Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
236
datasets available to search
ShareScore release 0.7.1
Dataset results
236 results for “leaf morphology”
Figure 8 in Morphological phylogeny of Megachilini and the evolution of leaf-cutter behavior in bees (Hymenoptera: Megachilidae)
Figure 8. Strict consensus tree of 30 parsimonious trees obtained under equal weighting. Numbers above nodes are standard bootstrap values, numbers below nodes are absolute Bremer values. Branches without numbers indicate bootstrap values below 50% and Bremer values of 1. A capital letter above a node indicates a clade discussed in the text. Species within boxes of the same color correspond to the same subgenus of Megachile Latreille s.l. following Michener's (2007) classification. The colored column after the species names indicates approximate number of species per subgenus. Half-colored boxes without a number correspond to species that did not cluster with the other species of the same subgenus included in the analysis. Species richness taken from Michener (2007), Moure et al. (2007), and Ascher & Pickering (2018). Mandibles with interdental laminae highlighted in green (odontogenic) and pink (ctenogenic).
Figure 9 in Morphological phylogeny of Megachilini and the evolution of leaf-cutter behavior in bees (Hymenoptera: Megachilidae)
Figure 9. Preferred total evidence dated phylogeny of Megachilidae. Majority-rule consensus tree from Bayesian analysis using fossils as terminals under the FBD tree prior. Blue bar at each node represents the 95% highest posterior density age range. Posterior probability below 100 indicated above each node.
Figure 6 in Morphological phylogeny of Megachilini and the evolution of leaf-cutter behavior in bees (Hymenoptera: Megachilidae)
Figure 6. Examples of the types of setae found on the male S4–S6 of Megachile Latreille s.l. A. Branched, unmodified, S4, Megachile (Acentron) albitarsis Cresson. B. Acuminate, S4, M. (Megachile) centuncularis (Linnaeus). C. Acuminate, S6, M. (Chalicodoma) sicula (Rossi). D. Fan-shaped, S6, M. (Chelostomoides) exilis Cresson. E. Capitate-spatulate, S5, M. (Chelostomoides) rugifrons (Smith). F. Capitate-spatulate, S5, M. (Xanthosarus) fortis Cresson.
Figure 4 in Morphological phylogeny of Megachilini and the evolution of leaf-cutter behavior in bees (Hymenoptera: Megachilidae)
Figure 4. Some female morphological features used in the phylogenetic analysis. A, B. Lateral view of axilla. C. Dorsal view of mesoscutellum and metanotum. D, E. Outer view of apex of mesotibia. F–I. Pretarsal claws. Megachile (Melanosarus) xylocopoides Smith (A); M. (Stenomegachile) dolichosoma Benoist (B, C); M. (Chelostomoides) rugifrons (Smith) (D); M. (Megachiloides) pascoensis Mitchell (E); Dioxys productus (Cresson) (F); M. (Acentron) albitarsis Cresson (G); M. (Hackeriapis) ferox Smith (H); M. (Schizomegachile) monstrosa Smith (I).
Figure 1 in Morphological phylogeny of Megachilini and the evolution of leaf-cutter behavior in bees (Hymenoptera: Megachilidae)
Figure 1. Species richness of currently recognized genera in the bee tribe Megachilini. A. Dorsal habitus of a female of Coelioxys sp. B. Lateral habitus of a female of Noteriades spinosus Griswold & Gonzalez. C. Male of Megachile (Zonomegachile) kalina Gonzalez, Griswold, & Engel on top of a brood cell built with leaf pieces. D. Facial habitus of leaf-cutter M. (Eutricharaea) minutissima Radoszkowski (left) and dauber bee M. (Callomegachile) pluto (Smith) (right). E. Outer surface of the female mandible of M. (Leptorachis) laeta Smith, a leaf-cutter bee, showing interdental lamina in pink. F. Dorsal habitus of M. (Rhyssomegachile) kartaboensis Mitchell. G. Dorsal views of M. (E.) minutissima (upper left) and M. (C.) pluto (right). Photographs are not at the same scale, except for the large and small species compared in figures D and G.
