DOI: 10.5061/dryad.zgmsbcc7v
title: Gross primary production responses to warming, elevated CO2 , and irrigation: quantifying the drivers of ecosystem physiology in a semiarid grassland

description: 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.
description: The Prairie Heating and CO2 Enrichment experiment is located in a
 temperate, mixed-grass prairie near Cheyenne, Wyoming (elevation = 1930
 m). The PHACE experiment involves an incomplete factorial design with 30
 plots randomly assigned to six treatments, with five plots per treatment
 level (Parton et al., 2007). The circular plots (3.4 m diameter) are
 separated from surrounding soil by a plastic flange buried to a depth of
 60 cm (Bachman et al., 2010). The six treatments – denoted as ct, cT, Ct,
 CT, ct-d, and ct-s – involve different combinations of atmospheric CO2
 [ambient at 380–400 ppm (denoted as ‘c’) vs. elevated at 600 ppm (‘C’)],
 temperature [ambient/not heated (‘t’) vs. heated by 1.5 (day) or 3.0
 (night) ̊C (‘T’)], and watering [none vs. shallow (‘s’) or deep (‘d’)
 irrigation, which are only applied under ambient CO2 and temperature
 (‘ct’)]. The goal of the irrigation treatments was to increase soil
 moisture to approximately match that of the Ct plots by irrigating when
 soil moisture fell below 85% of Ct at 5–25 cm depth.
 The SWC, SoilT, and micrometeorological data had occasional
 missing time periods or days due to instrument failure (&lt;1%, 6%,
 and 2.5% for the micrometeorological, SWC, and SoilT data, respectively).
 We primarily used data from a nearby plot of the same treatment to
 gap-fill soil moisture and temperature, and cubic spline interpolation was
 used to gap-fill the missing micrometeorological data. Since the dates
 when repeat plot photographs were taken for vegetation greenness did not
 coincide with days when Reco was measured, linear interpolation was
 employed to estimate greenness on Reco measurement days. See Appendix S1
 for full details of these gap-filling procedures.
description: 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. GPP was calculated as the difference between
 net ecosystem exchange and ecosystem respiration, described by Ryan et al.
 2015 (doi: 10.1111/gcb.12910).This package also includes the NEE and Reco
 data used for calucalating GPP.  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. See Read Me files for more details.