Abstract
Whether and how CO2 and nitrogen (N) availability interact to influence carbon (C) cycling processes such as soil respiration remains a question of considerable uncertainty in projecting future C–climate feedbacks, which are strongly influenced by multiple global change drivers, including elevated atmospheric CO2 concentrations (eCO2) and increased N deposition. However, because decades of research on the responses of ecosystems to eCO2 and N enrichment have been done largely independently, their interactive effects on soil respiratory CO2 efflux remain unresolved. Here, we show that in a multifactor free-air CO2 enrichment experiment, BioCON (Biodiversity, CO2, and N deposition) in Minnesota, the positive response of soil respiration to eCO2 gradually strengthened at ambient (low) N supply but not enriched (high) N supply for the 12-y experimental period from 1998 to 2009. In contrast to earlier years, eCO2 stimulated soil respiration twice as much at low than at high N supply from 2006 to 2009. In parallel, microbial C degradation genes were significantly boosted by eCO2 at low but not high N supply. Incorporating those functional genes into a coupled C–N ecosystem model reduced model parameter uncertainty and improved the projections of the effects of different CO2 and N levels on soil respiration. If our observed results generalize to other ecosystems, they imply widely positive effects of eCO2 on soil respiration even in infertile systems.
Original language | English (US) |
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Pages (from-to) | 33317-33324 |
Number of pages | 8 |
Journal | Proceedings of the National Academy of Sciences of the United States of America |
Volume | 117 |
Issue number | 52 |
DOIs | |
State | Published - Dec 29 2020 |
Bibliographical note
Funding Information:The data analysis by Q.G. was supported by the National Science Foundation of China (41825016), the Second Tibetan Plateau Scientific Expedition and Research program (2019QZKK0503), and the special fund of the State Key Joint Laboratory of Environment Simulation and Pollution Control (19L01ESPC). The BioCON experiment was funded by the US Department of Agriculture (USDA) (Project 2007-35319-18305) through NSF-USDA Microbial Observatories Program, Long-Term Ecological Research (LTER) grants DEB-0620652, DEB-1234162, and DEB-1831944, Long-Term Research in Environmental Biology (LTREB) grants DEB-1242531 and DEB-1753859, Biological Integration Institutes grant NSF-DBI-2021898, Ecosystem Sciences grant DEB-1120064, and Biocomplexity grant DEB-0322057 and by US Department of Energy Programs for Ecosystem Research grant DE-FG02-96ER62291 and the University of Minnesota to P.B.R. and/or S.E.H. The experimental measurements with GeoChip were supported by the USDA (Project 2007-35319-18305) through the NSF-USDA Microbial Observatories Program, and the modeling work was supported by the US Department of Energy, Office of Science, Genomic Science Program under Awards DESC0004601, DE-SC0010715, DE-SC0014079, DE-SC0016247, and DE-SC0020163 and by the Office of the Vice President for Research at the University of Oklahoma, all to J.Z.
Funding Information:
ACKNOWLEDGMENTS. The data analysis by Q.G. was supported by the National Science Foundation of China (41825016), the Second Tibetan Plateau Scientific Expedition and Research program (2019QZKK0503), and the special fund of the State Key Joint Laboratory of Environment Simulation and Pollution Control (19L01ESPC). The BioCON experiment was funded by the US Department of Agriculture (USDA) (Project 2007-35319-18305) through NSF-USDA Microbial Observatories Program, Long-Term Ecological Research (LTER) grants DEB-0620652, DEB-1234162, and DEB-1831944, Long-Term Research in Environmental Biology (LTREB) grants DEB-1242531 and DEB-1753859, Biological Integration Institutes grant NSF-DBI-2021898, Ecosystem Sciences grant DEB-1120064, and Biocomplexity grant DEB-0322057 and by US Department of Energy Programs for Ecosystem Research grant DE-FG02-96ER62291 and the University of Minnesota to P.B.R. and/or S.E.H. The experimental measurements with GeoChip were supported by the USDA (Project 2007-35319-18305) through the NSF-USDA Microbial Observatories Program, and the modeling work was supported by the US Department of Energy, Office of Science, Genomic Science Program under Awards DESC0004601, DE-SC0010715, DE-SC0014079, DE-SC0016247, and DE-SC0020163 and by the Office of the Vice President for Research at the University of Oklahoma, all to J.Z.
Publisher Copyright:
© 2020 National Academy of Sciences. All rights reserved.
Keywords
- Earth ecosystem model
- Elevated CO
- Metagenomics
- Nitrogen deposition
- Soil respiration
- Grassland
- Nitrogen/pharmacology
- Aerobiosis
- Soil/chemistry
- Soil Microbiology
- Computer Simulation
- Carbon Dioxide/pharmacology
PubMed: MeSH publication types
- Research Support, Non-U.S. Gov't
- Research Support, U.S. Gov't, Non-P.H.S.
- Journal Article