# 编者信息 熊荣川 明湖实验室 xiongrongchuan@126.com http://blog.sciencenet.cn/u/Bearjazz Here, we present a major new version of the molecular evolutionary software package Bayesian Evolutionary Analysis by Sampling Trees (BEAST), updated to version 1.7, and representing a signifcant software advance over that previously described (Drummond and Rambaut 2007). Alongside the primary analysis engine in BEAST, this package also includes a suite of utilities for specifying the analysis design, processing output files, and summarizing and visualizing the results. Taken together, these programs enable Bayesian inference of molecular sequences with an emphasis on time-structured evolutionary models including phylodynamic models, divergence time estimates, multiloci demographic models, gene–/species–tree inference, a range of spatial phylogeographic analyses, and discrete and continuous trait evolution. Implementing Markov chain Monte Carlo (MCMC) algorithms to perform these inferences, the package is intended and used for rigorous statistical inference and hypothesis testing of evolutionary models with joint inference of phylogeny. It is also possible to constrain portions of the phylogenetic model space to known values, including the tree topology, and perform conditional inference if required. 在这里，我们提出了 BEAST 一个重要更新版本（ 1.7 版），相较先前介绍的版本（ Drummond and Rambaut 2007 ）它代表了一个显著的软件进步。除了 BEAST 中的主要分析核心要件外，此软件包还包括一套用于指定分析设置、处理输出文件以及汇总和可视化结果的实用程序。综合起来，这些程序使分子序列的贝叶斯推断成为可能，重点是时间结构进化模型，包括系统动力学模型、分化时间估计、多基因座种群模型、基因 / 物种树推断、空间分布范围系统地理分析，以及离散和连续的特征进化。利用马尔可夫蒙特卡罗（ MCMC ）算法实现这些推断，并将其应用于系统发育联合推论的进化模型的严格统计推断和假设检验。还可以将系统发育模型空间的一部分限制为已知值，包括树拓扑结构，并在需要时执行条件推断。 Drummond A J , Suchard M A , Xie D , et al. Bayesian Phylogenetics with BEAUti and the BEAST 1.7 . Molecular Biology and Evolution, 2012, 29(8):1969-1973.
# 编者信息 熊荣川 明湖实验室 xiongrongchuan@126.com http://blog.sciencenet.cn/u/Bearjazz Molecular sequences, morphological measurements, geographic distributions, and fossil remains all provide a wealth of potential information about the evolutionary history of life on Earth, the dynamics of ancient and modern biological populations, and the emergence and spread of infectious diseases. One of the challenges of modern Evolutionary Biology is the integration of these different data sources to address evolutionary hypotheses over the full range of spatial and temporal scales. The field is witnessing a transition to an increasingly quantitative science. This transformation began first through an explosion of molecular sequence data with the parallel development of mathematical and computational tools for their analysis. However, increasingly, this transformation can be observed in other aspects of Evolutionary Biology where large global databases of complementary sources of information, such as fossils, geographical distributions, and population history, are being curated and made publicly available. 分子序列、形态测量、地理分布和化石遗迹都提供了大量关于地球生命进化史、古代和现代生物种群动态以及传染病出现及传播的潜在信息。现代进化生物学的一个挑战是整合这些不同的数据源，以解决全时空尺度上的进化假设。这一领域见证了一个越来越向定量科学过渡的过程。这种过渡是从分子序列数据爆炸式增长，伴随相应分析的数学和计算工具的开发开始的。然而，这种转变越来越多地可以在进化生物学的其他方面观察到，在这些领域，大量的全球互补信息源数据库（如化石、地理分布和种群历史）正在被建立和公开。 Drummond A J , Suchard M A , Xie D , et al. Bayesian Phylogenetics with BEAUti and the BEAST 1.7 . Molecular Biology and Evolution, 2012, 29(8):1969-1973.
