Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 2 de 2
Filtrar
Mais filtros








Base de dados
Intervalo de ano de publicação
1.
BMC Biol ; 15(1): 15, 2017 03 07.
Artigo em Inglês | MEDLINE | ID: mdl-28264718

RESUMO

BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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.


Assuntos
Biodiversidade , Flores/fisiologia , Clima Tropical , África , Bases de Dados como Assunto , Florestas , Geografia , Especificidade da Espécie , Fatores de Tempo , Árvores/crescimento & desenvolvimento
2.
PhytoKeys ; (74): 1-18, 2016.
Artigo em Inglês | MEDLINE | ID: mdl-28127234

RESUMO

The tropical vegetation of Africa is characterized by high levels of species diversity but is undergoing important shifts in response to ongoing climate change and increasing anthropogenic pressures. Although our knowledge of plant species distribution patterns in the African tropics has been improving over the years, it remains limited. Here we present RAINBIO, a unique comprehensive mega-database of georeferenced records for vascular plants in continental tropical Africa. The geographic focus of the database is the region south of the Sahel and north of Southern Africa, and the majority of data originate from tropical forest regions. RAINBIO is a compilation of 13 datasets either publicly available or personal ones. Numerous in depth data quality checks, automatic and manual via several African flora experts, were undertaken for georeferencing, standardization of taxonomic names and identification and merging of duplicated records. The resulting RAINBIO data allows exploration and extraction of distribution data for 25,356 native tropical African vascular plant species, which represents ca. 89% of all known plant species in the area of interest. Habit information is also provided for 91% of these species.

SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA