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FIGURE 1 in The type of Setophaga ruficoronata (Kaup 1851) is a hybrid: implications for the taxonomy of Myioborus warblers (Passeriformes: Parulidae)
FIGURE 1. Map of northwestern South America showing the geographic distribution of high-elevation Myioborus warblers of the Northern Andes (M. albifrons, M. ornatus and M. melanocephalus). Each colored polygon represents the approximate geographic distribution of taxa recognized in this study, except for the one in dark gray, which shows the extent of the hybrid zone (Céspedes-Arias et al. 2021) between chrysops and bairdi. Gray dots indicate type localities of valid taxa, and the star the location of Cali, Colombia, the supposed type locality of M. m. ruficoronatus, which is most likely an error (see text). The question mark indicates the uncertainty in the geographic limits between bairdi and griseonuchus in southern Ecuador.
FIGURE 7 in The type of Setophaga ruficoronata (Kaup 1851) is a hybrid: implications for the taxonomy of Myioborus warblers (Passeriformes: Parulidae)
FIGURE 7. The type of Setophaga chrysops Salvin, 1878 (NHMUK 1885.3.8.804). Dorsal, ventral and side views, with the detail of the face. This taxon is currently treated as M. ornatus chrysops, and is the "pure" northern form hybridizing with bairdi in southern Colombia (see text). Photographs by Mark Adams (Natural History Museum, Tring).
FIGURE 6 in The type of Setophaga ruficoronata (Kaup 1851) is a hybrid: implications for the taxonomy of Myioborus warblers (Passeriformes: Parulidae)
FIGURE 6. Type specimens of names synonymized with Myioborus ornatus sensu stricto, and M. chrysops. Types of flaveola (A, MCZ 76106) and leucophomma (B, NML-VZ D2009), which correspond to juvenile and immature individuals of M. ornatus, respectively. Kaup (1851) identified as flaveola a specimen that corresponds to M. chrysops (C, NML-VZ D1932), but this is not a true type specimen (see text). Photographs by Jeremiah Trimble (Museum Comparative Zoology, Harvard University), and by Tony Parker and John James Wilson (World Museum, National Museums Liverpool).
FIGURE 5 in The type of Setophaga ruficoronata (Kaup 1851) is a hybrid: implications for the taxonomy of Myioborus warblers (Passeriformes: Parulidae)
FIGURE 5. Type of Setophaga ornata Boissonneau, 1840 (MCZ 76106), currently treated as Myioborus ornatus sensu stricto. Dorsal, ventral, and side views, with the detail of the face. This is a "Bogotá" skin. Photographs by Jeremiah Trimble (Museum Comparative Zoology, Harvard University).
FIGURE 4 in The type of Setophaga ruficoronata (Kaup 1851) is a hybrid: implications for the taxonomy of Myioborus warblers (Passeriformes: Parulidae)
FIGURE 4. Illustrations of three Andean Myioborus as illustrated by Johannes Gerardus Keulemans in Salvin (1878). Top: chrysops of the Western and Central cordilleras of Colombia. Center: A hybrid individual painted based on the type of Setophaga ruficoronata (NML-VZ D1931, see Fig. 2). Bottom: bairdi based on a specimen assigned to Setopopha bairdi from Sical (sic) Ecuador (see Fig. 3). The taxon bairdi was until now considered a junior synonym of ruficoronatus (Meyer de Schauensee 1946). Illustrations from Salvin (1878) via the Biodiversity Heritage Library (https://www.biodiversitylibrary.org/item/34861)
Diagenesis decreasing the Mo isotopic composition in estuarine systems: Implications for constraining its riverine input to ocean
<p>Physical and chemical characteristics of water and particulate samples in the August and December 2014 cruises and characteristics of water samples from the July 2016 and February 2017 cruises.</p>
Evolution of microRNAs in Amoebozoa and implications for the origin of multicellularity
<h2>Evolution of microRNAs in Amoebozoa and implications for the origin of multicellularity</h2> <p>Repository accompanying "Evolution of microRNAs in Amoebozoa and implications for the origin of multicellularity" manuscript</p> <p> </p> <h3>microRNA curation</h3> <p>Potential miRNA clusters, generated using Shortstack (https://github.com/MikeAxtell/ShortStack), are analyzed with <strong>miRNA_curation.py</strong>. An example run of the miRNA curation can be performed by running the 'example_run/explore_all.sh' and 'example_run/refine_all.sh' scripts in order. A sample of the sRNA sequences from <em>D. discoideum</em> is included in the 'example/example_sizeselected_data' folder. A sample of miRNA candidates are included in 'example_run/pot-miRNAs_merged.fa' to facilitate the example run.