and are further compounded by a limited understanding of the factors controlling fluxes. This knowledge gap also limits our ability to estimate the upscaled fluxes in oil palm plantations which have different management zones such as Harvest Path (HP), Palm Base (PB) and Frond Pile (FP). This dissertation addresses knowledge gaps arising from potential biases due to spatial and temporal sampling strategies. Extensive measurements are then used to explore the magnitude and controls of carbon emissions in oil palm plantations of different ages and contrasted to neighbouring degraded peat swamp forest. Finally, I explore the tensions between competing goals of water table management (e.g., higher water tables to reduce emissions, versus lower water tables for optimal plantation management). Reduced emissions at the cost of lower yields might be uneconomical (and thus not adopted) or may even result in further land clearance to maintain overall production. I explore the influence of water table height on palm yields by combining extensive water table and yield data at the study sites.
In Chapter 3, the first main research data chapter, I quantify the bias arising from a reliance on single-time measurements, rather than continuous fluxes, and presents a bias equation to calculate the estimated bias percentage of flux using an Environmental Gas Monitor (EGM) chamber. This equation for mean diurnal patterns of fluxes can be used in correcting flux measurement that may arise from single time measurement to mitigate potential biases. In addition, the correction also applied specifically into each management zones or termed as microforms to reduce the spatial biases in oil palm ecosystem measurement. In Chapter 4, I identify gaps in understanding arising from poor availability of longer-term, highly replicated flux measurements, and instead a reliance on studies that have mostly been conducted over short periods (less than one year), with relatively low replication. Using data collected since 2014, I compare fluxes among young and mature oil palm peat plantations and logged-over peat swamp forest to assess differences over time and seasonal trends. This data set is one of the most comprehensive and I use it to compare the flux from each microform between young and mature oil palm plantation and with the peat swamp forest to explore the spatial and temporal effects. In Chapter 5, I focus on the role of water table management in oil palm yield and GHG emissions control in peat plantations. I investigate the impact of water table depths (WTD) on oil palm yield and CO2 emissions, aiming to optimize plantation areas for sustainable yields.
In summary, the findings of my study underscore the significance of characterizing diurnal flux patterns across various microforms to mitigate biases when extrapolating single time point measurements spatially and temporally. In future research, it is crucial to expand the number of measurement locations and extend the monitoring duration across diverse microforms to enhance the accuracy of plantation estimates obtained through manual chambers and further minimize potential biases. Many current lands use change studies focus on measuring CO2 measurement magnitude in oil tropical peat, but my research highlights the additional need to properly measured flux and the impacts of water table fluctuations on oil palm yield. | en_GB |
