FAIRWood: An open database for global xylogenesis research

Wood formation (xylogenesis) represents the mechanistic link between short-term physiological processes and long-term tree-ring patterns and thus provides a key entry point to connect processes, patterns, and predictions in tree growth research. Although numerous xylogenesis datasets already exist worldwide, their real strength emerges when they are considered together, enabling large-scale syntheses of growth phenology, cell production dynamics, and climate sensitivity across species and biomes. FAIRWood builds on this opportunity as an international initiative that is developing an open database to harmonize, connect, and increase the scientific value of xylogenesis data. This presentation introduces the FAIRWood project, its objectives, and the scope and description of the database.

FAIRWood brings together observations from intra-annual wood formation monitoring, including data on cambial activity and successive cell differentiation phases, collected across multiple sites, climates, and taxa. Each record is accompanied by metadata that describes the sampling design, protocols, temporal resolution, and sampling-, tree- and stand-level characteristics, ensuring data preservation, harmonization, reuse, and cross-study comparability according to the FAIR principles. The database aims to host data on both xylem and phloem formation of stems, branches and coarse roots for gymnosperms and angiosperms and integrate automated tools for data visualization, exploration and basic processing, with the aim of increasing the visibility and accessibility of past and ongoing monitoring efforts.

By unifying observations, metadata, and analytical tools within a single framework, FAIRWood aims to foster international collaboration while also acting as a shared platform to enhance the visibility of datasets and projects produced by research groups. This integrated approach enables large-scale analyses across space, time, and taxa, supports comparative studies, and strengthens the development and evaluation of vegetation models as well as forest responses to global environmental change.