生物多样性和均匀度显著性的随机化检验及计算软件

多样性指数和均匀度以其简单易用而被广泛应用于群落生物学和生物多样性等研究中,然而由于缺乏合适的统计检验方法等原因,其分析的可信性往往较低,因而限制了其应用。鉴于生物多样性研究中广泛应用主观和直接的比较不,有必要建立和使用较为严格的多样性统计检验。本研究建立和应用了如下随机化检验方法：单群落多样性指数和均匀度的显著性检验,单群落多样性指数和均匀度的置认区间,群落间多群样和均匀度的差异显著性检验。随机化方法已被成功地应用于群落生态学研究,其原理是：随机排序某一向量中的元素,或随机交换两向量中的对应元素。计算该随机化数据的多样性和均匀度,重复该过程多次,统计和计算显著性检验的p值,由向量中的对应元素。计算该随机化数据的多样性和均匀度,重复该过程多次,统计和显著性检验的p值。由此可确定多样性和差异的统计显著性。同时,研制了相应的Internet计算软件BiodiverisytTest。该软件由7个Java类和1个HTML文件组成,可运行于多种操作系统和网络浏览器上,可读取多种类型的ODBC数据库文件如Access,Excel,FoxPro,Dbase等。该软件中包括Shannon-Wiener多样性指数,Simpson多样性指数,McIntosh多样性指数,Berger-Parker多样性指数,Hrlbert多样性指数以及Brillouin多样性指数。基于Shannon-Wiener多样性指数和Berger-Parker多样性指数,用BiodiversityTest软件对水稻田节肢动物群落多样性（15个地点,17个功能群,125个节肢动物种）进行了比较和分析。结果显示,两组结果可较好地反映水稻节肢动物群落多样性的差异显著性,这些检验方法可有效地反映多样性指数和均匀度的变化。与水稻田节肢动物群落间多样性的直接比较法相比,该随机化检验方法获得更客观的结果。本算法与软件有助于改进生物多样性研究中使用的某些不甚严格的分析方法,为随机化检验方法在生物多样性研究中的进一步应用提供了一种可用的工具。     

生物多样性评价软件BiodiversityMapping的设计与实现

针对目前国内生物多样性相关软件缺乏的情况,利用可视化开发方法和地理信息系统组件包shape Viewer Objects开发了一个综合性的生物多样性评价软件BiodiversityMapping。该软件运行于Windows98／NT操作系统下,是一个32位Windows应用软件;可以计算8类37种d、D生物多样性测度并能利用地理信息系统技术将结果空间化表达。利用该软件计算了北京东灵山地区3个研究区域(小龙门、梨园岭和东灵山主峰)内11个生境中大步甲属(Carabus)昆虫的Shannon-Wiener多样性指数并制图,然后对这3个地区进行了右尾和排序。结果表明,BiodjversityMapping软件能够准确方便地计算多种生物多样性测度,是生物多样性评价的一个有力工具。     

中国生物多样性在线数据处理平台的构建

高质量的生物多样性数据能够为生物多样性的研究与保护提供数据支撑。目前研究人员开发了大量的生物多样性数据处理软件或工具, 包括工作流系统、R语言包、Python语言包和Excel工具等, 但是使用这些软件或工具需要用户安装相应的软件客户端, 并掌握一定的编程语言、软件开发和复杂的Excel公式等知识和技能。为降低用户的学习成本和使用门槛, 本文采用了Browser/Server模式设计技术、Web技术、可视化技术、响应式开发技术、网络爬虫技术、数据处理技术和Solr智能检索技术等, 针对不同维度的生物多样性数据设计和开发了相应的数据处理模块, 构建了中国生物多样性在线数据处理平台(http://dp.iflora.cn/)。该平台能够有效地帮助科研人员对物种名称、地理位置、时间日期和经纬度等数据进行处理, 并提供数据格式转换、数据质量评测和资源统计分析等辅助功能, 帮助科研人员实现零代码和低门槛地处理生物多样性数据, 提供便捷、高效和简单的数据清洗、校正、转换和整合等数据处理渠道, 为生物多样性研究和保护提供信息化技术支持与服务。     

