hydrographr: An R package for scalable hydrographic data processing

1. Freshwater ecosystems are considered biodiversity hotspots, but assessing the spatial distribution of species remains challenging. One major obstacle lies in the complex geospatial processing of large amounts of data, such as stream network, sub-catchment and basin data, that are necessary for addressing the longitudinal connectivity among water bodies. Workflows thus need to be scalable, especially when working across large spatial extents and at high spatial resolution. This in turn requires advanced command-line GIS skills and programming language integration, which often poses a challenge for freshwater researchers. 2. To address this challenge, we developed the package hydrographr that provides scalable hydrographic data processing in R. The package contains functions for downloading data of the high-resolution Hydrography90m dataset, processing, reading and extracting information, as well as assessing network distances and connectivity. While the functions are, by default, tailored toward the Hydrography90m data, they can also be generalised toward other data and purposes, such as efficient cropping and merging of raster and vector data, point-raster extraction, raster reclassification and data aggregation. The package depends on the open-source software GDAL/OGR, GRASS-GIS and the AWK programming language in the Linux environment, allowing a seamless language integration. Since the data is processed outside R, hydrographr allows creating scalable geo-processing workflows. 3. We illustrate the hydrographr functions using two workflows that focus on (i) a freshwater species distribution modelling approach, and (ii) assessing stream connectivity given the fragmentation by dams. We also provide a detailed guide for the initial installation of the required software. Windows users need to first enable the Windows Subsystem for Linux (WSL) feature, and can then follow the same software installation as Linux users. hydrographr is maintained on GitHub at https://github.com/glowabio/hydrographr. 4. hydrographr provides a set of key functions for processing freshwater geospatial data. We expect that the package will support the freshwater-related research communities given the easy-to-use wrapper functions that allow capitalizing on powerful open-source command-line software, which may otherwise require a steep learning curve. Users can thus perform large-scale freshwater-specific longitudinal connectivity and network analyses across large geographic extents while staying within the R environment

Mitigating Anticipated Effects of Systematic Errors Supports Sister-Group Relationship between Xenacoelomorpha and Ambulacraria

Xenoturbella and the acoelomorph worms (Xenacoe-lomorpha) are simple marine animals with controversial affinities. They have been placed as the sister group of all other bilaterian animals (Nephrozoa hypothesis), implying their simplicity is an ancient characteristic [1, 2]; alternatively, they have been linked to the complex Ambulacraria (echinoderms and hemichordates) in a Glade called the Xenambulacraria [3,5], suggesting their simplicity evolved by reduction from a complex ancestor. The difficulty resolving this problem implies the phylogenetic signal supporting the correct solution is weak and affected by inadequate modeling, creating a misleading non-phylogenetic signal. The idea that the Nephrozoa hypothesis might be an artifact is prompted by the faster molecular evolutionary rate observed within the Acoelomorpha. Unequal rates of evolution are known to result in the systematic artifact of long branch attraction, which would be predicted to result in an attraction between long-branch acoelomorphs and the outgroup, pulling them toward the root [6]. Other biases inadequately accommodated by the models used can also have strong effects, exacerbated in the context of short internal branches and long terminal branches [7]. We have assembled a large and informative dataset to address this problem. Analyses designed to reduce or to emphasize misleading signals show the Nephrozoa hypothesis is supported under conditions expected to exacerbate errors, and the Xenambulacraria hypothesis is preferred in conditions designed to reduce errors. Our reanalyses of two other recently published datasets [1, 2] produce the same result. We conclude that the Xenacoelomorpha are simplified relatives of the Ambulacraria

hydrographr: An R package for scalable hydrographic data processing

Abstract Freshwater ecosystems are considered biodiversity hotspots, but assessing the spatial distribution of species remains challenging. One major obstacle lies in the complex geospatial processing of large amounts of data, such as stream network, sub‐catchment and basin data, that are necessary for addressing the longitudinal connectivity among water bodies. Workflows thus need to be scalable, especially when working across large spatial extents and at high spatial resolution. This in turn requires advanced command‐line GIS skills and programming language integration, which often poses a challenge for freshwater researchers. To address this challenge, we developed the package hydrographr that provides scalable hydrographic data processing in R. The package contains functions for downloading data of the high‐resolution Hydrography90m dataset, processing, reading and extracting information, as well as assessing network distances and connectivity. While the functions are, by default, tailored toward the Hydrography90m data, they can also be generalised toward other data and purposes, such as efficient cropping and merging of raster and vector data, point‐raster extraction, raster reclassification and data aggregation. The package depends on the open‐source software GDAL/OGR, GRASS‐GIS and the AWK programming language in the Linux environment, allowing a seamless language integration. Since the data is processed outside R, hydrographr allows creating scalable geo‐processing workflows. We illustrate the hydrographr functions using two workflows that focus on (i) a freshwater species distribution modelling approach, and (ii) assessing stream connectivity given the fragmentation by dams. We also provide a detailed guide for the initial installation of the required software. Windows users need to first enable the Windows Subsystem for Linux (WSL) feature, and can then follow the same software installation as Linux users. hydrographr is maintained on GitHub at https://github.com/glowabio/hydrographr. hydrographr provides a set of key functions for processing freshwater geospatial data. We expect that the package will support the freshwater‐related research communities given the easy‐to‐use wrapper functions that allow capitalizing on powerful open‐source command‐line software, which may otherwise require a steep learning curve. Users can thus perform large‐scale freshwater‐specific longitudinal connectivity and network analyses across large geographic extents while staying within the R environment

Measuring the multisensory imagery of wine : The vividness of wine imagery questionnaire

When we imagine objects or events, we often engage in multisensory mental imagery. Yet, investigations of mental imagery have typically focused on only one sensory modality—vision. One reason for this is that the most common tool for the measurement of imagery, the questionnaire, has been restricted to unimodal ratings of the object. We present a new mental imagery questionnaire that measures multisensory imagery. Specifically, the newly developed Vividness of Wine Imagery Questionnaire (VWIQ) measures mental imagery of wine in the visual, olfactory, and gustatory modalities. Wine is an ideal domain to explore multisensory imagery because wine drinking is a multisensory experience, it involves the neglected chemical senses (smell and taste), and provides the opportunity to explore the effect of experience and expertise on imagery (from wine novices to experts). The VWIQ questionnaire showed high internal consistency and reliability, and correlated with other validated measures of imagery. Overall, the VWIQ may serve as a useful tool to explore mental imagery, for researchers, as well as individuals in the wine industry during sommelier training and evaluation of wine professionals

The genomic and phenotypic diversity of Schizosaccharomyces pombe

Natural variation within species reveals aspects of genome evolution and function. The fission yeast Schizosaccharomyces pombe is an important model for eukaryotic biology, but researchers typically use one standard laboratory strain. To extend the usefulness of this model, we surveyed the genomic and phenotypic variation in 161 natural isolates. We sequenced the genomes of all strains, finding moderate genetic diversity (π = 3 × 10(-3) substitutions/site) and weak global population structure. We estimate that dispersal of S. pombe began during human antiquity (∼340 BCE), and ancestors of these strains reached the Americas at ∼1623 CE. We quantified 74 traits, finding substantial heritable phenotypic diversity. We conducted 223 genome-wide association studies, with 89 traits showing at least one association. The most significant variant for each trait explained 22% of the phenotypic variance on average, with indels having larger effects than SNPs. This analysis represents a rich resource to examine genotype-phenotype relationships in a tractable model