Biodiversity in the Republic of Guinea: Evidence, Threats, Conservation and Research Priorities — A Review and Bibliometric Map
Abstract
This evidence map characterises how biodiversity research concerning the Republic of Guinea is represented in a fixed OpenAlex record set and complements the literature map with an illustrative Global Biodiversity Information Facility (GBIF) occurrence-data sample. Ten English-language query families were run in OpenAlex on 22 July 2026, producing 852 unique records after identifier deduplication. Lexical and thematic screening yielded a fixed 120-record descriptive corpus. Because the source search was restricted to OpenAlex and the corpus may contain contextual regional records and different publication versions, it is treated as a bibliometric record set rather than an exhaustive systematic-review corpus; Guinea-specific narrative conclusions are restricted to studies with identifiable evidence from the country. Non-exclusive coding identified strong representation of forests and flora (89 records), conservation pressures, and primates and other mammals, with marked concentration in Forest Guinea, Mount Nimba and established primate-research sites. An illustrative subset of 2,996 georeferenced GBIF occurrences was drawn from 415,770 country-coded occurrences reported by the API at retrieval; this subset is used only to visualise data availability and not to estimate national richness or taxonomic composition. The mapped literature documents substantial biological value and recurring pressures associated with habitat conversion, infrastructure and mining, hunting, fire and wood extraction, and climate-related risks, while revealing uneven geographic and taxonomic coverage. Priority needs include harmonised national inventories, longitudinal observatories, research on neglected taxa, cumulative-impact assessment, protected-area evaluation, ecological connectivity, aquatic systems and community-centred monitoring. The analysis is therefore best interpreted as an exploratory map of a bounded indexed corpus that identifies research clusters and information gaps and provides a transparent foundation for a future multi-database systematic map and a national biodiversity data infrastructure.