A Bayesian inference approach to determine experimental Typha latifolia paludiculture greenhouse gas exchange measured with eddy covariance

Measurements of greenhouse gas exchange (GHG) using the eddy covariance method are crucial for identifying strategies to achieve emission reductions and carbon sequestration. There are many sites that have heterogeneous land covers where it would be useful to have balances of particular land areas, such as field trials of emission mitigation strategies, but the flux footprint infrequently covers only the area of interest. Filtering the data based on a footprint area threshold can be done but may result in the loss of a high proportion of observations that contain valuable information. Here, we present a study that uses a single eddy covariance tower on the border of two land uses to compare GHG exchange from a Typha latifolia paludiculture experiment and the surrounding area (SA) which is primarily a dairy meadow. We used a Bayesian inference approach to predict carbon dioxide (CO 2 ) and methane (CH 4 ) fluxes where the relative contribution of the two source areas, derived from a two-dimensional footprint for each timestep, was used to weight and parameterise equations. Distinct differences in flux behaviour were observed when contributions of the two land areas changed and that resulted in clearly different parameter distributions. The annual totals (posterior mean ± 95% confidence interval) from the simulations showed that Typha was a net sink of CO 2 for both simulation years (−18.5 ± 2.9 and −17.8 ± 2.9 t CO 2 ha − 1 yr − 1 ) while SA was a net source (16.8 ± 2.9 and 17.4 ± 2.9 t CO 2 ha − 1 yr − 1 ). Using the 100-year global warming potential of CH 4 , even though CH 4 emissions were higher for paludiculture in both years (13.6 ± 0.6 and 15.9 ± 1.0 t CO 2 -eq ha − 1 yr − 1 ) than SA (7.1 ± 0.6 and 6.8 ± 1.2 t CO 2 -eq ha − 1 yr − 1 ), the net GHG balance indicates that Typha paludiculture is a viable strategy to limit GHG emissions from drained peatlands. • We present a new approach to model fluxes in heterogeneous situations using 1 tower • 2 years of flux data from an experimental Typha latifolia paludiculture field trial • Differences found in fluxes, parameters, and annual totals between source areas • Results indicate Typha paludiculture is a viable strategy to limit GHG emissions

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Publication Details

Journal
Agricultural and Forest Meteorology
Published
2024-08-13
DOI
https://doi.org/10.1016/j.agrformet.2024.110179
Citations
6
Primary Topic
Plant Water Relations and Carbon Dynamics
Type
article
Field-Weighted Citation Impact
1.70
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article

A Bayesian inference approach to determine experimental Typha latifolia paludiculture greenhouse gas exchange measured with eddy covariance

Pascal Wintjen, Merit van den Berg, Christian Fritz, Alexander Buzacott et al.
6 citations
Agricultural and Forest Meteorology
Plant Water Relations and Carbon Dynamics
1.70
article

A Bayesian inference approach to determine experimental Typha latifolia paludiculture greenhouse gas exchange measured with eddy covariance

Pascal Wintjen, Merit van den Berg, Christian Fritz, Alexander Buzacott, Ype van der Velde, Jeroen Pijlman, Bart Kruijt
article en
6 citations

Abstract

Measurements of greenhouse gas exchange (GHG) using the eddy covariance method are crucial for identifying strategies to achieve emission reductions and carbon sequestration. There are many sites that have heterogeneous land covers where it would be useful to have balances of particular land areas, such as field trials of emission mitigation strategies, but the flux footprint infrequently covers only the area of interest. Filtering the data based on a footprint area threshold can be done but may result in the loss of a high proportion of observations that contain valuable information. Here, we present a study that uses a single eddy covariance tower on the border of two land uses to compare GHG exchange from a Typha latifolia paludiculture experiment and the surrounding area (SA) which is primarily a dairy meadow. We used a Bayesian inference approach to predict carbon dioxide (CO 2 ) and methane (CH 4 ) fluxes where the relative contribution of the two source areas, derived from a two-dimensional footprint for each timestep, was used to weight and parameterise equations. Distinct differences in flux behaviour were observed when contributions of the two land areas changed and that resulted in clearly different parameter distributions. The annual totals (posterior mean ± 95% confidence interval) from the simulations showed that Typha was a net sink of CO 2 for both simulation years (−18.5 ± 2.9 and −17.8 ± 2.9 t CO 2 ha − 1 yr − 1 ) while SA was a net source (16.8 ± 2.9 and 17.4 ± 2.9 t CO 2 ha − 1 yr − 1 ). Using the 100-year global warming potential of CH 4 , even though CH 4 emissions were higher for paludiculture in both years (13.6 ± 0.6 and 15.9 ± 1.0 t CO 2 -eq ha − 1 yr − 1 ) than SA (7.1 ± 0.6 and 6.8 ± 1.2 t CO 2 -eq ha − 1 yr − 1 ), the net GHG balance indicates that Typha paludiculture is a viable strategy to limit GHG emissions from drained peatlands. • We present a new approach to model fluxes in heterogeneous situations using 1 tower • 2 years of flux data from an experimental Typha latifolia paludiculture field trial • Differences found in fluxes, parameters, and annual totals between source areas • Results indicate Typha paludiculture is a viable strategy to limit GHG emissions

Agricultural and Forest MeteorologyVol. 356
Radboud University Nijmegen (NL), Netherlands Organisation for Applied Scientific Research (NL), Louis Bolk Instituut (NL), Vrije Universiteit Amsterdam (NL), Wageningen University & Research (NL)
Zero hunger
Openalex Percentile: Top 17%
Plant Water Relations and Carbon Dynamics
1.70
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