Modelling alternative harvest effects on soil CO2 and CH4 fluxes from peatland forests.

Over the last century, many peatlands in northern Europe have been drained for forestry. Forest management with different harvesting regimes has a significant impact on soil water status and consequently on greenhouse gas emissions from peat soils. In this paper, we have used the process-based JSBACH-HIMMELI model to simulate the effects of alternative harvesting regimes, namely non-harvested (NH), selection harvesting (SH; 70 % of stem volume harvested) and clear-cutting (CC; 100 % of stem volume harvested), on soil CH4 and CO2 fluxes in peatland forests. We modified the model to account for the specific characteristics of peatland forests, where the water level (WL) is generally low and is regulated by the amount of aboveground vegetation through evapotranspiration. Multi-year measurements before and after the forest harvesting in a nutrient-rich peatland forest in southern Finland were used to constrain the model. The results showed that the modified model was able to reproduce the seasonal dynamics of water level, soil CH4 and soil CO2 fluxes under alternative harvesting regimes with reasonable accuracy. The averaged Pearson's r (Pearson correlation coefficient) and RMSE (Root Mean Square Error) between the model and the measurement were 0.75 and 7.3 cm for WL, 0.75 and 0.23 nmol m-2 s-1 for soil CH4 flux, 0.73 and 0. 88 µmol m-2 s-1 for soil CO2 flux. The modified model successfully reproduced soil CH4 uptake at both NH and SH sites and soil CH4 emission at the CC site, as observed in the measurements. Our study showed that increasing harvesting intensity (NH â†’ SH â†’ CC) in the model increased soil CH4 emission and decreased soil CO2 emission on an annual basis, but the magnitude of the decreased soil CO2 emission was much larger than that of the increased soil CH4 emission when comparing their global warming potentials. Therefore, in the short term as in our study (first three years after the harvest), the climate impacts of the soil GHG was reduced more in CC than in SH, which yet can be fundamentally different when considering in the long term.

Importance of vegetation classes in modeling CH4 emissions from boreal and subarctic wetlands in Finland.

Boreal/arctic wetlands are dominated by diverse plant species, which vary in their contribution to CH4 production, oxidation and transport processes. Earlier studies have often lumped the processes all together, which may induce large uncertainties into the results. We present a novel model, which includes three vegetation classes and can be used to simulate CH4 emissions from boreal and arctic treeless wetlands. The model is based on an earlier biogeophysical model, CH4MODwetland. We grouped the vegetation as graminoids, shrubs and Sphagnum and recalibrated the vegetation parameters according to their different CH4 production, oxidation and transport capacities. Then, we used eddy-covariance-based CH4 flux observations from a boreal (Siikaneva) and a subarctic fen (Lompolojänkkä) in Finland to validate the model. The results showed that the recalibrated model could generally simulate the seasonal patterns of the Finnish wetlands with different plant communities. The comparison between the simulated and measured daily CH4 fluxes resulted in a correlation coefficient (R2) of 0.82 with a slope of 1.0 and an intercept of -0.1mgm-2h-1 for the Siikaneva site (n=2249, p<0.001) and an R2 of 0.82 with a slope of 1.0 and an intercept of 0.0mgm-2h-1 for the Lompolojänkkä site (n=1826, p<0.001). Compared with the original model, the recalibrated model in this study significantly improved the model efficiency (EF), from -5.5 to 0.8 at the Siikaneva site and from -0.4 to 0.8 at the Lompolojänkkä site. The simulated annual CH4 emissions ranged from 7 to 24gm-2yr-1, which was consistent with the observations (7-22gm-2yr-1). However, there are some discrepancies between the simulated and observed daily CH4 fluxes for the Siikaneva site (RMSE=50.0%) and the Lompolojänkkä site (RMSE=47.9%). Model sensitivity analysis showed that increasing the proportion of the graminoids would significantly increase the CH4 emission levels. Our study demonstrated that the parameterization of the different vegetation processes was important in estimating long-term wetland CH4 emissions.

Field-scale simulation of methane emissions from coastal wetlands in China using an improved version of CH4MODwetland.

Coastal wetlands are important CH4 sources to the atmosphere. Coastal wetlands account for ~10% of the total area of natural wetlands in China, but the size of this potential CH4 source remains highly uncertain. We introduced the influence of salinity on CH4 production and CH4 diffusion into a biogeophysical model named CH4MODwetland so that it can be used in coastal wetlands. The improved model can generally simulate seasonal CH4 variations from tidal marshes dominated by Phragmites and Scirpus. However, the model underestimated winter CH4 fluxes from tidal marshes in the Yellow River Delta and YanCheng Estuary. It also failed to capture the accurate timing of the CH4 peaks in YanCheng Estuary and ChongMing Island in 2012. The improved model could generally simulate the difference between the annual mean CH4 fluxes from mangrove sites in GuangZhou and HaiKou city under different salinity and water table depth conditions, although fluxes were systematically underestimated in the mangrove site of HaiKou city. Using the improved model, the seasonal CH4 emissions simulated across all of the coastal wetlands ranged from 0.1 to 44.90gm(-2), with an average value of 7.89gm(-2), which is in good agreement with the observed values. The improved model significantly decreased the RMSE and RMD from 424% to 14% and 314% to -2%, respectively, and improved the EF from -18.30 to 0.99. Model sensitivity analysis showed that CH4 emissions were most sensitive to Pox in the tidal marshes and salinity in the mangroves. The results show that previous studies may have overestimated CH4 emissions on a regional or global scale by neglecting the influence of salinity. In general, the CH4MODwetland model can simulate seasonal CH4 emissions from different types of coastal wetlands under various conditions. Further improvements of CH4MODwetland should include the specific characteristics of CH4 processes in mangroves to decrease the uncertainty in estimating regional or global CH4 emissions from natural wetlands.