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BIOTA Africa


BIOTA Africa


The BIOTA AFRICA research network was initiated in 1999 and was funded by the German Federal Ministry of Education and Research (BMBF) until June 2010 in the context of the BIOLOG programme. This network involved more than 30 African and German projects which aimed at a holistic scientific contribution towards sustainable use and conservation of the biodiversity of the African continent. There Partners are mainly from Benin, Burkina Faso, Germany, Ivory Coast, Kenya, Uganda, Namibia and South Africa (compare


The BIOMAPS working group at the Nees Institute for Biodiversity of Plants in Bonn, focused in this context on the continental patterns of plant diversity in Africa as a model continent. In cooperation with BIOTA-internal and external partners, BIOTA BIOMAPS has established the International Biogeographical Information System on African Plant Diversity (BISAP), comprising distribution data for more than 6,500 African plant species.


Scholes, R. J., Küper, W. and Biggs, R. (2006): Chapter 2: Biodiversity, pp. 226-261. In UNEP (Ed.): Africa Environment Outlook II, Earthprint, Stevenage


Küper, W., Sommer, J. H., Lovett, J. C., Mutke, J., Linder, H. P., Beentje, H. J., van Rompaey, R. A. S. R., Chatelain, C., Sosef, M. and Barthlott, W. (2004): Africa's hotspots of biodiversity redefined. Annals of the Missouri Botanical Garden 91, 525 - 536.


Africa's hotspots of biodiversityA key problem for conservation is the coincidence of regions of high biodiversity with regions of high human impact. Twenty-five of the most threatened centers of plant diversity were identified by Myers et al., and these "hotspots" play a crucial role in international conservation strategies. The primary goal of the hotspots is to cover the most threatened centers of plant diversity, but their efficacy has not yet been tested empirically. For sub-Saharan Africa, our study evaluates the hotspots postulated by Myers and compares them to a set of redefined hotspots proposed on the basis of mapped distribution data for 5985 plant species. The two sets of hotspots overlap by 48%. Our redefined hotspots include 80% of the species and 66% of the range-restricted species of the sub-Saharan flora in areas under high human impact, whereas these values are 15% and 11% lower for Myers's hotspots. Despite having equal size and a considerable spatial overlap with Myers’s hotspots, our redefined hotspots include further highly threatened centers of plant diversity in the Maputaland Pondoland Region, in Katanga, the East African Afromontane region, the Lower Guinea Region, and the Albertine Rift. Many of these redefined hotspots are poorly protected centers of plant and animal diversity. Their conservation is essential for a comprehensive coverage of Africa’s centers of biodiversity.


Burgess, N. D., Küper, W., Mutke, J., Brown, J., Westaway, S., Turpie, S., Meshack, C., Taplin, J. R. D., McClean, C. and Lovett, J. C. (2005): Major gaps in the distribution of protected areas for threatened and narrow range Afrotropical plants. Biodiversity and Conservation 14, 1877-1894.


We investigated the major patterns of plant rarity in sub-Saharan Africa, and looked for the most significant gaps in the reserve network of the region in terms of representing the distribution of threatened and geographically rare plants. Comparisons of the species ranges captured by the network of reserves were made against the proportion of species captured by randomly generated sets of areas and against a theoretical near minimum set of areas that represent all species once. At this scale of analysis, the network of large IUCN-coded reserves (the official 'protected areas') performs poorly against random and systematic selection procedures. Significant gaps in the IUCN-coded protected areas are in coastal Gabon= Cameroon, in the various tropical montane forest areas (Cameroon Highlands, Eastern Arc Mountains, Ethiopian Mountains), in lowland coastal eastern Africa, and in the South African Cape. Some of these gaps, for example in the Eastern Arc and eastern African coastal regions, are covered on the ground by a network of Forest Reserves under the management of national Forestry Authorities. The networks of Forest Reserves in Ghana, Nigeria, Cameroon, Uganda, Kenya, Zimbabwe, Zambia and Sierra Leone also fill reservation gaps for rare African plants in these countries. Upgrading the conservation status of some key Forest Reserves, which has been gradually happening for some decades, is proposed as an efficient way to enhance the protected area network of the Afrotropical region for the conservation of rare African plant species.



