Ecologists and evolutionary biologists are increasingly using big-data approaches to tackle questions at large spatial, taxonomic, and temporal scales. However, despite recent efforts to gather two centuries of biodiversity inventories into comprehensive databases, many crucial research questions...

Ecologists and evolutionary biologists are increasingly using big-data approaches to tackle questions at large spatial, taxonomic, and temporal scales. However, despite recent efforts to gather two centuries of biodiversity inventories into comprehensive databases, many crucial research questions remain unanswered. Here, we update the concept of knowledge shortfalls and review the tradeoffs between generality and uncertainty. We present seven key shortfalls of current biodiversity data. Four previously proposed shortfalls pinpoint knowledge gaps for species taxonomy (Linnean), distribution (Wallacean), abundance (Prestonian), and evolutionary patterns (Darwinian). We also redefine the Hutchinsonian shortfall to apply to the abiotic tolerances of species and propose new shortfalls relating to limited knowledge of species traits (Raunkiaeran) and biotic interactions (Eltonian). We conclude with a general framework for the combined impacts and consequences of shortfalls of large-scale biodiversity knowledge for evolutionary and ecological research and consider ways of overcoming the seven shortfalls and dealing with the uncertainty they generate

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