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Title: Interannual variability of ecosystem carbon exchange: From observation to prediction

Abstract

Here, terrestrial ecosystems have sequestered, on average, the equivalent of 30% of anthropogenic carbon (C) emissions during the past decades, but annual sequestration varies from year to year. For effective C management, it is imperative to develop a predictive understanding of the interannual variability (IAV) of terrestrial net ecosystem C exchange (NEE). Location: Global terrestrial ecosystems. Furthermore, we conducted a comprehensive review to examine the IAV of NEE at global, regional and ecosystem scales. Then we outlined a conceptual framework for understanding how anomalies in climate factors impact ecological processes of C cycling and thus influence the IAV of NEE through biogeochemical regulation. As a result, the phenomenon of IAV in land NEE has been ubiquitously observed at global, regional and ecosystem scales. Global IAV is often attributable to either tropical or semi-arid regions, or to some combination thereof, which is still under debate. Previous studies focus on identifying climate factors as driving forces of IAV, whereas biological mechanisms underlying the IAV of ecosystem NEE are less clear. We found that climate anomalies affect the IAV of NEE primarily through their differential impacts on ecosystem C uptake and respiration. Moreover, recent studies suggest that the carbon uptake period makes lessmore » contribution than the carbon uptake amplitude to IAV in NEE. Although land models incorporate most processes underlying IAV, their efficacy to predict the IAV in NEE remains low. In conclusion, to improve our ability to predict future IAV of the terrestrial C cycle, we have to understand biological mechanisms through which anomalies in climate factors cause the IAV of NEE. Future research needs to pay more attention not only to the differential effects of climate anomalies on photosynthesis and respiration but also to the relative importance of the C uptake period and amplitude in causing the IAV of NEE. Ultimately, we need multiple independent approaches, such as benchmark analysis, data assimilation and time-series statistics, to integrate data, modelling frameworks and theory to improve our ability to predict future IAV in the terrestrial C cycle.« less

Authors:
ORCiD logo [1];  [1];  [2];  [3];  [4];  [5];  [1];  [6];  [7];  [8];  [1];  [1];  [1]
+ Show Author Affiliations
  1. Chinese Academy of Sciences (CAS), Beijing (China); Univ. of Chinese Academy of Sciences, Beijing (China)
  2. Univ. of Oklahoma, Norman, OK (United States)
  3. Montana State Univ., Bozeman, MT (United States)
  4. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  5. NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States)
  6. Peking Univ., Beijing (China)
  7. East China Normal Univ., Shanghai (China)
  8. Chinese Academy of Sciences (CAS), Beijing (China); Chinese Academy of Sciences, Xi'an (China)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1476560
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
Global Ecology and Biogeography
Additional Journal Information:
Journal Volume: 26; Journal Issue: 11; Related Information: © 2017 John Wiley & Sons Ltd; Journal ID: ISSN 1466-822X
Publisher:
Wiley
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; climate change; interannual variability; net ecosystem exchange; photosynthesis; respiration

