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Title: Gross primary production responses to warming, elevated CO 2 , and irrigation: quantifying the drivers of ecosystem physiology in a semiarid grassland

Abstract

Abstract Determining whether the terrestrial biosphere will be a source or sink of carbon (C) under a future climate of elevated CO 2 ( eCO 2 ) and warming requires accurate quantification of gross primary production ( GPP ), the largest flux of C in the global C cycle. We evaluated 6 years (2007–2012) of flux‐derived GPP data from the Prairie Heating and CO 2 Enrichment ( PHACE ) experiment, situated in a grassland in Wyoming, USA . The GPP data were used to calibrate a light response model whose basic formulation has been successfully used in a variety of ecosystems. The model was extended by modeling maximum photosynthetic rate ( A max ) and light‐use efficiency ( Q ) as functions of soil water, air temperature, vapor pressure deficit, vegetation greenness, and nitrogen at current and antecedent (past) timescales. The model fits the observed GPP well ( R 2  = 0.79), which was confirmed by other model performance checks that compared different variants of the model (e.g. with and without antecedent effects). Stimulation of cumulative 6‐year GPP by warming (29%, P  = 0.02) and eCO 2 (26%, P  = 0.07) was primarily driven by enhanced C uptake during spring (129%, P  = 0.001) andmore » fall (124%, P  = 0.001), respectively, which was consistent across years. Antecedent air temperature (Tair ant ) and vapor pressure deficit ( VPD ant ) effects on A max (over the past 3–4 days and 1–3 days, respectively) were the most significant predictors of temporal variability in GPP among most treatments. The importance of VPD ant suggests that atmospheric drought is important for predicting GPP under current and future climate; we highlight the need for experimental studies to identify the mechanisms underlying such antecedent effects. Finally, posterior estimates of cumulative GPP under control and eCO 2 treatments were tested as a benchmark against 12 terrestrial biosphere models ( TBM s). The narrow uncertainties of these data‐driven GPP estimates suggest that they could be useful semi‐independent data streams for validating TBMs.« less

Authors:
ORCiD logo [1];  [2];  [3];  [4]; ORCiD logo [5]; ORCiD logo [6];  [7];  [8];  [8];  [9];  [10];  [11];  [12];  [12];  [13];  [14];  [15];  [16]
  1. Lancaster Environment Centre (United Kingdom)
  2. Northern Arizona Univ., Flagstaff, AZ (United States). School of Informatics, Computing, and Cyber Systems; Northern Arizona Univ., Flagstaff, AZ (United States). Dept. of Biological Sciences
  3. Northern Arizona Univ., Flagstaff, AZ (United States). Dept. of Biological Sciences
  4. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Environmental Sciences Division and Climate Change Science Inst.
  5. Macquarie Univ., NSW (Australia). Dept. of Biological Sciences
  6. Univ. of Western Sydney, NSW (Australia). Hawkesbury Inst. for the Environment
  7. Univ. of Wyoming, Laramie, WY (United States). Dept. of Botany
  8. Colorado State Univ., Fort Collins, CO (United States). Natural Resource Ecology Lab.
  9. Univ. Paris-Saclay, Gif-sur-Yvette (France). Lab. des Sciences du Climat et de l'Environnement (LSCE)
  10. Univ. of Exeter (United Kingdom). College of Engineering, Mathematics, and Physical Sciences
  11. Commonwealth Scientific and Industrial Research Organization (CSIRO), Ocean and Atmosphere, Aspendale, Vic. (Australia)
  12. Max Planck Inst. for Biogeochemistry, Jena (Germany). Biogeochemical Integration Dept.
  13. Univ. of Illinois, Urbana, IL (United States). Dept. of Atmospheric Sciences
  14. Senckenberg Biodiversity and Climate Research Centre, Frankfurt (Germany)
  15. Univ. of Oklahoma, Norman, OK (United States). Dept. of Microbiology & Plant Biology; East China Normal Univ. (ECNU), Shanghai (China). Research Center for Global Change and Ecological Forecasting
  16. Univ. of Western Sydney, NSW (Australia). Hawkesbury Inst. for the Environment; Univ. of Wyoming, Laramie, WY (United States). Dept. of Botany
Publication Date:
Research Org.:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1349600
Alternate Identifier(s):
OSTI ID: 1400811
Grant/Contract Number:  
AC05-00OR22725; DE‐SC0006973
Resource Type:
Accepted Manuscript
Journal Name:
Global Change Biology
Additional Journal Information:
Journal Volume: 23; Journal Issue: 8; Journal ID: ISSN 1354-1013
Publisher:
Wiley
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES

