Ramírez Martín J, Michalik Peter
Museo Argentino de Ciencias Naturales "Bernardino Rivadavia" - CONICET, Av. Angel Gallardo 470, C1405DJR, Buenos Aires, Argentina.
Zoologisches Institut und Museum, Ernst-Moritz-Arndt-Universität, J.-S.-Bach-Str. 11/12, D-17489, Greifswald, Germany.
Cladistics. 2014 Dec;30(6):635-649. doi: 10.1111/cla.12075. Epub 2014 Apr 22.
Complexity is an important aspect of evolutionary biology, but there are many reasonable concepts of complexity, and its objective measurement is an elusive matter. Here we develop a simple measure of complexity based on counts of elements, incorporating the hierarchical information as represented in anatomical ontologies. Neomorphic and transformational characters are used to identify novelties and individuated morphological regions, respectively. By linking the characters to terms in an anatomical ontology a node-driven approach is implemented, where a node ontology and a complexity score are inferred from the optimization of individual characters on each ancestral or terminal node. From the atomized vector of character scorings, the anatomical ontology is used to integrate the hierarchical structure of morphology in terminals and ancestors. These node ontologies are used to calculate a measure of complexity that can be traced on phylogenetic trees and is harmonious with usual phylogenetic operations. This strategy is compared with a terminal-driven approach, in which the complexity scores are calculated only for terminals, and optimized as a continuous character on the internal nodes. These ideas are applied to a real dataset of 166 araneomorph spider species scored for 393 characters, using Spider Ontology (SPD, https://bioportal.bioontology.org/ontologies/SPD); complexity scores and transitions are calculated for each node and branch, respectively. This result in a distribution of transitions skewed towards simplification; the transitions in complexity have no apparent correlation with character branch lengths. The node-driven and terminal-driven estimations are generally correlated in the complexity scores, but have higher divergence in the transition values. The structure of the ontology is used to provide complexity scores for organ systems and body parts of the focal groups.
复杂性是进化生物学的一个重要方面，但复杂性有许多合理的概念，其客观测量是一个难以捉摸的问题。在这里，我们基于元素计数开发了一种简单的复杂性度量方法，纳入了解剖学本体中所表示的层次信息。新形态特征和转变特征分别用于识别新特征和个体化的形态区域。通过将这些特征与解剖学本体中的术语相联系，实现了一种节点驱动的方法，其中从每个祖先节点或终端节点上个体特征的优化中推断出节点本体和复杂性得分。从特征评分的原子化向量出发，解剖学本体用于整合终端和祖先形态的层次结构。这些节点本体用于计算一种复杂性度量，该度量可以在系统发育树上追溯，并且与通常的系统发育操作相协调。将这种策略与一种终端驱动的方法进行比较，在终端驱动的方法中，复杂性得分仅针对终端进行计算，并作为内部节点上的连续特征进行优化。这些想法应用于一个真实的数据集，该数据集包含166种蜘蛛目蜘蛛物种的393个特征评分，使用蜘蛛本体（SPD，https://bioportal.bioontology.org/ontologies/SPD）；分别计算每个节点和分支的复杂性得分和转变。这导致转变分布偏向于简化；复杂性的转变与特征分支长度没有明显的相关性。节点驱动和终端驱动的估计在复杂性得分上通常是相关的，但在转变值上有更高的差异。本体的结构用于为焦点群体的器官系统和身体部位提供复杂性得分。
