HIMMELI v1.0: HelsinkI Model of MEthane buiLd-up and emIssion for peatlands

Raivonen, Maarit; Smolander, Sampo; Backman, Leif; Susiluoto, Jouni; Aalto, Tuula; Markkanen, Tiina; Mäkelä, Jarmo; Rinne, Janne; Peltola, Olli; Aurela, Mika; Lohila, Annalea; Tomasic, Marin; Li, Xuefei; Larmola, Tuula; Juutinen, Sari; Tuittila, Eeva‐Stiina; Heimann, Martin; Sevanto, Sanna; Kleinen, Thomas; Brovkin, Victor; Vesala, Timo

doi:10.5194/gmd-10-4665-2017

Cited by 35 publications

(81 citation statements)

References 119 publications

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“…However, recent studies based on spatial (Turetsky et al, 2014) and temporal variation (Rinne et al, 2018) indicate maximum fluxes at intermediate WT positions. Vegetation has recently been included in the process models as a controlling factor of methane fluxes from peatlands (Li et al, 2016;Raivonen et al, 2017). However, these models do not yet take into account the impact of its spatial heterogeneity on methane fluxes.…”

Section: Introductionmentioning

confidence: 99%

Small spatial variability in methane emission measured from a wet patterned boreal bog

et al. 2018

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Abstract. 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)(2013)(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.

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Section: Introductionmentioning

confidence: 99%

Small spatial variability in methane emission measured from a wet patterned boreal bog

et al. 2018

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“…The Fortran codes describing the EBG modelling approach are included in the Supplement. The HIMMELI model codes are included in the supplement of Raivonen et al (2017) (https://doi.org/10.5194/ gmd-10-4665-2017-supplement). The data used in this study are available online at https://doi.org/10.5281/zenodo.1164760 (Peltola et al, 2018), as well as in the AVAA -open research data publishing platform (http://openscience.fi/avaa).…”

Section: Discussionmentioning

confidence: 99%

“…The former was distributed vertically according to the root distribution while the latter was distributed evenly into the peat layers below water level; therefore, the main factor driving the anoxic respiration was NPP modelled for Siikaneva. We used the same calibrated parameter values as in the discussion paper of Raivonen et al (2017). The model has been calibrated in ; however, parameters used in the different ebullition modelling approaches (see below) were not calibrated.…”

Section: Methodsmentioning

confidence: 99%

“…See the details about LAI and anoxic respiration simulation in Raivonen et al (2017) and . Peat temperature was measured at five depths below the surface (−5, −10, −20, −35 and −50 cm) and the measurements were interpolated linearly in time and space in order to match every model time step and depth.…”

Section: Site and Measurementsmentioning

confidence: 99%

“…Other ebullition modelling approaches have been implemented as well. For instance, Grant (1998), Tang et al (2010 and Raivonen et al (2017) triggered ebullition if the total pressure of water-dissolved gases exceeded the ambient pressure at a given depth, whereas in some studies (Segers et al, 2001;Granberg et al, 2001;Zhang et al, 2012) ebullition was modelled using a threshold for gaseous volume at a certain depth below surface.…”

Section: Introductionmentioning

confidence: 99%

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Technical note: Comparison of methane ebullition modelling approaches used in terrestrial wetland models

Peltola

Raivonen

et al. 2018

Biogeosciences

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Abstract. Emission via bubbling, i.e. ebullition, is one of the main methane (CH 4 ) emission pathways from wetlands to the atmosphere. Direct measurement of gas bubble formation, growth and release in the peat-water matrix is challenging and in consequence these processes are relatively unknown and are coarsely represented in current wetland CH 4 emission models. In this study we aimed to evaluate three ebullition modelling approaches and their effect on model performance. This was achieved by implementing the three approaches in one process-based CH 4 emission model. All the approaches were based on some kind of threshold: either on CH 4 pore water concentration (ECT), pressure (EPT) or free-phase gas volume (EBG) threshold. The model was run using 4 years of data from a boreal sedge fen and the results were compared with eddy covariance measurements of CH 4 fluxes.Modelled annual CH 4 emissions were largely unaffected by the different ebullition modelling approaches; however, temporal variability in CH 4 emissions varied an order of magnitude between the approaches. Hence the ebullition modelling approach drives the temporal variability in modelled CH 4 emissions and therefore significantly impacts, for instance, high-frequency (daily scale) model comparison and calibration against measurements. The modelling approach based on the most recent knowledge of the ebullition process (volume threshold, EBG) agreed the best with the measured fluxes (R 2 = 0.63) and hence produced the most reasonable results, although there was a scale mismatch between the measurements (ecosystem scale with heterogeneous ebullition locations) and model results (single horizontally homogeneous peat column). The approach should be favoured over the two other more widely used ebullition modelling approaches and researchers are encouraged to implement it into their CH 4 emission models.

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Plant mediated methane efflux from a boreal peatland complex

et al. 2021

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Purpose Aerenchymous plants are an important control for methane efflux from peatlands to the atmosphere, providing a bypass from the anoxic peat and avoiding oxidation in the oxic peat. We aimed to quantify the drivers of aerenchymous peatland species methane transport and the importance of this process for ecosystem-scale methane efflux. Methods We measured seasonal and interspecies variation in methane transport rate per gram of plant dry mass at a boreal fen and bog, which were upscaled to ecosystem-scale plant methane transport. Results Methane transport rate was better explained by plant species, leaf greenness and area than by environmental variables. Leaves appeared to transport methane even after senescence. Contrary to our expectations, both methane transport rate and the proportion of plant transport were lower in the fen (with greater sedge cover) than in the bog site. At the fen and bog, average methane transport rate was 0.7 and 1.8 mg g−1 d−1, and the proportion of seasonally variable plant transport was 7–41% and 6–90%, respectively. Species-specific differences in methane transport rate were observed at the ecosystem-scale: Scheuchzeria palustris, which accounted for 16% of the aerenchymous leaf area in the fen and displayed the greatest methane transport rate, was responsible for 45% of the ecosystem-scale plant transport. Conclusion Our study showed that plant species influence the magnitude of ecosystem-scale methane emissions through their properties of methane transport. The identification and quantification of these properties could be the pivotal next step in predicting plant methane transport in peatlands.

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HIMMELI v1.0: HelsinkI Model of MEthane buiLd-up and emIssion for peatlands

Cited by 35 publications

References 119 publications

Small spatial variability in methane emission measured from a wet patterned boreal bog

Small spatial variability in methane emission measured from a wet patterned boreal bog

Technical note: Comparison of methane ebullition modelling approaches used in terrestrial wetland models

Plant mediated methane efflux from a boreal peatland complex

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