# 编者信息 熊荣川 明湖实验室 xiongrongchuan@126.com http://blog.sciencenet.cn/u/Bearjazz Computational evolutionary biology, statistical phylogenetics, and coalescent-based population genetics are becoming increasingly central to the analysis and understanding of molecular sequence data. We present the Bayesian Evolutionary Analysis by Sampling Trees (BEAST) software package version 1.7, which implements a family of Markov chain Monte Carlo (MCMC) algorithms for Bayesian phylogenetic inference, divergence time dating, coalescent analysis, phylogeography, and related molecular evolutionary analyses. This package includes an enhanced graphical user interface program called Bayesian Evolutionary Analysis Utility (BEAUti) that enables access to advanced models for molecular sequence and phenotypic trait evolution that were previously available to developers only. The package also provides new tools for visualizing and summarizing multispecies coalescent and phylogeographic analyses. BEAUti and BEAST 1.7 are open source under the GNU lesser general public license and available at 计算进化生物学、统计系统发育学和基于溯祖理论的群体遗传学正日益成为分析和理解分子序列数据的焦点。我们提出了 BEAST （基于抽样树的贝叶斯进化分析） 1.7 版软件包，该软件包使用马尔可夫链蒙特卡罗（ MCMC ）算法，实现贝叶斯系统发育推断、分化时间推定、溯祖分析、系统地理学和相关分子进化的一系列分析。软件包包括一个名为 Bayesian 进化分析程序（ BEAUti ）的图形增强用户界面程序，允许访问分子序列和表型特征进化的高级模型，这些模型以前只供开发人员使用。该包还提供了可视化的综合多物种溯祖分析和系统地理学分析的新工具。 BEAUti 和 BEAST 1.7 是 GNU 标准较低通用公共许可证下的开源软件，可从以下网址下载： http://beast-mcmc.googlecode.com and http://beast.bio.ed.ac.uk . Drummond A J , Suchard M A , Xie D , et al. Bayesian Phylogenetics with BEAUti and the BEAST 1.7 . Molecular Biology and Evolution, 2012, 29(8):1969-1973.
1. European summer temperatures since Roman times Luterbacher et al., 2016 ERL The spatial context is critical when assessing present-day climate anomalies, attributing them to potentialforcings and making statements regarding their frequency and severity in a long-term perspective. Recentinternational initiatives have expanded the number of high-quality proxy-records and developed newstatistical reconstruction methods. These advances allow more rigorous regional past temperaturereconstructions and, in turn, the possibility of evaluating climate models on policy-relevant, spatiotemporalscales. Here we provide a new proxy-based, annually-resolved, spatial reconstruction of theEuropean summer(June – August)temperature fields back to 755 CE based on Bayesian hierarchicalmodelling (BHM), together with estimates of the European mean temperature variation since 138 BCEbased on BHM and composite-plus-scaling (CPS). Our reconstructions compare well with independentinstrumental and proxy-based temperature estimates, but suggest a larger amplitude in summertemperature variability than previously reported. Both CPS and BHM reconstructions indicate that themean 20th century European summer temperature was not significantly differentfrom some earliercenturies, including the 1st, 2nd, 8th and 10th centuries CE. The 1st century (in BHM also the 10thcentury) may even have been slightly warmer than the 20th century, but the difference is not statisticallysignificant. Comparing each 50 yr period with the 1951 – 2000 period reveals a similar pattern. Recentsummers, however, have been unusually warm in the context of the last two millennia and there are no30 yr periods in either reconstruction that exceed the mean average European summer temperature of thelast 3 decades(1986 – 2015 CE). A comparison with an ensemble of climate model simulations suggeststhat the reconstructed European summer temperature variability over the period 850 – 2000 CE reflectschanges in both internal variability and external forcing on multi-decadal time-scales. For pan-European temperatures we find slightly better agreement between the reconstruction and the model simulationswith high-end estimates for total solar irradiance. Temperature differences between the medieval period,the recent period and the Little Ice Age are larger in the reconstructions than the simulations. This mayindicate inflated variability of the reconstructions, a lack of sensitivity and processes to changes in externalforcing on the simulated European climate and/or an underestimation of internal variability oncentennial and longer time scales.
标签: 贝叶斯
