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Volcano plot of Sigma B-dependent differential gene expression of Clostridioides difficile
<p>A customized whole-genome DNA microarray of <em>Clostridioides difficile </em>630∆<em>erm</em> was used (8x15K format, Agilent). Quadruplicate samples were analysed for the DNA microarray. Using the ULS fluorescent labelling kit for Agilent arrays (Kreatech), 1 µg of total RNA was used for labelling with either Cy3 (P<sub>tet</sub>-<em>sigB</em>) or Cy5 (P<sub>tet</sub>-<em>sLuc<sup>opt</sup></em>). After pooling and fragmentation, 300 ng of labelled RNA per sample was hybridized according to the two-color microarray protocol from Agilent. DNA microarrays were scanned with an Agilent C scanner and analysed. CDS_ID=GenBank identifier, gene_name=annotated gene name (when available), locus_tag= locus tag, protein=annotation of protein function (when available), log2FC= log 2 of the fold change (sigB overproduction/control), adj_Pvalue = adjusted P-value, significance = -10log(adj_Pvalue).</p>
Additional HTML Figures: Exploding biplots with density axes in Plotly
<p>Two figures as seen in <em>Exploding biplots with density axes in Plotly, </em>in the HTML format produced by the code for this paper.</p>
Data from: Plotting for change: an analytic framework to aid decisions on which lineages are candidate species in phylogenomic species discovery
<p>A recent study argued that coalescent-based models of species delimitation mostly delineate population structure not species, and called for the validation of candidate species using biological information additional to the genetic information, such as phenotypic or ecological data. Here we introduce a framework to interrogate genomic datasets and coalescent-based species trees for the presence of candidate species in situations where additional biological data are unavailable, unobtainable, or uninformative. For <i>de novo</i> genomic studies of species boundaries, we propose six steps: (a) visualize genetic affinities among individuals to identify both discrete and admixed genetic groups from first principles, and to hold aside individuals involved in contemporary admixture for independent consideration; (b) apply phylogenetic techniques to identify lineages; (c) assess diagnosability of those lineages as potential candidate species; (d) interpret the diagnosable lineages in a geographic context (sympatry, parapatry, allopatry); (e) assess significance of difference or trends in the context of sampling intensity; and (f) adopt a holistic approach to available evidence to inform decisions on species status in the difficult cases of allopatry. We use this approach to distinguish candidate species from within-species lineages for a widespread species complex of Australian freshwater fishes (<i>Retropinna</i> spp.). Our framework addresses two cornerstone issues in systematics that are often not explicitly discussed in genomic species discovery: diagnosability and how to determine it, and what criteria should be used to decide whether diagnosable lineages are conspecific or represent different species.</p>
Data from: Global fern and lycophyte richness explained: how regional and local factors shape plot richness
<p>Aim<br> To disentangle the influence of environmental factors at different spatial grains (regional and local) on fern and lycophyte species richness and ask how regional and plot-level richness are related to each other.<br> Location<br> Global.<br> Time Period<br> Present.<br> Major Taxa studied<br> Ferns and lycophytes.<br> Methods<br> We explored fern and lycophyte species richness at two spatial grains, regional (hexagonal grid cells of 7666 km2) and plot-level (300–500 m2), in relation to environmental data at regional and local grains (the 7666-km2 hexagonal grid cells and 4-km2 square grid cells, respectively). For the regional grain, we obtained species richness data for 1243 spatial units and used them together with climatic, and topographical predictors to model global fern richness. For the plot-level grain, we collated a global dataset of nearly 83,000 vegetation plots with surface area in the range 300–500 m2 in which all fern and lycophyte species had been counted. We used structural equation modelling to identify which regional and local factors have the biggest effect on plot-level fern and lycophyte species richness worldwide. We investigate how plot-level richness is related to modelled regional richness at the plot's location.<br> Results<br> Plot-level fern and lycophyte species richness was best explained by models allowing a link between regional environment and plot-level richness. A link between regional richness and plot-level richness was essential, as models without it were rejected, while models without the regional environment - plot-level richness link were still valid but had a worse goodness-of-fit value. Plot-level richness showed a hump-shaped relationship with regional richness.<br> Main Conclusions<br> Both regional environment and regional fern and lycophyte species richness each are important determinants of plot-level richness, and the inclusion of one does not substitute the inclusion of the other. Plot-level richness increases with regional richness until a saturation point is reached, after which plot-level richness decreases despite increasing regional richness, possibly reflecting species interactions.</p>
