Tabular strategies for metadata in ecology,evolution, and the environmental sciences

Data support knowledge development and theory advances in ecology and evolution. We are increasingly reusing data within our teams and projects and through the global, openly archived datasets of others. Metadata can be challenging to write and interpret, but it is always crucial for reuse. The value metadata cannot be overstated—even as a relatively independent research object because it describes the work that has been done in a structured format. We advance a new perspective and classify methods for metadata curation and development with tables. Tables with templates can be effectively used to capture all components of an experiment or project in a single, easy‐to‐read file familiar to most scientists. If coupled with the R programming language, metadata from tables can then be rapidly and reproducibly converted to publication formats including extensible markup language files suitable for data repositories. Tables can also be used to summarize existing metadata and store metadata across many datasets. A case study is provided and the added benefits of tables for metadata, a priori, are developed to ensure a more streamlined publishing process for many data repositories used in ecology, evolution, and the environmental sciences. In ecology and evolution, researchers are often highly tabular thinkers from experimental data collection in the lab and/or field, and representations of metadata as a table will provide novel research and reuse insights.     

微生物生态研究中BIOLOG方法数据分析及R语言实现

微生物生态研究中,对微生物群落结构、群落特征以及其与环境因素的关系的揭示,一直受到广泛关注;适当的数据分析方法有助于更清晰地刻画微生物群落结构特征,明确其与环境因素的关系。结合实例,对微生物生态研究中基于BIOLOG微平板技术的数据分析方法进行梳理,分别介绍数据读取整理、特征指数计算、非限制性排序、限制性排序、聚类分析、环境向量拟合、蒙特尔检验等常用数据操作及生态分析方法;针对不同方法结论,结合研究目标和生态理论给出具有统计学意义的解释,并评价不同方法特点及适用场景;分析过程以R语言实现,并提供全部代码。结果表明,BIOLOG方法产生数据能从多个角度表征微生物群落功能特征,并结合环境指标梯度进行分析;但BIOLOG数据可能不满足正态性分布,在基于正态分布的分析前应提前进行检验;排序分析时应慎用主成分分析,可优先采用其他基于距离矩阵的排序方法;R语言能够简化BIOLOG数据读取及操作,易于完成各类统计分析。本研究能够对微生物生态研究者科学选择应用统计分析方法、提高数据处理效率提供直接参考。     

Open science and meta‐analysis allow for rapid advances in ecology: A response to Menegotto et al. (2019)

Menegotto and colleagues’ (2019) commentary on our paper (Kinlock et al., 2018) does not negate our findings, but by recategorizing and reanalysing a portion of our data set, advances our knowledge of the latitudinal diversity gradients (LDGs) in marine ecosystems, particularly emphasizing different findings for benthic LDGs as a result of the recategorization of the data. Furthermore, we see the contribution by Menegotto et al. (2019) as highlighting the importance of scientific transparency; we believe that this insight into the nature of LDGs in marine systems would have been delayed, if not unobtainable, had we not provided fully transparent methods and complete data in our paper.     

feedr and animalnexus.ca: A paired R package and user‐friendly Web application for transforming and visualizing animal movement data from static stations

Radio frequency identification (RFID) provides a simple and inexpensive approach for examining the movements of tagged animals, which can provide information on species behavior and ecology, such as habitat/resource use and social interactions. In addition, tracking animal movements is appealing to naturalists, citizen scientists, and the general public and thus represents a tool for public engagement in science and science education. Although a useful tool, the large amount of data collected using RFID may quickly become overwhelming. Here, we present an R package (feedr) we have developed for loading, transforming, and visualizing time‐stamped, georeferenced data, such as RFID data collected from static logger stations. Using our package, data can be transformed from raw RFID data to visits, presence (regular detections by a logger over time), movements between loggers, displacements, and activity patterns. In addition, we provide several conversion functions to allow users to format data for use in functions from other complementary R packages. Data can also be visualized through static or interactive maps or as animations over time. To increase accessibility, data can be transformed and visualized either through R directly, or through the companion site: http://animalnexus.ca , an online, user‐friendly, R‐based Shiny Web application. This system can be used by professional and citizen scientists alike to view and study animal movements. We have designed this package to be flexible and to be able to handle data collected from other stationary sources (e.g., hair traps, static very high frequency (VHF) telemetry loggers, observations of marked individuals in colonies or staging sites), and we hope this framework will become a meeting point for science, education, and community awareness of the movements of animals. We aim to inspire citizen engagement while simultaneously enabling robust scientific analysis.     

A conceptual framework for understanding the perspectives on the causes of the science–practice gap in ecology and conservation