Figure 2. Leaf excisions and a in Morphological phylogeny of Megachilini and the evolution of leaf-cutter behavior in bees (Hymenoptera: Megachilidae)
Figure 2. Leaf excisions and a sampling of the morphological diversity among the female mandible of leaf-cutter bees. A. Leaves of Rosa sp. (Rosaceae) from Lesvos, Greece. B. Fossil leaf cut (Fabaceae) from Eckfeld Maar, Germany (~43 Ma). C–J. Outer view of the mandible showing interdental laminae in green (odontogenic) and pink (ctenogenic). C. Megachile (Chrysosarus) parsonsiae Schrottky. D. M. (Rhyssomegachile) simillima Smith. E. M. (Pseudocentron) pruina Smith. F. M. (Zonomegachile) sp. G. M. (Moureapis) maculata Smith. H. M. (Melanosarus) xylocopoides Smith. I. M. (Acentron) albitarsis Cresson. J. M. (Leptorachis) petulans Cresson. Abbreviations: Mt = mandibular tooth.
Figure 13 in Morphological phylogeny of Megachilini and the evolution of leaf-cutter behavior in bees (Hymenoptera: Megachilidae)
Figure 13. Female mandible of leaf-cutter ants and extinct Baltic amber megachilids. A–C. Right mandible of leaf-cutter ant (Formicidae: Attini: Atta sp.) in frontal, lateral, and inner views, respectively. Arrow points to the lower margin. D–G. Synchrotron-radiation µCT scan of Glyptapis sp. (Glyptapini) from Eocene Baltic amber; facial view of the head and right mandible in outer, superior, and inner views, respectively [note that the scan resolution could not resolve the finest setae, such as those of the compound eyes which are present in this specimen as in all species of Glyptapis Cockerell (Engel, 2001)].
Figure 3 in Morphological phylogeny of Megachilini and the evolution of leaf-cutter behavior in bees (Hymenoptera: Megachilidae)
Figure 3. Female mandible of Megachile Latreille s.l. in outer (A, E, G), frontal (D), and inner views (B, C, F, H). A. Megachile (Callomegachile) pluto Smith. B. M. (Callomegachile) sp. C–E. M. (Chelostomoda) spissula Cockerell. F. M. (Rhyssomegachile) simillima Smith. G. M. (Creightonella) frontalis (Fabricius). H. M. (Pseudocentron) pruina Smith. Interdental laminae highlighted in green (odontogenic) and pink (ctenogenic). Abbreviations: CR = corono-radicular ridge; AP = adductor apical ridge.
Figure 5 in Morphological phylogeny of Megachilini and the evolution of leaf-cutter behavior in bees (Hymenoptera: Megachilidae)
Figure 5. Some male morphological features used in the phylogenetic analysis. A–C. Ventral projection of mandible. D–F. Dorsal (left half) and ventral (right half) views of sixth tergum. G–I. Dorsal view of seventh tergum. J. Ventral view of sixth sternum. K–M. Ventral view of eighth sternum. N–P. Dorsal view of genital capsule. Q, R. Profile view of genital capsule. S. Apex of penis valves. Taxa: Megachile (Acentron) albitarsis Cresson (A, L); M. (Callomegachile) biseta Vachal (B); M. (Maximegachile) maxillosa Guérin-Méneville (C); M. (Argyropile) longuisetosa Gonzalez & Griswold (D, G); M. (Grosapis) cockerelli (E, H, R); M. (Creightonella) cognata Smith (F, I); M. (Zonomegachile) moderata Smith (J, K); M. (Largella) donbakeri Gonzalez & Engel (M); M. (Austromegachile) montezuma Cresson (N); M. (M.) centuncularis (Linnaeus) (O); M. (Moureapis) maculata Smith (P); M. (Chalicodoma) parietina (Geoffroy) (Q); M. (Chalicodoma) sicula (Rossi) (S).
Linked collectors and determiners for: Applying n-dimensional hypervolumes for species delimitation: unexpected molecular, morphological, and ecological diversity in the Leaf-Toed Gecko Phyllodactylus reissii Peters, 1862 (Squamata: Phyllodactylidae) from northern Peru.
Natural history specimen data linked to collectors and determiners held within, "Applying n-dimensional hypervolumes for species delimitation: unexpected molecular, morphological, and ecological diversity in the Leaf-Toed Gecko Phyllodactylus reissii Peters, 1862 (Squamata: Phyllodactylidae) from northern Peru". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/4de18441-9329-474b-a4a0-dea3aaf1e1ee">https://bionomia.net/dataset/4de18441-9329-474b-a4a0-dea3aaf1e1ee</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/4de18441-9329-474b-a4a0-dea3aaf1e1ee">https://gbif.org/dataset/4de18441-9329-474b-a4a0-dea3aaf1e1ee</a>. Formatted as a Frictionless Data package.
