Szumik Claudia, Goloboff Pablo
Consejo Nacional de Investigaciones Científicas y Técnicas, Miguel Lillo 205, 4000 San Miguel de Tucumán, Tucumán, Argentina.
Syst Biol. 2004 Dec;53(6):968-77. doi: 10.1080/10635150490888859.
The grid-based method to identify areas of endemism proposed by Szumik et al. is extended. The improvements include the ability to assign scores of endemicity to sets of disjoint areas, and to have each species contribute more to the score of endemicity of an area, or less, according to how well its distribution matches the area. The modified method also allows for partially overlapping areas; an area partially overlapping with another one of higher score is retained when the set of lower score has a minimum proportion of species endemic to it. Algorithms to evaluate areas of endemism under this criterion are discussed, and implemented in a computer program (NDM). The new algorithms allow evaluation of much larger data sets.
苏米克等人提出的基于网格识别特有区域的方法得到了扩展。改进之处包括能够为不相交区域集赋予特有性得分,并且根据物种分布与区域的匹配程度,让每个物种对区域特有性得分的贡献更多或更少。改进后的方法还允许部分重叠区域;当得分较低的区域集具有该区域特有物种的最小比例时,与另一个得分较高的区域部分重叠的区域将被保留。讨论了在此标准下评估特有区域的算法,并在一个计算机程序(NDM)中实现。新算法允许评估大得多的数据集。