Gross primary production responses to warming, elevated CO2, and irrigation: quantifying the drivers of ecosystem physiology in a semiarid grassland

Edmund M. Ryan; Kiona Ogle; Drew Peltier; Anthony P. Walker; Martin G. De Kauwe; Belinda E. Medlyn; David G. Williams; William Parton; Shinichi Asao; Bertrand Guenet; Anna B. Harper; Xingjie Lu; Kristina A. Luus; Sönke Zaehle; Shijie Shu; Christian Werner; Jianyang Xia; Elise Pendall

doi:10.1111/gcb.13602

Gross primary production responses to warming, elevated CO₂, and irrigation: quantifying the drivers of ecosystem physiology in a semiarid grassland

Edmund M. Ryan, Kiona Ogle, Drew Peltier, Anthony P. Walker, Martin G. De Kauwe, Belinda E. Medlyn, David G. Williams, William Parton, Shinichi Asao, Bertrand Guenet, Anna B. Harper, Xingjie Lu, Kristina A. Luus, Sönke Zaehle, Shijie Shu, Christian Werner, Jianyang Xia, Elise Pendall

Ecosystem Processes

Research output: Contribution to journal › Article › peer-review

39 Scopus citations

Abstract

Determining whether the terrestrial biosphere will be a source or sink of carbon (C) under a future climate of elevated CO₂ (eCO₂) 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 CO₂ 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 (R² = 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 eCO₂ (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 eCO₂ treatments were tested as a benchmark against 12 terrestrial biosphere models (TBMs). The narrow uncertainties of these data-driven GPP estimates suggest that they could be useful semi-independent data streams for validating TBMs.

Original language	English
Pages (from-to)	3092-3106
Number of pages	15
Journal	Global Change Biology
Volume	23
Issue number	8
DOIs	https://doi.org/10.1111/gcb.13602
State	Published - Aug 2017

Funding

This material is based upon work supported by the US Department of Agriculture, Agricultural Research Service Climate Change, Soils & Emissions Program, USDA-CSREES Soil Processes Program (#2008-35107-18655), US Department of Energy Office of Science (BER), through the Terrestrial Ecosystem Science program (#DE-SC0006973), and the Western Regional Center of the National Institute for Climatic Change Research, and by the National Science Foundation (DEB#1021559). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. We thank D. LeCain, J.A. Morgan, J. Heisler-White, A. Brennan, S. Bachman, Y. Sorokin, T.J. Zelikova, D. Blumenthal, K. Mueller, and numerous others for assistance in data collection and operation of PHACE facilities, and B. Yang for use of his gap-filled meteorological data at the site. We also thank D. Kinsman for his helpful comments on the discussion section.

Keywords

Bayesian modeling
carbon cycle
elevated CO
grasslands
gross primary production
multifactor global change experiment
warming

Access to Document

10.1111/gcb.13602

Cite this

Ryan, E. M., Ogle, K., Peltier, D., Walker, A. P., De Kauwe, M. G., Medlyn, B. E., Williams, D. G., Parton, W., Asao, S., Guenet, B., Harper, A. B., Lu, X., Luus, K. A., Zaehle, S., Shu, S., Werner, C., Xia, J., & Pendall, E. (2017). Gross primary production responses to warming, elevated CO₂, and irrigation: quantifying the drivers of ecosystem physiology in a semiarid grassland. Global Change Biology, 23(8), 3092-3106. https://doi.org/10.1111/gcb.13602

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title = "Gross primary production responses to warming, elevated CO2, and irrigation: quantifying the drivers of ecosystem physiology in a semiarid grassland",

abstract = "Determining whether the terrestrial biosphere will be a source or sink of carbon (C) under a future climate of elevated CO2 (eCO2) 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 CO2 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 (Amax) 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 (R2 = 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 eCO2 (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 (Tairant) and vapor pressure deficit (VPDant) effects on Amax (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 VPDant 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 eCO2 treatments were tested as a benchmark against 12 terrestrial biosphere models (TBMs). The narrow uncertainties of these data-driven GPP estimates suggest that they could be useful semi-independent data streams for validating TBMs.",

keywords = "Bayesian modeling, carbon cycle, elevated CO, grasslands, gross primary production, multifactor global change experiment, warming",

author = "Ryan, {Edmund M.} and Kiona Ogle and Drew Peltier and Walker, {Anthony P.} and {De Kauwe}, {Martin G.} and Medlyn, {Belinda E.} and Williams, {David G.} and William Parton and Shinichi Asao and Bertrand Guenet and Harper, {Anna B.} and Xingjie Lu and Luus, {Kristina A.} and S{\"o}nke Zaehle and Shijie Shu and Christian Werner and Jianyang Xia and Elise Pendall",

note = "Publisher Copyright: {\textcopyright} 2017 John Wiley & Sons Ltd",

year = "2017",

month = aug,

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language = "English",

volume = "23",

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Ryan, EM, Ogle, K, Peltier, D, Walker, AP, De Kauwe, MG, Medlyn, BE, Williams, DG, Parton, W, Asao, S, Guenet, B, Harper, AB, Lu, X, Luus, KA, Zaehle, S, Shu, S, Werner, C, Xia, J & Pendall, E 2017, 'Gross primary production responses to warming, elevated CO₂, and irrigation: quantifying the drivers of ecosystem physiology in a semiarid grassland', Global Change Biology, vol. 23, no. 8, pp. 3092-3106. https://doi.org/10.1111/gcb.13602

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T1 - Gross primary production responses to warming, elevated CO2, and irrigation

T2 - quantifying the drivers of ecosystem physiology in a semiarid grassland

AU - Ryan, Edmund M.

AU - Ogle, Kiona

AU - Peltier, Drew

AU - Walker, Anthony P.

AU - De Kauwe, Martin G.

AU - Medlyn, Belinda E.

AU - Williams, David G.

AU - Parton, William

AU - Asao, Shinichi

AU - Guenet, Bertrand

AU - Harper, Anna B.

AU - Lu, Xingjie

AU - Luus, Kristina A.

AU - Zaehle, Sönke

AU - Shu, Shijie

AU - Werner, Christian

AU - Xia, Jianyang

AU - Pendall, Elise

PY - 2017/8

Y1 - 2017/8

N2 - Determining whether the terrestrial biosphere will be a source or sink of carbon (C) under a future climate of elevated CO2 (eCO2) 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 CO2 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 (Amax) 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 (R2 = 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 eCO2 (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 (Tairant) and vapor pressure deficit (VPDant) effects on Amax (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 VPDant 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 eCO2 treatments were tested as a benchmark against 12 terrestrial biosphere models (TBMs). The narrow uncertainties of these data-driven GPP estimates suggest that they could be useful semi-independent data streams for validating TBMs.

AB - Determining whether the terrestrial biosphere will be a source or sink of carbon (C) under a future climate of elevated CO2 (eCO2) 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 CO2 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 (Amax) 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 (R2 = 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 eCO2 (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 (Tairant) and vapor pressure deficit (VPDant) effects on Amax (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 VPDant 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 eCO2 treatments were tested as a benchmark against 12 terrestrial biosphere models (TBMs). The narrow uncertainties of these data-driven GPP estimates suggest that they could be useful semi-independent data streams for validating TBMs.

KW - Bayesian modeling

KW - carbon cycle

KW - elevated CO

KW - grasslands

KW - gross primary production

KW - multifactor global change experiment

KW - warming

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DO - 10.1111/gcb.13602

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JO - Global Change Biology

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