McClean, C. J., Doswald, N., Küper, W., Sommer, J. H., Barnard, P. and Lovett, J.C. (2006): Potential impacts of climate change on Sub-Saharan African plant priority area selection. Diversity and Distributions 12, 645-655.


The Global Strategy for Plant Conservation (GSPC) aims to protect 50% of the most important areas for plant diversity by 2010. This study selects sets of 1-degree grid cells for 37 sub-Saharan African countries on the basis of a large database of plant species distributions. We use two reserve selection algorithms that attempt to satisfy two of the criteria set by the GSPC. The grid cells selected as important plant cells (IPCs) are compared between algorithms and in terms of country and continental rankings between cells. The conservation value of the selected grid cells are then considered in relation to their future species complement given the predicted climate change in three future periods (2025, 2055, and 2085). This analysis uses predicted climate suitability for individual species from a previous modelling exercise. We find that a country-by-country conservation approach is suitable for capturing most, but not all, continentally IPCs. The complementarity-based reserve selection algorithms suggest conservation of a similar set of grid cells, suggesting that areas of high plant diversity and rarity may be well protected by a single pattern of conservation activity.

Although climatic conditions are predicted to deteriorate for many species under predicted climate change, the cells selected by the algorithms are less affected by climate change predictions than non-selected cells. For the plant species that maintain areas of climatic suitability in the future, the selected set will include cells with climate that is highly suitable for the species in the future. The selected cells are also predicted to conserve a large proportion of the species richness remaining across the continent under climate change, despite the network of cells being less optimal in terms of future predicted distributions. Limitations to the modelling are discussed in relation to the policy implications for those implementing the GSPC.



McClean, C., Lovett, J. C., Küper, W., Hannah, L., Sommer, J. H., Barthlott, W., Termansen, M., Smith, G. F., Tokumine, S. and Taplin, J. (2005): African Plant Diversity and Climate Change. Annals of the Missouri Botanical Garden 92, 139-152.


International goals have been set to protect global plant diversity and limit ecosystem damage due to climate change, but large-scale effects of changing climate on species distributions have yet to be fully considered in conservation efforts. For sub-Saharan Africa we study the shifts in climatically suitable areas for 5197 African plant species under future climate models for the years 2025, 2055, and 2085 generated by the Hadley Center's third generation coupled ocean-atmosphere General Circulation Model. We use three species distribution models, a "Box model," a simple genetic algorithm, and a Bayes-based genetic algorithm. The results show major shifts in areas suitable for most species with large geographical changes in species composition. The areas of suitable climate for 81%–97% of the 5197 African plant species are projected to decrease in size and/or shift in location, many to higher altitudes, and 25%–42% are projected to lose all of their area by 2085. In particular, the models indicate dramatic change in the Guineo-Congolian forests, mirroring proposed ecological dynamics in the past. Although these models are preliminary and may overestimate potential extinctions, they suggest that efforts to protect African plant diversity should take future climate-forced distribution changes into account.


Linder, H. P., Lovett, J. C., Mutke, J., Barthlott, W., Jürgens, N., Rebelo, T. and Küper, W. (2005): A numerical re-evaluation of the sub-Saharan Phytochoria of mainland Africa. Biologiske Skrifter 55, 229-252.


The delimitation of the sub-Saharan mainland African phytochoria was investigated by cluster analysis and non-metric multidimensional scaling of the distributions of 5438 species, recorded from 1918 one-degree grid squares. The clusters obtained were in many instances very similar to the phytochoria delimited by White. The Guineo-Congolian Regional Centre of Endemism (RCE) was retrieved with almost the same borders, including the northern and southern transition zones and the Lake Victoria Regional Mosaic (RM). A larger Zambesian phytochorion was found – this included the Zanzibar-Inhambane Regional Mosaic, as well as part of the Somali-Masai RCE and all of the Ethiopian and Kenyan parts of the Afromontane RCE. In southern Africa the Cape RCE, the Namib-Karoo RCE, as well as an expanded Tongaland – Pondoland RM, which included all the eastern slopes of the subcontinent were located. The central parts of the subcontinent (Kalahari-Highveld Regional Transition Zone (RTZ)) was expanded to include the Drakensberg, but divided into a south-eastern and north-western unit. None of the regional mosaics were retrieved, and the blocks of the Afromontane RCE were included in the various phytochoria in which they are embedded. Cluster analysis retrieved a Sudanian phytochorion, but ordination suggested that the delimitation between the floristic zones in West Africa is complex,and that there may be very broad transitions from one phytochorion to the next.


