Understanding the dynamics and persistence of biodiversity patterns over short (contemporary) and long (thousands of years) time scales is crucial for predicting ecosystem changes under global climate and land-use changes. A key challenge is integrating currently scattered ecological data to assess complex vegetation dynamics over time. Here, we present VegVault, an interdisciplinary SQLite database that uniquely integrates paleo- and neo-ecological plot-based vegetation data on a global and millennial scale, directly linking them with functional traits, soil, and climate information. VegVault currently comprises data from BIEN, sPlotOpen, TRY, Neotoma, CHELSA, and WoSIS, providing a comprehensive and ready-to-use resource for researchers across various fields to address questions about past and contemporary biodiversity patterns and their abiotic drivers. To further support the usability of the data, VegVault is complemented by the {vaultkeepr} R package, enabling streamlined data access, extraction, and manipulation. This study introduces the structure, content, and diverse applications of VegVault, emphasizing its potential role in advancing ecological research to improve predictions of biodiversity responses to global climate change.

Bjerknes Centre for Climate Research Bergen Norway

Center for Theoretical Study Charles University Jilská 1 CZ 11000 Prague Czech Republic

Department of Biological Sciences University of Bergen PO Box 7803 N 5020 Bergen Norway

Department of Botany Faculty of Science Charles University Benátská 2 CZ 12801 Prague Czech Republic

Department of Ecology Faculty of Science Charles University Viničná 7 CZ 12800 Prague Czech Republic

Sport Ecology Bayreuth Center of Ecology and Environmental Research University of Bayreuth 95447 Bayreuth Germany

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VegVault dataset: linking global paleo-, and neo-vegetation data with functional traits and abiotic drivers