Table 6 in Simonachne, a new genus for Australia segregated from Ancistrachne s. l. (Poaceae: Panicoideae: Paniceae) and a new subtribe Cleistochloinae

Table 6. Summary of results from cluster analyses. VariableDescription of variationFigureRemarksAlgorithmClassification analysis using baseline dataset of 24 samples and 161 characters using two assocaition measures, Czekanowski and GowerFig. 5Topologies using the two association measures are congruent.Ordination using dataset of 24 samples and 161 characters with Gower association measureFig. 6Relationships of clusters compatible with those from the classification analysis for the same dataset.Sample set compositionDatasets with 10, 24 and 30 samples dataset and 161 characters and classification analysis using Gower association measure (Test 1)Fig. 5, Appendix 3All topologies agree with results from analysis of baseline dataset.Character formatAll characters in binary format comprising dataset of 365 characters and 24 samples and classification analysis using Gower association measure (Test 2)Fig. 5Topology congruent with that for the baseline dataset.Character set composition102 characters from Thompson and Fabillo (2021) and classification analysis using Gower association measure (Test 3)Fig. 5Topology shows the same relationships of taxa as for baseline dataset. Taxon relationships congruent with cladogram by Thompson and Fabillo (2021).Fifteen datasets compiled from the most discriminating characters and classification analyses using Gower association measure (Test 4)Appendix 4For the top 30 most discriminating characters, the three major clusters were the same as for the baseline dataset. Results for the top 130–150 characters were congruent with the baseline results.A priori set of 15 characters from Morrone et al. (2012), datasets with 8 and 24 samples andAppendix 5Topology for the 8-sample set congruent with the baseline dataset at 3-group level.classification analyses using Gower and Czekanowski association measures (Test 5)Topology for 24-sample set not congruent with baseline at 3-group level using Gower association measure, congruent using Czekanowski. Clusters for Cleistochloinae and Neurachninae congruent with baseline.表6 聚类分析结果汇总 1. 变量：分类分析 变异描述：采用包含24个样本、161个性状的基线数据集，结合两种关联度量——切卡诺夫斯基（Czekanowski）与高爾（Gower） 图表：图5 备注：两种关联度量得到的拓扑结构一致。 2. 变量：排序分析 变异描述：采用包含24个样本、161个性状的数据集，使用高爾关联度量开展排序分析 图表：图6 备注：聚类关系与同一数据集的分类分析结果相符。 3. 变量：样本集组成 变异描述：构建包含10、24、30个样本及161个性状的数据集，采用高爾关联度量开展分类分析（试验1） 图表：图5、附录3 备注：所有拓扑结构均与基线数据集的分析结果一致。 4. 变量：性状格式 变异描述：采用二进制格式的全部性状，数据集包含365个性状、24个样本，使用高爾关联度量开展分类分析（试验2） 图表：图5 备注：拓扑结构与基线数据集的分析结果一致。 5. 变量：性状集组成 变异描述：采用取自Thompson与Fabillo (2021)的102个性状，使用高爾关联度量开展分类分析（试验3） 图表：图5 备注：拓扑结构显示的类群间关系与基线数据集一致，且与Thompson和Fabillo (2021)的分支图类群关系相符。 6. 变量：分类分析（试验4） 变异描述：从最具区分度的性状中构建15个数据集，采用高爾关联度量开展分类分析 图表：附录4 备注：选取前30个最具区分度的性状时，得到的3个主要聚类与基线数据集一致；选取前130~150个性状时，分析结果与基线结果一致。 7. 变量：分类分析（试验5） 变异描述：采用取自Morrone等人 (2012)的15个先验性状，构建包含8个和24个样本的数据集，分别使用高爾与切卡诺夫斯基关联度量开展分类分析 图表：附录5 备注：8样本集的拓扑结构在3分组水平上与基线数据集一致；使用高爾关联度量时，24样本集的拓扑结构在3分组水平上与基线不一致，而使用切卡诺夫斯基关联度量时则一致；Cleistochloinae与Neurachninae两个亚科的聚类结果与基线一致。