BioFTF: An R package for biodiversity assessment with the functional data analysis approach

This paper presents the R package BioFTF, which is a tool for statistical biodiversity assessment in the functional data analysis framework. Diversity is a key topic in many research fields; however, in the literature, it is demonstrated that the existing indices do not capture the different aspects of this concept. Thus, a main drawback is that different indicators may lead to different orderings among communities according to their biodiversity. A possible method to evaluate biodiversity consists in using diversity profiles that are curves depending on a specific parameter. In this setting, it is possible to adopt some functional instruments proposed in the literature, such as the first and second derivatives, the curvature, the radius of curvature and the arc length. Specifically, the derivatives and the curvature (or the radius of curvature) highlight any peculiar behaviour of the profiles, whereas the arc length helps in ranking curves, given the richness. Because these instruments do not solve the issue of ranking communities with different numbers of species, we propose an important methodological contribution that introduces the surface area. Indeed, this tool is a scalar measure that reflects the information provided by the biodiversity profile and allows for ordering communities with different richness. However, this approach requires mathematical skills that the average user may not have; thus, our idea is to provide a user-friendly tool for both non-statistician and statistician practitioners to measure biodiversity in a functional context.     

获取生物物种名录信息的R程序包SP2000

物种名录为衡量区域和全球生物多样性提供了数据基础。随着互联网的兴起与发展, 人们将地球上已知的动物、植物、微生物等类群的物种名录信息存储到公共数据平台中, 并对物种名录进行快速及时地更新, 这极大地促进了分类学、保护生物学和宏观生态学等学科的发展, 成为政府或国际组织开展物种保育现状评估、红色名录编撰和生物多样性保护的重要依据。物种2000中国节点(http://www.sp2000.org.cn)和Catalogue of Life网站(http://www.catalogueoflife.org)分别是中国和全球最大的生物物种名录数据平台, 截至2020年6月4日, 其收录的物种数分别为122,280种和1,829,672种。然而这些数据平台仅提供物种查询、检索、下载等基本功能, 难以满足使用者准确、快速地批量获取所需生物物种名录数据信息的需求, 制约了这些大数据平台在生物多样性研究和保护中的作用。因此, 我们选取R语言开发了程序包SP2000, 旨在帮助用户批量获取中国或全球生物物种名录信息。该程序包具有跨Windows、MacOS、Linux等多个系统运行、操作便捷、代码开源等特点。为了方便用户使用, 本文详细介绍了SP2000的基本原理、特点及使用指南, 包括程序包的下载、安装、运行和参数设置等。     

Functional rarity of plants in German hay meadows — Patterns on the species level and mismatches with community species richness

Functional rarity (FR) — a feature combining a species'' rarity with the distinctiveness of its traits — is a promising tool to better understand the ecological importance of rare species and consequently to protect functional diversity more efficiently. However, we lack a systematic understanding of FR on both the species level (which species are functionally rare and why) and the community level (how is FR associated with biodiversity and environmental conditions). Here, we quantify FR for 218 plant species from German hay meadows on a local, regional, and national scale by combining data from 6500 vegetation relevés and 15 ecologically relevant traits. We investigate the association between rarity and trait distinctiveness on different spatial scales via correlation measures and show which traits lead to low or high trait distinctiveness via distance‐based redundancy analysis. We test how species richness and FR are correlated, and use boosted regression trees to determine environmental conditions that are driving species richness and FR. On the local scale, only rare species showed high trait distinctiveness while on larger spatial scales rare and common species showed high trait distinctiveness. As infrequent trait attributes (e.g., legumes, low clonality) led to higher trait distinctiveness, we argue that functionally rare species are either specialists or transients. While specialists occupy a particular niche in hay meadows leading to lower rarity on larger spatial scales, transients display distinct but maladaptive traits resulting in high rarity across all spatial scales. More functionally rare species than expected by chance occurred in species‐poor communities indicating that they prefer environmental conditions differing from characteristic conditions of species‐rich hay meadows. Finally, we argue that functionally rare species are not necessarily relevant for nature conservation because many were transients from surrounding habitats. However, FR can facilitate our understanding of why species are rare in a habitat and under which conditions these species occur.     

NetLogoR: a package to build and run spatially explicit agent‐based models in R

NetLogoR is an R package to build and run spatially explicit agent‐based models (SE‐ABMs) using the R language. SE‐ABMs are models that simulate the fate of entities at the individual level within a spatial context and where patterns emerge at the population level. NetLogoR follows the same framework as the NetLogo software (Wilensky 1999). Rather than a call function to use the NetLogo software, NetLogoR is a translation into the R language of the structure and functions of NetLogo. Models built with NetLogoR are written in R language and are run on the R platform; no other software or language has to be involved. NetLogoR provides new R classes to define model agent objects and functions to implement spatially explicit agent‐based models in the R environment. Users of this package benefit from the fast and easy coding provided by the highly developed NetLogo framework, coupled with the versatility, power and massive resources of the R language.     

