Seven Shortfalls that Beset Large-Scale Knowledge of Biodiversity

TLDR

Ecologists increasingly use big‑data to address large‑scale biodiversity questions, yet compiling two centuries of inventories has left many key research gaps unresolved. The study updates the concept of knowledge shortfalls and examines the trade‑offs between generality and uncertainty. The authors review existing shortfall categories and propose new ones, integrating generality and uncertainty considerations. They identify seven shortfalls—Linnean, Wallacean, Prestonian, Darwinian, Hutchinsonian, Raunkiæran, and Eltonian—highlighting gaps in taxonomy, distribution, abundance, evolutionary patterns, abiotic tolerances, traits, and biotic interactions, and present a framework to assess their combined impacts and suggest ways to overcome them.

Abstract

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 (Raunkiæran) 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.