Browsing by Subject "FEN ECOSYSTEM"

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  • Susiluoto, Jouni; Raivonen, Maarit; Backman, Leif; Laine, Marko; Makela, Jarmo; Peltola, Olli; Vesala, Timo; Aalto, Tuula (2018)
    Estimating methane (CH4) emissions from natural wetlands is complex, and the estimates contain large uncertainties. The models used for the task are typically heavily parameterized and the parameter values are not well known. In this study, we perform a Bayesian model calibration for a new wetland CH4 emission model to improve the quality of the predictions and to understand the limitations of such models. The detailed process model that we analyze contains descriptions for CH4 production from anaerobic respiration, CH4 oxidation, and gas transportation by diffusion, ebullition, and the aerenchyma cells of vascular plants. The processes are controlled by several tunable parameters. We use a hierarchical statistical model to describe the parameters and obtain the posterior distributions of the parameters and uncertainties in the processes with adaptive Markov chain Monte Carlo (MCMC), importance resampling, and time series analysis techniques. For the estimation, the analysis utilizes measurement data from the Siikaneva flux measurement site in southern Finland. The uncertainties related to the parameters and the modeled processes are described quantitatively. At the process level, the flux measurement data are able to constrain the CH4 production processes, methane oxidation, and the different gas transport processes. The posterior covariance structures explain how the parameters and the processes are related. Additionally, the flux and flux component uncertain-ties are analyzed both at the annual and daily levels. The parameter posterior densities obtained provide information regarding importance of the different processes, which is also useful for development of wetland methane emission models other than the square root HelsinkI Model of MEthane buiLd- up and emIssion for peatlands (sqHIMMELI). The hierarchical modeling allows us to assess the effects of some of the parameters on an annual basis. The results of the calibration and the cross validation suggest that the early spring net primary production could be used to predict parameters affecting the annual methane production. Even though the calibration is specific to the Siikaneva site, the hierarchical modeling approach is well suited for larger-scale studies and the results of the estimation pave way for a regional or global- scale Bayesian calibration of wetland emission models.
  • Korrensalo, Aino; Mannisto, Elisa; Alekseychik, Pavel; Mammarella, Ivan; Rinne, Janne; Vesala, Timo; Tuittila, Eeva-Stiina (2018)
    We measured methane fluxes of a patterned bog situated in Siikaneva in southern Finland from six different plant community types in three growing seasons (2012-2014) using the static chamber method with chamber exposure of 35 min. A mixed-effects model was applied to quantify the effect of the controlling factors on the methane flux. The plant community types differed from each other in their water level, species composition, total leaf area (LAI(TOT)) and leaf area of aerenchymatous plant species (LAI(AER)). Methane emissions ranged from -309 to 1254 mg m(-2) d(-1). Although methane fluxes increased with increasing peat temperature, LAI(TOT) and LAI(AER), they had no correlation with water table or with plant community type. The only exception was higher fluxes from hummocks and high lawns than from high hummocks and bare peat surfaces in 2013 and from bare peat surfaces than from high hummocks in 2014. Chamber fluxes upscaled to ecosystem level for the peak season were of the same magnitude as the fluxes measured with the eddy covariance (EC) technique. In 2012 and in August 2014 there was a good agreement between the two methods; in 2013 and in July 2014, the chamber fluxes were higher than the EC fluxes. Net fluxes to soil, indicating higher methane oxidation than production, were detected every year and in all community types. Our results underline the importance of both LAI(AER) and LAI(TOT) in controlling methane fluxes and indicate the need for automatized chambers to reliably capture localized events to support the more robust EC method.