A new model for efficient, need‐driven progress in generating primary biodiversity information resources

Abstract

Premise The field of biodiversity informatics has developed rapidly in recent years, with broad availability of large‐scale information resources. However, online biodiversity information is biased spatially as a result of slow and uneven capture and digitization of existing data resources. The West African Plants Initiative approach to data capture is a prototype of a novel solution to the problems of the traditional model, in which the institutional “owner” of the specimens is responsible for digital capture of associated data.

Methods We developed customized workflows for data capture in formats directly and permanently useful to the “owner” herbarium, and digitized significant numbers of new biodiversity records, adding to the information available for the plants of the region.

Results In all, 190,953 records of species in 1965 genera and 331 families were captured by mid‐2018. These data records covered 16 West African countries, with most of the records (10,000–99,999) from Côte d'Ivoire, Ghana, Togo, Nigeria, and Cameroon, and the fewest data records from Mauritania (<100 records). The West African Plants Initiative has increased available digital accessible knowledge records for West African plants by about 54%. Several of the project institutions have put initial project data online as part of their Global Biodiversity Information Facility data contributions. The average cost of data capture ranged from US$0.50−1.00 per herbarium sheet.

Discussion Data capture has been cost‐effective because it is much less expensive than de novo field collections, allows for development of information resources even for regions in which political situations make contemporary field sampling impossible, and provides a historical baseline against which to compare newer data as they become available. This new paradigm in specimen digitization has considerable promise to accelerate and improve the process of generating high‐quality biodiversity information, and can be replicated and applied in many biodiversity‐rich, information‐poor regions to remedy the present massive gaps in information availability.