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Fig. 1 in Global checklist of species of Grania (Clitellata: Enchytraeidae) with remarks on their geographic distribution
Fig. 1. Specimen of Grania chilensis Prantoni, De Wit & Erséus, 2016. Photograph by Pierre De Wit.
Fig. 2 in Global checklist of species of Grania (Clitellata: Enchytraeidae) with remarks on their geographic distribution
Fig. 2. World map showing the description localities, and the three evolutionary lineages (color-marked) of Grania spp. genetically analyzed by Prantoni et al. (2016: clades A, B and C). Green numbers = Atlantic species (clade A); red numbers = South Pacific and Atlantic species (clade B); blue numbers = Australian and Asian species (clade C); black numbers = species presently without molecular data, i.e., not yet allocated to any particular lineage.
Geographical distribution of co-authors of Nobel laureates 1994-2018 in Physics, Chemistry and Physiology or Medicine
<p>Geographical distribution of co-authors of Nobel laureates 1994-2018 in Physics, Chemistry and Physiology or Medicine. Appendix to the article «Quantitative analysis of the co-publications of Ukrainian scientists with the Nobel laureates 1994-2018 in Science».</p>
Figs 9–13 in Gallancyra gen. nov. (Phthiraptera: Ischnocera), with an overview of the geographical distribution of chewing lice parasitizing chicken
Figs 9–13. Gallancyra dentata (Sugimoto, 1934) gen. et comb. nov. ex Gallus gallus (Linnaeus, 1758) (NHMUK010682393). 9. Male head, dorsal and ventral views. 10. Female antenna, ventral view. 11. Male genitalia, dorsal view. 12. Male paramere, dorsal view. 13. Male mesosome, ventral view. Female antenna at same scale as male head. Abbreviations: ads = anterior dorsal seta; as2 = anterior seta 2; pst1–2 = parameral setae 1–2. All genitalic component drawn at same scale.
Fig. 2 in Gallancyra gen. nov. (Phthiraptera: Ischnocera), with an overview of the geographical distribution of chewing lice parasitizing chicken
Fig. 2. Geographical distribution of four species of ischnoceran chewing lice parasitizing wild and domestic chicken (Gallus spp.). Each circle is divided into four sectors, representing the four louse species: upper left = Lipeurus caponis (Linnaeus, 1758); upper right = Lipeurus tropicalis Peters, 1931; lower left = Cuclotogaster heterographus (Nitzsch, 1866); lower right = Lagopoecus sinensis (Sugimoto, 1930). Black sectors indicate that this louse species is known from this country, whereas hollow sectors indicate that we have found no published records of this species in this country. Presence of the four species of chewing lice in a country is based on the reports summarized in Table 1.
Geographic patterns in morphometric and genetic variation for coyote populations with emphasis on southeastern coyotes
Prior to 1900, coyotes (Canis latrans) were restricted to the western and central regions of North America, but by the early 2000s coyotes became ubiquitous throughout the eastern United States. Information regarding morphological and genetic structure of coyote populations in the southeastern United States is limited, and where data exist, they are rarely compared to those from other regions of North America. We assessed geographic patterns in morphology and genetics of coyotes with special consideration of coyotes in the southeastern United States. Mean body mass of coyote populations increased along a west-to-east gradient, with southeastern coyotes being intermediate to western and northeastern coyotes. Similarly, principal component analysis of body mass and linear body measurements suggested that southeastern coyotes were intermediate to western and northeastern coyotes in body size but exhibited shorter tails and ears from other populations. Genetic analyses indicated that southeastern coyotes represented a distinct genetic cluster that differentiated strongly from western and northeastern coyotes. We postulate that southeastern coyotes experienced lower immigration from western populations than did northeastern coyotes, and over time, genetically diverged from both western and northeastern populations. Coyotes colonizing eastern North America experienced different selective pressures than did stable populations in the core range and we offer that the larger body size of eastern coyotes reflect an adaptation that improved dispersal capabilities of individuals in the expanding range.
Datasets for The Effect of COVID-19 on AGU Journal Authors by Gender and Geographical Location
<p>These files provide anonymized source data and tabular data on gender, age, and country of corresponding authors (submitting author) of American Geophysical Union (AGU) journals from January 2018 through June 2020. These datasets supplement an iposter presented at Japan Geosciences Union- American Geophysical Union joint 2020 meeting and supplement the corresponding preprint submission to ESSOAR.</p>
Figure 5 in Geographic distribution, host plants, and morphological variation of the currently radiating phytophagous ladybird beetle Henosepilachna diekei
Figure 5. Elytra height of seven populations of Henosepilachna diekei. (A) Females; (B) males. The host plants were denoted in the parentheses as M, Mikania; L, Leucas; D, Dicliptera; P, Plectranthus. The different letter on the right shoulder of each box indicates significant difference (P <0.05) after adjustment of P-value for multiple comparisons (NS, P ≥ 0.05).
