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Exploring the floristic diversity of tropical Africa

Authors: Jan J. Wieringa; Jan J. Wieringa; Steven Janssens; Jeike L. van de Poel; Yannick Klomberg; Yannick Klomberg; Xander M. van der Burgt; +36 Authors

Exploring the floristic diversity of tropical Africa

Abstract

Understanding the patterns of biodiversity distribution and what influences them is a fundamental pre-requisite for effective conservation and sustainable utilisation of biodiversity. Such knowledge is increasingly urgent as biodiversity responds to the ongoing effects of global climate change. Nowhere is this more acute than in species-rich tropical Africa, where so little is known about plant diversity and its distribution. In this paper, we use RAINBIO - one of the largest mega-databases of tropical African vascular plant species distributions ever compiled - to address questions about plant and growth form diversity across tropical Africa.The filtered RAINBIO dataset contains 609,776 georeferenced records representing 22,577 species. Growth form data are recorded for 97% of all species. Records are well distributed, but heterogeneous across the continent. Overall, tropical Africa remains poorly sampled. When using sampling units (SU) of 0.5°, just 21 reach appropriate collection density and sampling completeness, and the average number of records per species per SU is only 1.84. Species richness (observed and estimated) and endemism figures per country are provided. Benin, Cameroon, Gabon, Ivory Coast and Liberia appear as the botanically best-explored countries, but none are optimally explored. Forests in the region contain 15,387 vascular plant species, of which 3013 are trees, representing 5-7% of the estimated world's tropical tree flora. The central African forests have the highest endemism rate across Africa, with approximately 30% of species being endemic.The botanical exploration of tropical Africa is far from complete, underlining the need for intensified inventories and digitization. We propose priority target areas for future sampling efforts, mainly focused on Tanzania, Atlantic Central Africa and West Africa. The observed number of tree species for African forests is smaller than those estimated from global tree data, suggesting that a significant number of species are yet to be discovered. Our data provide a solid basis for a more sustainable management and improved conservation of tropical Africa's unique flora, and is important for achieving Objective 1 of the Global Strategy for Plant Conservation 2011-2020. In turn, RAINBIO provides a solid basis for a more sustainable management and improved conservation of tropical Africa's unique flora.

Countries
France, Denmark, Netherlands, Belgium, Netherlands
Keywords

Time Factors, herbarium specimens, floristic patterns, Tropical forests, [SDV]Life Sciences [q-bio], herbier, forêt tropicale, Forests, Trees, CITIZEN SCIENCE, R PACKAGE, species richness, SUB-SAHARAN AFRICA, herbarium, tropical forests, Plant growth form, Agricultural and Biological Sciences(all), Geography, FLOWERING PLANTS, Floristic patterns, SPECIES RICHNESS, Biodiversity, BETA DIVERSITY, [SDV] Life Sciences [q-bio], climate change, Databases as Topic, RAIN-FORESTS, EFFECTIVE NUMBER, Biologie, Research Article, tropical forest, TOME-AND-PRINCIPE, Flowers, 333, botanical composition, Species Specificity, botanical exploration, Botanical exploration, Herbarium specimens, 580, Digitization, Tropical Climate, [ SDV ] Life Sciences [q-bio], Biochemistry, Genetics and Molecular Biology(all), plant growth forms, digitization, Herbarium specimens;Digitization;Botanical exploration; Plant growth form ;Species richness ;Floristic patterns, Africa, VASCULAR PLANTS, Species richness

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
133
Top 1%
Top 10%
Top 1%
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