## 5 Conclusions  
We provide the first regional assessment of the ecophysiological and physiological dynamics of the forest, integrating functional and orbital data in an installed plot in the southwest of the Amazonia. Additionally, we assess the forest's response to the recent drought (2015/2016) using image-derived orbital products with corrections that exclude artifacts that may influence seasonal forest patterns (EVI MAIAC and Gcc MAIAC).  
Our results, using remote sensing and in situ measurements, suggest that:  
1. EVI and Gcc are sensitive to different responses of the forest canopy structure. During the dry season, the forest reduces its photosynthetic activity even as it renews its leaves at the same time, a browning effect. During the wet season, photosynthetic activity increases, with a greening effect, revealing the relationship of this response with leaf maturity.
2. The pattern of vulnerability to drought does not follow that of other Amazonian sites. Trees with larger stem diameters are more resistant than trees with thinner stem diameters.
3. Negative effects on stem growth post-El-Nino 2015/2016 were observed, suggesting that the persistence of negative rainfall anomalies may be very critical for the forest, regardless of whether extreme drought is influenced by changes in ocean temperature.
4. It is expected that precipitation is climatic forcing with the greatest influence on both the stem growth and the increase in photosynthetic activity of the canopy.
5. In situ ecophysiological data are essential for this type of analysis; however, they are scarce, difficult to collect and have limited temporal resolution. Satellites provide a practical method to assess forest dynamics, at appropriate scales, to which this research sought to contribute.  
All authors have made significant contributions to this manuscript. [PERSON] and [PERSON] idealized the research proposal. [PERSON], [PERSON] and [PERSON] designed the experiment and performed all field collection and data processing. [PERSON], [PERSON] and [PERSON] collected the field data. [PERSON] and [PERSON] discussed and defined the appropriate methodological procedure.  
[PERSON], [PERSON] and [PERSON] processed the weather data from the flux tower. [PERSON] obtained financing. [PERSON] assisted in the processing of ecophysiological data. [PERSON], [PERSON] and [PERSON] wrote this manuscript together. All authors have read and agreed to the published version of the manuscript.  
GoAmazon project supported by FAPESP 2013/50531-2, and Public Notice 12/2019/REIT-PROPESP/IFRO, 19 June 2019; Public Notice 180/2017/REIT-CGAB/REIT-CPOSG/IFRO, 17 August 2017 and Ordinance 2016/REIT-CGAB/IFRO, 11 October 2017 supported by Federal Institute of Education, Science and Technology of Rondonia (IFRO).  
The data presented in this study are available on reasonable request from the corresponding author. The data are not publicly available due to privacy restrictions.  
We thank the and Federal Institute of Education, Science and Technology of Rondonia (IFRO) for providing equipment, National Institute For Space Research (INPE) for the Ph.D. course in Remote Sensing, and Academic Excellence Program (CAPES/PROEX) for granting a research grant. We also thank [PERSON] for processing the MAIAC images, [PERSON] for helping with field collections, LBA program for the partnership and supply of data from the Micrometeorological Tower. We would like to thank Chico Mendes Institute of Biodiversity (ICMBio), to the coordinators [PERSON] and [PERSON], for their authorization and support to this research. We also thank [PERSON] and [PERSON] for field data processing assistance and scripts.  
The authors declare no conflict of interest.