Large-extent vegetation datasets that co-occur with long-term hydrology data provide new ways to develop bio- logically meaningful hydrologic variables and to determine plant community responses to hydrology. We analyzed the suitability of different hydrological variables to predict vege- tation in two water conservation areas (WCAs) in the Florida Everglades, USA, and developed metrics to define realized hydrologic optima and tolerances. Using vegetation data spa- tially co-located with long-term hydrological records, we evaluated seven variables describingwater depth, hydroperiod length, and number of wet/dry events; each variable was tested for 2-, 4- and 10-year intervals for Julian annual aver- ages and environmentally-defined hydrologic intervals. Maximum length and maximum water depth during the wet period calculated for environmentally-defined hydrologic in- tervals over a 4-year period were the best predictors of vege- tation type. Proportional abundance of vegetation types along hydrological gradients indicated that communities had differ- ent realized optima and tolerances acrossWCAs. Although in both WCAs, the trees/shrubs class was on the drier/shallower end of hydrological gradients, while slough communities occupied the wetter/deeper end, the distribution of Cladium, Typha, wet prairie and Salix communities, which were inter- mediate for most hydrological variables, varied in proportion- al abundance along hydrologic gradients between WCAs, indicating that realized optima and tolerances are context- dependent.