Applying scientific knowledge to confront societal challenges is a difficult task, an issue known as the science–practice gap. In Ecology and Conservation, scientific evidence has been seldom used directly to support decision‐making, despite calls for an increasing role of ecological science in developing solutions for a sustainable future. To date, multiple causes of the science–practice gap and diverse approaches to link science and practice in Ecology and Conservation have been proposed. To foster a transparent debate and broaden our understanding of the difficulties of using scientific knowledge, we reviewed the perceived causes of the science–practice gap, aiming to: (i) identify the perspectives of ecologists and conservation scientists on this problem, (ii) evaluate the predominance of these perspectives over time and across journals, and (iii) assess them in light of disciplines studying the role of science in decision‐making. We based our review on 1563 sentences describing causes of the science–practice gap extracted from 122 articles and on discussions with eight scientists on how to classify these sentences. The resulting process‐based framework describes three distinct perspectives on the relevant processes, knowledge and actors in the science–practice interface. The most common perspective assumes only scientific knowledge should support practice, perceiving a one‐way knowledge flow from science to practice and recognizing flaws in knowledge generation, communication, and/or use. The second assumes that both scientists and decision‐makers should contribute to support practice, perceiving a two‐way knowledge flow between science and practice through joint knowledge‐production/integration processes, which, for several reasons, are perceived to occur infrequently. The last perspective was very rare, and assumes scientists should put their results into practice, but they rarely do. Some causes (e.g. cultural differences between scientists and decision‐makers) are shared with other disciplines, while others seem specific to Ecology and Conservation (e.g. inadequate research scales). All identified causes require one of three general types of solutions, depending on whether the causal factor can (e.g. inadequate research questions) or cannot (e.g. scientific uncertainty) be changed, or if misconceptions (e.g. undervaluing abstract knowledge) should be solved. The unchanged predominance of the one‐way perspective over time may be associated with the prestige of evidence‐based conservation and suggests that debates in Ecology and Conservation lag behind trends in other disciplines towards bidirectional views ascribing larger roles to decision‐makers. In turn, the two‐way perspective seems primarily restricted to research traditions historically isolated from mainstream conservation biology. All perspectives represented superficial views of decision‐making by not accounting for limits to human rationality, complexity of decision‐making contexts, fuzzy science–practice boundaries, ambiguity brought about by science, and different types of knowledge use. However, joint knowledge‐production processes from the two‐way perspective can potentially allow for democratic decision‐making processes, explicit discussions of values and multiple types of science use. To broaden our understanding of the interface and foster productive science–practice linkages, we argue for dialogue among different research traditions within Ecology and Conservation, joint knowledge‐production processes between scientists and decision‐makers and interdisciplinarity across Ecology, Conservation and Political Science in both research and education.     

AT2R − 1332 G:A polymorphism and its interaction with AT1R 1166 A:C,ACE I/D and MMP-9 − 1562 C:T polymorphisms: Risk factors for susceptibility to preeclampsia

The possible association of angiotensin type 2 receptor (AT2R) − 1332 G:A polymorphism with susceptibility to preeclampsia was studied in 252 women consisted of 155 women with preeclampsia and 97 healthy pregnant women. Also, the interaction of this polymorphism with angiotensin type 1 receptor (AT1R) 1166 A:C, angiotensin converting enzyme insertion/deletion (ACE I/D) and also with matrix metalloproteinase-9 (MMP-9) − 1562 C:T polymorphism was investigated. The AT2R − 1332 G:A polymorphism was detected using PCR–RFLP method. Significantly higher frequencies of GG+GA genotype and G allele of AT2R were observed in mild (80.2%, p = 0.003 and 47.5%, p = 0.012, respectively) and severe (77.8%, p = 0.034 and 48.1%, p = 0.026, respectively) preeclampsia compared to controls (60.8% and 35.1%, respectively). The presence of G allele was associated with 1.69-fold increased risk of preeclampsia (p = 0.005). In severe preeclamptic women, systolic and diastolic blood pressures in the presence of GG+GA genotype were significantly higher compared to those in the presence of AA genotype. The concomitant presence of both alleles of AT2R G and AT1R C was associated with 1.3 times increased risk of mild preeclampsia (p = 0.03). There was an interaction between AT2R G and ACE D alleles that significantly increased the risk of mild and severe preeclampsia by 1.38- and 1.3-fold, respectively. Also, interaction between MMP-9 T and AT2R G alleles increased the risk of severe preeclampsia 1.39-fold (p = 0.028). Our study demonstrated that the G allele of AT2R − 1332 G:A polymorphism is associated with an increased risk of preeclampsia. Also, epistatic interaction of G allele and each allele of the AT1R C, ACE D and MMP-9 T was associated with the risk of preeclampsia. Our findings suggest that the renin–angiotensin system (RAS) variants and gene–gene interactions affect the risk of preeclampsia.     

popsicleR: A R Package for Pre-processing and Quality Control Analysis of Single Cell RNA-seq Data

The advent of single-cell sequencing is providing unprecedented opportunities to disentangle tissue complexity and investigate cell identities and functions. However, the analysis of single cell data is a challenging, multi-step process that requires both advanced computational skills and biological sensibility. When dealing with single cell RNA-seq (scRNA-seq) data, the presence of technical artifacts, noise, and biological biases imposes to first identify, and eventually remove, unreliable signals from low-quality cells and unwanted sources of variation that might affect the efficacy of subsequent downstream modules. Pre-processing and quality control (QC) of scRNA-seq data is a laborious process consisting in the manual combination of different computational strategies to quantify QC-metrics and define optimal sets of pre-processing parameters.Here we present popsicleR, a R package to interactively guide skilled and unskilled command line-users in the pre-processing and QC analysis of scRNA-seq data. The package integrates, into several main wrapper functions, methods derived from widely used pipelines for the estimation of quality-control metrics, filtering of low-quality cells, data normalization, removal of technical and biological biases, and for cell clustering and annotation. popsicleR starts from either the output files of the Cell Ranger pipeline from 10X Genomics or from a feature-barcode matrix of raw counts generated from any scRNA-seq technology. Open-source code, installation instructions, and a case study tutorial are freely available at https://github.com/bicciatolab/popsicleR.     

A role for sialic acid containing substrates in the exocytosis-like in vitro interaction between adrenal medullary plasma membranes and chromaffin granules

The “in vitro” interaction between bovine adrenal medullary plasma membranes and chromaffin granules has recently been proposed as a putative cell-free model for exocytosis because calcium ions specifically control the plasma membrane-induced release of 10^?7 and 10^?5 M. Addition of ruthenium red or pretreatment with neuraminidase gradually blocks this interaction indicating that sialic acid containing substrates may be of major importance. These observations and similar results obtained by other authors working on different systems suggest a role for sialic acid containing moieties in exocytosis.