</p> <p><em>Prerequisites: Python 3, Biopython, RNAlib, matplotlib, numpy</em></p> <p> </p> <h3>microRNA analysis</h3> <p>Following miRNA curation, high confidence miRNAs are identified and further analysed in <strong>amoeba_miRNAevo.Rmd</strong>. The data for the analysis is located in 'data_in' and are mostly derived from the miRNA_curation.py script and other scripts located in the 'helper_scripts' folder. The plots generated in the analysis is located in the 'plots' folder. Tables and other data generated from the analysis are located in the 'data_out' folder. In order to perform the <strong>miRNA conservation search</strong>, refer to the '<strong>helper_scripts/miRNA_conservation_search/</strong>' folder.</p> <p><em>Prerequisites: R, Blast, bash</em></p> <p> </p> <h3>Access genomes/annotations</h3> <p>For <em>Dictyostelium firmibasis</em>, the genome was de-novo sequenced and assembled and is located in '<strong>data_in/novel_assembly'</strong>. Assembly was done using Flye v2.9.1 in nano-hq mode, and two rounds of long-read polishing were done using Medaka v1.7.2. The filtered reads used for assembly can be accessed from NCBI BioProject PRJNA972620. The <em>Acanthamoeba castellanii</em> genome and annotation were accessed at https://www.doi.org/10.5281/zenodo.680005. The other genomes and annotations for this study were accessed from NCBI and can be downloaded using the 'get_references.sh' script located in the helper_scripts folder.</p>
Different Formation Modes of the North‒South-Trending Rifts in Southern Tibet: Implications from Ambient Noise Tomography
<p>To reveal the formation modes of the southern Tibetan rifts, we performed ambient noise tomography to image the shear-wave velocity structure beneath different rifts. This dataset consists of there parts. The CFs_STB.zip contains correlation functions of all the station pairs. The disps_STB.zip contains the Rayleigh surface wave phase velocity dispersion curves. And the 3-D shear-wave model beneath the rifts of southern Tibet Pleatau is provided in Rift_STB_Vs_model.zip.</p>
Figure 5 in Multivariate analysis of neognath skeletal measurements: implications for body mass estimation in Mesozoic birds
Figure 5. Box plots with whiskers showing the variation among locomotion modes of percentage prediction errors (%PE) for the multiple regression analysis (MR; grey) and the single regression analysis (SR; white) equations adjusted in modern birds. Box length shows the interquartile range (25th and 75th percentiles). The horizontal line within boxes indicates the median. Vertical lines show the 5–95% confidence limits. Points indicate values outside these limits (i.e. outliers). Black horizontal lines between the grey and white boxes show the %PE estimates obtained with the equation based on humeral length (HL), the osteological variable less affected by ecological groupings (as shown by its lower F-statistic values; see Tables 6 and 7). %PE values greater than zero indicate an underestimation and %PE values lower than zero indicate an overestimation. A, %PE variation with respect to groups of aerial locomotion. Abbreviations: CF, continuous flapping; FG, flapping and gliding; FB, flapping and bounding; S, soaring. B, %PE variation with respect to groups of non-aerial locomotion. Abbreviations: A, aquatic; TG, terrestrial ground-dwelling; TN, terrestrial non-ground-dwelling; ATG, aquatic and grounddwelling; TGN, perching and ground-dwelling.
Figure 1. Calibrated phylogeny for the main avian taxa. Tree topology was obtained from O in Multivariate analysis of neognath skeletal measurements: implications for body mass estimation in Mesozoic birds
Figure 1. Calibrated phylogeny for the main avian taxa. Tree topology was obtained from O'Connor, Chiappe & Bell (2011) and divergence times are based on a 'literal' interpretation of the fossil record from Brockelhurst et al. (2012). Taxa abbreviations: Nth, Neornithes; Orph, Ornithuromorpha; Orn, Ornithothoraces; Orth, Ornithurae; Pyg, Pygostylia.
Figure 4 in Multivariate analysis of neognath skeletal measurements: implications for body mass estimation in Mesozoic birds
Figure 4. Biplots used in the selection of four variables for each fossil group of Mesozoic birds: humeral length (HL), femoral length (FL), diaphyseal craniocaudal width of ulna (dUW), and diaphyseal craniocaudal width of femur (dFWcc). Each predictor variable was plotted against a combination of the 14 remaining variables used for estimating body mass (BM; Table S3). The biplots show the regression line fitted for extant birds (grey circles) with the 95% confidence intervals for BM predictions (dotted lines). Following the procedure of selection of variables (see text), HL and FL were used for generating functions that can be applied to all fossil avian taxa. In contrast, dUW and dFWcc could not be incorporated into the functions adjusted for estimating BM in Archaeopterygidae and Enantiornithes, respectively.
