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 CO2Enrichment (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 VPDantsuggests 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 eCO2treatments 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.
authors.affiliation: Lancaster Environment Centre, Lancaster, UK.
authors.forename: Edmund M
authors.identifier: 0000-0002-7003-9707
authors.initials: EM
authors.lastname: Ryan
authors.affiliation: School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ, USA.|Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA.
authors.forename: Kiona
authors.initials: K
authors.lastname: Ogle
authors.affiliation: Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA.
authors.forename: Drew
authors.initials: D
authors.lastname: Peltier
authors.affiliation: Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, USA.
authors.forename: Anthony P
authors.initials: AP
authors.lastname: Walker
authors.affiliation: Department of Biological Sciences, Macquarie University, Sydney, NSW, 2109, Australia.
authors.forename: Martin G
authors.identifier: 0000-0002-3399-9098
authors.initials: MG
authors.lastname: De Kauwe
authors.affiliation: Hawkesbury Institute for the Environment, Western Sydney University, Penrith, NSW, Australia.
authors.forename: Belinda E
authors.identifier: 0000-0001-5728-9827
authors.initials: BE
authors.lastname: Medlyn
authors.affiliation: Department of Botany, University of Wyoming, Laramie, WY, USA.
authors.forename: David G
authors.initials: DG
authors.lastname: Williams
authors.affiliation: Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO, 80523-1499, USA.
authors.forename: William
authors.initials: W
authors.lastname: Parton
authors.affiliation: Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO, 80523-1499, USA.
authors.forename: Shinichi
authors.initials: S
authors.lastname: Asao
authors.affiliation: Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, F-91191, Gif-sur-Yvette, France.
authors.forename: Bertrand
authors.initials: B
authors.lastname: Guenet
authors.affiliation: College of Engineering, Mathematics, and Physical Sciences, University of Exeter, Exeter, UK.
authors.forename: Anna B
authors.initials: AB
authors.lastname: Harper
authors.affiliation: CSIRO Ocean and Atmosphere, PBM #1, Aspendale, Vic., 3195, Australia.
authors.forename: Xingjie
authors.initials: X
authors.lastname: Lu
authors.affiliation: Biogeochemical Integration Department, Max Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10, 07745, Jena, Germany.
authors.forename: Kristina A
authors.initials: KA
authors.lastname: Luus
authors.affiliation: Biogeochemical Integration Department, Max Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10, 07745, Jena, Germany.
authors.forename: Sönke
authors.initials: S
authors.lastname: Zaehle
authors.affiliation: Department of Atmospheric Sciences, University of Illinois, 105 South Gregory Street, Urbana, IL, 61801-3070, USA.
authors.forename: Shijie
authors.initials: S
authors.lastname: Shu
authors.affiliation: Senckenberg Biodiversity and Climate Research Centre (BiK-F), Senckenberganlage 25, 60325, Frankfurt, Germany.
authors.forename: Christian
authors.initials: C
authors.lastname: Werner
authors.affiliation: Department of Microbiology & Plant Biology, University of Oklahoma, Norman, OK, 73019, USA.|Research Center for Global Change and Ecological Forecasting, East China Normal University, Shanghai, 200062, China.
authors.forename: Jianyang
authors.initials: J
authors.lastname: Xia
authors.affiliation: Hawkesbury Institute for the Environment, Western Sydney University, Penrith, NSW, Australia.|Department of Botany, University of Wyoming, Laramie, WY, USA.
authors.forename: Elise
authors.initials: E
authors.lastname: Pendall
mesh_terms: D057486:Carbon Cycle; D002245:Carbon Dioxide; D002980:Climate; D017753:Ecosystem; D065948:Grassland; D014959:Wyoming
chemical_list: D002245:Carbon Dioxide
keywords: Bayesian modeling; carbon cycle; elevated CO2; grasslands; gross primary production; multifactor global change experiment; warming