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.

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 (<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.

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.

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