Title data
Mottl, Ondřej ; Gaiser, Franka ; Šímová, Irena ; Flantua, Suzette G. A.:
VegVault database: linking global paleo-, and neo-vegetation data with functional traits and abiotic drivers.
Prague
:
bioRxiv
,
2025
DOI: https://doi.org/10.1101/2025.01.31.635213
Abstract in another language
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 role in advancing ecological research to improve predictions of biodiversity responses to global climate change.Competing Interest StatementThe authors have declared no competing interest.
Further data
Item Type: | Preprint, postprint |
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Institutions of the University: | Faculties > Faculty of Cultural Studies > Department of Sport Science > Chair Sport Ecology Profile Fields > Advanced Fields > Ecology and the Environmental Sciences |
Result of work at the UBT: | No |
DDC Subjects: | 500 Science > 560 Fossils, prehistoric life 500 Science > 580 Plants (Botany) |
Date Deposited: | 25 Apr 2025 07:51 |
Last Modified: | 25 Apr 2025 07:51 |
URI: | https://eref.uni-bayreuth.de/id/eprint/93355 |