Divergence, gene flow and the origin of leapfrog geographic distributions: the history of color pattern variation in Phyllobates poison-dart frogs
<p>The geographic distribution of phenotypic variation among closely related populations is a valuable source of information about the evolutionary processes that generate and maintain biodiversity. Leapfrog distributions, in which phenotypically similar populations are disjunctly distributed and separated by one or more phenotypically distinct populations, represent geographic replicates for the existence of a phenotype, and are therefore especially informative. Phyllobates poison frogs. We found evidence for high levels of gene flow between neighboring populations but not over long distances, indicating that gene flow between populations exhibiting the central phenotype may have a homogenizing effect that maintains their similarity, and that introgression between "leapfroging" taxa has not played a prominent role as a driver of phenotypic diversity in <i>Phyllobates</i>. Although phylogenetic analyses suggest that the leapfrog distribution was formed through independent evolution of the peripheral (i.e. leapfrogging) populations, the elevated levels of gene flow between geographically close populations poise alternative scenarios, such as the history of phenotypic change becoming decoupled from genome-averaged patterns of divergence, which we cannot rule out. These results highlight the importance of incorporating gene flow between populations into the study of geographic variation in phenotypes, both as a driver of phenotypic diversity and as a confounding factor of phylogeographic inferences.</p>
Interaction of hydric and thermal conditions drive geographic variation in thermoregulation in a widespread lizard
<p>Raw data and scripts of the article "Interaction of hydric and thermal conditions drive geographic variation in thermoregulation in a widespread lizard" by Rozen-Rechels D. et al., in Ecological Monographs. These data are freely available in csv format. See the readme file for metadata explanation.</p> <p>Data were formatted by the first author David Rozen-Rechels and collected according to standards and procedures described in the companion journal article.</p> <p> </p> <p>Abstract of the paper:</p> <p>Behavioral thermoregulation is an efficient mechanism to buffer the physiological effects of climate change. Thermal ecology studies have traditionally tested how thermal constraints shape thermoregulatory behaviors without accounting for the potential major effects of landscape structure and water availability. Thus, we lack a general understanding of the multifactorial determinants of thermoregulatory behaviors in natural populations. In this study, we quantified the relative contribution of elevation, thermal gradient, moisture gradient and landscape structure in explaining geographic variation in thermoregulation strategies of a terrestrial ectotherm species. We measured field active body temperature, thermal preferences and operative environmental temperatures to calculate thermoregulation indices, including thermal quality of the habitat and thermoregulation efficiency for a very large sample of common lizards (<em>Zootoca vivipara</em>) from 21 populations over 3 years across the Massif Central mountain range in France. We used an information-theoretic approach to compare eight <em>a priori</em> thermo-hydroregulation hypotheses predicting how behavioral thermoregulation should respond to environmental conditions. Environmental characteristics exerted little influence on thermal preference with the exception that females from habitats with permanent access to water had lower thermal preferences. Field body temperatures and accuracy of thermoregulation were best predicted by the interaction between air temperature and a moisture index. In mesic environments, field body temperature and thermoregulation inaccuracy increased with air temperature, but they decreased in drier habitats. Thermoregulation efficiency (difference between thermoregulation inaccuracy and the thermal quality of the habitat) was maximized in cooler and more humid environments and was mostly influenced by the thermal quality of the habitat. Our study highlights complex patterns of variation in thermoregulation strategies, which are mostly explained by the interaction between temperature and water availability, independent of the elevation gradient or thermal heterogeneity. Although changes in landscape structure were expected to be the main driver of extinction rate of temperate zone ectotherms with ongoing global change, we conclude that changes in water availability coupled with rising temperatures might have a drastic impact on the population dynamics of some ectotherm species.</p>
Fig. 1 in Molecular phylogenetics of the African horseshoe bats (Chiroptera: Rhinolophidae): expanded geographic and taxonomic sampling of the Afrotropics
Fig. 1 Type localities for recognized species of Rhinolophus (black circles), as well as subspecies and synonyms (white circles); label names represent the specific epithets of currently recognized species. Biomes of Africa and neighboring regions indicated by color shading, dark yellow: Tropical and subtropical moist broadleaf forests; orange: Flooded grasslands and savannas; gray: Tropical and subtropical grasslands, savannas, and shrublands; olive brown: Deserts and xeric shrublands; gray-green: Tropical and subtropical moist broadleaf forests; peach: Mangroves; ochre: Mediterranean forests, woodlands, and shrub; dark tan: Tropical and subtropical dry broadleaf forests [14]
Fig. 5 in Molecular phylogenetics of the African horseshoe bats (Chiroptera: Rhinolophidae): expanded geographic and taxonomic sampling of the Afrotropics
Fig. 5 Species tree estimated in StarBEAST2 using the four nuclear intron dataset. Numbers adjacent to nodes indicate posterior probabilities. Terminal tips in the tree that are statistically well-supported (PP ≥ 0.95) from BPP are indicated by "*" preceding the clade name, and terminal tips that had PP <0.95 are indicated by "?" preceding the clade name. Species groups are from [13]
Dataset for the paper "Slavic morphosyntax is primarily determined by its geographic location and contact configuration", Scando-Slavica Journal
<p>This is the raw dataset for the paper "Slavic morphosyntax is primarily determined by its geographic location and contact configuration", Scando-Slavica</p>
Point, polygon, or marker? In search of the best geographic entity for mapping Cultural Ecosystem Services using the online PPGIS tool, "My Green Place."
