TY - JOUR

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

AU - Ogle, Kiona

AU - Peltier, Drew

AU - Walker, Anthony

AU - De Kauwe, Martin

AU - Medlyn, Belinda

AU - Williams, David

AU - Parton, William

AU - Asao, Shinichi

AU - Guenet, Bertrand

AU - Harper, Anna

AU - Lu, Xingjie

AU - Luus, Kristina

AU - Shu, Shijie

AU - Werner, Christian

AU - Xia, Jianyang

AU - Zaehle, Sonke

AU - Pendall, Elise

N1 - This is the peer reviewed version of the following article: 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. and Pendall, E. (2017), Gross primary production responses to warming, elevated CO2, and irrigation: quantifying the drivers of ecosystem physiology in a semiarid grassland. Glob Change Biol, 23: 3092–3106. doi:10.1111/gcb.13602 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/gcb.13602/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

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 six years (2007-2012) of flux-derived GPP data (~2500 values) from the Prairie Heating and CO2 Enrichment (PHACE) experiment, situated in a mixed prairie 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, however, was extended to allow for variable maximum photosynthetic rate (Amax) and light-use efficiency (Q) by modeling these terms as functions of time varying driving variables (soil water content, air temperature, vapor pressure deficit, vegetation greenness, nitrogen) at current and antecedent (past) time scales. The model fit the observed GPP well (R2 = 0.79), which was confirmed by other model performance checks (deviance information criterion and posterior predictive loss) that compared different variants of the model (e.g., with and without antecedent effects). Stimulation of cumulative six-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. These enhancements were consistent across each year, suggesting mechanisms for extending the growing season. Antecedent air temperature (Tairant) and vapor pressure deficit (VPDant) effects on Amax were the most significant predictors of temporal variability in GPP among most treatments. The importance of VPDant suggests that atmospheric drought plays an important role for predicting GPP under current and future climate. Given the limited research supporting the role of VPDant in this context, we highlight the need for experimental studies to identify the mechanisms underlying such antecedent effects.

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 six years (2007-2012) of flux-derived GPP data (~2500 values) from the Prairie Heating and CO2 Enrichment (PHACE) experiment, situated in a mixed prairie 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, however, was extended to allow for variable maximum photosynthetic rate (Amax) and light-use efficiency (Q) by modeling these terms as functions of time varying driving variables (soil water content, air temperature, vapor pressure deficit, vegetation greenness, nitrogen) at current and antecedent (past) time scales. The model fit the observed GPP well (R2 = 0.79), which was confirmed by other model performance checks (deviance information criterion and posterior predictive loss) that compared different variants of the model (e.g., with and without antecedent effects). Stimulation of cumulative six-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. These enhancements were consistent across each year, suggesting mechanisms for extending the growing season. Antecedent air temperature (Tairant) and vapor pressure deficit (VPDant) effects on Amax were the most significant predictors of temporal variability in GPP among most treatments. The importance of VPDant suggests that atmospheric drought plays an important role for predicting GPP under current and future climate. Given the limited research supporting the role of VPDant in this context, we highlight the need for experimental studies to identify the mechanisms underlying such antecedent effects.

KW - gross primary production

KW - elevated CO2

KW - warming

KW - multi-factor global change experiment

KW - Bayesian modelling

KW - carbon cycle

KW - grasslands

U2 - 10.1111/gcb.13602

DO - 10.1111/gcb.13602

M3 - Journal article

VL - 23

SP - 3092

EP - 3106

JO - Global Change Biology

JF - Global Change Biology

SN - 1354-1013

IS - 8

ER -