Species discovery and validation in a cryptic radiation of endangered primates: coalescent-based species delimitation in Madagascar's mouse lemurs

Implementation of the coalescent model in a Bayesian framework is an emerging strength in genetically based species delimitation studies. By providing an objective measure of species diagnosis, these methods represent a quantitative enhancement to the analysis of multilocus data, and complement more traditional methods based on phenotypic and ecological characteristics. Recognized as two species 20 years ago, mouse lemurs (genus Microcebus) now comprise more than 20 species, largely diagnosed from mtDNA sequence data. With each new species description, enthusiasm has been tempered with scientific scepticism. Here, we present a statistically justified and unbiased Bayesian approach towards mouse lemur species delimitation. We perform validation tests using multilocus sequence data and two methodologies: (i) reverse-jump Markov chain Monte Carlo sampling to assess the likelihood of different models defined a priori by a guide tree, and (ii) a Bayes factor delimitation test that compares d...在贝叶斯框架（Bayesian framework）下应用溯祖模型（coalescent model），是当前基于遗传学的物种界定研究领域新兴的重要研究方向。这类方法通过为物种鉴定提供客观的衡量标准，实现了多位点数据分析的量化升级，同时可作为基于表型和生态特征的传统研究方法的重要补充。20年前曾被认定为2个物种的鼠狐猴属（Microcebus），目前已被划分为超过20个物种，其物种界定大多基于线粒体DNA（mtDNA）序列数据。每有新的物种被正式描述，学界的研究热情总会伴随科学性质疑而有所降温。本研究提出了一种具备统计学合理性且无偏的贝叶斯方法，用于鼠狐猴的物种界定。本研究采用多位点序列数据与两种方法开展验证测试：其一为可逆跳马尔可夫链蒙特卡洛（reverse-jump Markov chain Monte Carlo）采样，用于评估由向导树（guide tree）先验定义的不同模型的似然值；其二为贝叶斯因子界定检验（Bayes factor delimitation test），用于比较……