<p>Excel files include the raw database and the processed data that led to the quadrat analyses. The "Matrix_raw data" file includes the raw data as downloaded from the server. This data was cleaned and organized for its posterior use. "Quadrat analyzes "file includes all the quadrat analyses resulting in each research question in the paper except question four. Question 4 can be seen in the file "Water analysis_Blaarmeersen." All excel files come with a "CODE" tab that describes each of the codes used, their meaning, and ways that were calculated where necessary. Two zip files include all the GIS files. The first one includes the GIS files from which "Matrix_raw data" was built from. The second folder includes the resulting maps from the quadrat analyses. In order to visualize them as in the paper, configure the symbology tab at the GIS software in quantile and the categories number, as shown in the paper.</p> <p>The production of the files in the "GIS_Processed data" folder was done via a repetitive line of commands in ArcGIS pro. The same process was followed for each one of the quadrat analysis described in the paper. Refer to "<a href="https://zenodo.org/api/files/72403e0b-78a9-4bbf-8dca-ed9b8702e3ae/Reproduction%20commands%20and%20parameters.pdf">Reproduction commands and parameters.pdf</a>" for further information.</p>
Electron density and altitude of the main ionospheric peak of Mars as observed by Mars Express instruments. Archived data for the paper "Seasonal and geographical variability of the Martian ionosphere from Mars Express observations", submitted to JGR-Planets
<p>This repository contains archived data for the manuscript "Seasonal and geographical variability of the Martian ionosphere from Mars Express observations", published in Journal of Geophysical Research-Planets. Details about the methods to generate the data can be found in the paper.</p> <p>5 data files plus 2 readme text files are included.</p> <p>The file MEx_ionpeak.dat (described in the readme file README_ionpeak.txt) contains the peak electron densities and peak altitudes resulting from 34539 observations. Each record includes 14 columns. The content of each column is:</p> <p>Column 1: Instrument providing the observation (MARSIS or MaRS)<br> Column 2: Mars Year at which the observation was obtained (from MY27 to MY33)<br> Column 3: Solar Longitude (Ls) of the observation (unit: degrees)<br> Column 4: Latitude of the observation (unit: degrees)<br> Column 5: Longitude of the observation (unit: degrees)<br> Column 6: Solar Zenith Angle (SZA) of the observation (unit: degrees)<br> Column 7: F10.7 solar proxy index at 1 Astronomic Unit (unit: solar flux units)<br> Column 8: Peak electron density measured by the instrument (unit: cm-3)<br> Column 9: Peak electron density at the subsolar point, i.e., corrected for the SZA variation (unit: cm-3)<br> Column 10: Peak electron density at the subsolar point and at F10.7 (1AU)=100, i.e., corrected for the SZA and the solar radiation output variations (unit: cm-3)<br> Column 11: Peak electron density at the subsolar point, at F10.7 (1AU)=100 and corrected for the seasonal variation (unit: cm-3)<br> Column 12: Peak altitude measured by the instrument (unit: km)<br> Column 13: Peak altitude at the subsolar point, i.e. corrected for the SZA variation (unit: km)<br> Column 14: Peak altitude at the subsolar point and corrected for the seasonal variation (unit: km)</p> <p> </p> <p>The files eprofiles_MaRS.dat, eprofiles_MARSIS_prof1.dat, eprofiles_MARSIS_prof2.dat and eprofiles_MARSIS_prof3.dat contain 4 electron density profiles. They are described in the file README_eprofiles.txt. Each file includes 2 columns, the first one being the altitude (unit: km) and the second one the electron density (unit: cm-3).</p> <p> </p> <p>Contact: Francisco Gonzalez-Galindo, ggalindo@iaa.es<br> </p>
FIG. 10 in The oldest erymnochelyine turtle skull, Ragechelus sahelica n. gen., n. sp., from the Iullemmeden basin, Upper Cretaceous of Africa, and the associated fauna in its geographical and geological context
FIG. 10. — Podocnemididae from Ibeceten, south-western Niger, Senonian, Gularo-Intergular pattern, MNHN.F.IBC coll. A-F, Erymnochelyine Erymnochelys group, variability in shape of plates and scutes: alternative epiplastral and entoplastral combinations: A, epiplastron IBC560 and entoplatron IBC1898; B, epiplastron IBC560 and entoplastron IBC1903; C, entoplastron IBCx1; D, IBCx2, fragmentary epiplastron; E, epiplastron IBC1893 and entoplastron IBC1898; F, epiplastron IBC1893 and entoplastton IBC542. Podocnemididae indet., primitive intergular pattern; G, IBC1899, entoplastron. Ventral views. Scale bar: 2 cm.
FIG. 9. — Ragechelus sahelica n. gen., n in The oldest erymnochelyine turtle skull, Ragechelus sahelica n. gen., n. sp., from the Iullemmeden basin, Upper Cretaceous of Africa, and the associated fauna in its geographical and geological context
FIG. 9. — Ragechelus sahelica n. gen., n. sp., Indamane, southwestern Niger, late Maastrichtian; detail of the skull, cavum tympani area, holotype MNHN- RA-2018.0031. Abbreviations: ant, antrum squamosum; cq, commissura quadrati; ica+Et, incisura columellae auris with Eustachian tube. Left lateral view. Scale bar: 2 cm.
FIG. 8. — Ragechelus sahelica n. gen., n in The oldest erymnochelyine turtle skull, Ragechelus sahelica n. gen., n. sp., from the Iullemmeden basin, Upper Cretaceous of Africa, and the associated fauna in its geographical and geological context
FIG. 8. — Ragechelus sahelica n. gen., n. sp., Indamane, southwestern Niger, late Maastrichtian; detail of the skull, holotype MNHN-RA-2018.0031, showing the rounded carotid foramen for entrance in te besicranium, at the back of the deep cavum pterygoideum, below the (broken here) podocnemidid pterygoid wing; Abbreviations:boc, basioccipital; bsph, basisphenoid; car can, enlarged carotid foramen; cav pter, cavum pterygoideum; pw, break of the pterygoid wing at its posterior base; q, quadrate; q art, area articularis quadrati. Ventral view. Scale bar: 2 cm.
FIG. 7. — Ragechelus sahelica n. gen., n in The oldest erymnochelyine turtle skull, Ragechelus sahelica n. gen., n. sp., from the Iullemmeden basin, Upper Cretaceous of Africa, and the associated fauna in its geographical and geological context
FIG. 7. — Ragechelus sahelica n. gen., n. sp., Indamane, southwestern Niger, late Maastrichtian; interpretative drawing of the skull, holotype MNHN-RA-2018.0031. Abbreviations: aaq, area articularis quadrati; boc, basioccipital; bsph, basiphenoid; car c, carotid canal; cav pter, cavum pterygoideum; co, condylus occipitalis; col-Et, columella auris with the Eustachian tube passage; cq, commissura quadrati; fpp, foramen palatinum posterius; fp, fenestra postotica; imc, intermediate maxillo-palatine crest; ju, jugal; mc, medial maxillo-palatine crest; ms, muscle insertion zone; mx, maxilla; pal, palatine; pmx, premaxilla; po, postorbital; ppo, processus paroccipitalis opisthotici; pter w, pterygoid wing; ptp, processus trochlearis pterygoideus; q, quadrate. Ventral view. Scale bar: 4 cm.
FIG. 6. — Ragechelus sahelica n. gen., n in The oldest erymnochelyine turtle skull, Ragechelus sahelica n. gen., n. sp., from the Iullemmeden basin, Upper Cretaceous of Africa, and the associated fauna in its geographical and geological context
FIG. 6. — Ragechelus sahelica n. gen., n. sp., Indamane, southwestern Niger, late Maastrichtian. Lateral view of the skull, holotype MNHN-RA-2018.0031. Abbreviations: an sq, antrum squamosum; co, condylus occipitalis; com q, commissura quadrati; fpp; foramen palatinum posterius; fr, frontal; ica+Et, incisura columellae auris with the Eustachian tube; ju, jugal; l pfr, left prefrontal; mq, meatus quadrati; mx, maxilla; na, external nare; pal, palatine; pfr, prefrontal; pmx, premaxilla; paq, processus articularis quadrati; pmx, premaxilla; po, postorbital; ppo, processus paroccipitalis opisthotici; pro, prootic; pter, pterygoid; ptp, processus trochlearis pterygoideus; q, quadrate; r paq, right processus articularis quadrati; r pter, right pterygoid; soc, supraoccipital; sq, squamosal; V, foramen trigemini; black arrow, position of the foramen stapediotemporale; blue and green dotted lines, hypothetic positions for the skull lateral notch border; red line, border of the palatal medial crest. Scale bar: 4 cm.
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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.