Figure 9. Various generic leaf cushion morphologies. L in A "Mystery Fossil" is Evidence for Massive Devonian Trees in Australia
Figure 9. Various generic leaf cushion morphologies. L, ligule scar; p, parichnos scar; VB, vascular bundle scar. (a) Lepidodendron sp. from Scotland (AM F.17751); (b) Lepidodendron (after Taylor & Taylor, 1993); (c) Lepidodendron aculeatum before secondary expansion (after Thomas, 1970); (d) L. aculeatum after secondary expansion (after Thomas, 1970); (e) Lepidophloios (after Taylor & Taylor, 1993); (f) Leptophloem australe; and (g) Sigillaria.
Data from: Geographical variation of Artemisia leaf morphology along a large environmental gradient in China
<p>We collected 60 species of <em>Artemisia</em> from 81 sampling sites in 15 provinces in China from the end of July to August 2018. At each site, we recorded latitude and longitude. Then we identified all<em> Artemisia</em> species and randomly sampled 4 plants for each species. A total of 1,041 plants were sampled. In the laboratory, 10 leaves in the middle of each plant were selected and detached. Because light might have effect on leaf morphology, we only used sun exposed leaves. The leaves were soaked in distilled water for 24 h to fully restore their shapes. After blotted-dried, leaves were place as petiole to the left and tip to the right, and an Epson V370 (Seiko Epson Corp., Nagano, Japan) was used to scan the leaves at a resolution of 600 DPI. </p> <p>We set 40 landmarks along the blade edge on each leaf. The first point was set at the petiole and the 21st point at the tip, and these two points were defined as landmarks. The remaining points were evenly distributed at the blade edge and defined as semilandmarks. Landmarks were saved in tps format using Geomorph package.</p>
Leaf litter quality induces morphological and developmental changes in larval amphibians.
Aquatic consumers exhibit many types of inducible phenotypic responses to variation in resource quantity and quality. Leaf litter constitutes a primary resource in freshwater systems and variation in litter quality can alter the growth and development of aquatic consumers. It is therefore reasonable to hypothesize that variation in litter quality might also induce phenotypic changes in consumers. To test this hypothesis, we exposed two densities of wood frog (Lithobates sylvaticus [Rana sylvatica]) tadpoles to six chemically distinct species of leaf litter from temperate broadleaf and coniferous trees. After several weeks, we quantified development rate, growth rate, intestinal length, size of the oral disc, and five external dimensions of the tadpoles. In addition to substantial changes in growth and development rates, we found striking changes in all morphological responses among different leaf litter environments, including up to 14% longer intestines, 11% deeper tails, and 6% deeper tail muscles. In addition, we found strong relationships of total nitrogen content with all morphological features except growth rate. Our results indicate that differences in resource quality can induce phenotypic changes that are as large as or larger than changes induced by resource quantity. Our study also has substantial implications for the future of aquatic consumers living in forested wetlands given that these forests are currently experiencing widespread changes in tree composition.
Figure 5 in Morphology of the adult and immatures of a striking new species of leaf-mining Brachys Dejean from Brazil (Buprestidae, Agrilinae)
Figure 5. Brachys cleidecostae sp. nov. Pupa, habitus: (A) dorsal; (B) ventral. Scale bar: = 0,5 mm.
Figure 1 in Morphology of the adult and immatures of a striking new species of leaf-mining Brachys Dejean from Brazil (Buprestidae, Agrilinae)
Figure 1. Brachys cleidecostae sp. nov. Holotype (male), habitus: (A) dorsal; (B) ventral. Scale bar: = 0.5 mm.
Figure 4 in Morphology of the adult and immatures of a striking new species of leaf-mining Brachys Dejean from Brazil (Buprestidae, Agrilinae)
Figure 4. Brachys cleidecostae sp. nov. Mature larva: (A-B) Head (dorsal, ventral); (C) Antenna (dorsal); (D) Labrum, clypeum and antenna; (E) Epipharynx; (F-G) Mandible (dorsal, ventral); (H) Labium and maxillae; (I) Hypopharynx; (J) Thoracic spiracle. Scale bars: (A-C) = 1 mm; (D-J) = 0.5 mm.