中国半翅目昆虫多样性和地理分布数据集

全球生物多样性逐渐丧失已成为最严重的环境问题之一, 探究各地生物多样性资源及形成机制是生态学和生物地理学领域关注的重要科学问题。生物多样性数据的整合和共享可以为相关研究的开展提供科学依据。昆虫是地球上多样性最高的生物类群, 但是由于目前关于昆虫多样性数据的整理不足, 相关研究较为缺乏。为了促进昆虫类群的多样性数据整理和共享工作的发展, 本研究选取昆虫纲中重要且多样的半翅目作为对象, 通过广泛的数据检索和收集, 系统整理了截至2017年已发表的中国半翅目昆虫的多样性及地理分布信息。数据集中共收集了102科2,090属7,822种半翅目昆虫的分类信息及其39,298条地理分布记录。该数据集可以为今后开展生物多样性格局、生物区系演化和害虫防治等方面的研究工作提供帮助。     

中国半翅目等29目昆虫2020年新分类单元

以中国半翅目等29目昆虫类群(除鞘翅目、双翅目、鳞翅目、膜翅目之外的其他目)为研究对象, 基于2020年度发表的新分类单元与文献资料, 编制了物种名录, 分析了新分类单元的地理分布与模式标本存放情况等。2020年, 中国半翅目等29目昆虫共描述349个新分类单元, 包括新属35个, 新种311个, 新亚种3个; 新种发表的热点地区在我国的西南山地及其邻近地区。模式标本存放单位多达69家, 其中正模标本主要存放在国内保藏机构, 而境外机构保藏的标本较少且以副模标本为主。本年度描述的349个新分类单元由356位作者所贡献, 共发表文献182篇; Zootaxa和ZooKeys是发表的主要期刊。本次调查为进一步深入研究物种演化的时空格局及生物多样性保护提供了基础数据。同时, 由于人类面临生物多样性急剧下降的威胁, 应加快大数据平台的建设及其多样化信息的挖掘, 支撑生物多样性的研究和保护。     

计算机在昆虫分类中的新用途

计算机作为一种昆虫分类的工具 ,已广泛用于昆虫的数值分类和支序分类中。随着多媒体计算机以及计算机网络技术的迅速发展 ,它在昆虫分类中又有了新的用途。多媒体计算机的使用将使传统的形态分类产生质的飞跃 ,并能通过互联网核对模式标本和进行昆虫种类的共同鉴定 ,使传统分类充满新的活力。     

计算机在昆虫分类中的新作用

计算机作为一种昆虫分类的工具,已广泛用于昆虫的数值分类和支序分类中,随着多媒体计算机以及计算机网络技术的迅速发展,它在昆虫分类中有了新的作用。多媒体计算机的使用将使用传统的形态分类产生质的飞跃,并能通过互联网核对模式标本和进行昆虫种类的共同鉴定,使传统分类充满新的活力。     

Fact Sheet Fusion:生物多样性自动化建库工具

随着全球对生物多样性保护和持续利用的重视,在现代信息技术支撑下,生物多样性数据库和信息系统不断趋向多媒体、超链接和分布式等特点.Fact Stleet Fusion (FSF)是一款顺应该发展趋势的生物多样性自动化建库工具,生物分类专家无须设计编辑数据库和网页,就可快速设计与创建规范标准、风格统一、维护简便的生物信息系统.文章介绍它的建库框架和功能特色,并以膜翅目茧蜂科滑茧蜂属Homolobus昆虫为例简要说明如何应用FSF建立昆虫多样性信息系统.     

中国半翅目等29目昆虫新分类单元2021年年度报告

本文以2021年度中国半翅目等29目昆虫(除昆虫纲鞘翅目、双翅目、鳞翅目、膜翅目之外的其他昆虫类群)发表的新分类单元为研究对象, 系统编汇了新分类单元信息、模式标本名录与文献目录, 并分析了描述新种的热点地区、模式标本存放情况以及发表期刊的特点等。2021年度中国半翅目等29目昆虫描述了新属35个, 新物种386个以及1个新种下分类单元, 共计422个新分类单元; 基于对新物种在省级行政区分布的分析, 新物种发现的热点地区分布于中国西南(云南、贵州以及四川等)及其邻近地区(广西和西藏等), 而以200 km × 200 km栅格为操作单位, 新物种发现的热点地区主要集中在山地地区。395位研究者参与了本年度新分类单元命名和描述工作, 相关结果发表在28种期刊上, 共205篇文章。本研究及时更新了2021年度中国半翅目等29目昆虫的生物多样性基础数据, 对于加快建设数据共享平台、支撑生物多样性保护和管理, 以及保障国门生物安全等具有重要的作用。     

