## 4 Discussions  
The fAPAR3g used to calculate a LUE observation-based product was computed from the latest version of the GIMMS NDVI [40]. NDVI3g is calibrated using SeaWifs data during 1997-2010 [40], improving the data quality. The fAPAR3g trend during 1982-2010 computed from fAPAR annual values shows no significant trend over the Sahelian band. This result can be explained by the compensation between a positive fAPAR trend in growing seasons and a negative trend during the dry season [35, 65, 66, 67, 68]. The MTE algorithm is mainly trained on spatial gradients between flux towers to produce long-term series. However, no flux tower measurements were available to calibrate the MTE data-driven model over Africa, involving a moderate confidence in MTE products. The performance of MTE based on cross validation was found to be better for ET whereas MTE-GPP was found to be smaller than GPP deduced from GOSAT fluorescence data as a proxy or against MODIS GPP datasets [41, 69, 70, 71]. This potential negative bias of MTE-GPP value could partly explain the low MTE-iWUE* values for Evergreen Broad-Leaved Forest ecosystems in comparison with, e.g., the flux tower data analyzed in [18]. The LUE trend that we constructed from observations can be analyzed as the difference between GPP trend and APAR trend. Over the northern savannahs, both GPP and APAR increased simultaneously during 1982-2010 and approximately in the same range. These GPP and APAR positive trends imply a stabilization of the LUE in the African northern savannahs during the last 30 years. Over the rest of Africa, there is no significant trend for both GPP and APAR. Since the GPP and ET trends show a roughly comparable geographical pattern, especially over the southern Sahel (see Figure 5B,C), the geographical pattern of the iWUE* trend ends up being mainly explained by the VPD trend (data not shown). We found a strong positive VPD trend (from WFDEI) over the central African forest and the northern savannahs during 1982-2010 probably related to rising temperatures. This iWUE* increase, related to the positive VPD trend, reflects positive physiological responses of plant functional types to environmental changes, as found in previous studies in steppe or rainforest [28, 72, 73]. The LUE trend simulated by ORCHIDEE is only significant over the central African forest and matches the geographical pattern of the simulated GPP trend (Figure 4B,C compared to Figure 5E,H), since ORCHIDEE failed to simulate the significant fAPAR trend (calculated from annual value) over the northern savannahs as seen in fAPAR3g satellite data. The positive GPP trend simulated over the central Africa is probably due to the high sensitivity of ORCHIDEE to CO\({}_{2}\) fertilization especially in forest areas. The difficulties of ORCHIDEE to simulate a statistically significant ET trend over the northern savannahs could explain the low significance of the simulated iWUE* trend over these areas. As for LUE, ORCHIDEE only succeeds to produce a positive and significant iWUE* trend over the central African forest, which is highly related to the CO\({}_{2}\) increase, and is consistent with the relationship between CO\({}_{2}\) and iWUE* found in previous studies [30, 31, 32, 33]. Note that the two versions of ORCHIDEE used in this study do not have as many differences in the spatial patterns of the trends compared to their averages, indicating that the soil diffusion scheme has no effect on fAPAR, GPP and ET trends but affects the mean values of these variables. Therefore, the difficulties of ORCHIDEE to reproducegeographical patterns of trends from satellite and data-driven model could be related to the phenology scheme instead of the soil hydrology model. Besides the difference between the hydrological schemes of both ORCHIDEE versions, uncertainties from soil water availability on iWUE* and LUE trends are not specifically addressed in this study as well as ecological processes such as photosynthesis, respiration or fire.