Citation Formats

Niu, Shuli, Fu, Zheng, Luo, Yiqi, Stoy, Paul C., Keenan, Trevor F., Poulter, Benjamin, Zhang, Leiming, Piao, Shilong, Zhou, Xuhui, Zheng, Han, Han, Jiayin, Wang, Qiufeng, and Yu, Guirui. Interannual variability of ecosystem carbon exchange: From observation to prediction. United States: N. p., 2017. Web. doi:10.1111/geb.12633.
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Niu, Shuli, Fu, Zheng, Luo, Yiqi, Stoy, Paul C., Keenan, Trevor F., Poulter, Benjamin, Zhang, Leiming, Piao, Shilong, Zhou, Xuhui, Zheng, Han, Han, Jiayin, Wang, Qiufeng, & Yu, Guirui. Interannual variability of ecosystem carbon exchange: From observation to prediction. United States. https://doi.org/10.1111/geb.12633
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Niu, Shuli, Fu, Zheng, Luo, Yiqi, Stoy, Paul C., Keenan, Trevor F., Poulter, Benjamin, Zhang, Leiming, Piao, Shilong, Zhou, Xuhui, Zheng, Han, Han, Jiayin, Wang, Qiufeng, and Yu, Guirui. Sun . "Interannual variability of ecosystem carbon exchange: From observation to prediction". United States. https://doi.org/10.1111/geb.12633. https://www.osti.gov/servlets/purl/1476560.
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@article{osti_1476560,
title = {Interannual variability of ecosystem carbon exchange: From observation to prediction},
author = {Niu, Shuli and Fu, Zheng and Luo, Yiqi and Stoy, Paul C. and Keenan, Trevor F. and Poulter, Benjamin and Zhang, Leiming and Piao, Shilong and Zhou, Xuhui and Zheng, Han and Han, Jiayin and Wang, Qiufeng and Yu, Guirui},
abstractNote = {Here, terrestrial ecosystems have sequestered, on average, the equivalent of 30% of anthropogenic carbon (C) emissions during the past decades, but annual sequestration varies from year to year. For effective C management, it is imperative to develop a predictive understanding of the interannual variability (IAV) of terrestrial net ecosystem C exchange (NEE). Location: Global terrestrial ecosystems. Furthermore, we conducted a comprehensive review to examine the IAV of NEE at global, regional and ecosystem scales. Then we outlined a conceptual framework for understanding how anomalies in climate factors impact ecological processes of C cycling and thus influence the IAV of NEE through biogeochemical regulation. As a result, the phenomenon of IAV in land NEE has been ubiquitously observed at global, regional and ecosystem scales. Global IAV is often attributable to either tropical or semi-arid regions, or to some combination thereof, which is still under debate. Previous studies focus on identifying climate factors as driving forces of IAV, whereas biological mechanisms underlying the IAV of ecosystem NEE are less clear. We found that climate anomalies affect the IAV of NEE primarily through their differential impacts on ecosystem C uptake and respiration. Moreover, recent studies suggest that the carbon uptake period makes less contribution than the carbon uptake amplitude to IAV in NEE. Although land models incorporate most processes underlying IAV, their efficacy to predict the IAV in NEE remains low. In conclusion, to improve our ability to predict future IAV of the terrestrial C cycle, we have to understand biological mechanisms through which anomalies in climate factors cause the IAV of NEE. Future research needs to pay more attention not only to the differential effects of climate anomalies on photosynthesis and respiration but also to the relative importance of the C uptake period and amplitude in causing the IAV of NEE. Ultimately, we need multiple independent approaches, such as benchmark analysis, data assimilation and time-series statistics, to integrate data, modelling frameworks and theory to improve our ability to predict future IAV in the terrestrial C cycle.},
doi = {10.1111/geb.12633},
journal = {Global Ecology and Biogeography},
number = 11,
volume = 26,
place = {United States},
year = {2017},
month = {9}
}
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    Impacts of Precipitation on Ecosystem Carbon Fluxes in Desert-Grasslands in Inner Mongolia, China
    journal, February 2019

    • Zhang, Rui; Zhao, Xueyong; Zuo, Xiaoan
    • Journal of Geophysical Research: Atmospheres, Vol. 124, Issue 3
    • DOI: 10.1029/2018jd028419

    Direct measurements of carbon exchange at forest disturbance sites: a review of results with the eddy covariance method
    journal, August 2019

    Forests dominate the interannual variability of the North American carbon sink
    journal, August 2018

    • Shiga, Yoichi P.; Michalak, Anna M.; Fang, Yuanyuan
    • Environmental Research Letters, Vol. 13, Issue 8
    • DOI: 10.1088/1748-9326/aad505

    Shifts in the dynamics of productivity signal ecosystem state transitions at the biome-scale
    journal, July 2018

    • Hu, Zhongmin; Guo, Qun; Li, Shenggong
    • Ecology Letters, Vol. 21, Issue 10
    • DOI: 10.1111/ele.13126

    Scaling‐up biodiversity‐ecosystem functioning research
    journal, April 2020

    • Gonzalez, Andrew; Germain, Rachel M.; Srivastava, Diane S.
    • Ecology Letters, Vol. 23, Issue 4
    • DOI: 10.1111/ele.13456

    Divergent long‐term trends and interannual variation in ecosystem resource use efficiencies of a southern boreal old black spruce forest 1999–2017
    journal, May 2019

    • Liu, Peng; Black, T. Andrew; Jassal, Rachhpal S.
    • Global Change Biology, Vol. 25, Issue 9
    • DOI: 10.1111/gcb.14674

    Maximum carbon uptake rate dominates the interannual variability of global net ecosystem exchange
    journal, July 2019

    • Fu, Zheng; Stoy, Paul C.; Poulter, Benjamin
    • Global Change Biology, Vol. 25, Issue 10
    • DOI: 10.1111/gcb.14731

    How eddy covariance flux measurements have contributed to our understanding of Global Change Biology
    journal, September 2019

    • Baldocchi, Dennis D.
    • Global Change Biology, Vol. 26, Issue 1
    • DOI: 10.1111/gcb.14807
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