Kraken analysis from shotgun sequenced museum specimens via krona plot visualization
<p>This dataset contains html files with krona plots from Kraken analysis on shotgun sequenced museum specimens.</p>
Data from: Informative plot sizes in presence-absence sampling of forest floor vegetation
1. Plant communities are attracting increased interest in connection with forest and landscape inventories due to society's interest in ecosystem services. However, the acquisition of accurate information about plant communities poses several methodological challenges. Here we investigate the use of presence-absence sampling with the aim to monitor state and change of plant density. We study what plot sizes are informative, i.e. the estimators should have as high precision as possible. 2. Plant occurrences were modeled through different Poisson processes and tests were developed for assessing the plausibility of the model assumptions. Optimum plot sizes were determined by minimizing the variance of the estimators. While state estimators of similar kind as ours have been proposed in previous studies, our tests and change estimation procedures are new. 3. We found that the most informative plot size for state estimation is 1.6 divided by the plant density, i.e. if the true density is 1 plant per square meter the optimum plot size is 1.6 square meters. This is in accordance with previous findings. More importantly, the most informative plot size for change estimation was smaller and depended on the change patterns. We provide theoretical results as well as some empirical results based on data from the Swedish National Forest Inventory. 4. Use of too small or too large plots resulted in poor precision of the density (and density change) estimators. As a consequence, a range of different plot sizes would be required for jointly monitoring both common and rare plants using presence-absence sampling in monitoring programmes.
Data from: Habitat patterns in tropical rain forests: a comparison of 105 plots in northwest Borneo
Understanding the maintenance of high tropical tree species diversity requires disentangling the effects of habitat vs. geographic distance. Using floristic, topographic, and soil nutrient data from 105 0.6-ha plots in mixed dipterocarp forest throughout Sarawak, Malaysian Borneo, we explore the degree to which floristic patterns are habitat-driven from local to landscape scales. We assess how the floristic influence of geographic distance vs. abiotic factors varies from local to regional scales. We employ several multivariate analytical techniques and perform a hierarchical clustering of the research plots using the Steinhaus index of floristic dissimilarity, as well as Mantel analyses on matrices of floristic, habitat, and geographic distance. These analyses indicate that floristic variation is more strongly correlated with habitat than with geographic distance on the regional scale. On the local-landscape to community scale, we find evidence of a resource threshold above which habitat effects weaken; that is, below the resource threshold floristic similarity between sites is dominated by habitat effects, while above the threshold floristic similarity between sites is dominated by geographic-distance effects. We also find evidence that topography and soil nutrients correlate in part independently with floristics. These results, together with previous studies in the Neotropics, emphasize that tree species distribution and community composition are variously influenced by the interplay of both habitat and dispersal-driven effects.
Data from: The contribution of rare species to community phylogenetic diversity across a global network of forest plots
Niche differentiation has been proposed as an explanation for rarity in species assemblages. Testing this hypothesis requires quantifying the ecological similarity of species. This similarity can potentially be estimated by using phylogenetic relatedness. In this study, we predicted that if niche differentiation does explain the co-occurrence of rare and common species, then rare species should contribute greatly to the overall community phylogenetic diversity (PD), abundance will have phylogenetic signal and that common and rare species will be phylogenetically dissimilar. We tested these predictions by developing a novel method that integrates species rank abundance distributions with phylogenetic trees and trend analyses to examine the relative contribution of individual species to the overall community PD. We then supplement this approach with analyses of phylogenetic signal in abundances and measures of phylogenetic similarity within and between rare and common species groups. We applied this analytical approach to 15 long-term temperate and tropical forest dynamics plots from around the world. We show that the niche differentiation hypothesis is supported in six forests but is rejected in nine forests, and that the three metrics utilized in this study each provide unique but corroborating information regarding the phylogenetic distribution of rarity in communities.
