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The Challenge: Estimating Greenhouse Gas Budgets from Heterogeneous Forest Soils
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Forests soils are characterized by a pronounced spatial variability of chemical, biological and physical soil parameters, and therefore pose a great challenge for the monitoring of greenhouse gas fluxes (GHG). Disturbances such as compaction caused by forest machinery, affecting up to 40% of the area of an actively managed forest stand, additionally contribute to the variation of soil conditions over short distances and lead to large spatial differences in GHG fluxes.To address spatial variability, current approaches often rely on spatially distributed manual measurements, which provide good spatial coverage but typically miss episodic extreme events, leading to an underestimation of GHG fluxes. In contrast, automated measurements provide high temporal resolution but are usually limited to small areas and, due to a lack of spatial replication, cannot capture the forest stand heterogeneity properly. Resolving this trade-off is crucial for improving the accuracy of GHG budgets. Therefore, our study aims not only to provide high-resolution temporal data on soil GHG fluxes, but also to combine automatic and manual measurements through means of modeling to overcome these limitations.The long-term monitoring site Klausen-Leopoldsdorf, Austria, established in 1990 as part of the Austrian ICP Forests Program, offers the opportunity to address this challenge. The beech forest on Stagnic Cambisol developed from Flysch sediments, is representative for the highly productive, forested parts of the Wienerwald. In 2016, part of the forest stand was thinned using a fully mechanized harvesting system (single-grip harvester, forwarder), creating a plot of a thinned beech stand (BS) with skid trails (ST). Within this area, an automated GHG measurement system was installed to measure CO2 soil fluxes at 5-minute intervals at 2 subplots with 6 chambers each (LI-840A, LI-COR Inc., USA). In 2022, the measurement equipment system was replaced by 2 LI-COR trace gas analyzers (LI-7810 and LI-7820) to facilitate the detection of CH4 and N2O soil fluxes. This setup allows for high-resolution measurements of GHG fluxes from disturbed and undisturbed soils. From 2022 to 2024, supplemental manual measurements were carried out at 3-week intervals on collars (n = 24) along a transect within the 19-ha forest stand using a soil respiration chamber (8200-01S LI-COR Smart Chamber). Stratified regression modeling of the automated and manual measurements is used to calculate GHG fluxes at the forest stand scale.Preliminary results highlight substantial differences in GHG flux rates between control (BS) and compacted (ST) areas. Disturbed areas exhibit elevated and prolonged emission peaks following precipitation events. These findings underscore the huge impact of soil compaction on heavy clayey soils and altered soil structure on GHG dynamics.By combining high-frequency soil flux measurements with comprehensive environmental monitoring, this study improves the understanding of factors driving GHG flux variability. These findings contribute to more accurate stand-scale GHG budgets for managed temperate beech forests and provide a robust dataset for upscaling to national GHG budgets and improving biogeochemical models.
Title: The Challenge: Estimating Greenhouse Gas Budgets from Heterogeneous Forest Soils
Description:
Forests soils are characterized by a pronounced spatial variability of chemical, biological and physical soil parameters, and therefore pose a great challenge for the monitoring of greenhouse gas fluxes (GHG).
Disturbances such as compaction caused by forest machinery, affecting up to 40% of the area of an actively managed forest stand, additionally contribute to the variation of soil conditions over short distances and lead to large spatial differences in GHG fluxes.
To address spatial variability, current approaches often rely on spatially distributed manual measurements, which provide good spatial coverage but typically miss episodic extreme events, leading to an underestimation of GHG fluxes.
In contrast, automated measurements provide high temporal resolution but are usually limited to small areas and, due to a lack of spatial replication, cannot capture the forest stand heterogeneity properly.
Resolving this trade-off is crucial for improving the accuracy of GHG budgets.
Therefore, our study aims not only to provide high-resolution temporal data on soil GHG fluxes, but also to combine automatic and manual measurements through means of modeling to overcome these limitations.
The long-term monitoring site Klausen-Leopoldsdorf, Austria, established in 1990 as part of the Austrian ICP Forests Program, offers the opportunity to address this challenge.
The beech forest on Stagnic Cambisol developed from Flysch sediments, is representative for the highly productive, forested parts of the Wienerwald.
In 2016, part of the forest stand was thinned using a fully mechanized harvesting system (single-grip harvester, forwarder), creating a plot of a thinned beech stand (BS) with skid trails (ST).
Within this area, an automated GHG measurement system was installed to measure CO2 soil fluxes at 5-minute intervals at 2 subplots with 6 chambers each (LI-840A, LI-COR Inc.
, USA).
In 2022, the measurement equipment system was replaced by 2 LI-COR trace gas analyzers (LI-7810 and LI-7820) to facilitate the detection of CH4 and N2O soil fluxes.
This setup allows for high-resolution measurements of GHG fluxes from disturbed and undisturbed soils.
From 2022 to 2024, supplemental manual measurements were carried out at 3-week intervals on collars (n = 24) along a transect within the 19-ha forest stand using a soil respiration chamber (8200-01S LI-COR Smart Chamber).
Stratified regression modeling of the automated and manual measurements is used to calculate GHG fluxes at the forest stand scale.
Preliminary results highlight substantial differences in GHG flux rates between control (BS) and compacted (ST) areas.
Disturbed areas exhibit elevated and prolonged emission peaks following precipitation events.
These findings underscore the huge impact of soil compaction on heavy clayey soils and altered soil structure on GHG dynamics.
By combining high-frequency soil flux measurements with comprehensive environmental monitoring, this study improves the understanding of factors driving GHG flux variability.
These findings contribute to more accurate stand-scale GHG budgets for managed temperate beech forests and provide a robust dataset for upscaling to national GHG budgets and improving biogeochemical models.
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