## 1 Introduction
Currently, our understanding of tropical vegetation seasonality and seasonality response to different environments remains uncertain [1; 22; 49]. While the Amazon tropical forest has been studied at multiple scales, no studies have yet analyzed seasonal cycles of SIF\({}_{\text{d}}\) in Amazon tropical forests in relation to other, lesser studied vegetation classes and biomes [47; 49; 63]. Past studies utilizing VIs have suggested that the seasonality of photosynthesis in the Amazon is related to leaf phenology responses to high light availability in the dry season triggering a \"green up\" [63; 64; 65],but recent studies employing SIF from satellites [35], enumerating sun-sensor geometry and the atmospheric contamination of VIs [64; 66; 67; 68] have questioned the \"green up\" results. Satellite-based VIs have been used widely in past studies to explore and understand the seasonal rhythms and phenology as well as drivers, again mostly focused on temperate regions and tropical forests in the Amazon. The remaining questions regarding Amazonian tropical forest phenology, the lack of investigation of other vegetation and regions in Brazil, coupled with recent advancements in dedicated SIF instrumentation onboard satellites, improved spectral resolution, and improvements in data processing and retrieval techniques prompt us to address phenology of different vegetation types across Brazil using satellite SIF [15; 27; 28; 42; 51; 69; 70; 71]. Temperature (T) and vapor pressure deficit (VPD) are influential factors affecting photosynthesis and are important inputs to model productivity [72; 73; 74; 75; 76]. As temperature increases, generally, SIF decreases, especially at very high temperatures which increase non-photochemical quenching (NPQ) and excess absorbed energy is given off as heat by the plant [13; 77; 78]. Higher VPD levels induce water stress and usually indicate higher temperature and lower soil moisture conditions, also triggering an increase in NPQ and reducing SIF [79]. Considering the relationships of T and VPD to productivity is challenging in the tropics due to sparse or scale mismatched data, and data issues become increasingly complex across tropical spatial gradients containing multiple vegetation types [35; 47; 50; 80]. Studies have examined temperature, water availability and VPD as drivers of satellite-based SIF in temperate regions and where ground-based measurements or climate data have been co-located and show resulting SIF-GPP relationships are reduced in high temperature or high VPD [13; 81; 82; 13]. Environmental conditions, including water availability and VPD, have also been examined in relation to satellite-based SIF in the Amazon and correlations were found between water stress conditions and increased variability in SIF measurements, yet specific relationships among VPD, T, and SIF remain uncertain in Amazon tropical forests and unexamined for other vegetation and biomes [83; 22; 35; 84]. Measurements of canopy temperature (T\({}_{\text{can}}\)) have been shown to differ from air temperature (T\({}_{\text{air}}\)) in a tropical forest canopy by as much as 7 degrees Celsius and display better agreement with GPP [85]. Brazil contains 19% of the world's flora, the world's largest area of tropical forest, the highest carbon stocks and thus contributes significantly to global productivity, terrestrial biomass, and biodiversity [86; 87; 88; 4; 35; 62; 89]. Among the six biomes of Brazil (Amazon, Atlantic Forest, Caatinga, Cerrado, Pampa, and Pantanal), most studies are focused on the Amazon [90; 91; 92; 93; 94]. Brazil's tropical savanna is the second most dominant vegetation cover at an estimated 20-35% and it contains the region considered to be the most biodiverse savanna in the world [90; 95; 96].