RT Journal Article SR Electronic T1 MOSAIC: A Unified Trait Database to Complement Structured Population Models JF bioRxiv FD Cold Spring Harbor Laboratory SP 2022.03.09.483599 DO 10.1101/2022.03.09.483599 A1 Bernard, Connor A1 Santos, Gabriel Silva A1 Deere, Jacques A1 Rodriguez-Caro, Roberto A1 Capdevila, Pol A1 Kusch, Erik A1 Gascoigne, Samuel J L A1 Jackson, John A1 Salguero-Gómez, Roberto YR 2022 UL http://biorxiv.org/content/early/2022/03/10/2022.03.09.483599.abstract AB The ecological sciences have joined the big data revolution. However, despite exponential growth in data availability, broader interoperability amongst datasets is still needed to unlock the potential of open access. The interface of demography and functional traits is well-positioned to benefit from said interoperability. Trait-based ecological approaches have been criticised because of their inability to predict fitness components, the core of demography; likewise, demographic approaches are data-hungry, and so using traits as ecological shortcuts to understanding and forecasting population viability could offer great value.Here, we introduce MOSAIC, an open-access trait database that unlocks the demographic potential stored in the COMADRE, COMPADRE, and PADRINO open-access databases. MOSAIC data have been digitised and curated through a combination of existing datasets and additional taxonomic and/or trait records sourced from primary literature. In its first release, MOSAIC (v. 1.0.0) includes 14 trait fields for 300 animal and plant species: biomass, height, growth determination, regeneration, sexual dimorphism, mating system, hermaphrodism, sequential hermaphrodism, dispersal capacity, type of dispersal, mode of dispersal, dispersal classes, volancy, and aquatic habitat dependency. MOSAIC also includes species-level phylogenies for 1,359 species and population-specific climate data where locations are recorded.Using MOSAIC, we highlight a taxonomic mismatch of widely used trait databases with existing structured population models. Despite millions of trait records available in open- access databases, taxonomic overlap between open-access demographic and trait databases is <5%. We identify where traits of interest to ecologists can benefit from database integration and start to quantify traits that are poorly quantified (e.g., growth determination, modularity).The MOSAIC database evidences the importance of improving interoperability in open- access efforts in ecology as well as the need for complementary digitisation to fill targeted taxonomic gaps. In addition, MOSAIC highlights emerging challenges associated with the disparity between locations where different trait records are sourced.Competing Interest StatementThe authors have declared no competing interest.