Annual CO2 Budget Estimation From Chamber-Based Flux Measurements on Intensively Drained Peat Meadows: Effect of Gap-Filling Strategies
Estimating annual CO2 budgets on drained peatlands is important in understanding the significance of CO2 emissions from peatland degradation and evaluating the effectiveness of mitigation techniques. The closed-chamber technique is widely used in combination with gap-filling of CO2 fluxes by paramet...
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| Format: | Article |
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Frontiers Media S.A.
2022-05-01
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| Series: | Frontiers in Environmental Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fenvs.2022.803746/full |
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| author | Weier Liu Christian Fritz Christian Fritz Stefan T. J. Weideveld Ralf C. H. Aben Merit van den Berg Merit van den Berg Mandy Velthuis |
| author_facet | Weier Liu Christian Fritz Christian Fritz Stefan T. J. Weideveld Ralf C. H. Aben Merit van den Berg Merit van den Berg Mandy Velthuis |
| author_sort | Weier Liu |
| collection | DOAJ |
| description | Estimating annual CO2 budgets on drained peatlands is important in understanding the significance of CO2 emissions from peatland degradation and evaluating the effectiveness of mitigation techniques. The closed-chamber technique is widely used in combination with gap-filling of CO2 fluxes by parameter fitting empirical models of ecosystem respiration (Reco) and gross primary production (GPP). However, numerous gap-filling strategies are available which are suitable for different circumstances and can result in large variances in annual budget estimates. Therefore, a need for guidance on the selection of gap-filling methodology and its influence on the results exists. Here, we propose a framework of gap-filling methods with four Tiers following increasing model complexity at structural and temporal levels. Tier one is a simple parameter fitting of basic empirical models on an annual basis. Tier two adds structural complexity by including extra environmental factors such as grass height, groundwater level and drought condition. Tier three introduces temporal complexity by separation of annual datasets into seasons. Tier four is a campaign-specific parameter fitting approach, representing highest temporal complexity. The methods were demonstrated on two chamber-based CO2 flux datasets, one of which was previously published. Performance of the empirical models were compared in terms of error statistics. Annual budget estimates were indirectly validated with carbon export values. In conclusion, different gap-filling methodologies gave similar annual estimates but different intra-annual CO2 fluxes, which did not affect the detection of the treatment effects. The campaign-wise gap-filling at Tier four gave the best model performances, while Tier three seasonal gap-filling produced satisfactory results throughout, even under data scarcity. Given the need for more complete carbon balances in drained peatlands, our four-Tier framework can serve as a methodological guidance to the handling of chamber-measured CO2 fluxes, which is fundamental in understanding emissions from degraded peatlands and its mitigation. The performance of models on intra-annual data should be validated in future research with continuous measured CO2 flux data. |
| first_indexed | 2024-04-14T05:00:08Z |
| format | Article |
| id | doaj.art-d8e4966875f34215ba856eaad3b7ce50 |
| institution | Directory Open Access Journal |
| issn | 2296-665X |
| language | English |
| last_indexed | 2024-04-14T05:00:08Z |
| publishDate | 2022-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Environmental Science |
| spelling | doaj.art-d8e4966875f34215ba856eaad3b7ce502022-12-22T02:11:01ZengFrontiers Media S.A.Frontiers in Environmental Science2296-665X2022-05-011010.3389/fenvs.2022.803746803746Annual CO2 Budget Estimation From Chamber-Based Flux Measurements on Intensively Drained Peat Meadows: Effect of Gap-Filling StrategiesWeier Liu0Christian Fritz1Christian Fritz2Stefan T. J. Weideveld3Ralf C. H. Aben4Merit van den Berg5Merit van den Berg6Mandy Velthuis7Integrated Research on Energy, Environment and Society (IREES), University of Groningen, Groningen, NetherlandsIntegrated Research on Energy, Environment and Society (IREES), University of Groningen, Groningen, NetherlandsAquatic Ecology and Environmental Biology, Radboud Institute for Biological and Environmental Sciences (RIBES), Radboud University, Nijmegen, NetherlandsAquatic Ecology and Environmental