## 4 Discussion
While mean WSAV SIF\({}_{\text{d}}\) was not significantly different than SAV and GRA, it had a significant correlation with T\({}_{\text{air}}\) most strongly, then with T\({}_{\text{can}}\) next, and neither SAV nor GRA were correlated with these climate variables. This suggests that for these classes T\({}_{\text{air}}\) is more influential compared to the other biomes. Seasonality analysis showed that EBF had the highest integrated base and total integrated SIF\({}_{\text{d}}\), but DBF had the highest seasonal pulse integrated SIF\({}_{\text{d}}\) of the Atlantic Forest vegetation classes. The lack of difference in means and correlations between SIF\({}_{\text{d}}\) and environmental variables for some vegetation classes in the Atlantic Forest may have resulted from several factors. First, the range of latitudes spanned by the Atlantic Forest biome is large (approximately 29\({}^{\circ}\), \(\sim\)-3\({}^{\circ}\) to -30\({}^{\circ}\)) having a corresponding large range of changes in solar angles as well as environmental conditions, the altitutional range is large, and the Atlantic Ocean borders this latitudinal gradient, driving differences in rainfall and vegetation composition [120]. These conditions are expected to have an impact when averaging over space and time to mask trends and relationships [120; 141]. Second, the degree of deforestation in the Atlantic Forest original vegetation is over 88% of the original forest and the remaining forest fragments are small (<50 ha) and isolated [120; 142]. This mosaic of highly anthropogenic vegetation would make it difficult to capture the proper vegetation classification at these coarse scales and highlights the possibility that the vegetation classification may need to be improved or at higher resolution to capture vegetation class specific relationships to the environment in future studies. Third, much of the biome has been converted to cropland with asynchronous cycles of harvest and planting and it may be reasonable that croplands erroneously included in the classes examined, especially GRA and SAV, due course resolution or misclassification, would additionally affect the results and mask trends [120; 142]. Investigating the biome level mean SIF\({}_{\text{d}}\) and mean SIF\({}_{\text{d}}\) among vegetation classes in the Caatinga only confirmed expectations, while comparisons to climate variables and analysis of seasonality further elucidated the root behavior of SIF\({}_{\text{d}}\) in the Caatinga. Mean SIF\({}_{\text{d}}\) of the Caatinga was lowest among all biomes, had the highest variability, and mean SIF\({}_{\text{d}}\) among vegetation classes in the Caatinga had lower magnitudes than their counterparts in other biomes. This was anticipated based on the dry climate and vegetation makeup of dry shrubland, seasonally dry tropical forest, and xeric in contrast to other biomes [116; 117]. However, correlations of mean SIF to T\({}_{\text{can}}\), T\({}_{\text{air}}\), and VPD for the Caatinga were all negative and strongest between mean SIF\({}_{\text{d}}\) and VPD followed by T\({}_{\text{can}}\), just as they were in the Cerrado. This indicates mean SIF\({}_{\text{d}}\) responds similarly in these two biomes, but in contrast to the others, potentially related to their similar latitudinal ranges and climate. Seasonality analysis revealed more intricate differences in the Caatinga. Base integrated SIF\({}_{\text{d}}\) in the Caatinga for all vegetation classes was lowest of the biomes and seasonal pulse integrated SIF\({}_{\text{d}}\) was not lowest, indicating that the base integrated SIF\({}_{\text{d}}\) is responsible for the overall lower mean SIF\({}_{\text{d}}\) (Figure 5). The lengths of individual vegetation class SIF seasons varied from those of the Cerrado (Figure S12), but the average length of the seasons for SIF in the Caatinga was not different than other biomes and was calculated within one day of the Cerrado (Figure S13).