Dataset for: Transcending data gaps: a framework to reduce inferential errors in ecological analyses

The analysis of functional diversity has gained increasing importance due to its generality and utility in ecology. In particular, patterns in the spatial distribution and temporal change of functional diversity are being used to predict locations and functional groups that are immediately vulnerable to global changes. A major impediment to the accurate measurement of functional diversity is the pervasiveness of missing data in trait datasets. Whilst such prevalent data gaps can engender misleading inferences in functional diversity analyses, we currently lack any practical guide to handle missing data in trait datasets. Here, we identify significant mismatches between true functional diversity and values derived from datasets that contain missing data. We demonstrate that imputing missing data with a phylogeny-informed approach reduces the risk of misinterpretation of functional diversity patterns, and provides baseline information against which central questions in ecology can be evaluated.