Figure 3 in Morphology of the adult and immatures of a striking new species of leaf-mining Brachys Dejean from Brazil (Buprestidae, Agrilinae)
Figure 3. Brachys cleidecostae sp. nov. Mature larva, habitus: (A) dorsal; (B) ventral. Scale bar: = 1 mm.
Figure 6 in Morphology of the adult and immatures of a striking new species of leaf-mining Brachys Dejean from Brazil (Buprestidae, Agrilinae)
Figure 6. Brachys cleidecostae sp. nov. Mine and mature larva: (A) Leaf with two mines after opening and removal of larva and pupa; (B) Leaf with mine with pupa inside; (C) Mature larva dorsal (head and thorax).
Broad- and small-scale environmental gradients drive variation in chemical, but not morphological, leaf traits of vascular epiphytes
<p>Variation in leaf functional traits along environmental gradients can reveal how vascular epiphytes respond to broad- and small-scale environmental gradients. Along elevational gradients, both temperature and precipitation likely play an important role as drivers of leaf trait variation, but these traits may also respond to small-scale changes in light, temperature, and humidity along the vertical environmental gradient within forest canopies. However, the relative importance of broad- and small-scale environmental gradients as drivers of variation in leaf functional traits of vascular epiphytes is poorly understood. Here, we examined variation in morphological and chemical leaf traits of 102 vascular epiphyte species spanning two environmental gradients along Cofre de Perote mountain in Mexico: i) a broad-scale environmental gradient approximated by elevation as well as by species' lower and upper elevational limits, and ii) small-scale environmental gradients using the relative height of attachment of an epiphyte on a host tree as a proxy for variation in environmental conditions within the forest canopy. We also assessed whether variation in morphological and chemical leaf traits along these gradients were consistent across photosynthetic pathways (CAM and C<sub>3</sub>). Broad- and small-scale environmental gradients explained more variation in chemical traits (marginal R2: 11-89%) than in morphological traits (marginal R2: 2-31%). For example, leaf carbon isotope signatures (δ<sup>13</sup>C), which reflects water-use efficiency, varied systematically across both environmental gradients, suggesting a decrease in water-use efficiency with increasing lower and upper elevational limits and an increase in water-use efficiency with relative height of attachment. The influence of lower and upper elevational limits on trait variation differed between photosynthetic pathways, except for leaf dry matter content and leaf nitrogen-to-phosphorus ratio. Contrary to our expectations, broad- and small-scale environmental gradients explained minimal variation in morphological leaf traits, suggesting that environmental conditions do not constrain morphological leaf trait values of vascular epiphytes. Our findings suggest that assessing multiple drivers of leaf trait variation among photosynthetic pathways is key for disentangling the mechanisms underlying responses of vascular epiphytes to environmental conditions.</p>
Data from: Leaf morphological traits show greater responses to changes in climate than leaf physiological traits and gas exchange variables
<p>Adaptation to changing conditions is one of the strategies plants use to survive climate change. Here, we ask whether plants' leaf morphological and physiological traits/gas exchange variables have changed in response to recent, anthropogenic climate change. We grew seedlings from resurrected historic seeds from <em>ex-situ </em>seed banks and paired modern seeds in a common-garden experiment. Species pairs were collected from regions that had undergone differing levels of climate change using an emerging framework – Climate Contrast Resurrection Ecology, allowing us to hypothesise that regions with greater changes in climate (including temperature, precipitation, climate variability and climatic extremes) there would be greater trait responses in leaf morphology and physiology over time. Our found that in regions where there were greater changes in climate, there were greater changes in average leaf area, leaf margin complexity, leaf thickness and leaf intrinsic water use efficiency. Changes in leaf roundness, photosynthetic rate, stomatal density and the leaf economic strategy of our species were not correlated with changes in the climate. Our results show that leaves do have the ability to respond to changes in climate, however, there are greater inherited responses in morphological leaf traits than in physiological traits/variables, and greater responses to extreme measures of climate than gradual changes in climatic means. It is vital for accurate predictions of species' responses to impending climate change to ensure that future climate change ecology studies utilise knowledge about the difference in both leaf trait and gas exchange responses, and the climate variables that they respond to.</p>
ScienceDex guides
Understand access before you commit
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.