Digital Knowledge of Kenyan Succulent Flora and Priorities for Future Inventory and Documentation

Biodiversity inventory in Kenya has been ongoing for about a century and a half, coinciding with the arrival of naturalists from Europe, America, and elsewhere outside Africa. Since the first collections in the mid-to-late 1800s, there has been a steady increase of plant surveys, frequency of inventory, and discovery of new species that have considerably increased knowledge of faunal and floristic elements. However, as in all other countries, such historical biological collection activities are more often than not, ad hoc, resulting in gaps in knowledge of species and their habitats. While Kenya is relatively rich botanically, with a succulent flora of about 428 taxa, it is apparent that the list is understated owing to, among other factors, difficulty of preparing herbarium material and restricted access to some sites. This study investigated completeness of geographic knowledge of succulent plants in Kenya, with the aim of establishing species distribution patterns and identifying gaps that will guide and justify priority setting for future work on the group. Species data were filtered from the general BRAHMS database at the East African Herbarium and cleaned via an iterative series of inspections and visualizations designed to detect and document inconsistencies in taxonomic concepts, geographic coordinates, and dates of collection. Eight grid squares fulfilled criteria for completeness of inventory: one in the city of Mombasa, one in the Kulal–Nyiro complex, one in Garissa, one in Baringo, and four grid squares in the Nairobi–Nakuru–Laikipia area. Poorly-known areas, mostly in the west, north, and north-eastern regions of the country, were extremely isolated from well-known sites, both geographically and environmentally. These localities should be prioritised for future inventory as they are likely to yield species new to science, species new to the national flora, and/or contribute new knowledge on habitats. To avoid inconsistencies and data leakage, biodiversity inventory and documentation needs streamlining to generate standardised metadata that should be digitised to enhance access and synthesis.