Soil respiration (SR) rate was measured at the burned land (BL), the cropland (CL), the forest land (FL) and the grassland (GL) of a tropical peatland in Central Kalimantan, Indonesia from 2002 to 2011 for the purpose of analysis with a relation to the drying and rewetting. The SR rate was fitted with groundwater level (GWL) to the equation of log(SR) = α – β × GWL using hierarchical Bayesian analysis where α and β were regression coefficients classified by GWL changing directions (drying, rewetting and fluctuating), water-filled pore space (WFPS) ranges in topsoil (low 0–0.54, intermediate 0.54–0.75 and high 0.75–1 m³ m⁻³), and land uses (BL, CL, FL and GL). SR rate (Mean ± SD, mg C m⁻² h⁻¹) was the significantly largest in the CL (333 ± 178) followed by GL (259 ± 151), FL (127 ± 69) and lastly BL (100 ± 90). In the CL, the significantly larger SR rate was found in the rewetting period than in the drying period in the high WFPS range. Also, the significantly steeper slope (β) in the rewetting period was obtained in the high WFPS range than in the drying period. These results suggested that the rewetting of peatland enhanced the SR rate rapidly in the CL, and that the further rise of GWL decreased the SR rate. In contrast, the SR rate in the rewetting period was significantly smaller than in the drying period in the BL in the high WFPS range, because the BL in the high WFPS range was flooded in most cases. The SR rate in the rewetting period was not significantly different from the drying period in the FL and GL. All of β were significant in the high WFPS range in all land uses, but not in the low–intermediate WFPS ranges, suggesting that GWL was not controlling factor of the SR rate when the GWL was deep due to the disconnection of capillary force under dry conditions. According to the results of correlation analysis of the α and β, the α was significantly correlated with relative humidity, soil temperature and soil pH, suggesting that the α was enhanced by dry condition, high soil temperature and neutralization of soil acidity, respectively. The β was significantly correlated with exchangeable Na⁺ and Mg²⁺ in the soil, but the reason was not clear. In conclusion, SR rate was enhanced by rising GWL with rewetting in the CL in the high WFPS ranges as well as by deepening GWL.

This study investigated spatial factors controlling CO₂, CH₄, and N₂O fluxes and compared global warming potential (GWP) among undrained forest (UDF), drained forest (DF), and drained burned land (DBL) on tropical peatland in Central Kalimantan, Indonesia. Sampling was performed once within two weeks in the beginning of dry season. CO₂ flux was significantly promoted by lowering soil moisture and pH. The result suggests that oxidative peat decomposition was enhanced in drier position, and the decomposition acidify the peat soils. CH₄ flux was significantly promoted by a rise in groundwater level, suggesting that methanogenesis was enhanced under anaerobic condition. N₂O flux was promoted by increasing soil nitrate content in DF, suggesting that denitrification was promoted by substrate availability. On the other hand, N₂O flux was promoted by lower soil C:N ratio and higher soil pH in DBL and UDF. CO₂ flux was the highest in DF (241 mg C m⁻² h⁻¹) and was the lowest in DBL (94 mg C m⁻² h⁻¹), whereas CH₄ flux was the highest in DBL (0.91 mg C m⁻² h⁻¹) and was the lowest in DF (0.01 mg C m⁻² h⁻¹), respectively. N₂O flux was not significantly different among land uses. CO₂ flux relatively contributed to 91–100% of GWP. In conclusion, it is necessary to decrease CO₂ flux to mitigate GWP through a rise in groundwater level and soil moisture in the region.