Data from: OpenNahele: the open Hawaiian forest plot database
This data paper provides a description of OpenNahele, the open Hawaiian forest plot database. OpenNahele includes 530 forest plots across the Hawaiian archipelago containing 43,590 individuals of 185 native and alien tree, shrub and tree fern species across six islands. We include estimates of maximum plant size (D950.1 and Dmax3) for 58 woody plant species, a key functional trait associated with dispersal distance and competition for light. OpenNahele can serve as a platform to test key ecological, evolutionary and conservation questions in a hotspot archipelago.
Figure 5. Per-base coverage plots for the 16S in Target-enriched DNA sequencing from historical type material enables a partial revision of the Madagascar giant stream frogs (genus Mantidactylus)
Figure 5. Per-base coverage plots for the 16S fragment in four Mantidactylus type specimens from the MNHN and BMNH collections. (a) BMNH 1947.2.25.48 (paralectotype of Rana guttulata); (b) BMNH 1947.2.25.51 (paralectotype of Rana guttulata); (c) MNHN 1895.255 (syntype of M. grandidieri); (d) MNHN 1883.520 (syntype of M. grandidieri).
Cascadia FakeQuakes waveform data and scenario plots
<p>Supplementary data for the paper "Kinematic Rupture Scenarios and Synthetic Displacement Data: An Example Application to the Cascadia Subduction Zone<strong>" </strong>by D.Melgar, RJ Leveque, DS Dreger and RM Allen in the Journal of Geophysical Research. Cascadia.zip contains the waveforms, rupture descriptions and scenario plots. File formats are explained in fakequakes_readme.pdf</p>
FIGURE 6. STRUCTURE Plots for K in A new member of the greater double-collared sunbird complex (Passeriformes: Nectariniidae) from the Eastern Arc Mountains of Africa
FIGURE 6. STRUCTURE Plots for K = 2, light grey—whytei, dark grey—the new taxon: top, analysis of nine microsatellite loci; bottom, analysis of seven microsatellite loci.
FIGURE 10. Bivariate plots with 95 in Morphological variation, polymorphism, and Taxonomy of the Atractus torquatus complex (Serpentes: Dipsadidae)
FIGURE 10. Bivariate plots with 95% confidence regions for the first two axes derived from scores of PCA analyses for male (A–B) and female (C–D) of Atractus torquatus complex.
FIGURE 34. L–H scatter plot for Neonesidea bacata n in New and poorly known species of Neonesidea (Bairdiidae, Ostracoda, Crustacea) from French Frigate Shoals, the Hawaiian Islands
FIGURE 34. L–H scatter plot for Neonesidea bacata n. sp., Bairdia hanaumaensis Holden, and Indo-Pacific species of Papillatabairdia.
FIGURE 9. Bivariate plots with 95 in Morphological variation and taxonomy of Atractus latifrons (Günther, 1868) (Serpentes: Dipsadidae)
FIGURE 9. Bivariate plots with 95% confidence regions for the first two axes derived from scores of discriminant analyses for males (A) and females (B) of Atractus latifrons.
FIGURE 33. A single waveform plot showing a in A revision of the Ewartia oldfieldi (Distant) species complex (Hemiptera: Cicadidae: Cicadettinae) with five new species from eastern and northern Australia
FIGURE 33. A single waveform plot showing a breakdown of two phrases of the complex mode of the calling song of Ewartia oldfieldi (Distant). This illustrates the various components that were measured for the purposes of the Non-metric Multidimensional Scaling Analysis.
