Understanding the natural world is not possible with out an extensive knowledge of organismal morphology. The encyclopedia of life (Wilson, 2003) would be an empty, sterile list without detailed information about the full range of morphological diversity. Morphology plays a pivotal role in our understanding of life cycles, geographical distributions, identification, conservation status, evolution, development, and species delimitation (Buzgo et al, 2004; Endress, 2000; Kaplan, 2001; Scotland et al., 2003a). Nonetheless, there remains considerable debate about the precise role of morphology in one par ticular area of biology ? computer-based phylogenetic inference (Baker and Gatesy, 2002; Hillis and Wiens, 2000; Jenner, 2004; Scotland et al, 2003b; Smith and Turner, 2005; Wortley and Scotland, 2006; Wiens, 2004). One widespread contemporary use of morphological data in phylogeny reconstruction is in combined anal ysis with molecular sequence data (recent examples in clude Aagesen and Sanso, 2003; Cameron and Williams, 2003; Cohen et al, 2004; Dorchin et al, 2004; Hebsgaard et al., 2004; Lundberg and Bremer, 2003; Michelangeli et al, 2003; Near et al, 2003; Pedersen et al., 2003; Zrzavy, 2003). Despite the methodological, conceptual, and philosophical issues surrounding combined analy ses of independent data partitions (Ballard, 1996; Bal lard et al., 1998; Brower et al., 1996; Bull et al, 1993; De Queiroz et al., 1995; Farris, 2000; Huelsenbeck et al., 1996; Kluge, 1998; Levasseur and Lapointe, 2001; Nixon and Carpenter, 1996; Page, 1996; Pupko et al, 2002), the number of combined analyses conducted recently demonstrates that this is a popular way of integrating morphological data into phylogenetic analyses. Recent empirical studies have both questioned (e.g., Gaubert et al., 2005) and defended (e.g., Wahlberg et al., 2005) the role of morphology in phylogenetic analysis, with equal vigor. Although individual studies such as these can be highly informative and compelling, it is doubtful whether they can effectively reflect general trends. In 1998, Baker et al. investigated the contribution of morphological data sets to combined analyses with molecular data across a range of studies and found that the support contributed by morphological data was substantial, and often greater than that provided by molecular data. Since then, molecular sequence data sets have dramatically increased in size (from an average of 156 parsimony-informative characters across the 15 molecular data sets studied in Baker et al. (1998) to an average of 391 parsimony-informative characters across the 26 data sets analyzed in this paper), whereas morpho logical data sets have remained approximately the same (from an average of 40 parsimony-informative charac ters in Baker et al., 1998, to 47 parsimony-informative characters here). Since the first phylogenetic analyses using molecular data, more than 20 years ago (e.g., Curtis and Clegg, 1984; Hillis, 1987; Rogers and Bendick, 1985), the composition of molecular data sets has also changed. Molecular data sets can include amplified fragment length polymorphisms (AFLPs), restriction fragment length polymorphisms (RFLPs), protein and DNA sequences, coded gaps, and secondary chemicals. At the time of Baker et al.'s (1998) study, only two-thirds of "molecular" analyses considered comprised DNA sequence data. Today, the vast majority of analyses of molecular data comprise DNA sequences (all of the molecular data sets studied in this paper included DNA sequence, 24 out of 26 exclusively). Changes in the size and composition of molecular data sets used in phyloge netic analysis imply that the relative contribution of mor phological data to combined analyses with molecular data may also have changed significantly in recent years. In the context of the ongoing debate surrounding molecular and morphological data in phylogenetic stud ies, there is a need for a broad survey to assess this de velopment, and in particular to determine the effect of adding morphological data to molecular sequence data in combined analysis today. This has the potential to provide important general insights about current prac tice that individual, taxon-specific analyses do not. Two

中文翻译：

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在已发表的系统发育分析中结合分子和形态学数据的影响

如果没有广泛的有机体形态知识，就不可能了解自然世界。生命百科全书 (Wilson, 2003) 将是一个空洞的、没有内容的清单，没有关于所有形态多样性的详细信息。形态学在我们理解生命周期、地理分布、鉴定、保护状态、进化、发展和物种定界方面发挥着关键作用（Buzgo 等，2004；Endress，2000；Kaplan，2001；Scotland 等，2003a）。尽管如此，关于形态在生物学的一个特定领域中的确切作用仍然存在相当多的争论？基于计算机的系统发育推断（Baker 和 Gatesy，2002；Hillis 和 Wiens，2000；Jenner，2004；Scotland 等，2003b；Smith 和 Turner，2005；Wortley 和 Scotland，2006；Wiens，2004）。现代在系统发育重建中广泛使用形态学数据的一种方法是结合分析与分子序列数据（最近的例子包括 Aagesen 和 Sanso，2003；Cameron 和 Williams，2003；Cohen 等，2004；Dorchin 等，2004；Hebsgaard 等al.，2004；Lundberg 和 Bremer，2003；Michelangeli 等，2003；Near 等，2003；Pedersen 等，2003；Zrzavy，2003）。尽管围绕独立数据分区的组合分析存在方法论、概念和哲学问题（Ballard，1996 年；Bal lard 等人，1998 年；Brower 等人，1996 年；Bull 等人，1993 年；De Queiroz 等人，1995 年） ; Farris, 2000; Huelsenbeck et al., 1996; Kluge, 1998; Levasseur and Lapointe, 2001; Nixon and Carpenter, 1996; Page, 1996; Pupko et al, 2002), 最近进行的组合分析的数量表明，这是将形态学数据整合到系统发育分析中的一种流行方式。最近的实证研究对形态学在系统发育分析中的作用提出了质疑（例如，Gaubert 等人，2005 年）并为其辩护（例如，Wahlberg 等人，2005 年）。尽管诸如此类的个别研究可能具有很高的信息量和说服力，但它们能否有效反映总体趋势仍值得怀疑。1998 年，贝克等人。调查了形态学数据集对一系列研究中分子数据组合分析的贡献，发现形态学数据提供的支持是巨大的，并且通常比分子数据提供的支持更大。自那时候起，分子序列数据集的大小显着增加（从 Baker et al. (1998) 研究的 15 个分子数据集的平均 156 个简约信息字符到 26 个分析的 26 个数据集的平均 391 个简约信息字符）本文），而形态学数据集保持大致相同（从 Baker et al., 1998 中的平均 40 个简约信息字符到这里的 47 个简约信息字符）。自 20 多年前首次使用分子数据进行系统发育分析以来（例如 Curtis 和 Clegg，1984；Hillis，1987；Rogers 和 Bendick，1985），分子数据集的组成也发生了变化。分子数据集可以包括扩增片段长度多态性 (AFLP)、限制性片段长度多态性 (RFLP)、蛋白质和 DNA 序列、编码间隙和二级化学品。在 Baker 等人 (1998) 的研究中，只有三分之二的“分子”分析被认为包含 DNA 序列数据。今天，绝大多数分子数据分析都包含 DNA 序列（本文研究的所有分子数据集都包括 DNA 序列，26 个中的 24 个）。系统发育分析中使用的分子数据集的大小和组成的变化意味着近年来形态学数据对分子数据组合分析的相对贡献也可能发生了显着变化。在系统发育研究中围绕分子和形态学数据持续争论的背景下，需要进行广泛的调查来评估这种发展，尤其是确定在当今的组合分析中将形态学数据添加到分子序列数据中的效果。这有可能提供有关当前实践的重要一般见解，而个别、特定于分类单元的分析则没有。二