基于web的等翅目昆虫分类系统的设计和开发

以《中国动物志·昆虫纲·第十七卷·等翅目》一书资料为基础,结合白蚁分类的最新成果,开发了基于web的等翅目昆虫分类系统。本系统由白蚁分类资料显示子系统、白蚁分类资料检索子系统、后台数据库在线管理子系统和白蚁种类鉴定子系统等4个功能模块组成。用户通过Internet网络,可实现白蚁分类资料的查询与未知种类的鉴定。本系统的开发,为我国白蚁种类的识别和相关信息的共享提供了快捷、高效的网络工具。这是计算机信息处理技术与白蚁形态分类学的有机结合,是利用计算机技术提高生物形态学研究、教学效率的一种新途径。     

Place prioritization for biodiversity conservation using probabilistic surrogate distribution data

We analyse optimal and heuristic place prioritization algorithms for biodiversity conservation area network design which can use probabilistic data on the distribution of surrogates for biodiversity. We show how an Expected Surrogate Set Covering Problem (ESSCP) and a Maximal Expected Surrogate Covering Problem (MESCP) can be linearized for computationally efficient solution. For the ESSCP, we study the performance of two optimization software packages (XPRESS and CPLEX) and five heuristic algorithms based on traditional measures of complementarity and rarity as well as the Shannon and Simpson indices of α‐diversity which are being used in this context for the first time. On small artificial data sets the optimal place prioritization algorithms often produced more economical solutions than the heuristic algorithms, though not always ones guaranteed to be optimal. However, with large data sets, the optimal algorithms often required long computation times and produced no better results than heuristic ones. Thus there is generally little reason to prefer optimal to heuristic algorithms with probabilistic data sets.     

HCV抗原表位预测

应用网络生物信息资源查找丙型肝炎病毒基因组全序列,用软件Lasergene中的EditSeq将来自中国河北株mRNA序列翻译为氨基酸序列,尔后用程序Protean进行氨基酸序列分析,对HCV各区段的B细胞抗原指数进行预测。同时又在两个网站对中国汉族人中频率较高的HLA基因型进行CD8和CD4T细胞表位预测。B细胞和T细胞抗原表位预测结果对于HCV诊断试剂和疫苗研制有重要的指导意义。     

Reliable,verifiable and efficient monitoring of biodiversity via metabarcoding

To manage and conserve biodiversity, one must know what is being lost, where, and why, as well as which remedies are likely to be most effective. Metabarcoding technology can characterise the species compositions of mass samples of eukaryotes or of environmental DNA. Here, we validate metabarcoding by testing it against three high‐quality standard data sets that were collected in Malaysia (tropical), China (subtropical) and the United Kingdom (temperate) and that comprised 55,813 arthropod and bird specimens identified to species level with the expenditure of 2,505 person‐hours of taxonomic expertise. The metabarcode and standard data sets exhibit statistically correlated alpha‐ and beta‐diversities, and the two data sets produce similar policy conclusions for two conservation applications: restoration ecology and systematic conservation planning. Compared with standard biodiversity data sets, metabarcoded samples are taxonomically more comprehensive, many times quicker to produce, less reliant on taxonomic expertise and auditable by third parties, which is essential for dispute resolution.     

Design of reserve networks and the persistence of biodiversity

Sophisticated computational methods have been developed to help us to identify sets of nature reserves that maximize the representation of regional diversity, but, until recently, the methods have not dealt explicitly and directly with the main goal of reserve networks, that of the long-term maintenance of biodiversity. Furthermore, the successful application of current methods requires reliable information about species distributions, which is not always available. Recent results show that data quality, as well as the choice of surrogates for biodiversity, could be critical for successful reserve design. Because of these problems and a lack of communication between scientists and managers, the impact of computational site-selection tools in applied conservation planning has been minimal.     

Rapid prediction of multi-dimensional NMR data sets

We present a computational environment for Fast Analysis of multidimensional NMR DAta Sets (FANDAS) that allows assembling multidimensional data sets from a variety of input parameters and facilitates comparing and modifying such ??in silico?? data sets during the various stages of the NMR data analysis. The input parameters can vary from (partial) NMR assignments directly obtained from experiments to values retrieved from in silico prediction programs. The resulting predicted data sets enable a rapid evaluation of sample labeling in light of spectral resolution and structural content, using standard NMR software such as Sparky. In addition, direct comparison to experimental data sets can be used to validate NMR assignments, distinguish different molecular components, refine structural models or other parameters derived from NMR data. The method is demonstrated in the context of solid-state NMR data obtained for the cyclic nucleotide binding domain of a bacterial cyclic nucleotide-gated channel and on membrane-embedded sensory rhodopsin II. FANDAS is freely available as web portal under WeNMR (http://www.wenmr.eu/services/FANDAS).     

