Leveraging observed soil heterotrophic respiration fluxes as a novel constraint on global-scale models
Microbially explicit models may improve understanding and projections of carbon dynamics in response to future climate change, but their fidelity in simulating global-scale soil heterotrophic respiration (R H ), a stringent test for soil biogeochemical models, has never been evaluated. Here, we used...
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Online Access: | http://www.osti.gov/servlets/purl/1826030 https://www.osti.gov/biblio/1826030 https://doi.org/10.1111/gcb.15795 |
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ftosti:oai:osti.gov:1826030 2023-07-30T04:01:53+02:00 Leveraging observed soil heterotrophic respiration fluxes as a novel constraint on global-scale models Jian, Jinshi Bond‐Lamberty, Ben Hao, Dalei Sulman, Benjamin N. Patel, Kaizad F. Zheng, Jianqiu Dorheim, Kalyn Pennington, Stephanie C. Hartman, Melannie D. Warner, Dan Wieder, William R. 2022-07-11 application/pdf http://www.osti.gov/servlets/purl/1826030 https://www.osti.gov/biblio/1826030 https://doi.org/10.1111/gcb.15795 unknown http://www.osti.gov/servlets/purl/1826030 https://www.osti.gov/biblio/1826030 https://doi.org/10.1111/gcb.15795 doi:10.1111/gcb.15795 59 BASIC BIOLOGICAL SCIENCES 2022 ftosti https://doi.org/10.1111/gcb.15795 2023-07-11T10:07:42Z Microbially explicit models may improve understanding and projections of carbon dynamics in response to future climate change, but their fidelity in simulating global-scale soil heterotrophic respiration (R H ), a stringent test for soil biogeochemical models, has never been evaluated. Here, we used statistical global R H products, as well as 7821 daily site-scale R H measurements, to evaluate the spatiotemporal performance of one first-order decay model (CASA-CNP) and two microbially explicit biogeochemical models (CORPSE and MIMICS) that were forced by two different input datasets. CORPSE and MIMICS did not provide any measurable performance improvement; instead, the models were highly sensitive to the input data used to drive them. Spatial variability in R H fluxes was generally well simulated except in the northern middle latitudes (~50°N) and arid regions; models captured the seasonal variability of R H well, but showed more divergence in tropic and arctic regions. Our results demonstrate that the next generation of biogeochemical models shows promise but also needs to be improved for realistic spatiotemporal variability of R H . Finally, we emphasize the importance of net primary production, soil moisture, and soil temperature inputs, and that jointly evaluating soil models for their spatial (global scale) and temporal (site scale) performance provides crucial benchmarks for improving biogeochemical models. Other/Unknown Material Arctic Climate change SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) Arctic Global Change Biology 27 20 5392 5403 |
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SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) |
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59 BASIC BIOLOGICAL SCIENCES |
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59 BASIC BIOLOGICAL SCIENCES Jian, Jinshi Bond‐Lamberty, Ben Hao, Dalei Sulman, Benjamin N. Patel, Kaizad F. Zheng, Jianqiu Dorheim, Kalyn Pennington, Stephanie C. Hartman, Melannie D. Warner, Dan Wieder, William R. Leveraging observed soil heterotrophic respiration fluxes as a novel constraint on global-scale models |
topic_facet |
59 BASIC BIOLOGICAL SCIENCES |
description |
Microbially explicit models may improve understanding and projections of carbon dynamics in response to future climate change, but their fidelity in simulating global-scale soil heterotrophic respiration (R H ), a stringent test for soil biogeochemical models, has never been evaluated. Here, we used statistical global R H products, as well as 7821 daily site-scale R H measurements, to evaluate the spatiotemporal performance of one first-order decay model (CASA-CNP) and two microbially explicit biogeochemical models (CORPSE and MIMICS) that were forced by two different input datasets. CORPSE and MIMICS did not provide any measurable performance improvement; instead, the models were highly sensitive to the input data used to drive them. Spatial variability in R H fluxes was generally well simulated except in the northern middle latitudes (~50°N) and arid regions; models captured the seasonal variability of R H well, but showed more divergence in tropic and arctic regions. Our results demonstrate that the next generation of biogeochemical models shows promise but also needs to be improved for realistic spatiotemporal variability of R H . Finally, we emphasize the importance of net primary production, soil moisture, and soil temperature inputs, and that jointly evaluating soil models for their spatial (global scale) and temporal (site scale) performance provides crucial benchmarks for improving biogeochemical models. |
author |
Jian, Jinshi Bond‐Lamberty, Ben Hao, Dalei Sulman, Benjamin N. Patel, Kaizad F. Zheng, Jianqiu Dorheim, Kalyn Pennington, Stephanie C. Hartman, Melannie D. Warner, Dan Wieder, William R. |
author_facet |
Jian, Jinshi Bond‐Lamberty, Ben Hao, Dalei Sulman, Benjamin N. Patel, Kaizad F. Zheng, Jianqiu Dorheim, Kalyn Pennington, Stephanie C. Hartman, Melannie D. Warner, Dan Wieder, William R. |
author_sort |
Jian, Jinshi |
title |
Leveraging observed soil heterotrophic respiration fluxes as a novel constraint on global-scale models |
title_short |
Leveraging observed soil heterotrophic respiration fluxes as a novel constraint on global-scale models |
title_full |
Leveraging observed soil heterotrophic respiration fluxes as a novel constraint on global-scale models |
title_fullStr |
Leveraging observed soil heterotrophic respiration fluxes as a novel constraint on global-scale models |
title_full_unstemmed |
Leveraging observed soil heterotrophic respiration fluxes as a novel constraint on global-scale models |
title_sort |
leveraging observed soil heterotrophic respiration fluxes as a novel constraint on global-scale models |
publishDate |
2022 |
url |
http://www.osti.gov/servlets/purl/1826030 https://www.osti.gov/biblio/1826030 https://doi.org/10.1111/gcb.15795 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Climate change |
genre_facet |
Arctic Climate change |
op_relation |
http://www.osti.gov/servlets/purl/1826030 https://www.osti.gov/biblio/1826030 https://doi.org/10.1111/gcb.15795 doi:10.1111/gcb.15795 |
op_doi |
https://doi.org/10.1111/gcb.15795 |
container_title |
Global Change Biology |
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27 |
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20 |
container_start_page |
5392 |
op_container_end_page |
5403 |
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1772812636168126464 |