Perera Sandun J, ProcheŞ Şerban, Ratnayake-Perera Dayani, Ramdhani Syd
School of Agricultural, Earth and Environmental Sciences, University of KwaZulu-Natal, Westville Campus, Private Bag X54001, Durban 4000, South Africa. Current Address: Department of Natural Resources, Sabaragamuwa University of Sri Lanka, P.O. Box. 2, Belihuloya 70140, Sri Lanka..
Zootaxa. 2018 Feb 20;4382(1):56-92. doi: 10.11646/zootaxa.4382.1.2.
We use numerical methods to explore patterns of vertebrate endemism in south-eastern Africa, refining the boundaries of the intuitively-defined Maputaland-Pondoland-Albany biodiversity hotspot, also proposing a zoogeographic regionalisation. An incidence matrix of 300 vertebrate species endemic to south-eastern Africa sensu lato in 37 operational geographic units were used in (a) phenetic cluster analysis (PCA) using the algorithm of unweighted pair-group method with arithmetic averages (phenetic approach), and (b) parsimony analysis of endemicity (PAE; parsimony approach), in order to numerically evaluate the bioregional delimitations. The analyses provide a valid biogeographical entity 37% larger than the Maputaland-Pondoland-Albany hotspot, but substantially (131%) higher in vertebrate endemicity viz. the Greater Maputaland-Pondoland-Albany (GMPA) region of vertebrate endemism. South-east Africa is recognised as a dominion in the global zoogeographical area hierarchy, with subordinate units including the GMPA province. Various spatially-based measures of endemism were mapped for vertebrate species restricted to the dominion, i.e. endemic to south-eastern Africa sensu stricto. Areas and centres of endemism detected respectively from PAE and PCA, within the south-east Africa dominion also support the refined boundary of the GMPA region of endemism, which provides a better spatial conservation priority compared to the Maputaland-Pondoland-Albany hotspot. Reptiles and amphibians are found to be the main drivers of the overall pattern of endemism, while the pattern in freshwater fish is the most distinctive. Our analyses also indicate a good congruence of the centres of endemism across different terrestrial vertebrate taxa.
我们运用数值方法来探究非洲东南部脊椎动物的特有性模式,完善直观定义的马普托兰-蓬多兰-奥尔巴尼生物多样性热点地区的边界,并提出一种动物地理区划。在37个操作地理单元中,使用了300种非洲东南部广义特有脊椎动物物种的发生率矩阵,用于(a)采用算术平均法的非加权配对组法算法的表型聚类分析(PCA,表型方法),以及(b)特有性简约分析(PAE,简约方法),以便从数值上评估生物区域划分。分析得出一个有效的生物地理实体,其面积比马普托兰-蓬多兰-奥尔巴尼热点地区大37%,但脊椎动物特有性显著更高(高131%),即脊椎动物特有性的大马普托兰-蓬多兰-奥尔巴尼(GMPA)地区。非洲东南部被认为是全球动物地理区域层次中的一个区域,下属单元包括GMPA省。针对仅限于该区域的脊椎动物物种,即非洲东南部狭义特有物种,绘制了各种基于空间的特有性度量图。在非洲东南部区域内,分别从PAE和PCA检测到的特有性区域和中心也支持特有性GMPA地区的细化边界,与马普托兰-蓬多兰-奥尔巴尼热点地区相比,该边界提供了更好的空间保护优先级。研究发现,爬行动物和两栖动物是特有性总体模式的主要驱动因素,而淡水鱼的模式最为独特。我们 的分析还表明,不同陆地脊椎动物类群的特有性中心具有良好的一致性。