Historical tree phenology data across contrasting sites in the Congo Basin

Indroduction We present a unique dataset of historical tropical tree phenology observations at two sites from different bioclimatic regions across the Congo Basin. We cover both the Atlantic Mayombe forest and the tropical forest in the central Congo Basin. To our knowledge this is complete extant historical (1937 - 1957) phenology data across the Congo basin. The data contains 10 million observations of 876 species, across 6339 individuals, and phenology metrics including leaf, flowering, and fruiting phenology. The data were recovered through expert transcription and validated community science based crowdsourcing. These data may provide a reference baseline and key information on how tree species are responding to a changing climate. Main data files PhenoDRC.rds: This is an R data serialization file. Contains a structured dataset, holding the main phenological data for the DRC. PhenoDRC.tar.gz: This is a compressed archive file of the data contained in the PhenoDRC.rds file as a flat csv file - for compatibility. PhenoDRC_life_history.rds: This R data file contains specific data related to the life history traits, separate from the primary phenological observations. Pierlot_1966_inventories.csv: Contains the inventory data of sampling plots described in Pierlot 1966. Appendix data Yangambi_observation_schedule.csv: The observation schedule as run by the observers at Yangambi. Capon_1947.pdf: A copy of Capon 1947 describing the phenology research at Yangambi. yangambi_validation_annotations.rds: Validation data as an R data serialization file. yangambi_validation_data.xlsx: Validation data in the Excel format - for compatibility. Acknowledgements Historical phenological data recovery was supported by the Institut National pour l'Étude et la Recherche Agronomiques (INERA) at Yangambi. Initial digitization was funded through the COBIMFO project funded by the Belgian Science Policy Office (Belspo; contract no. SD/AR/01A). Additional, postdoctoral funding was granted by the BOF Special Research Fund, Ghent University, Belgium, the Belgian Science Policy office COBECORE project (BELSPO; grant BR/175/A3/COBECORE), the European Union Marie Skłodowska-Curie Action (project number 797668) and the NSF Macrosystems Biology programme (Award Numbers: EF-1065029). Consolidation and post-processing of the data was privately funded by BlueGreen Labs (BV).