## 4 Discussion  
We observed that GPP, Reco, and NEE showed marked seasonal variation in sync with precipitation. The GPP (positive values) and NEE (negative values) increased after leaf expansion (higher EVI and NDVI) at the beginning of the rainy season, increasing the soil water availability necessary to supply the photosynthetic processes of the plants, as a consequence the rates of GPP overcame the Reco and the study area in the Caatinga acted as a carbon sink. Reco showed similar seasonality to NEE and GPP, following the pattern of rainfall. [PERSON] [44] reports that the greater availability of water in the soil is associated with high microbial activity, contributing to an increase in autotrophic respiration, and consequently in ecosystem respiration. Results showed that evapotranspiration strongly controls GPP, varying with the local rainfall pattern throughout the year. ET rates reach up to 100 kg H\({}_{2}\)O m\({}^{-2}\) month\({}^{-1}\) in the wet season and remain lower than  
Figure 8: Relationship between measured gross primary production (GPP Tower) and the two vegetation indices (NDVI (**a**), EVI (**b**)) for the ESEC-Serido site. Gray bands represent the 95% confidence interval for the fitted linear model. Figure 7: Heatmap based on the correlation matrix between gross primary production (GPP) and the other water and energy flux variables, and meteorological variables in the dry season (**a**) and wet season (**b**) of 2014 and 2015 in the Caatinga (ESEC-Serido). Warm colors represent positive correlation and cold colors represent negative correlations. Crossed-out values were not statistically significant (\(p\)-value > 0.05). 10 kg H\({}_{2}\)O m\({}^{-2}\) month\({}^{-1}\) in the dry season. Overall, the studied Caatinga site behaves as a carbon sink, as previously shown in other studies [19], with productivity pulses directly related to water availability, with the highest rainfall and evapotranspiration rates occurring in April. Both tower data and remote sensing data indicate that this ecosystem strongly responds to local rainfall, but water availability may not be the only factor limiting vegetation growth since GPP was similar in both studied years despite 2015 being a slightly drier year. Thus, even if our results comprise only one site, we hypothesize that available energy may also be a limiting factor for this type of vegetation, which would explain the correlation patterns shown in Figure 5a (dry season), with GPP and Rn closely located at the same unit circle, and in Figure 5b (wet season) where they are located at opposite circles. Similar results were reported in seasonal tropical forests in Brazil, where rainfall seasonality and soil water content were not relevant for the energy partitioning because vegetation growth was more limited by available energy than water [45; 46]. This is a plausible explanation since high precipitation rates are usually associated with increased cloud cover and, therefore, reduced incident solar radiation. The MODI7A2 product demonstrated dexterity in describing the average monthly seasonal variability of the GPP in the Caatinga. The results show a consistent correlation between gross primary production (GPP Tower) and MODIS gross primary production (GPP MODIS), R\({}^{2}\) = 0.76 in the dry season and R\({}^{2}\) = 0.66 in the rainy season, where the GPP MODIS overestimated the GPP Tower data (Figures 4 and 6). This overestimation is most evident during the period from February to May 2014 and February to April 2015, which corresponds to the wettest period in the years 2014-2015. On the other hand, during the dry periods (especially from July to November) the GPP MODIS was more related to the observed values. The relationship between tower GPP and MODIS GPP agrees with results previously reported in the literature [20; 47; 48; 49], with stronger correlations if compared to similar analysis carried out in tropical forests [49].