Synergistic effects of four climate change drivers on terrestrial carbon cycling

Peter B. Reich, Sarah E. Hobbie, Tali D. Lee, Roy Rich, Melissa A. Pastore, Kally Worm

Research output: Contribution to journalArticlepeer-review

53 Scopus citations

Abstract

Disentangling impacts of multiple global changes on terrestrial carbon cycling is important, both in its own right and because such impacts can dampen or accelerate increases in atmospheric CO2 concentration. Here we report on an eight-year grassland experiment, TeRaCON, in Minnesota, United States, that factorially manipulated four drivers: temperature, rainfall, CO2 and nitrogen deposition. Net primary production increased under warming, elevated CO2 and nitrogen deposition, and decreased under diminished summer rainfall. Treatment combinations that increased net primary production also increased soil CO2 emissions, but less so, and hence ecosystem carbon storage increased overall. Productivity, soil carbon emissions and plant carbon stock responses to each individual factor were influenced by levels of the other drivers, in both amplifying and dampening ways. Percentage increases in productivity, soil carbon emissions and plant carbon stocks in response to two, three or four global changes experienced jointly were generally much greater than those expected based on the effects of each individual driver alone. Multiple global change drivers had a profound combined influence on observed outcomes that would have been poorly predicted by knowledge of each driver alone. If such interacting impacts of multiple global change drivers on carbon cycling occur widely among ecosystems, accurately projecting biosphere responses to multifactorial global changes will remain a major challenge in the decades ahead.

Original languageEnglish (US)
Pages (from-to)787-793
Number of pages7
JournalNature Geoscience
Volume13
Issue number12
DOIs
StatePublished - Dec 2020

Bibliographical note

Funding Information:
We thank numerous summer interns for assistance with the experimental operation and data collection and management. This study was funded by programs from the US National Science Foundation (NSF) Long-Term Ecological Research (DEB-0620652, DEB-1234162 and DEB-1831944), Long-Term Research in Environmental Biology (DEB-1242531 and DEB-1753859), Biological Integration Institutes (NSF-DBI-2021898), Ecosystem Sciences (NSF DEB-1120064) and MRI (DBI-1725683), as well as the US Department of Energy Programs for Ecosystem Research (DE-FG02-96ER62291).

Publisher Copyright:
© 2020, The Author(s), under exclusive licence to Springer Nature Limited.

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