EcoGenetics: An R package for the management and exploratory analysis of spatial data in landscape genetics

The integration of ecology and genetics has become established in recent decades, in hand with the development of new technologies, whose implementation is allowing an improvement of the tools used for data analysis. In a landscape genetics context, integrative management of population information from different sources can make spatial studies involving phenotypic, genotypic and environmental data simpler, more accessible and faster. Tools for exploratory analysis of autocorrelation can help to uncover the spatial genetic structure of populations and generate appropriate hypotheses in searching for possible causes and consequences of their spatial processes. This study presents EcoGenetics, an R package with tools for multisource management and exploratory analysis in landscape genetics.     

MicroWeaR: A new R package for dental microwear analysis

Mastication of dietary items with different mechanical properties leaves distinctive microscopic marks on the surface of tooth enamel. The inspection of such marks (dental microwear analysis) is informative about the dietary habitus in fossil as well as in modern species. Dental microwear analysis relies on the morphology, abundance, direction, and distribution of these microscopic marks. We present a new freely available software implementation, MicroWeaR, that, compared to traditional dental microwear tools, allows more rapid, observer error free, and inexpensive quantification and classification of all the microscopic marks (also including for the first time different subtypes of scars). Classification parameters and graphical rendering of the output are fully settable by the user. MicroWeaR includes functions to (a) sample the marks, (b) classify features into categories as pits or scratches and then into their respective subcategories (large pits, coarse scratches, etc.), (c) generate an output table with summary information, and (d) obtain a visual surface‐map where marks are highlighted. We provide a tutorial to reproduce the steps required to perform microwear analysis and to test tool functionalities. Then, we present two case studies to illustrate how MicroWeaR works. The first regards a Miocene great ape obtained from through environmental scanning electron microscope, and other a Pleistocene cervid acquired by a stereomicroscope.     

hzar: hybrid zone analysis using an R software package

We present a new software package (hzar ) that provides functions for fitting molecular genetic and morphological data from hybrid zones to classic equilibrium cline models using the Metropolis–Hastings Markov chain Monte Carlo (MCMC) algorithm. The software applies likelihood functions appropriate for different types of data, including diploid and haploid genetic markers and quantitative morphological traits. The modular design allows flexibility in fitting cline models of varying complexity. To facilitate hypothesis testing, an autofit function is included that allows automated model selection from a set of nested cline models. Cline parameter values, such as cline centre and cline width, are estimated and may be compared statistically across clines. The package is written in the R language and is available through the Comprehensive R Archive Network (CRAN; http://cran.r-project.org/ ). Here, we describe hzar and demonstrate its use with a sample data set from a well‐studied hybrid zone in western Panama between white‐collared (Manacus candei) and golden‐collared manakins (M. vitellinus). Comparisons of our results with previously published results for this hybrid zone validate the hzar software. We extend analysis of this hybrid zone by fitting additional models to molecular data where appropriate.     

MPAgenomics: an R package for multi-patient analysis of genomic markers

Background

Last generations of Single Nucleotide Polymorphism (SNP) arrays allow to study copy-number variations in addition to genotyping measures.

Results

MPAgenomics, standing for multi-patient analysis (MPA) of genomic markers, is an R-package devoted to: (i) efficient segmentation and (ii) selection of genomic markers from multi-patient copy number and SNP data profiles. It provides wrappers from commonly used packages to streamline their repeated (sometimes difficult) manipulation, offering an easy-to-use pipeline for beginners in R.The segmentation of successive multiple profiles (finding losses and gains) is performed with an automatic choice of parameters involved in the wrapped packages. Considering multiple profiles in the same time, MPAgenomics wraps efficient penalized regression methods to select relevant markers associated with a given outcome.

Conclusions

MPAgenomics provides an easy tool to analyze data from SNP arrays in R. The R-package MPAgenomics is available on CRAN.     

