Mechanistic Modeling of Microtopographic Impacts on CO2 and CH4 Fluxes in an Alaskan Tundra Ecosystem Using the CLM‐Microbe Model
Abstract Spatial heterogeneities in soil hydrology have been confirmed as a key control on CO2 and CH4 fluxes in the Arctic tundra ecosystem. In this study, we applied a mechanistic ecosystem model, CLM‐Microbe, to examine the microtopographic impacts on CO2 and CH4 fluxes across seven landscape typ...
Published in: | Journal of Advances in Modeling Earth Systems |
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2019
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Online Access: | https://doi.org/10.1029/2019MS001771 https://doaj.org/article/dfa8c097fba54973bd3e4fac7df54323 |
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ftdoajarticles:oai:doaj.org/article:dfa8c097fba54973bd3e4fac7df54323 2023-05-15T14:52:03+02:00 Mechanistic Modeling of Microtopographic Impacts on CO2 and CH4 Fluxes in an Alaskan Tundra Ecosystem Using the CLM‐Microbe Model Yihui Wang Fengming Yuan Fenghui Yuan Baohua Gu Melanie S. Hahn Margaret S. Torn Daniel M. Ricciuto Jitendra Kumar Liyuan He Donatella Zona David A. Lipson Robert Wagner Walter C. Oechel Stan D. Wullschleger Peter E. Thornton Xiaofeng Xu 2019-12-01T00:00:00Z https://doi.org/10.1029/2019MS001771 https://doaj.org/article/dfa8c097fba54973bd3e4fac7df54323 EN eng American Geophysical Union (AGU) https://doi.org/10.1029/2019MS001771 https://doaj.org/toc/1942-2466 1942-2466 doi:10.1029/2019MS001771 https://doaj.org/article/dfa8c097fba54973bd3e4fac7df54323 Journal of Advances in Modeling Earth Systems, Vol 11, Iss 12, Pp 4288-4304 (2019) Arctic tundra CH4 flux microtopographic sensitivity analysis net carbon exchange Physical geography GB3-5030 Oceanography GC1-1581 article 2019 ftdoajarticles https://doi.org/10.1029/2019MS001771 2022-12-31T16:33:14Z Abstract Spatial heterogeneities in soil hydrology have been confirmed as a key control on CO2 and CH4 fluxes in the Arctic tundra ecosystem. In this study, we applied a mechanistic ecosystem model, CLM‐Microbe, to examine the microtopographic impacts on CO2 and CH4 fluxes across seven landscape types in Utqiaġvik, Alaska: trough, low‐centered polygon (LCP) center, LCP transition, LCP rim, high‐centered polygon (HCP) center, HCP transition, and HCP rim. We first validated the CLM‐Microbe model against static‐chamber measured CO2 and CH4 fluxes in 2013 for three landscape types: trough, LCP center, and LCP rim. Model application showed that low‐elevation and thus wetter landscape types (i.e., trough, transitions, and LCP center) had larger CH4 emissions rates with greater seasonal variations than high‐elevation and drier landscape types (rims and HCP center). Sensitivity analysis indicated that substrate availability for methanogenesis (acetate, CO2 + H2) is the most important factor determining CH4 emission, and vegetation physiological properties largely affect the net ecosystem carbon exchange and ecosystem respiration in Arctic tundra ecosystems. Modeled CH4 emissions for different microtopographic features were upscaled to the eddy covariance (EC) domain with an area‐weighted approach before validation against EC‐measured CH4 fluxes. The model underestimated the EC‐measured CH4 flux by 20% and 25% at daily and hourly time steps, suggesting the importance of the time step in reporting CH4 flux. The strong microtopographic impacts on CO2 and CH4 fluxes call for a model‐data integration framework for better understanding and predicting carbon flux in the highly heterogeneous Arctic landscape. Article in Journal/Newspaper Arctic Tundra Alaska Directory of Open Access Journals: DOAJ Articles Arctic Journal of Advances in Modeling Earth Systems 11 12 4288 4304 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Arctic tundra CH4 flux microtopographic sensitivity analysis net carbon exchange Physical geography GB3-5030 Oceanography GC1-1581 |
spellingShingle |
Arctic tundra CH4 flux microtopographic sensitivity analysis net carbon exchange Physical geography GB3-5030 Oceanography GC1-1581 Yihui Wang Fengming Yuan Fenghui Yuan Baohua Gu Melanie S. Hahn Margaret S. Torn Daniel M. Ricciuto Jitendra Kumar Liyuan He Donatella Zona David A. Lipson Robert Wagner Walter C. Oechel Stan D. Wullschleger Peter E. Thornton Xiaofeng Xu Mechanistic Modeling of Microtopographic Impacts on CO2 and CH4 Fluxes in an Alaskan Tundra Ecosystem Using the CLM‐Microbe Model |
