As a megadiverse country with a rapidly growing population, South Africa is experiencing a biodiversity crisis: natural habitats are being degraded and species are becoming threatened with extinction. In an era of big biodiversity data and limited conservation resources, conservation biologists are challenged to use such data for cost-effective conservation planning. However, while extensive, key genomic and distributional databases remain incomplete and contain biases. Here, we compiled data on the distribution of South Africa’s > 10,000 endemic plant species, and used species distribution modelling to identify regions with climate suitable for supporting high diversity, but which have been poorly sampled. By comparing the match between projected species richness from climate to observed sampling effort, we identify priority areas and taxa for future biodiversity sampling. We reveal evidence for strong geographical and taxonomic sampling biases, indicating that we have still not fully captured the extraordinary diversity of South Africa’s endemic flora. We suggest that these knowledge gaps contribute to the insufficient protection of plant biodiversity within the country—which reflect part of a broader Leopoldean shortfall in conservation data.

南非是一个人口迅速增长的多元化国家，它正在遭受生物多样性危机：自然栖息地正在退化，物种正面临灭绝的威胁。在生物多样性数据庞大且保护资源有限的时代，保护生物学家面临着将此类数据用于经济有效的保护计划的挑战。但是，尽管广泛，关键的基因组和分布数据库仍然不完整，并且存在偏差。在这里，我们收集了有关南非超过10,000种特有植物物种分布的数据，并使用物种分布模型来确定气候适宜于支持高度多样性但采样率较低的区域。通过比较预估的气候物种丰富度与观察到的采样工作之间的匹配，我们确定了未来生物多样性采样的优先领域和分类单元。我们揭示了强大的地理和生物分类抽样偏见的证据，表明我们仍未完全捕捉到南非特有植物群的非凡多样性。我们建议这些知识鸿沟导致该国对植物生物多样性的保护不足-这反映了Leopoldean保护数据不足。