澜沧江中游水生昆虫生活史和生态学性状多样性的海拔格局: 气候和土地利用的影响

物种通过功能性状响应环境变化, 探究群落功能性状多样性的海拔格局是揭示生物多样性空间分布格局和形成机制的重要研究内容。气候变化和土地利用是影响溪流生物多样性变化及其群落构建的重要因素, 然而气候和土地利用沿海拔梯度如何影响水生昆虫功能性状垂直分布格局的系统研究仍旧比较缺乏。本文基于2016年和2018年在云南澜沧江中游1,000-3,000 m海拔共56个溪流样点的水生昆虫群落调查数据, 利用线性和二次回归模型探索并比较了生活史性状(化性、生活史快慢、成虫寿命)和生态学性状(营养习性、生活习性、温度偏好)的群落加权平均性状多样性指数沿海拔梯度的分布特征, 并通过随机森林模型解析流域尺度气候和土地利用变量对生活史和生态学性状多样性垂直分布格局的影响。结果表明: 生活史性状中, 少于1世代、无季节性、慢季节性、成虫寿命长等性状多样性沿海拔梯度呈显著的“U”型分布格局, 而快季节性和成虫寿命极短多样性呈显著的单峰型海拔格局, 成虫寿命短多样性呈显著递增的海拔格局。生态学性状中, 温度偏好多样性与海拔梯度无关, 附着者和爬行者的多样性沿海拔梯度分别呈显著的递增和“U”型格局, 滤食者、植食者和捕食者的多样性分别呈显著递增、递减和“U”型海拔格局。随机森林模型分析结果表明, 气候和土地利用对生活史性状多样性的解释量高于对生态学性状多样性的解释量, 年平均温度和农业面积百分比是共同的关键因素。综上, 水生昆虫群落功能性状多样性海拔格局存在差异, 主要受不同自然环境梯度和人类干扰因素驱动。研究结果可为制定澜沧江流域生物多样性保护对策提供理论基础。     

phylosignal: an R package to measure,test, and explore the phylogenetic signal

Phylogenetic signal is the tendency for closely related species to display similar trait values as a consequence of their phylogenetic proximity. Ecologists and evolutionary biologists are becoming increasingly interested in studying the phylogenetic signal and the processes which drive patterns of trait values in the phylogeny. Here, we present a new R package, phylosignal which provides a collection of tools to explore the phylogenetic signal for continuous biological traits. These tools are mainly based on the concept of autocorrelation and have been first developed in the field of spatial statistics. To illustrate the use of the package, we analyze the phylogenetic signal in pollution sensitivity for 17 species of diatoms.     

Transcending data gaps: a framework to reduce inferential errors in ecological analyses

The analysis of functional diversity (FD) has gained increasing importance due to its generality and utility in ecology. In particular, patterns in the spatial distribution and temporal change of FD are being used to predict locations and functional groups that are immediately vulnerable to global changes. A major impediment to the accurate measurement of FD is the pervasiveness of missing data in trait datasets. While such prevalent data gaps can engender misleading inferences in FD analyses, we currently lack any practical guide to handle missing data in trait datasets. Here, we identify significant mismatches between true FD and values derived from datasets that contain missing data. We demonstrate that imputing missing data with a phylogeny‐informed approach reduces the risk of misinterpretation of FD patterns, and provides baseline information against which central questions in ecology can be evaluated.     

MtreeRing: An R package with graphical user interface for automatic measurement of tree ring widths using image processing techniques

Accurate measurements of ring-width series are essential for dendrochronological analyses. We present an R package MtreeRing for ring-width measurements on scanned digital images. A morphological alternate sequential filter is used for noise reduction in the original image. Ring boundaries are determined by the steepest negative slopes in the light reflectance of latewood-earlywood transitions. To automatically identify tree rings, the package provides three alternative methods (watershed-based segmentation, Canny edge detector, and a linear detection algorithm), each with advantages and disadvantages and suited to different wood anatomical features. The user can also manually mark tree rings on species with complex anatomical structures. The arcs of inner-rings and angles of successive inclined ring boundaries are used to correct ring-width series. Differences in ring-width measurements between MtreeRing and WinDENDRO in a given coniferous species (Larix gmelinii) were assessed, and no significant difference between programs was found. Furthermore, the package provides an R-based web application which was developed using the Shiny framework. This beginner-friendly application allows viewing and interacting with tree ring images. It requires no programming experience and can run on either a local computer or a remote server.     

Basing conservation policies for the deep-sea floor on current-diversity concepts: a consideration of rarity

Exploitation of deep-sea resources is now underway and there is economic pressure to renew and expand currently restricted waste disposal in that environment. Since the deep sea is noted for very high species diversity, it is appropriate that diversity conservation be initiated. Review of current concepts of diversity maintenance finds that the ideas have evolved more through increasing information about sources of heterogeneity than through rigorous testing. This history weakens the immediate value of these concepts for the development of conservation strategies and demonstrates the need for additional investigation. Such inquiry might focus upon the rare component of overall species richness. A comparison of box core samples at 2100m in the western Atlantic and the Gulf of Mexico continental shelf reveals that deep soft bottoms are not unique in having many rare species. The rare component at depth is largely comprised of species more common at other locations near and far. The rare component on the shelf is comprised mostly of species which are consistently rare and restricted in distribution. These observations suggest a shallow–deep difference that is more one of degree than fundamental in nature; the deep having larger regions and regional species pools.     

