## 2 Materials and Methods
### SCOPE Model Simulations  
Forward and inverse simulations with the SCOPE model were conducted to assess the robustness of fAPAR, Fesc, and LE\({}_{\text{ISO}}\) derived from field observations. The forward runs model was parameterized using the structural and functional traits derived from the field sampling as well as meteorological and chamber data. Vapor pressure deficit (VPD, hPa), air pressure (p, hPa), short wave downwelling radiation (Rin, W m\({}^{-2}\)), long wave downwelling radiation (Rli, W m\({}^{-2}\)), air temperature (Ta, \({}^{\circ}\)C), wind speed (u, m s\({}^{-1}\)), soil moisture content (SMC, %), leaf area index (LAI m\({}^{2}\) m\({}^{-2}\)), canopy height (h, m), chlorophyll a and b content (Cab, \(\mu\)g cm\({}^{-2}\)), dry matter content (Cdm, g cm\({}^{-2}\)), maximum carboxylation rate (Vcmax, \(\mu\)mol m\({}^{-2}\) s\({}^{-1}\)) and the parameters to characterize the leaf angle distribution (LAD), respectively, LIDFa and LIDPb, were used to parameterize the model run. SCOPE meteorological drivers were measured along with chamber measurements for the majority; in the case they were not available with the chambers, such as Rin, Rli, p, VPD, wind speed, atmospheric CO\({}_{2}\) concentration (Ca, ppm), and atmospheric O\({}_{2}\) concentration (Oa, ppm), they were derived by linearly interpolating two consecutive measurements around the chambers measurement time collected at the nearby eddy covariance flux tower at 10 min of temporal resolution. Canopy height was estimated in the field with a meter stick in five positions within the measurement collar. Additional parameters such as leaf equivalent water thickness, leaf width, Ball-Berry stomatal conductance parameter and dark respiration rate at 25 \({}^{\circ}\)C as fraction of Vcmax were obtained from the literature for C3 grasses [8]. The SZA at the time of the collection of the spectral measurements was used as model input. Soil reflectance spectra were collected in a dedicated field campaign in April 2015 and used for all the runs. Leaf angle distribution was parameterized in SCOPE as in [8] by assuming grasses to be erectophile, forbs spherical and legumes planophiles. The accuracy of F\({}_{760}\) and GPP simulated with SCOPE (F\({}_{760\text{FW}}\) and GPP\({}_{\text{FW}}\), respectively) was evaluated by root mean-squared error (RMSE), slope, intercept, and the determination coefficient (R\({}^{2}\)) of the linear regression between observed and modeled data (Figure S6). Inverse runs of SCOPE against reflectance, F\({}_{760}\), GPP and thermal radiance, as described in [42], were carried out to obtain LE\({}_{\text{canopyinv}}\) and Fesc (Fesc\({}_{\text{inv}}\)). Calculation of the Light Use Efficiency of Photosynthesis (LUE\({}_{p}\)), Light use Efficiency of Fluorescence Emission (LUE\({}_{f}\)) and Escape Probability of F\({}_{760}\) (Fesc)  
For each plot and campaign, LUE\({}_{\rm P}\), LUE\({}_{\rm f}\) and Fesc were computed. LUE\({}_{\rm P}\) was calculated as in Equation (12):  
\[LUE_{p}\ \ =\ \frac{GPP}{APAR} \tag{12}\]  
where GPP is the one measured with the chambers and APAR was calculated as in Equation (13):  
\[APAR\ \ =\ \ fAPAR_{RENDVI}\ \times\ PAR \tag{13}\]  
LUE\({}_{\rm f}\) was computed as in Equation (14):  
\[LUE_{f}\ \ =\ \ \frac{F_{760}}{APAR_{radiance}\ \times\ Fesc_{fw}} \tag{14}\]  
where F\({}_{760}\) is the TOC fluorescence retrieved and Fesc\({}_{\rm fw}\) is the escape probability calculated from forward runs of SCOPE and APARradiance (mW m\({}^{-2}\) nm\({}^{-1}\) sr\({}^{-1}\)) is calculated from APAR (umol m\({}^{-2}\) s\({}^{-1}\)) as shown in Equation (15). \[APAR_{radiance}\ \ =\ \ \frac{APAR}{(4.6\ \times\ wl\ \times\ \pi\ )}\ \times 1000 \tag{15}\]  
where 4.6 represent the conversion factor from umol m\({}^{-2}\) s\({}^{-1}\) to W m-2 for radiation from 400 to 700 nm [48] and wl is the wavelength interval (300 nm), and \(\pi\) is used to transform irradiance to radiance.