• Energy Research

To accurately quantify tropical peatlands’ contribution to global greenhouse gas emissions, and to understand how emissions from peat may change in the future, long-term measurements over seasons and years are needed. Sampling soil respiration over a range of temperature and moisture conditions in the field is valuable for understanding how peat soil emissions may respond to climate change. We collected monthly measurements of total soil respiration, moisture and temperature from forest and smallholder oil palm plantations on peat in Central Kalimantan, Indonesia. Our study period, from January 2014 through September 2015, covered wet–dry transitions during 1 year with relatively normal precipitation and one El Nino year. Oil palm plots, with lower water table, had 22% higher total soil respiration (0.71 ± 0.04 g CO2 m-2 h-1) than forest plots (0.58 ± 0.04 g CO2 m-2 h-1) over the entire monitoring period. However, during the El Nino event in September 2015, despite overall lower water table levels in oil palm plots, total soil respiration was higher in forest (1.24 ± 0.20 g CO2 m-2 h-1) than in oil palm (0.90 ± 0.09 g CO2 m-2 h-1). Land-use change continues to be an important driver of carbon dioxide (CO2) emissions from Indonesian peatlands. However, the stronger response of total soil respiration to extreme drought in forest indicates the potential importance of climate regime in determining future net carbon (C) emissions from these ecosystems. Future warming and increased intensity of seasonal drying may increase C emissions from Indonesian peatlands, regardless of land-use.

AbstractTropical peatlands store copious amounts of carbon (C) and play a critical role in the global C cycle. However, this C store is vulnerable to natural and anthropogenic disturbances, leading these ecosystems to become weaker C sinks or even net C sources. Variabilities in water table (WT) greatly influence the magnitude of greenhouse gas flux in these biomes. Despite its importance in C cycling, observations of the spatiotemporal dynamics of tropical peatland WT are limited in spatial extent and length. Here, we use in situ WT measurements from tropical peatlands in Indonesia, Malaysia, and Peru to evaluate the satellite‐based Optical Trapezoid Model (OPTRAM). The model uses the pixel distribution in the shortwave infrared transformed reflectance and normalized difference vegetation index (NDVI) space to calculate indices that are then compared against in situ WT data. 30‐m resolution Landsat 7 and Landsat 8 images were utilized for model parameterization. We found OPTRAM to best capture tropical peatland WT dynamics in minimally forested and non‐forested areas (low to intermediate NDVI) (0.7 < R < 1) using the “best pixel” approach (the pixel with the highest Pearson‐R correlation value). In areas with relatively higher NDVI, OPTRAM index did not correlate with WT (average R of −0.04 to 0.24), likely due to trees being less sensitive to WT fluctuations. OPTRAM shows potential for reliably estimating tropical peatland WT without the need for direct measurements, which is challenging due to site remoteness and harsh conditions.

AbstractGreenhouse gas (GHGs) emissions from peatlands contribute significantly to ongoing climate change because of human land use. To develop reliable and comprehensive estimates and predictions of GHG emissions from peatlands, it is necessary to have GHG observations, including carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), that cover different peatland types globally. We synthesize published peatland studies with field GHG flux measurements to identify gaps in observations and suggest directions for future research. Although GHG flux measurements have been conducted at numerous sites globally, substantial gaps remain in current observations, encompassing various peatland types, regions and GHGs. Generally, there is a pressing need for additional GHG observations in Africa, Latin America and the Caribbean regions. Despite widespread measurements of CO2 and CH4, studies quantifying N2O emissions from peatlands are scarce, particularly in natural ecosystems. To expand the global coverage of peatland data, it is crucial to conduct more eddy covariance observations for long-term monitoring. Automated chambers are preferable for plot-scale observations to produce high temporal resolution data; however, traditional field campaigns with manual chamber measurements remain necessary, particularly in remote areas. To ensure that the data can be further used for modeling purposes, we suggest that chamber campaigns should be conducted at least monthly for a minimum duration of one year with no fewer than three replicates and measure key environmental variables. In addition, further studies are needed in restored peatlands, focusing on identifying the most effective restoration approaches for different ecosystem types, conditions, climates, and land use histories.

Carbon dioxide (CO2) emissions from Southeast Asia peatlands are contributing substantially to global anthropogenic emissions to the atmosphere. Peatland emissions associated with land-use change, and fires are closely related to changes in the water table level. Remote sensing is a powerful tool that is potentially useful for estimating peat CO2 emissions over large spatial and temporal scales. We related ground measurements of total soil respiration and water table depth collected over 19 months in an Indonesian peatland to remotely sensed gravity recovery and climate experiment (GRACE) terrestrial water storage anomoly (TWSA) data. GRACE TWSA can be used to predict changes in water storage on land. We combined ground observations from undrained forest and drained smallholder oil palm plantations on peat in Central Kalimantan to produce a representation of the peatland landscape in one 0.5° × 0.5° GRACE grid cell. In both ecosystem types, total soil respiration increased with increasing water table depth. Across the landscape grid, monthly changes in water table depth were significantly related to fluctuations in GRACE TWSA. GRACE TWSA explained 76% of variation in water table depth and 75% of variation in total soil respiration measured on the ground. By facilitating regular sampling across broad spatial scales that captures essential variation in a major driver of soil respiration and peat fires, our approach could improve information available to decision makers to monitor changes in water table depth and peat CO2 emissions. This would enable measures better targeted in space and time to more effectively mitigate CO2 emissions from tropical peat drainage and fires. Testing over larger regions is needed to operationalize this exploratory approach.