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FIGURE 2. Key characters that distinguish Bignonia binata Thunb. from B in Deciphering the Neotropical Bignonia binata species complex (Bignoniaceae)
FIGURE 2. Key characters that distinguish Bignonia binata Thunb. from B. noterophila Mart. ex DC. A–F: B. binata. A. Terminal inflorescence. B. Young branch node. C. Leaflet. D. Fruit. E. Winged seed. F. Pantoaperturate (central C-shape) pollen grain. G–L: B. noterophila. G. Axillary inflorescence. H. Young winged branch node; arrow indicates branch wing. I. Leaflet. J. Fruit. K. Wingless seed. L. Inaperturate pollen grain. A–D: Zuntini 355 (SPF); E: Hoenhe s.n. (SPF-46408); F: Pedersen 6546 (MO), G: Stevens 31475 (MO); H, J: Zuntini CR3 (USJ); I: Evans 2355 (SPF); K: Gentry 8478 (SPF); L: Steyermark 114851 (MO). Photo G was taken by Olga Martha Montiel, while all other photos were taken by ARZ.
FIGURE 3. Distinguishing features between Hampea lanceolata and Hampea longipes. A–B in Hampea lanceolata (Malvaceae, Malvoideae), a new species from Chiapas and Oaxaca, Mexico
FIGURE 3. Distinguishing features between Hampea lanceolata and Hampea longipes. A–B. Holotype of Hampea lanceolata (D. E. Breedlove 27604, MO). C–D. Holotype of Hampea longipes (F. Miranda 7769, MEXU). Note the longer bracteoles and the coarse brown pubescence in Hampea lanceolata (A), and the leaf bases with main nerves diverging at narrower angles and forming pocket domatia (B). The scale bar equals 2 cm.
FIGURES 1–8 in A new genus from southern China in the tribe Nicertini and discussion of distinguishing tribes of Derbinae (Hemiptera: Fulgoromorpha: Derbidae)
FIGURES 1–8. Neomegatropis rubrimacula, sp. nov., adult. 1. male, head and thorax, dorsal view; 2. male, head and thorax, ventral view; 3. male, head and thorax, lateral view; 4. male, habitus, lateral view;5. female, head and thorax, dorsal view; 6. female, head and thorax, ventral view; 7. female, head and thorax, lateral view; 8. female, habitus, lateral view. Scale bars = 1 mm
FIGURES 22–28 in A new genus from southern China in the tribe Nicertini and discussion of distinguishing tribes of Derbinae (Hemiptera: Fulgoromorpha: Derbidae)
FIGURES 22–28. Neomegatropis rubrimacula, sp. nov., adult. 22. tegmen; 23. male, anal tube, dorsal view; 24. pygofer, ventral view; 25. gonostylus, lateral view; 26. aedeagus, lateral view; 27. female, anal tube, dorsal view; 28. gonoplac, laterodorsal view. Scale bars = 0.1 mm
FIGURES 9–21 in A new genus from southern China in the tribe Nicertini and discussion of distinguishing tribes of Derbinae (Hemiptera: Fulgoromorpha: Derbidae)
FIGURES 9–21. Neomegatropis rubrimacula, sp. nov., adult. 9. jugal margin of hind wing; 10. female, apical part of abdomen, lateral view; 11. female, apical part of abdomen, ventral view; 12. male, metatibiotarsal formula; 13. female, metatibiotarsal formula; 14. eggs; 15. female, anal tube, dorsal view; 16. female, anal tube, lateral view; 17. female, anal tube, laterodorsal view; 18. anterior connective lamina of gonapophysis VIII and endogonocoxal process, lateroventral view; 19. endogonocoxal process and gonocoxa VIII; 20. gonapophyses IX, ventral view; 21. gonapophyses IX, laterodorsal view. Scale bars = 0.2 mm
FIGURE 1 in Using the size independent discriminant analysis to distinguish the species of Myliobatis Cuvier (Batoidea: Myliobatidae) from Brazil
FIGURE 1: Morphometric characters used in Size Independent Discriminant Analysis: 1GOL First gill opening length; 5GOL Fifth gill opening length; 1ID First interbranchial distance; 5ID Fifth interbranchial distance; DBL Dorsal fin base length; DH Dorsal fin height; DL Disc length; DW Disc width; HDE Horizontal diameter of eye ball; HW Head width; IED Interespiracular distance; IND Internarial distance; IOD Interorbital distance; MW mouth width; PCD Precloacal distance; PD Predorsal distance; PL Pelvic fin length; POBL preorbital length; PORL preoral length; PW Pelvic fin width; SL Spiracle length
Data from: A flicker of hope: genomic data distinguish Northern Flicker taxa despite low levels of divergence