FIGURE 19. Wave plots illustrating a in A revision of the Ewartia oldfieldi (Distant) species complex (Hemiptera: Cicadidae: Cicadettinae) with five new species from eastern and northern Australia
FIGURE 19. Wave plots illustrating a short duration subphrase example from the complex calling song mode of Ewartia lapidosa n. sp. This is presented as two single subphrases, one of which is broken into its various components. A and B: each a single subphrase in its entirety. C: expanded diagram of the first half of the subphrase (from B above), showing several a sequence of syllables interspersed occasionally with short macrosyllables (syllable doublets). D: expanded diagram of the second half of the subphrase (from B), showing two macrosyllables, each separated by two syllables, followed by an echeme, four syllables, and the accentuation, which contains two macrosyllables separated by two syllables. The recording was obtained from Miles (26°37'S 150°10'E) using RS3 (see Methods).
FIGURE 18. Wave plots illustrating a in A revision of the Ewartia oldfieldi (Distant) species complex (Hemiptera: Cicadidae: Cicadettinae) with five new species from eastern and northern Australia
FIGURE 18. Wave plots illustrating a single, intermediate duration subphrase example from the complex calling song mode of Ewartia lapidosa n. sp., presented as two single subphrases, one of which is broken into its various components. A and B: each a single subphrase in its entirety. C and D: expanded diagram of the opening and middle sections of the subphrase (from B above), showing several macrosyllables, each separated by 1–3 syllables. E: expanded diagram of the end of the subphrase (from B), showing a series of macrosyllables, increasing successively in duration and each punctuated by 2–3 syllables, followed by a short echeme, two syllables, another macrosyllable, a syllable sequence, and the accentuation, which contains two macrosyllables separated by two syllables. The recording was obtained from Capertee (33°07'S 150°08'E) using RS6 (see Methods).
FIGURE 16. Wave plots illustrating a in A revision of the Ewartia oldfieldi (Distant) species complex (Hemiptera: Cicadidae: Cicadettinae) with five new species from eastern and northern Australia
FIGURE 16. Wave plots illustrating a single, long duration subphrase example from the complex calling song mode of Ewartia lapidosa n. sp. A: complete subphrase. B: expanded diagram of the start of the subphrase (from A above), showing several macrosyllables, each separated by 3–14 syllables. C: expanded diagram of the middle of the subphrase (from A), showing a long sequence of syllables, interrupted by a single macrosyllable. D: expanded diagram of the end of the subphrase (from A), showing a series of macrosyllables, increasing successively in duration and each punctuated by 3–4 syllables, followed by a climactic echeme, an additional short syllable sequence, another macrosyllable and a longer syllable sequence, which then proceeds to an accentuation, containing three macrosyllables followed by long gaps and each separated by 1–2 syllables. The recording was obtained from Bringalily State Forest (28°11'S 151°07'E) using RS3 (see Methods).
FIGURE 17. Wave plots illustrating a in A revision of the Ewartia oldfieldi (Distant) species complex (Hemiptera: Cicadidae: Cicadettinae) with five new species from eastern and northern Australia
FIGURE 17. Wave plots illustrating a single, long duration subphrase example from the complex calling song mode of Ewartia lapidosa n. sp. A: complete subphrase. B and C: expanded diagram of the initial part of the subphrase (from A above), showing several macrosyllables, each separated by 2–3 syllables. D: expanded diagram of the middle of the subphrase (from A), also showing several syllables, separated by a gradually increasing number of syllables (2–5). E: expanded diagram of the end of the subphrase (from A), showing a series of macrosyllables, increasing successively in duration and each punctuated by a syllable sequence (10–16 syllables), followed by a climactic echeme, an additional short syllable sequence, then an accentuation, containing two macrosyllables separated by a long gap, which is broken by four syllables. The recording was obtained from White Mountains (20°43'S 145°13'E) using RS3 (see Methods).
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.