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South African Journal of Science

versión On-line ISSN 1996-7489
versión impresa ISSN 0038-2353


PERERA, Sandun J.; RATNAYAKE-PERERA, Dayani  y  PROCHES, Serban. Vertebrate distributions indicate a greater Maputaland-Pondoland-Albany region of endemism. S. Afr. j. sci. [online]. 2011, vol.107, n.7-8, pp.52-66. ISSN 1996-7489.

The Maputaland-Pondoland-Albany (MPA) biodiversity hotspot (~274 316 km2) was primarily recognised based on its high plant endemism. Here we present the results of a qualitative biogeographical study of the endemic vertebrate fauna of south-eastern Africa, in an exercise that (1) refines the delimitation of the MPA hotspot, (2) defines zoogeographical units and (3) identifies areas of vertebrate endemism. Initially we listed 62 vertebrate species endemic and 60 near endemic to the MPA hotspot, updating previous checklists. Then the distributions of 495 vertebrate taxa endemic to south-eastern Africa were reviewed and 23 endemic vertebrate distributions (EVDs: distribution ranges congruent across several endemic vertebrate taxa) were recognised, amongst which the most frequently encountered were located in the Eastern Escarpment, central KwaZulu-Natal, Drakensberg and Maputaland. The geographical patterns illustrated by the EVDs suggest that an expansion of the hotspot to incorporate sections of the Great Escarpment from the Amatola-Winterberg-Sneeuberg Mountains through the Drakensberg to the Soutpansberg would be justified. This redefinition gives rise to a Greater Maputaland-Pondoland-Albany (GMPA) region of vertebrate endemism adding 135% more endemics with an increase of only 73% in surface area to the MPA hotspot. The GMPA region has a more natural boundary in terms of EVDs as well as vegetation units. An accurate delimitation of this hotspot, as well as a better understanding of biogeography in the region, would greatly benefit conservation planning and implementation. Towards these aims, we used EVDs to delimit non-overlapping zoogeographical units (including 14 areas of vertebrate endemism), facilitating numerical biogeographical analyses. More importantly, this study opens up possibilities of refining hotspot delimitation and identifying local conservation priorities in regions of the world where data do not allow numerical analyses.

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