Floodplains contribute significantly to terrestrial ecosystem service provision but are also among the most vulnerable and degraded ecosystems worldwide. Heterogeneity in floodplain properties arises from variations in river-specific flood regimes, watershed characteristics, and valley morphology, influencing seasonally flooded forests' taxonomic, functional, and phylogenetic diversity. This study addresses persisting knowledge gaps in floodplain ecology, focusing on the seasonally dry tropics. We explore the relationships between flood regime, environmental conditions, vegetation composition, functional and phylogenetic diversity, and the impact of environmental variables on above-ground biomass (AGB) and ecological strategies. The study spans six rivers in southeastern Brazil's main river basins: Rio Grande and São Francisco. We identified five eco-units in each floodplain based on flooding regimes and surveyed six plots per eco-unit. We measured trees with DBH > 5 cm and collected functional traits, along with detailed soil, climate, and water level data. We calculated plot-level floristic composition, taxonomic, functional, and phylogenetic diversity, wood density, and AGB. Functional and phylogenetic dissimilarity were analyzed, and the effects of climate, soil, and hydrological variables were quantified using generalized linear mixed models. We show how flood frequency and duration affect floristic composition across the floodplains. Taxonomic and phylogenetic diversity responded to climate, soil, and hydrological variables, while functional diversity responded primarily to hydrological variables, emphasizing the role of environmental filtering. Hydrological seasonality, soil fertility, and flood regime emerged as key factors shaping community structure and ecological strategies in the studied seasonally flooded tropical forests. Plot-level AGB responded to phosphorus but not to climate or hydrological variables. The study also highlights functional and phylogenetic dissimilarities among eco-units and basins, indicating potential climate change impacts.
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