Burgess, N. D., Balmford, A., Cordeiro, N.J., Fjeldså, J., Küper, W., Rahbek, C., Sanderson, E., Scharlemann, J.P.W., Sommer, J. H. and Williams, P. H. (2007): Relationships between biodiversity value, human density and human infrastructure across the high biodiversity tropical mountains of Africa. Biological Conservation 134, 164-177.


This paper explores whether spatial variation in the biodiversity values of vertebrates and plants (species richness, range-size rarity and number or proportion of IUCN Red Listed threatened species) of three African tropical mountain ranges (Eastern Arc, Albertine Rift and Cameroon-Nigeria mountains within the Biafran Forests and Highlands) co-vary with proxy measures of threat (human population density and human infrastructure). We find that species richness, range-size rarity, and threatened species scores are all significantly higher in these three tropical African mountain ranges than across the rest of sub-Saharan Africa. When compared with the rest of sub-Saharan Africa, human population density is only significantly higher in the Albertine Rift mountains, whereas human infrastructure is only significantly higher in the Albertine Rift and the Cameroon-Nigeria mountains. Statistically there are strong positive correlations between human density and species richness, endemism and density or proportion of threatened species across the three tropical African mountain ranges, and all of sub-Saharan Africa. Kendall partial rank-order correlation shows that across the African tropical mountains human population density, but not human infrastructure, best correlates with biodiversity values. This is not the case across all of sub-Saharan Africa where human density and human infrastructure both correlate almost equally well with biodiversity values. The primary conservation challenge in the African tropical mountains is a fairly dense and poor rural population that is reliant on farming for their livelihood. Conservation strategies have to address agricultural production and expansion, in some cases across the boundaries and into existing reserves. Strategies also have to maintain, or finalise, an adequate protected area network. Such strategies cannot be implemented in conflict with the local population, but have to find ways to provide benefits to the people living adjacent to the remaining forested areas, in return for their assistance in conserving the forest habitats, their biodiversity, and their ecosystem functions.


Küper, W., Sommer, J. H., Lovett, J. C. and Barthlott, W. (2006): Deficiency in African plant distribution data-missing pieces of the puzzle. Botanical Journal of the Linnean Society 150, 355-368.


Deficiency in African plant distributionBiodiversity is spatially unevenly distributed, and so is the information on its spatial patterns. This uneven distribution of information on species occurrences is an important impediment to the conservation of biodiversity. Based on 185,427 collection records of 5873 plant species in sub-Saharan Africa, we analyse the availability of distribution data suitable for the GIS-based mapping of plant diversity patterns at a one-degree resolution. Using the bioclimatic model GARP, distribution ranges for each species were modeled. In order to identify data deficient areas, the documented and modeled diversity patterns were compared. Only for a few, well-known centres of plant diversity comparatively many collection records data are available. For several of the areas with very few collection records such as the Guinean montane forests, the northwestern Congolian lowland forests, and the southern Albertine Rift montane forests, the model predicts a species richness much higher than currently documented. In many of the data deficient areas, difficult conditions for scientific work seem to have limited collection activities over decades. Only strategic field collections could fill these gaps. Another cause of data deficiency is that data yet collected and even digitised do not match quality requirements for GIS-based work at super-regional scale. In particular, regional databases documenting partial ranges of species are rarely connected. One challenge for the Global Strategy for Plant Conservation is therefore to establish international collaborative structures and technical standards that allow analysing biogeographic patterns across political boundaries.


Küper, W., Wagner, T. and Barthlott, W. (2005): Diversity patterns of plants and phytophagous beetles in Sub-Saharan Africa. Bonner Zoologische Beiträge. In commemoration of Clas Michael Naumann zu Königsbrück. 53, 283-289.