topic_facet |
Arctic tundra CH4 flux microtopographic sensitivity analysis net carbon exchange Physical geography GB3-5030 Oceanography GC1-1581 |
description |
Abstract Spatial heterogeneities in soil hydrology have been confirmed as a key control on CO2 and CH4 fluxes in the Arctic tundra ecosystem. In this study, we applied a mechanistic ecosystem model, CLM‐Microbe, to examine the microtopographic impacts on CO2 and CH4 fluxes across seven landscape types in Utqiaġvik, Alaska: trough, low‐centered polygon (LCP) center, LCP transition, LCP rim, high‐centered polygon (HCP) center, HCP transition, and HCP rim. We first validated the CLM‐Microbe model against static‐chamber measured CO2 and CH4 fluxes in 2013 for three landscape types: trough, LCP center, and LCP rim. Model application showed that low‐elevation and thus wetter landscape types (i.e., trough, transitions, and LCP center) had larger CH4 emissions rates with greater seasonal variations than high‐elevation and drier landscape types (rims and HCP center). Sensitivity analysis indicated that substrate availability for methanogenesis (acetate, CO2 + H2) is the most important factor determining CH4 emission, and vegetation physiological properties largely affect the net ecosystem carbon exchange and ecosystem respiration in Arctic tundra ecosystems. Modeled CH4 emissions for different microtopographic features were upscaled to the eddy covariance (EC) domain with an area‐weighted approach before validation against EC‐measured CH4 fluxes. The model underestimated the EC‐measured CH4 flux by 20% and 25% at daily and hourly time steps, suggesting the importance of the time step in reporting CH4 flux. The strong microtopographic impacts on CO2 and CH4 fluxes call for a model‐data integration framework for better understanding and predicting carbon flux in the highly heterogeneous Arctic landscape. |
format |
Article in Journal/Newspaper |
author |
Yihui Wang Fengming Yuan Fenghui Yuan Baohua Gu Melanie S. Hahn Margaret S. Torn Daniel M. Ricciuto Jitendra Kumar Liyuan He Donatella Zona David A. Lipson Robert Wagner Walter C. Oechel Stan D. Wullschleger Peter E. Thornton Xiaofeng Xu |
author_facet |
Yihui Wang Fengming Yuan Fenghui Yuan Baohua Gu Melanie S. Hahn Margaret S. Torn Daniel M. Ricciuto Jitendra Kumar Liyuan He Donatella Zona David A. Lipson Robert Wagner Walter C. Oechel Stan D. Wullschleger Peter E. Thornton Xiaofeng Xu |
author_sort |
Yihui Wang |
title |
Mechanistic Modeling of Microtopographic Impacts on CO2 and CH4 Fluxes in an Alaskan Tundra Ecosystem Using the CLM‐Microbe Model |
title_short |
Mechanistic Modeling of Microtopographic Impacts on CO2 and CH4 Fluxes in an Alaskan Tundra Ecosystem Using the CLM‐Microbe Model |
title_full |
Mechanistic Modeling of Microtopographic Impacts on CO2 and CH4 Fluxes in an Alaskan Tundra Ecosystem Using the CLM‐Microbe Model |
title_fullStr |
Mechanistic Modeling of Microtopographic Impacts on CO2 and CH4 Fluxes in an Alaskan Tundra Ecosystem Using the CLM‐Microbe Model |
title_full_unstemmed |
Mechanistic Modeling of Microtopographic Impacts on CO2 and CH4 Fluxes in an Alaskan Tundra Ecosystem Using the CLM‐Microbe Model |
title_sort |
mechanistic modeling of microtopographic impacts on co2 and ch4 fluxes in an alaskan tundra ecosystem using the clm‐microbe model |
publisher |
American Geophysical Union (AGU) |
publishDate |
2019 |
url |
https://doi.org/10.1029/2019MS001771 https://doaj.org/article/dfa8c097fba54973bd3e4fac7df54323 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Tundra Alaska |
genre_facet |
Arctic Tundra Alaska |
op_source |
Journal of Advances in Modeling Earth Systems, Vol 11, Iss 12, Pp 4288-4304 (2019) |
op_relation |
https://doi.org/10.1029/2019MS001771 https://doaj.org/toc/1942-2466 1942-2466 doi:10.1029/2019MS001771 https://doaj.org/article/dfa8c097fba54973bd3e4fac7df54323 |
op_doi |
https://doi.org/10.1029/2019MS001771 |
container_title |
Journal of Advances in Modeling Earth Systems |
container_volume |
11 |
container_issue |
12 |
container_start_page |
4288 |
op_container_end_page |
4304 |
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1766323181374668800 |