Next-generation sequencing technologies are increasingly being employed to explore patterns of genomic variation in avian taxa previously characterized using morphology and/or traditional genetic markers. The hybridization dynamics of the Northern Flicker complex have received considerable attention, primarily due to the conspicuous plumage differences among these birds and the geographically extensive hybrid zone between the Red-shafted (Colaptes auratus cafer) and Yellow-shafted (Colaptes auratus auratus) flickers in the Great Plains region of North America. However, no traditional molecular techniques have been able to differentiate these 2 morphologically well-defined taxa from one another, or conclusively from the closely related Gilded Flicker (Colaptes chrysoides). Here, we use a next-generation sequencing approach to assess the genetic diversity and evolutionary history of these 3 taxa. We confirm the overall low levels of differentiation found using traditional molecular markers, but are able to distinguish between the 3 taxa for the first time, using a dataset of thousands of SNP loci distributed across the genome. Through demographic modeling and phylogenetic reconstructions, we find that Red-shafted and Yellow-shafted flickers are likely sister taxa, and that their divergence from the Gilded Flicker was comparatively older. The low level of divergence and lack of fixed differences in our dataset between Red-shafted and Yellow-shafted flickers, in particular, suggests whole-genome re-sequencing may be necessary to assess the dynamics of their hybridization and identify the genetic basis of their striking differences in plumage.
Data from: Finding a needle in a haystack: distinguishing Mexican maize landraces using a small number of SNPs
In Mexico's territory, the center of origin and domestication of maize (Zea mays), there is a large phenotypic diversity of this crop. This diversity has been classified into "landraces." Previous studies have reported that genomic variation in Mexican maize is better explained by environmental factors, particularly those related with altitude, than by landrace. Still, landraces are extensively used by agronomists, who recognize them as stable and discriminatory categories for the classification of samples. In order to investigate the genomic foundation of maize landraces, we analyzed genomic data (35,909 SNPs from Illumina MaizeSNP50 BeadChip) obtained from 50 samples representing five maize landraces (Comiteco, Conejo, Tehua, Zapalote Grande, and Zapalote Chico), and searched for markers suitable for landrace assignment. Landrace clusters could not be identified taking all the genomic information, but they become manifest taking only a subset of SNPs with high FST among landraces. Discriminant analysis of principal components was conducted to classify samples using SNP data. Two classification analyses were done, first classifying samples by landrace and then by altitude category. Through this classification method, we identified 20 landrace-informative SNPs and 14 altitude-informative SNPs, with only 6 SNPs in common for both analyses. These results show that Mexican maize phenotypic diversity can be classified in landraces using a small number of genomic markers, given the fact that landrace genomic diversity is influenced by environmental factors as well as artificial selection due to bio-cultural practices.
FIGURE 2 in Cryptic speciation: distinguishing serpentine affiliated sister species Navarretia paradoxiclara and N. paradoxinota from N. intertexta (Polemoniaceae)
FIGURE 2. Box plots of variation in floral features among N. intertexta (N. int), N. paradoxiclara (N. p_c.), and N. paradoxinota (N. p_n.). Boxes bound the 25 and 75 percentiles; horizontal line marks the 50 percentile, whiskers extend to the 5 and 95 percentiles with outliers shown as dots. The diamond demarks the mean (horizontal vertices) and standard deviation (vertical vertices).
FIGURE 4 in Cryptic speciation: distinguishing serpentine affiliated sister species Navarretia paradoxiclara and N. paradoxinota from N. intertexta (Polemoniaceae)
FIGURE 4. Map of California, U.S.A., with county borders (gray lines) showing the distribution of Navarretia paradoxiclara (stars with four points) and Navarretia paradoxinota (stars with five points). Serpentine areas are shaded black (derived from 2010 Geologic Map of California; http://www.quake.ca.gov/gmaps/GMC/stategeologicmap.html).
