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Digital accessible Knowledge (DAK) is of utmost importance for biodiversity conservation; indeed, their use are indispensable to provide evidence and strategies to support decision-making on natural resource management and sustainable use. The Global Biodiversity Information Facility (GBIF, www.gbif.org) is a mega data infrastructure with more than two billion occurrence records as of 28th May 2022. It is by far the largest initiative assembling and sharing DAK to support scientific research, conservation, and sustainable development. We decided to analyze plant data published on GBIF site at the scale of Africa. This will highlight the contribution of the continent to GBIF and thereby underline data gaps across taxonomic groups, basis of records, and geographic space. In order to achieve our purpose, we downloaded data of the Plantae kingdom from Africa. They are available at https://doi.org/10.15468/dl.f79228. We achieved data treatment and analysis using R, several packages and related functions. Although Africa is home to a rich biodiversity with many hotspots, the global data contribution of Africa to GBIF is still incredibly low (1.37%). Furthermore, there are huge disparities between African countries with South Africa contributing alone for 65% of the data of the continent. The plant data of Africa (2,713,790 occurrence records) accounted for 9.11% of the data of the continent; this underlines huge gaps between taxonomic groups. Furthermore, the Magnoliopsida is the dominant plant class with the highest number of records (79.62%) and the highest number of species (71.85%) followed by the Liliopsida with 15.10% of the records and 18.16% of the species. Two basis of records were dominant: preserved specimens (75.49%) and human observation (18.60%). In geographic space, plant data gaps are also quite huge across the continent at either spatial resolution (half degree or one degree spatial grid cells); data completeness is more achieved in West Africa, East Africa, Southern Africa, and Madagascar. The huge multidimensional data gaps identified in this study should be in priority addressed in the future data collections. Accessibility either by roads or waterways and protected areas are underpinning factors of data completeness across the continent. We deplored important data loss during the process of data cleaning; indeed the total number of records with adequate coordinates accounted for 71.03% of the initial data while the data fitness for use in completeness analysis (records with adequate coordinates and full dates) are only about 65% of the total data records initially downloaded. |