不同木本植物功能型当年生小枝功能性状差异

为探讨不同植物功能型之间小枝功能特征的差异,在重庆金佛山和缙云山分别采集20和26个木本植物,选择当年生的小枝测定其叶片和枝条性状。结果表明:1)叶片厚度表现为:落叶植物<常绿植物,乔木<灌木;单叶面积和叶片总面积表现为:落叶植物>常绿植物,乔木>灌木;不同植物功能型间小枝的叶片数量均无显著差异。2)落叶植物和乔木的小枝横截面积、小枝长度和小枝干重均显著高于常绿植物和灌木,不同植物功能型间小枝密度无显著差异。3)与常绿植物和灌木相比,落叶植物和乔木有较高的展叶效率(单位长度小枝支撑的叶片面积),小枝的出叶强度(单位长度小枝支撑的叶片数)无显著差异。4)在小枝水平上,常绿植物比落叶植物投入更多的生物量到叶片。     

GOCompare: An R package to compare functional enrichment analysis between two species

Functional enrichment analysis is a cornerstone in bioinformatics as it makes possible to identify functional information by using a gene list as source. Different tools are available to compare gene ontology (GO) terms, based on a directed acyclic graph structure or content-based algorithms which are time-consuming and require a priori information of GO terms. Nevertheless, quantitative procedures to compare GO terms among gene lists and species are not available. Here we present a computational procedure, implemented in R, to infer functional information derived from comparative strategies. GOCompare provides a framework for functional comparative genomics starting from comparable lists from GO terms. The program uses functional enrichment analysis (FEA) results and implement graph theory to identify statistically relevant GO terms for both, GO categories and analyzed species. Thus, GOCompare allows finding new functional information complementing current FEA approaches and extending their use to a comparative perspective. To test our approach GO terms were obtained for a list of aluminum tolerance-associated genes in Oryza sativa subsp. japonica and their orthologues in Arabidopsis thaliana. GOCompare was able to detect functional similarities for reactive oxygen species and ion binding capabilities which are common in plants as molecular mechanisms to tolerate aluminum toxicity. Consequently, the R package exhibited a good performance when implemented in complex datasets, allowing to establish hypothesis that might explain a biological process from a functional perspective, and narrowing down the possible landscapes to design wet lab experiments.     

Woody species in resource‐rich microrefugia of granite outcrops display unique functional signatures

Refugia are key environments in biogeography and conservation. Because of their unique eco‐evolutionary formation and functioning, they should display distinct functional trait signatures. However, comparative trait‐based studies of plants in refugia and non‐refugia are lacking. Here, we provide a comparison between resource‐rich (putative microrefugia for species preferring mesic habitats under increasing aridity) and resource‐impoverished woodlands (non‐refugia) around two granite outcrops in south‐western Australia. We measured and compared six functional traits (bark thickness, foliar δ¹³C, foliar C:N, leaf dry matter content, plant height, specific leaf area) in four woody species. We performed multiple‐trait, multiple‐species and single‐trait, within‐species analyses to test whether plants in resource‐rich habitats were functionally distinct and more diverse than those in the surrounding resource‐impoverished woodlands. We found that species in resource‐rich woodlands occupied larger and distinct multiple‐trait functional spaces and showed distinct single‐trait values (for specific leaf area and bark thickness). This suggests that plants in resource‐rich woodlands can deploy unique and more diverse ecological strategies, potentially making these putative microrefugia more resilient to environmental changes. These findings suggest that species in microrefugia may be characterised by unique functional signatures, illustrating the utility of comparative trait‐based approaches to improve understanding of the functioning of refugia.     

Management of DNA reference libraries for barcoding and metabarcoding studies with the R package refdb

DNA barcoding and metabarcoding are revolutionizing the study and survey of biodiversity. In order to assign taxonomic labels to the DNA sequence data retrieved, these methods are strongly dependent on comprehensive and accurate reference databases. Producing reliable databases linking biological sequences and taxonomic data can be—and often has been—done using mainstream tools such as spreadsheet software. However, spreadsheets quickly become insufficient when the amount of data increases to thousands of taxa and sequences to be matched, and validation operations become more complex and are error prone if done in a manual way. Thus, there is a clear need for providing scientists with user-friendly, reliable and powerful tools to manipulate and manage DNA reference databases in tractable, sound and efficient ways. Here, we introduce the R package refdb as an environment for semi-automatic and assisted construction of DNA reference libraries. The refdb package is a reference database manager offering a set of powerful functions to import, organize, clean, filter, audit and export the data. It is broadly applicable in metabarcoding data generally obtained in biodiversity and biomonitoring studies. We present the main features of the package and outline how refdb can speed up reference database generation, management and handling, and thus contribute to standardization and repeatability in barcoding and metabarcoding studies.