Species distribution of flowering plants (Angiospermae) and the phytophagous beetle group Monolepta (Chrysomelidae) in Sub-Saharan Africa (south of 17° N) are compared based on species numbers per square degree grid. The beetle data comprise all 89 valid species for Africa (21,000 specimens of Afrotropical Monolepta have been currently revised). The plant diversity data are based on 6,269 species with some 330,000 distributional records (10–15 % of all African angiosperm species). Shared centres of species richness of both taxa are geodiverse, montane forests, namely the Albertine Rift, Eastern Arc Mountains, isolated East African volcanoes, montane areas in Cameroon and northeastern parts of a the Republic of South Africa. However, the Cape and the Upper Guinea Region show diverging patterns: plant species richness is higher than the richness of Chrysomelidae. Actual diversity patterns versus sampling artefacts are discussed. Certain mechanisms, like allopatric speciation processes, contribute to a diverse flora and fauna in areas of high geodiversity. Thus, if there is a general and taxon-independent positive relationship between geodiversity and species richness, these areas are of explicit value for the conservation of terrestrial biodiversity.


Schmidt, M., Kreft, H., Thiombiano, A. and Zizka, G. (2005): Herbarium collections and field data-based plant diversity maps for Burkina Faso. Diversity and Distributions 11, 509-516.


A map of plant species diversity in Burkina Faso is presented based on field observations and specimen data from the Ouagadougou University Herbarium (OUA) and the Herbarium Senckenbergianum (FR). A map of collecting intensity and field observations illustrates centres of botanical research activities in Burkina Faso. To overcome problems associated with biased sampling intensity, distributions of species have been modelled and extrapolated to maps of vascular plant diversity, life forms and diversity of four selected families (Poaceae, Cyperaceae, Dioscoreaceae and Rubiaceae). The area of most intensive collection and observation is around Gorom-Gorom and Fada N'Gourma. Modelled diversity generally increases towards the south, as does the proportion of phanerophytes, lianas and hemicryptophytes, while the opposite trend is observed for therophytes. Poaceae diversity is highly correlated with total vascular plant diversity, making the family especially suitable as an indicator for overall plant diversity. Cyperaceae are rather evenly distributed throughout the country, Dioscoreaceae are restricted to the Sudanian Zone. Rubiaceae have their highest diversities in the very south.

Our approach can be transferred to areas with a similar database, certainly to other areas within West Africa. Future research should focus on distribution data for rare species, enabling our approach to evaluate the West African system of protected areas.


Mutke, J., Kier, G., Braun, G., Schultz, C. and Barthlott, W. (2001): Patterns of African vascular plant diversity – a GIS based analysis. Systematics and Geography of Plants 71, 1125-1136.

 Mutke et al 2001: African Plant Diversity

Using a GIS based approach, a new map of African vascular plant species richness is presented. The underlying phytodiversity dataset comprises metadata on the floras of 450 geographical units in Africa and Madagascar, including the data records used by Lebrun (1960) and Barthlott & al. (1996, 1999a) for their maps. 151 of these were selected as suitable to analyse correlation of species richness with different environmental parameters in a GIS and to generate the map of African phytodiversity. For the production of the map we used a weighted overlay of the raw data, an interpolation approach and a multiple regression model. Best correlation with species richness were found for annual sum of NDVI, number of dry months and water balance. Centres of high species richness in Africa are the Capensis, Eastern Madagascar, the coastal areas of SE Nigeria, Cameroon, Equatorial Guinea and Gabon, as well as the Drakensberg mountains, and the East African Mountains. These areas are also centres of high geodiversity. For one aspect of geodiversity, the topodiversity, we present a first map for Africa.


Kier, G. and Barthlott, W. (2001): Measuring and mapping endemism and species richness: a new methodological approach and its application on the flora of Africa. Biodiversity and Conservation 10, 1513-1529.


The adjustment of an existing index which combines endemism and species richness (Williams 1993) is proposed so that it requires markedly less data on the study area and its flora or fauna than was necessary with the conventional calculation method. Using this adjusted method, the resulting scores are calculated and mapped for the seed plant flora of the 20 African regions as delineated by White (1983). We argue that this index, here referred to as a measure of 'endemism richness', can be regarded as the specific contribution of an area to global biodiversity. We demonstrate that at a given sampling scale it shows a linear relation with area. We further demonstrate that, within certain limits, this linearity can also be observed in many cases when sampling scales vary which makes the comparison of differently sized geographic units easier than is the case for species richness. The two most important advantages over species richness are that this index is more suitable to measure both the conservation value of an area and the negative impact of invaders. The latter quality is due to the fact that it yields scores which usually do not rise substantially but can rather be expected to drop in many cases when an area is invaded by alien species.

See also: world map of endemism richness


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