Limited access to taxonomic and biogeographical data on plants across large spatial scales poses challenges for biodiversity research. This study examined richness, taxonomic contributions and biogeographic insights derived from a floristic inventory encompassing 56,144 km² of the Caatinga Phytogeographic Domain (CPD), carried out within the framework of environmental licensing for a water infrastructure project (São Francisco River Transposition Project – PISF). Over a period of fifteen years, specimens from various plant groups (algae, angiosperms, bryophytes, ferns and lycophytes) were collected and taxonomic, ecological and biogeographic data were compiled for the species occurring in the study area (e.g. threat status, life form, geographic origin, endemism within the CPD), resulting in a checklist and a biodiversity dataset. The number of plant samples and species richness recorded in the study area was compared with previously available data. Rarefaction curves were used to assess the increase in species richness in relation to sampling effort within the study area. A total of 29,247 samples were collected, resulting in the identification of 1,610 species. Herbaceous plants represented the dominant group, accounting for 40.89% of the species richness. A total of 173 species endemic to the CPD were recorded, along with 16 species listed in the Brazilian national list of threatened species. Furthermore, 284 first occurrences of 110 species were registered for one or more states in the Northeast of Brazil or within the CPD. Two new species were described in collaboration with taxonomic specialists and the donation of duplicate samples to national herbaria led to the citation of five paratypes. The checklist increased the number of specimens previously recorded in the study area by 240% and expanded the known species richness by approximately 14%. The rarefaction curve computed from the dataset indicated a tendency towards stabilisation of species numbers in the area. These findings highlight the value of primary data generated through environmental licensing linked to infrastructure projects in addressing biodiversity knowledge gaps.
Cotarelli et al. (Mon,) studied this question.