Zandee M, Roos M C
Institute for Theoretical Biology, University of Leiden, The Netherlands.
Institute for Systematic Botany, University of Utrecht, The Netherlands.
Cladistics. 1987 Dec;3(4):305-332. doi: 10.1111/j.1096-0031.1987.tb00896.x.
The problems of reconstructing historical relationships for areas of endemism from distributional data for groups of taxa and the cladistic relationships among the members of those groups can be solved by applying the two principles of parsimony and mutual inclusion or exclusion (compatibility) of components. Components can be extracted from a data matrix by means of transcription into partial monothetic sets. The data matrix thus derived represents the distribution over areas for the monophyletic groups in one or more cladograms. It is derived from two different matrices by boolean multiplication. The first matrix gives the binary representation of distributions of taxa over areas of endemism; the second describes the cladogram for the same taxa, in terms of character states converted into binary form by additive binary coding. The derived data matrix can be used in historical biogeography to represent the given phyletic data (Assumption 0 here newly defined), and can be amended to reflect Assumptions 1 or 2 to accomodate the problems of wide-spread taxa and missing areas. Areacladograms are determined from the derived matrix by searching for the largest sets of mutually compatible components. Area-cladograms are evaluated in terms of support (vicariance) and contradiction (ad hoc interpretations such as dispersal and extinction). Area-cladograms that best fit the data matrix regarding the balance between support and contradiction are selected as the best possible recontructions of relationships among the areas of endemism. The procedure is illustrated by the example of the poeciliid fish genera Heterandria and Xiphophorus, and several other standard examples.
利用简约原则以及各组成部分的相互包含或排斥（兼容性）这两条原则，可以解决从分类群的分布数据重建特有区域的历史关系以及这些分类群成员之间的分支关系的问题。组成部分可以通过转录为部分单系集从数据矩阵中提取出来。这样得到的数据矩阵表示一个或多个分支图中单一谱系类群在各个区域的分布情况。它是通过布尔乘法从两个不同的矩阵推导而来的。第一个矩阵给出了分类群在特有区域分布的二进制表示；第二个矩阵则描述了相同分类群的分支图，是通过加性二进制编码将特征状态转换为二进制形式得到的。推导得到的数据矩阵可用于历史生物地理学中表示给定的系统发育数据（这里新定义的假设0），并且可以进行修正以反映假设1或假设2，从而适应广泛分布的分类群和缺失区域的问题。通过搜索最大的相互兼容组成部分集，从推导得到的矩阵中确定区域分支图。根据支持（隔离分化）和矛盾（如扩散和灭绝等特殊解释）对区域分支图进行评估。在支持和矛盾之间的平衡方面最符合数据矩阵的区域分支图被选为特有区域之间关系的最佳可能重建。以食蚊鱼属的异棉鳉属和剑尾鱼属为例以及其他几个标准例子来说明该过程。
