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Identifying areas of high biodiversity is an established way to prioritize areas for conservation [1-3], but global approaches have been criticized for failing to render global biodiversity value at a scale suitable for local management [4-6]. We assembled 3.1 million species distribution records for 40,401 vascular plant species of tropical Africa from sources including plot data, herbarium databases, checklists, and the Global Biodiversity Information Facility (GBIF) and cleaned the records for geographic accuracy and taxonomic consistency. We summarized the global ranges of tropical African plant species into four weighted categories of global rarity called Stars. We applied the Star weights to summaries of species distribution data at fine resolutions to map the bioquality (range-restricted global endemism) of areas [7]. We generated confidence intervals around bioquality scores to account for the remaining uncertainty in the species inventory. We confirm the broad significance of the Horn of Africa, Guinean forests, coastal forests of East Africa, and Afromontane regions for plant biodiversity but also reveal the variation in bioquality within these broad regions and others, particularly at local scales. Our framework offers practitioners a quantitative, scalable, and replicable approach for measuring the irreplaceability of particular local areas for global biodiversity conservation and comparing those areas within their global and regional context., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Aim: Existing phytogeographical frameworks for tropical Africa lack either spatial completeness, unit definitions smaller than the regional scale or a quantitative approach. We investigate whether physical environmental variables can be used to interpolate floristically defined vegetation units, presenting an interpolated, hierarchical, quantitative phytogeographical framework for tropical Africa, which is compared to previously defined regions. Location: Tropical mainland Africa 24°N to 24°S. Taxon: 31,046 vascular plant species and infraspecific taxa. Methods: We calculate a betasim dissimilarity matrix from a comprehensive whole‐flora database of plant species distributions. We investigate environmental correlates of floristic turnover with local non‐metric multidimensional scaling. We derive a hierarchical biogeographical framework by clustering the dissimilarity matrix. The framework is modelled using a classification decision tree method and 12 physical environmental variables to interpolate and increase the resolution of the framework across the study region. Results: Floristic turnover is related strongly to water availability and temperature, with smaller contributions from land cover, topographic ruggedness and lithology. Region can be predicted with 90% accuracy by the model. We define 19 regions and 99 districts. We find a novel arrangement of the arid regions. Regional subdivision within the savanna biome is supported with minor variation to borders. Within the forests of west and central Africa, our whole‐flora gridded regionalization supports the divisions identified by a previous analysis of trees only. Main conclusions: Physical environmental variables can be used to predict floristically defined vegetation units with very high accuracy, and the approach could be pursued for other incompletely sampled taxa and areas outside of tropical Africa. Geographical coherence is higher than in previous quantitative phytoregional definitions. For most tropical African vascular plant species, we provide predictions of which species will occur within each mapped district and region of tropical Africa. The framework should be useful for future studies in ecology, evolution and conservation. [ABSTRACT FROM AUTHOR]