Minoli Ignacio, Morando Mariana, Avila Luciano J
CENPAT-CONICET. Boulevard Almirante Brown 2915, (U9120ACD), Puerto Madryn, Chubut, Argentina; Email:
CENPAT-CONICET. Boulevard Almirante Brown 2915, (U9120ACD), Puerto Madryn, Chubut, Argentina; Email: unknown.
Zootaxa. 2014 Aug 26;3856(4):501-28. doi: 10.11646/zootaxa.3856.4.3.
It has long been considered sufficient a single method or only a descriptive diagnosis to propose a new species. Recently, many works have proposed new theoretical paradigms to consider multiple sources of evidence to support the hypothesis of new taxa within an integrative approach. Despite this, many new described species continue to be merely descriptive and without any reproducible statistical analysis to support these descriptions. We tested whether five species described as members of a species complex of the lizard genus Liolaemus from Patagonia, can be differentiated based on classical morphometric analyses and ecological niche modeling. Individuals were sampled from their type localities. Our results showed that the univariate tests and Principal Component Analyses (PCA) were more accurate to differentiate species compared to the Linear Discriminant Analyses (LDA). However, there were almost no morphometric differences between two of the analyzed species. Major differences were found in bioclimatic variables of four of the species through Maxent ENMs and PCA using the original worldclim variables. Our results partially support the hypothesis that species can be differentiated by classical morphometric analyses, and found a strong support for the hypothesis that these taxa can be differentiated through their bioclimatic niches. These two approaches based on repeatable statistical basis, can supplement qualitative descriptive diagnoses of new species of the genus Liolaemus.
长期以来,人们一直认为仅用单一方法或仅进行描述性诊断就足以提出一个新物种。最近,许多研究提出了新的理论范式,以在综合方法中考虑多种证据来源来支持新分类单元的假设。尽管如此,许多新描述的物种仍然只是描述性的,没有任何可重复的统计分析来支持这些描述。我们测试了来自巴塔哥尼亚的被描述为鬃狮蜥属一个物种复合体成员的五个物种,是否可以基于经典形态测量分析和生态位建模进行区分。个体是从它们的模式产地采集的。我们的结果表明,与线性判别分析(LDA)相比,单变量测试和主成分分析(PCA)在区分物种方面更准确。然而,在所分析的两个物种之间几乎没有形态测量差异。通过使用原始的世界气候变量进行最大熵生态位模型(Maxent ENMs)和主成分分析,在四个物种的生物气候变量中发现了主要差异。我们的结果部分支持了物种可以通过经典形态测量分析进行区分的假设,并为这些分类单元可以通过其生物气候生态位进行区分的假设提供了有力支持。这两种基于可重复统计基础的方法,可以补充鬃狮蜥属新物种的定性描述性诊断。