Marshalling existing biodiversity data to evaluate biodiversity status and trends in planning exercises

A thorough understanding of biodiversity status and trends through time is necessary for decision-making at regional, national, and subnational levels. Information readily available in databases allows for development of scenarios of species distribution in relation to habitat changes. Existing species occurrence data are biased towards some taxonomic groups (especially vertebrates), and are more complete for Europe and North America than for the rest of the world. We outline a procedure for development of such biodiversity scenarios using available data on species distribution derived from primary biodiversity data and habitat conditions, and analytical software, which allows estimation of species’ distributions, and forecasting of likely effects of various agents of change on the distribution and status of the same species. Such approaches can translate into improved knowledge for countries regarding the 2010 Biodiversity Target of reducing significantly the rate of biodiversity loss—indeed, using methodologies such as those illustrated herein, many countries should be capable of analyzing trends of change for at least part of their biodiversity. Sources of errors that are present in primary biodiversity data and that can affect projections are discussed.     

Integrative analysis of gene expression and copy number alterations using canonical correlation analysis

Background  

With the rapid development of new genetic measurement methods, several types of genetic alterations can be quantified in a high-throughput manner. While the initial focus has been on investigating each data set separately, there is an increasing interest in studying the correlation structure between two or more data sets. Multivariate methods based on Canonical Correlation Analysis (CCA) have been proposed for integrating paired genetic data sets. The high dimensionality of microarray data imposes computational difficulties, which have been addressed for instance by studying the covariance structure of the data, or by reducing the number of variables prior to applying the CCA. In this work, we propose a new method for analyzing high-dimensional paired genetic data sets, which mainly emphasizes the correlation structure and still permits efficient application to very large data sets. The method is implemented by translating a regularized CCA to its dual form, where the computational complexity depends mainly on the number of samples instead of the number of variables. The optimal regularization parameters are chosen by cross-validation. We apply the regularized dual CCA, as well as a classical CCA preceded by a dimension-reducing Principal Components Analysis (PCA), to a paired data set of gene expression changes and copy number alterations in leukemia.     

Monitoring change in aquatic invertebrate biodiversity: sample size, faunal elements and analytical methods

Replication is usually regarded as an integral part of biological sampling, yet the cost of extensive within-wetland replication prohibits its use in broad-scale monitoring of trends in aquatic invertebrate biodiversity. In this paper, we report results of testing an alternative protocol, whereby only two samples are collected from a wetland per monitoring event and then analysed using ordination to detect any changes in invertebrate biodiversity over time. Simulated data suggested ordination of combined data from the two samples would detect 20% species turnover and be a cost-effective method of monitoring changes in biodiversity, whereas power analyses showed about 10 samples were required to detect 20% change in species richness using ANOVA. Errors will be higher if years with extreme climatic events (e.g. drought), which often have dramatic short-term effects on invertebrate communities, are included in analyses. We also suggest that protocols for monitoring aquatic invertebrate biodiversity should include microinvertebrates. Almost half the species collected from the wetlands in this study were microinvertebrates and their biodiversity was poorly predicted by macroinvertebrate data.     

Latent Dirichlet Allocation reveals spatial and taxonomic structure in a DNA‐based census of soil biodiversity from a tropical forest

High‐throughput sequencing of amplicons from environmental DNA samples permits rapid, standardized and comprehensive biodiversity assessments. However, retrieving and interpreting the structure of such data sets requires efficient methods for dimensionality reduction. Latent Dirichlet Allocation (LDA) can be used to decompose environmental DNA samples into overlapping assemblages of co‐occurring taxa. It is a flexible model‐based method adapted to uneven sample sizes and to large and sparse data sets. Here, we compare LDA performance on abundance and occurrence data, and we quantify the robustness of the LDA decomposition by measuring its stability with respect to the algorithm's initialization. We then apply LDA to a survey of 1,131 soil DNA samples that were collected in a 12‐ha plot of primary tropical forest and amplified using standard primers for bacteria, protists, fungi and metazoans. The analysis reveals that bacteria, protists and fungi exhibit a strong spatial structure, which matches the topographical features of the plot, while metazoans do not, confirming that microbial diversity is primarily controlled by environmental variation at the studied scale. We conclude that LDA is a sensitive, robust and computationally efficient method to detect and interpret the structure of large DNA‐based biodiversity data sets. We finally discuss the possible future applications of this approach for the study of biodiversity.