FIGURE 1 in Cryptic speciation: distinguishing serpentine affiliated sister species Navarretia paradoxiclara and N. paradoxinota from N. intertexta (Polemoniaceae)
FIGURE 1. Representative most parsimonious phylograms inferred from analysis of DNA sequence data. Acronyms following species names are correlated to specimens in Appendix 1. Lower case letters ('a' and 'b') following acronyms in Figs. 1B, C indicate multiple copies indicative of either polyploidy (e.g. N. propinqua) or possibly gene duplication or intrapopulation variation among multiple individuals (e.g. N. leucocephala). Total character change (base substitutions and indels) are reconstructed above interior branches (terminal values can be inferred by branch length). Branches not found in all shortest trees are indicated by dotted lines. Bootstrap support values are shown in bold italics below branches. A. One of six trees inferred from concatenated cpDNA sequences. B. One of 32 trees inferred from nrDNA ITS sequences. C. One of six trees inferred from nuclear PI sequences.
FIGURE 3 in Cryptic speciation: distinguishing serpentine affiliated sister species Navarretia paradoxiclara and N. paradoxinota from N. intertexta (Polemoniaceae)
FIGURE 3. Features of Navarretia paradoxiclara (all Johnson, Gowen & Mort 09-032) and N. paradoxinota (all Johnson, Gowen & Mort 09-021), with some comparison to N. intertexta and N. propinqua. All vouchers deposited at BRY unless otherwise indicated. A– D. flowers, top and side views, scale bar = 1 cm. A. N. paradoxiclara. B. N. paradoxinota. C. N. intertexta Gowen 1133, 1134-B. D. N. propinqua Johnson & Johnson 11-076. E–H. Corolla dissections, scale bar = 1 cm. E. N. paradoxiclara. F. N. paradoxinota. G. N. intertexta (left = Gowen 1133; right = Ahart 3453 [CAS]). H. N. propinqua Johnson & Johnson 09-067. I–J. Plant habit (note, either species can have a single leader (I) or be variously branched (J), scale bar = 1 cm. I. N. paradoxiclara. J. N. paradoxinota. K–L. Inflorescence, scale bars = 2 cm. K. N. paradoxiclara. L. N. paradoxinota. M–N. Outer inflorescence bract, N. paradoxiclara, scale bar = 1 cm. M. Adaxial view. N. Lateral view. O–P. Inner inflorescence bract, N. paradoxiclara, scale bar = 1 cm. O. Adaxial view. P. Lateral view. Q. Pollen grain, N. paradoxinota, scale bar = 10 µm. R. mature capsule, N. paradoxinota, scale bar = 1 mm (distal end to the left). S. Partially hydrated seed with thin halo of mucilaginous spiracles, N. paradoxinota, scale bar = 1 mm.
Data from: Distinguishing noise from signal in patterns of genomic divergence in a highly polymorphic avian radiation
Recently diverged taxa provide the opportunity to search for the genetic basis of the phenotypes that distinguish them. Genomic scans aim to identify loci that are diverged with respect to an otherwise weakly differentiated genetic background. These loci are candidates for being past targets of selection because they behave differently from the rest of the genome that has either not yet differentiated or that may cross species barriers through introgressive hybridization. Here we use a reduced-representation genomic approach to explore divergence among six species of southern capuchino seedeaters, a group of recently radiated sympatric passerine birds in the genus Sporophila. For the first time in these taxa, we discovered a small proportion of markers that appeared differentiated among species. However, when assessing the significance of these signatures of divergence, we found that similar patterns can also be recovered from random grouping of individuals representing different species. A detailed demographic inference indicates that genetic differences among Sporophila species could be the consequence of neutral processes, which include a very large ancestral effective population size that accentuates the effects of incomplete lineage sorting. As these neutral phenomena can generate genomic scan patterns that mimic those of markers involved in speciation and phenotypic differentiation, they highlight the need for caution when ascertaining and interpreting differentiated markers between species, especially when large numbers of markers are surveyed. Our study provides new insights into the demography of the southern capuchino radiation and proposes controls to distinguish signal from noise in similar genomic scans.