(1) Background: Nitrogen (N) fertilization on drained tropical peatland will likely stimulate peat decomposition and mineralization, enhancing N₂O emission from the peat soil. (2) Methods: A field experiment was conducted to quantify the N₂O emissions from soil in an oil palm plantation (Elaeis guineensis Jacq.) located in a tropical peatland in Sarawak, Malaysia, under different rates of N fertilizers. The study was conducted from January 2010 to December 2013 and resumed from January 2016 to December 2017. Nitrous oxide (N₂O) flux was measured every month using a closed chamber method for four different N rates; control—without N (T1), 31.1 kg N ha⁻¹ yr⁻¹ (T2), 62.2 kg N ha⁻¹ yr⁻¹ (T3), and 124.3 kg N ha⁻¹ yr⁻¹ (T4); (3) Results: Application of the N fertilizer significantly increased annual cumulative N₂O emissions for T4 only in the years 2010 (p = 0.017), 2011 (p = 0.012), 2012 (p = 0.007), and 2016 (p = 0.048). The highest average annual cumulative N₂O emissions were recorded for T4 (41.5 ± 28.7 kg N ha⁻¹ yr⁻¹), followed by T3 (35.1 ± 25.7 kg N ha⁻¹ yr⁻¹), T1 (25.2 ± 17.8 kg N ha⁻¹ yr⁻¹), and T2 (25.1 ± 15.4 kg N ha⁻¹ yr⁻¹), indicating that the N rates of 62.2 kg N ha⁻¹ yr⁻¹ and 124.3 kg N ha⁻¹ yr⁻¹ increased the average annual cumulative N₂O emissions by 39% and 65%, respectively, as compared to the control. The N fertilization had no significant effect on annual oil palm yield (p = 0.994). Alternating between low (deeper than −60 cm) and high groundwater level (GWL) (shallower than −60 cm) enhanced nitrification during low GWL, further supplying NO₃⁻ for denitrification in the high GWL, and contributing to higher N₂O emissions in high GWL. The emissions of N₂O ranged from 17 µg N m⁻² hr⁻¹ to 2447 µg N m⁻² hr⁻¹ and decreased when the water-filled pore space (WFPS) was between 70% and 96%, suggesting the occurrence of complete denitrification. A positive correlation between N₂O emissions and NO₃⁻ at 70–96% WFPS indicated that denitrification increased with increased NO₃⁻ availability. Based on their standardized regression coefficients, the effect of GWL on N₂O emissions increased with increased N rate (p < 0.001). Furthermore, it was found that annual oil palm yields negatively correlated with annual N₂O emission and NO₃⁻ for all treatments. Both nitrification and denitrification increased with increased N availability, making both processes important sources of N₂O in oil palm cultivation on tropical peatland.; and (4) Conclusions: To improve understanding of N₂O mitigation strategies, further studies should consider plant N uptake on N₂O emissions, at least until the completion of the planting.

Hierarchical Bayesian (HB) methods are useful tools for modeling multifaceted, nonlinear phenomena such as those encountered in ecology, and have been increasingly applied in environmental sciences, e.g., to estimate soil gas flux from different soil textures or sites. We have developed a model of soil carbon dioxide (CO₂) flux based on soil temperature (T, 5 cm depth) and water-filled pore space (WFPS, 5 cm depth) using HB theory. The HB model was calibrated using a dataset of CO₂ flux measured from bare soils belonging to four texture classes in 14 upland field sites in a watershed in central Hokkaido, Japan, in the nonsnow-cover season from 2003 to 2011. The numerical software HYDRUS-1D was used to simulate daily WFPS, and the estimated values were significantly correlated with the measured WFPS (R² = 0.68, P < 0.001). Compared to a nonhierarchical Bayesian model (Bayesian pooled model), the CO₂ predictions with the HB model more accurately represented texture-specific observations. The simulation–observation fit of the CO₂ flux model was R² = 0.64 (P < 0.001). More than 90% of the observed daily data were within the 95% confidence interval. The HB model exhibited high uncertainty for high CO₂ flux values. The HB model calibration revealed differing sensitivity of CO₂ flux to T and WFPS in different soil texture classes. CO₂ flux increased with an increase in T, and it increased to a lesser degree with a finer texture, possibly because the clay and silt facilitated soil aggregation, thus reducing temperature fluctuations. WFPS values between 0.48 and 0.64 resulted in optimal conditions for CO₂ flux. The minimum WFPS value increased with an increase in clay content (P < 0.05). Although only a small number of soil types were studied in only one season in this study, the HB model may provide a method for predicting how the effects of soil temperature and moisture on CO₂ flux change with texture, and soil texture could be regarded as an upscaling factor in future research on regional extrapolation.