Figure 3 in Multivariate analysis of neognath skeletal measurements: implications for body mass estimation in Mesozoic birds
Figure 3. Effects of weighting for the best-fitting multiple regression equation obtained from the modern data set (see Table 2). A, distribution of familiar residuals for unweighted data, and for data weighted by families. Each box plot with whiskers represents one family. Box length shows the interquartile range (25th and 75th percentiles). Horizontal lines indicate the 5–95% confidence limits. Asterisks show outliers. Abbreviations for families: Ac, Accipitridae; Ad, Alcedinidae; Ae, Aegothelidae; Al, Alcidae; An, Anatidae; Ap, Apodidae; Ar, Ardeidae; At, Artamidae; Au, Alaudidae; Ca, Caprimulgidae; Cc, Cacatuidae; Ch, Charadriidae; Ci, Ciconiidae; Co, Columbidae; Cn, Cinclidae; Cr, Coraciidae; Ct, Catharthidae; Cu, Cuculidae; Cv, Corvidae; Di, Diomedeidae; Fa, Falconidae; Fg, Fringillidae; Fr, Fregatidae; Ga, Gaviidae; Gr, Gruidae; He, Hemiprocnidae; Hi, Hirundinidae; La, Laridae; Ln, Lanidae; Me, Meleagridae; Mg, Megapodidae; Mo, Motacillidae; Mp, Meropidae; Ms, Musophagidae; Mu, Muscicapidae; Ot, Otididae; Pa, Paridae; Pc, Pelecanoididae; Pd, Podicipedidae; Pe, Pelecanidae; Ph, Phasianidae; Pic, Picidae; Pit, Pittidae; Pl, Phalacrocoracidae; Pn, Pandionidae; Po, Podargidae; Pr, Procellaridae; Ps, Psittacidae; Pt, Pteroclidae; Pu, Prunellidae; Ra, Rallidae; Re, Recurvirostridae; Ry, Rynchopidae; Sc, Stercoriidae; Sg, Strigidae; So, Scolopacidae; Sr, Sturnidae; St, Sternidae; Su, Sulidae; Sy, Sylviidae, Te, Tetraonidae; Th, Threskiornithidae; Tt, Tytonidae; Tu, Turdidae; Ty, Tyrannidae; Up, Upupidae. B, plot showing the variations of %MPE with the increase of individuals per family. The dashed line represents the unweighted multiple regression analysis (MR) and the grey line represents the weighted MR.
Figure 2 in Multivariate analysis of neognath skeletal measurements: implications for body mass estimation in Mesozoic birds
Figure 2. Illustration of osteological limb measurements used in this study and defined in Table 1: A, cranial aspect of the humerus; B, dorsal aspect of the ulna and the radius; C, dorsal aspect of the carpometacarpus; D, caudal aspect of the femur; E, caudal aspect of the tibiotarsus; F, cranial aspect of the tarsometarsus.
Uranium isotope constraints on the pre-deposition time of Asian dust to the North Pacific Ocean: Implications for provenance and iron supply
<p>This dataset presents uranium isotope data covering a 300,000-year period retrieved from Ocean Drilling Program site 1209B in the North Pacific Ocean. Additionally, it incorporates uranium-neodymium isotope data sourced from multiple deserts in China, providing a comprehensive reexamination of the origin of dust in the North Pacific region.</p>
Basal force fluctuations and granular rheology: Linking macroscopic descriptions of granular flows to bed forces with implications for monitoring signals
<p>Herein lies user defined functions, submission scripts, and intitial particle data necessary to build a discrete element solver (using MFiX-DEM version 21.1.1: https://mfix.netl.doe.gov/products/mfix/) and run a monodisperse pure granular flow with 5mm beads in a shear cell configuration. Contained within this dataset are particle velocity and force data for the entire collection of particles ('VELOCITY<em>'* </em>and 'FORCES*.DAT', respectively). This dataset also contains particle-force data recorded at the bottom force plate, writen at 10 kHz. Two MATLAB scripts are included for post processing the force plate data. </p>
The dataset for β diversity pattern of megabenthic community on a seamount of Philippine Sea: Implications for conservation planning on the Kyushu-Palau Ridge
Open the record for dataset details and reuse information.
The elasticity of seifertite at lowermost mantle conditions: implication for velocities anomaly at the Earth's core-mantle boundary
<p>the open data of the study "<span>The elasticity of seifertite at lowermost mantle conditions: implication for</span><span> </span><span>velocities anomaly at the Earth's core-mantle boundary"</span></p>
Data from: preserved appendages in a Silurian binodicope: implications for the evolutionary history of ostracod crustaceans
<p>Derima paparme gen. et sp. nov. from the Herefordshire Silurian Lagerstätte is one of only a handful of exceptionally preserved ostracod crustaceans known from the Palaeozoic. A male specimen provides the first evidence of the soft-part morphology of Binodicopina, a major group of Palaeozoic ostracods comprising some 135 Ordovician to Permian genera. The appendage morphology of D. paparme, but not its shell, indicates that binodicopes belong to Podocopa. The discovery that the soft-part morphology of binodicopes allies them with podocopes affirms that using the shell alone is an unreliable basis for classifying certain fossil ostracods and that knowledge of soft-part morphology is critical for the task. Current assignment of many fossil ostracods to higher taxa may require reconsideration.</p>
Melting of hydrogen-unsaturated iron hydride at high pressure and implications for core solidification in terrestrial planets
Open the record for dataset details and reuse information.
Organic and inorganic carbon sinks reduce long-term deep carbon emissions in the continental collision margin of the southern Tibetan Plateau: Implications for Cenozoic climate cooling
<p>Hydrogeochemical data including aqueous chemistry, hydrogen and oxygen isotopes, gas components, gas helium, carbon isotopes from southern Tibet. Supporting the manuscript titled "Organic and inorganic carbon sinks reduce long-term deep carbon emissions in the continental collision margin of the southern Tibetan Plateau: Implications for Cenozoic climate cooling".</p>
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.