Data from: The challenges of recognising individuals with few distinguishing features: identifying red foxes Vulpes vulpes from camera-trap photos
Over the last two decades, camera traps have revolutionised the ability of biologists to undertake faunal surveys and estimate population densities, although identifying individuals of species with subtle markings remains challenging. We conducted a two-year camera-trapping study as part of a long-term study of urban foxes: our objectives were to determine whether red foxes could be identified individually from camera-trap photos, and highlight camera-trapping protocols and techniques to facilitate photo identification of species with few or subtle natural markings. We collected circa 800,000 camera-trap photos over 4945 camera days in suburban gardens in the city of Bristol, UK: 152,134 (19 %) included foxes, of which 13,888 (9 %) contained more than one fox. These provided 174,063 timestamped capture records of individual foxes; 170,923 were of foxes ≥ 3 months old. Younger foxes were excluded because they have few distinguishing features. We identified the individual (192 different foxes: 110 males, 49 females, 33 of unknown sex) in 168,417 (99 %) of these capture records; the remainder could not be identified due to poor image quality or because key identifying feature(s) were not visible. We show that carefully designed survey techniques facilitate individual identification of subtly-marked species. Accuracy is enhanced by camera-trapping techniques that yield large numbers of high resolution, colour images from multiple angles taken under varying environmental conditions. While identifying foxes manually was labour-intensive, currently available automated identification systems are unlikely to achieve the same levels of accuracy, especially since different features were used to identify each fox, the features were often inconspicuous, and their appearance varied with environmental conditions. We discuss how studies based on low numbers of photos, or which fail to identify the individual in a significant proportion of photos, risk losing important biological information, and may come to erroneous conclusions.
FIGURE 1. A–B. Cyathea corcovadensis. A in A proposal to distinguish several taxa in the Brazilian tree fern Cyathea corcovadensis (Cyatheaceae)
FIGURE 1. A–B. Cyathea corcovadensis. A. Pinna, silhouette (D.B.G. Bussmann 90, JOI); B. Detail of fertile pinnule, abaxially (N.P. Smith 330, FLOR). C–D. Cyathea feeana. C. Pinna, silhouette (A.F. Regnell 479, S); D. Detail of fertile pinnule, abaxially (G. Hatschbach 23226, MBM). E. Cyathea miersii. Pinna, silhouette (J. Miers 149, B). Same scale for all pinnae and details, respectively.
FIGURE 2 in A proposal to distinguish several taxa in the Brazilian tree fern Cyathea corcovadensis (Cyatheaceae)
FIGURE 2. Distributions of A. Cyathea atrovirens; B. Cyathea corcovadensis; C. Cyathea feeana; D. Cyathea miersii.
FIG. 3 in Notes on distinguishing the cocoons and the juveniles of Hirudo medicinalis and Haemopis sanguisuga (Hirudinea)
FIG. 3. Ventral view of the two forms of Haemopis sanguisuga: the more normal light form above, and the less common dark form below. Scales in millimetres.
FIG. 2 in Notes on distinguishing the cocoons and the juveniles of Hirudo medicinalis and Haemopis sanguisuga (Hirudinea)
FIG. 2. Top: typical new cocoons of Haemopis sanguisuga (above) and Hirudo medicinalis (below). Bottom: older, stained, cocoons of Hirudo medicinalis (left) and Haemopis sanguisuga (right). Note the diOEerence in the texture of the cocoon wall between the two species. Scales in millimetres.
FIG. 1 in Notes on distinguishing the cocoons and the juveniles of Hirudo medicinalis and Haemopis sanguisuga (Hirudinea)
FIG. 1. Length frequency distribution of cocoon (A) lengths and (B) widths of Hirudo medicinalis and Haemopis sanguisuga from sites in Scotland.
FIGURE 3 in Distinguishing ten sympatric species of fiddler crab (Decapoda: Ocypodidae) using a suite of phenotypic characteristics
FIGURE 3. Austruca cryptica Naderloo, Türkay & H.-L. Chen, 2010: a–d Sulawesi Tenggara, Indonesia.Adult male colouration; a, large chela; b, carapace dorsal view. Adult female colouration; c, frontal view; d, carapace dorsal view. Photos credit L. Michie. Line drawing of right G1; e, mesial view; f, lateral view; CLSM images of apical part of G1; g, mesial view; h, lateral view; SEM images of male gastric mill; i, median tooth plate, ventral view; j, left lateral tooth plate, mesial view.
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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.