Citation Formats

Ryan, Edmund M., Ogle, Kiona, Peltier, Drew, Walker, Anthony P., de Kauwe, Martin G., Medlyn, Belinda E., Williams, David G., Parton, William, Asao, Shinichi, Guenet, Bertrand, Harper, Anna B., Lu, Xingjie, Luus, Kristina A., Zaehle, Sönke, Shu, Shijie, Werner, Christian, Xia, Jianyang, and Pendall, Elise. Gross primary production responses to warming, elevated CO 2 , and irrigation: quantifying the drivers of ecosystem physiology in a semiarid grassland. United States: N. p., 2016. Web. doi:10.1111/gcb.13602.
Ryan, Edmund M., Ogle, Kiona, Peltier, Drew, Walker, Anthony P., de Kauwe, Martin G., Medlyn, Belinda E., Williams, David G., Parton, William, Asao, Shinichi, Guenet, Bertrand, Harper, Anna B., Lu, Xingjie, Luus, Kristina A., Zaehle, Sönke, Shu, Shijie, Werner, Christian, Xia, Jianyang, & Pendall, Elise. Gross primary production responses to warming, elevated CO 2 , and irrigation: quantifying the drivers of ecosystem physiology in a semiarid grassland. United States. https://doi.org/10.1111/gcb.13602
Ryan, Edmund M., Ogle, Kiona, Peltier, Drew, Walker, Anthony P., de Kauwe, Martin G., Medlyn, Belinda E., Williams, David G., Parton, William, Asao, Shinichi, Guenet, Bertrand, Harper, Anna B., Lu, Xingjie, Luus, Kristina A., Zaehle, Sönke, Shu, Shijie, Werner, Christian, Xia, Jianyang, and Pendall, Elise. Mon . "Gross primary production responses to warming, elevated CO 2 , and irrigation: quantifying the drivers of ecosystem physiology in a semiarid grassland". United States. https://doi.org/10.1111/gcb.13602. https://www.osti.gov/servlets/purl/1349600.
@article{osti_1349600,
title = {Gross primary production responses to warming, elevated CO 2 , and irrigation: quantifying the drivers of ecosystem physiology in a semiarid grassland},
author = {Ryan, Edmund M. and Ogle, Kiona and Peltier, Drew and Walker, Anthony P. and de Kauwe, Martin G. and Medlyn, Belinda E. and Williams, David G. and Parton, William and Asao, Shinichi and Guenet, Bertrand and Harper, Anna B. and Lu, Xingjie and Luus, Kristina A. and Zaehle, Sönke and Shu, Shijie and Werner, Christian and Xia, Jianyang and Pendall, Elise},
abstractNote = {Abstract Determining whether the terrestrial biosphere will be a source or sink of carbon (C) under a future climate of elevated CO 2 ( eCO 2 ) and warming requires accurate quantification of gross primary production ( GPP ), the largest flux of C in the global C cycle. We evaluated 6 years (2007–2012) of flux‐derived GPP data from the Prairie Heating and CO 2 Enrichment ( PHACE ) experiment, situated in a grassland in Wyoming, USA . The GPP data were used to calibrate a light response model whose basic formulation has been successfully used in a variety of ecosystems. The model was extended by modeling maximum photosynthetic rate ( A max ) and light‐use efficiency ( Q ) as functions of soil water, air temperature, vapor pressure deficit, vegetation greenness, and nitrogen at current and antecedent (past) timescales. The model fits the observed GPP well ( R 2  = 0.79), which was confirmed by other model performance checks that compared different variants of the model (e.g. with and without antecedent effects). Stimulation of cumulative 6‐year GPP by warming (29%, P  = 0.02) and eCO 2 (26%, P  = 0.07) was primarily driven by enhanced C uptake during spring (129%, P  = 0.001) and fall (124%, P  = 0.001), respectively, which was consistent across years. Antecedent air temperature (Tair ant ) and vapor pressure deficit ( VPD ant ) effects on A max (over the past 3–4 days and 1–3 days, respectively) were the most significant predictors of temporal variability in GPP among most treatments. The importance of VPD ant suggests that atmospheric drought is important for predicting GPP under current and future climate; we highlight the need for experimental studies to identify the mechanisms underlying such antecedent effects. Finally, posterior estimates of cumulative GPP under control and eCO 2 treatments were tested as a benchmark against 12 terrestrial biosphere models ( TBM s). The narrow uncertainties of these data‐driven GPP estimates suggest that they could be useful semi‐independent data streams for validating TBMs.},
doi = {10.1111/gcb.13602},
journal = {Global Change Biology},
number = 8,
volume = 23,
place = {United States},
year = {Mon Dec 19 00:00:00 EST 2016},
month = {Mon Dec 19 00:00:00 EST 2016}
}

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Cited by: 35 works
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Figures / Tables:

Figure 1 Figure 1: Observed versus predicted GPP for each treatment. The predicted values were obtained from the main model (with antecedent effects) and are represented by the posterior means and central 95% credible intervals of replicated observations (Gelman et al., 2013) of GPP, based on Eqns (1) and (2). The solid,more » diagonal gray line represents the 1:1 line; the dashed line represents the best fit line. Treatment codes involve combinations of: c (ambient CO2), C (elevated CO2), t (no warming), T (warming), d (deep irrigation), or s (shallow irrigation).« less

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