Biogeography_analyses

To investigate the factors that may have influenced the distribution of <i>Ocymyrmex</i> species in southern Africa, we inferred their biogeographic histories using the R package BioGeoBEARS (BioGeography with Bayesian (and likelihood) Evolutionary Analysis in R Scripts) (Matzke, 2018). This likelihood-based model is designed to perform inferences of biogeographical histories on phylogenies and to compare different models of range evolution (Matzke, 2013a). The following biogeographical models were tested against our data to estimate the ancestral area of <i>Ocymyrmex</i> species: a Dispersal-Extinction-Cladogenesis (DEC) model, which allows the geographic range to change across a phylogeny through several events (Ree, 2005; Ree and Smith, 2008); a likelihood version of the Dispersal-Vicariance model (DIVALIKE) (Ronquist, 1997); and a likelihood version of the Bayesian Analysis of Biogeography (BAYAREA-LIKE), which is a Bayesian model that samples geographical history along phylogenetic branches, together with sampling parameter values (Landis et al., 2013). These models have free parameters specifying the rate of dispersal (<i>d</i> = range expansion) and extinction (<i>e</i> = range of contraction)<i> </i>along the phylogeny branches. At cladogenesis events, DEC assumes that one daughter lineage will always inherit the ancestral range if the ancestor lives in a single area; if the ancestor is widespread, one daughter lineage will live in a subset of that area, or one area will split off by vicariance. By contrast, DIVA only allows vicariance. BayArea assumes that no range evolution occurs at cladogenesis, and therefore the ancestral range is copied by both daughters (Matzke, 2013b). A founder event speciation model (+j) was also tested in combination with each base model.BioGeoBears requires a time calibrated tree and geographic distribution units as input files. <i>Ocymyrmex </i>distribution records were extracted from Iziko Museum’s Specify6 database (Specify version 6.7.01; Specify Collections Consortium | Software for Biological Collections and Samples). Given the tight habitat affinity of <i>Ocymyrmex</i>, species occurrences were assigned and coded according to the biomes defined by Dinerstein et al. (2017) (Appendix B: Table B2). The following biome regions were designated and used as biogeographical units: Tropical &amp; subtropical moist broadleaf forests; Tropical &amp; subtropical grasslands, savannas &amp; shrublands; Flooded grasslands &amp; savannas; Montane grasslands &amp; shrublands; Mediterranean forests, woodlands &amp; scrub; and Deserts &amp; xeric shrublands. The dated phylogeny produced by MCMCTREE was pruned to exclude outgroups and was used as an input file. The Akaike information criterion (AIC) was used to select the best-fitting model. The maximum number of areas any species may occupy was set to five, as the <i>Ocymyrmex </i>species with the largest distribution range, <i>O. flaviventris</i>, can be found in five biomes. We followed guidelines in http://phylo.wikidot.com/biogeobears.

为探究影响南部非洲捷蚁属（Ocymyrmex）物种分布的潜在因素，我们采用R语言包BioGeoBEARS（全称：BioGeography with Bayesian (and likelihood) Evolutionary Analysis in R Scripts，即贝叶斯（与似然）进化生物地理分析工具）（Matzke，2018）对其生物地理历史进行推断。该基于似然的模型旨在对系统发育树开展生物地理历史推断，并对比不同的分布范围演化模型（Matzke，2013a）。
本研究针对研究数据测试了以下生物地理模型，以估算捷蚁属物种的祖先分布区域：其一为扩散-灭绝-分支（Dispersal-Extinction-Cladogenesis, DEC）模型，该模型允许类群的地理范围通过多种事件在系统发育树上发生改变（Ree，2005；Ree和Smith，2008）；其二为扩散-分化模型的似然版本（DIVALIKE）（Ronquist，1997）；其三为贝叶斯生物地理分析（Bayesian Analysis of Biogeography, BAYAREA-LIKE）模型的似然版本，该模型可沿系统发育分支采样地理历史，并同步采样参数值（Landis等，2013）。这些模型设有自由参数，用以指定系统发育分支上的扩散速率（d=分布范围扩张）与灭绝速率（e=分布范围收缩）。
在分支成种事件中，DEC模型假定：若祖先类群仅分布于单个区域，则其中一个子分支将继承祖先的分布范围；若祖先类群分布广泛，则其中一个子分支将仅占据该范围的一个子集，或通过分化事件分离出独立区域。相较之下，DIVA模型仅允许分化事件；而BayArea模型假定分支成种过程中无分布范围演化，因此两个子分支均会继承祖先的分布范围（Matzke，2013b）。本研究还针对每个基础模型，组合测试了奠基者成种模型（+j）。
BioGeoBEARS工具需要以时间校准的系统发育树与地理分布单元作为输入文件。捷蚁属的分布记录提取自Iziko博物馆的Specify6数据库（Specify 6.7.01版本；Specify标本收藏联盟 | 生物标本与样本管理软件）。鉴于捷蚁属对生境具有严格的偏好，本研究根据Dinerstein等人（2017）定义的生物群系对物种出现记录进行赋值与编码（附录B：表B2）。本研究选定的生物地理单元包括以下6类生物群系：热带与亚热带湿润阔叶林；热带与亚热带草原、稀树草原与灌丛；淹水草原与稀树草原；山地草原与灌丛；地中海森林、林地与灌丛；以及荒漠与旱生灌丛。
通过MCMCTREE生成的定年系统发育树经修剪以移除外类群，随后作为输入文件使用。本研究采用赤池信息准则（Akaike Information Criterion, AIC）筛选最优拟合模型。考虑到分布范围最广的捷蚁属物种——黄腹捷蚁（O. flaviventris）可分布于5个生物群系中，本研究将单个物种可占据的最大区域数设为5。本研究严格遵循http://phylo.wikidot.com/biogeobears中的操作指南。