Biology, Radboud Institute for Biological and Environmental Sciences (RIBES), Radboud University, Nijmegen, NetherlandsAquatic Ecology and Environmental Biology, Radboud Institute for Biological and Environmental Sciences (RIBES), Radboud University, Nijmegen, NetherlandsAquatic Ecology and Environmental Biology, Radboud Institute for Biological and Environmental Sciences (RIBES), Radboud University, Nijmegen, NetherlandsDepartment of Earth Sciences, Vrije Universiteit Amsterdam, Amsterdam, NetherlandsAquatic Ecology and Environmental Biology, Radboud Institute for Biological and Environmental Sciences (RIBES), Radboud University, Nijmegen, NetherlandsEstimating annual CO2 budgets on drained peatlands is important in understanding the significance of CO2 emissions from peatland degradation and evaluating the effectiveness of mitigation techniques. The closed-chamber technique is widely used in combination with gap-filling of CO2 fluxes by parameter fitting empirical models of ecosystem respiration (Reco) and gross primary production (GPP). However, numerous gap-filling strategies are available which are suitable for different circumstances and can result in large variances in annual budget estimates. Therefore, a need for guidance on the selection of gap-filling methodology and its influence on the results exists. Here, we propose a framework of gap-filling methods with four Tiers following increasing model complexity at structural and temporal levels. Tier one is a simple parameter fitting of basic empirical models on an annual basis. Tier two adds structural complexity by including extra environmental factors such as grass height, groundwater level and drought condition. Tier three introduces temporal complexity by separation of annual datasets into seasons. Tier four is a campaign-specific parameter fitting approach, representing highest temporal complexity. The methods were demonstrated on two chamber-based CO2 flux datasets, one of which was previously published. Performance of the empirical models were compared in terms of error statistics. Annual budget estimates were indirectly validated with carbon export values. In conclusion, different gap-filling methodologies gave similar annual estimates but different intra-annual CO2 fluxes, which did not affect the detection of the treatment effects. The campaign-wise gap-filling at Tier four gave the best model performances, while Tier three seasonal gap-filling produced satisfactory results throughout, even under data scarcity. Given the need for more complete carbon balances in drained peatlands, our four-Tier framework can serve as a methodological guidance to the handling of chamber-measured CO2 fluxes, which is fundamental in understanding emissions from degraded peatlands and its mitigation. The performance of models on intra-annual data should be validated in future research with continuous measured CO2 flux data.https://www.frontiersin.org/articles/10.3389/fenvs.2022.803746/fullclosed-chamber methodsdrained peatlandcarbon dioxideCO2 flux modelingdata interpolation |
| spellingShingle | Weier Liu Christian Fritz Christian Fritz Stefan T. J. Weideveld Ralf C. H. Aben Merit van den Berg Merit van den Berg Mandy Velthuis Annual CO2 Budget Estimation From Chamber-Based Flux Measurements on Intensively Drained Peat Meadows: Effect of Gap-Filling Strategies Frontiers in Environmental Science closed-chamber methods drained peatland carbon dioxide CO2 flux modeling data interpolation |
| title | Annual CO2 Budget Estimation From Chamber-Based Flux Measurements on Intensively Drained Peat Meadows: Effect of Gap-Filling Strategies |
| title_full | Annual CO2 Budget Estimation From Chamber-Based Flux Measurements on Intensively Drained Peat Meadows: Effect of Gap-Filling Strategies |
| title_fullStr | Annual CO2 Budget Estimation From Chamber-Based Flux Measurements on Intensively Drained Peat Meadows: Effect of Gap-Filling Strategies |
| title_full_unstemmed | Annual CO2 Budget Estimation From Chamber-Based Flux Measurements on Intensively Drained Peat Meadows: Effect of Gap-Filling Strategies |
| title_short | Annual CO2 Budget Estimation From Chamber-Based Flux Measurements on Intensively Drained Peat Meadows: Effect of Gap-Filling Strategies |
| title_sort | annual co2 budget estimation from chamber based flux measurements on intensively drained peat meadows effect of gap filling strategies |
| topic | closed-chamber methods drained peatland carbon dioxide CO2 flux modeling data interpolation |
| url | https://www.frontiersin.org/articles/10.3389/fenvs.2022.803746/full |
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