The large flood pulse of the Amazon basin is a principal driver of environmental heterogeneity with important implications for ecosystem function and the assembly of natural communities. Understanding species ecological response to the flood pulse is thus a key question with implications for theories of species coexistence, resource management, and conservation. Yet these remain largely undescribed for most species, and in particular for trees. The large flood pulse and high tree diversity of the Negro River floodplain makes it an ideal system to begin filling this knowledge gap. We merged historical hydrologic data with 41 forest inventories under variable flooding conditions distributed across the Negro River basin, comprising a total area of 34 ha, to (i) assess the importance of flood duration as a driver of compositional variation, (ii) model the response curve shapes of 111 of the most frequent tree species in function of flood duration, and (iii) derive their niche properties (optima and tolerance). We found that flood duration is a strong driver of compositional turnover, although the majority site-to-site variation in forest composition still remains unexplained. About 73% of species responded to the flood duration gradient, exhibiting a diversity of shapes, but most frequently skewed. About 29% of species were clearly favored by flood durations >120 days year^–1, and 44% of species favored by shorter floods. The median niche breadth was 85 flood days year^–1, corresponding to approximately 30% of the flood duration gradient. A significant subset of species (27%) did not respond to flooding, but rather exhibited wide tolerance to the flood gradient. The response models provided here offer valuable information regarding tree species differential capacity to grow, survive, and regenerate along an ecologically important gradient and are spatially valid for the Amazon Negro basin. These attributes make them an appealing tool with wide applicability for field and experimental studies in the region, as well as for vegetation monitoring and simulation models of floodplain forest change in the face of hydrologic alteration.