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9,680 results for “Leaf”
Reproductive hormones mediate changes in the gut microbiome during pregnancy and lactation in Phayre's leaf monkeys
Studies in multiple host species have shown that gut microbial diversity and composition change during pregnancy and lactation. However, the specific mechanisms underlying these shifts are not well understood. Here, we use longitudinal data from wild Phayre's leaf monkeys to test the hypothesis that fluctuations in reproductive hormone concentrations contribute to gut microbial shifts during pregnancy. We described the microbial taxonomic composition of 91 fecal samples from 15 females (n=16 cycling, n=36 pregnant, n=39 lactating) using 16S rRNA gene amplicon sequencing and assessed whether the resulting data were better explained by overall reproductive stage or by fecal estrogen (fE) and progesterone (fP) concentrations. Our results indicate that while overall reproductive stage affected gut microbiome composition, the observed patterns were driven by reproductive hormones. Females had lower gut microbial diversity during pregnancy and fP concentration was negatively correlated with diversity. Additionally, fP concentration predicted both unweighted and weighted UniFrac distances, while reproductive state only predicted unweighted UniFrac distances. Seasonality (rainfall and periods of phytoprogestin consumption) additionally influenced gut microbial diversity and composition. Our results indicate that reproductive hormones, specifically progestagens, contribute to the shifts in the gut microbiome during pregnancy and lactation.
Figure 3 in Intense inhabitation and relaxed host-leaf preference of aquatic chironomid leaf-miners in headwater streams in Asian lucidophyllous forests
Figure 3. Frequency distributions of unmined (open) and mined (solid) leaves among representative plant species. (Cs, Castanopsis sieboldii; Qg, Quercus glauca; Qm, Quercus miyagii; Mj, Machilus japonica; Mt, Machilus thunbergii; Mr, Myrica rubra; Ot, others.)
Figure 2 in Intense inhabitation and relaxed host-leaf preference of aquatic chironomid leaf-miners in headwater streams in Asian lucidophyllous forests
Figure 2. Habitats and leaf-mining habits of Stenochironomus okialbus. (A–B) headwater streams at S4 and S9; (C) submerged litter at S9; (D–F) leaf-mines; (G) a larva undulating in a mine; (H) a pupa; (I) head of a mining larva; (J–K) a female and a male adult midge. Plant species of the leaves: C, D, G, I: Castanopsis sieboldii; E, H: Dendropanax trifidus; E: Myrica rubra.
Figure 1 in Conservation in a changing landscape: habitat occupancy of the critically endangered Tennent's leaf-nosed lizard (Ceratophora tennentii) in Sri Lanka
Figure 1. Location of Knuckles forest reserve within Kandy and Matale Districts (left) and the four study sites [two at Riverston (1 and 2), Hunasgiriya (3) and Deanston (4)] within the reserve (right).
Figure 3 in Conservation in a changing landscape: habitat occupancy of the critically endangered Tennent's leaf-nosed lizard (Ceratophora tennentii) in Sri Lanka
Figure 3. Comparison of climatic and structural parameters among the four habitat types during the dry (dashed line) and wet (solid line) seasons. Data from both locations with lizards and random locations are considered in combination. (C = Cardamom plantations, M = Mixed cardamom forests, N = Natural forests, P = Pine plantations.)
Figure 2 in Conservation in a changing landscape: habitat occupancy of the critically endangered Tennent's leaf-nosed lizard (Ceratophora tennentii) in Sri Lanka
Figure 2. Mean number of sightings of Ceratophora tennentii within three habitat types at Knuckles Range, Sri Lanka.
Figure 10 in A checklist of the non-leaf-cutting fungus-growing ants (Hymenoptera, Formicidae) from Colombia, with new biogeographic records
Figure 10. Paratrachymyrmex species encountered in Colombia. A, B. Paratrachymyrmex diversus, CASENT0901693. C, D. Paratrachymyrmex irmgardae, CASENT0909392. E, F. Paratrachymyrmex phaleratus, D. Mera-Rodríguez. Photographs taken by W. Erichson and obtained from the Antweb database (http://www.antweb.org).
Figure 9 in A checklist of the non-leaf-cutting fungus-growing ants (Hymenoptera, Formicidae) from Colombia, with new biogeographic records
Figure 9. Mycetomoellerius and Paratrachymyrmex species encountered in Colombia. A, B. Mycetomoellerius jamaicensis, CASENT0919971/ M. Esposito. C, D. Mycetomoellerius urichii, CASENT0904990/ W. Ericson. E, F. Paratrachymyrmex bugnioni, CASENT0919968/ M. Esposito. G, H. Paratrachymyrmex cornetzi, CASENT0909389/ W. Ericson. Photographs obtained from the Antweb database (http://www.antweb.org).
Figure 3 in A checklist of the non-leaf-cutting fungus-growing ants (Hymenoptera, Formicidae) from Colombia, with new biogeographic records
Figure 3. Apterostigma species encountered in Colombia. A, B. Apterostigma chocoense, CASENT0922037. C, D. Apterostigma collare, CASENT0922041. E, F. Apterostigmadentigerum, CASENT0922039. G, H. Apterostigma goniodes, CASENT0922040. Photographs taken by M. Esposito obtained from the Antweb database (http://www.antweb.org).
Figure 5 in A checklist of the non-leaf-cutting fungus-growing ants (Hymenoptera, Formicidae) from Colombia, with new biogeographic records
Figure 5. Apterostigma and Cyphomyrmex species encountered in Colombia. A, B. Apterostigma reburrum, CASENT0901686/ R. Perry. C, D. Apterostigma robustum, CASENT0904977/ Z. Lieberman. E, F. Apterostigma pilosum complex, CASENT0603533/ A. Nobile. G, H. Cyphomyrmex cornutus, CASENT0923103/ W. Lee. Photographs obtained from the Antweb database (http://www.antweb.org).
Close range hyperspectral camera dataset with high temporal resolution of strawberry with eco-physiological data of one leaf
<p>This high temporal resolution dataset of a strawberry plant was captured in two experiments, each lasting 100h. On leaf was inserted into a leaf chamber of the LI-6400XT gas exchange system, capturing information on transpiration, photosynthesis and stomatal conductance. Environmental characteristics are also captured at canopy height. These experiments were conducted in a growth chamber at ILVO (Melle, Belgium) and only covered conditions that did not result in stress in the plant. As such, this dataset attempts to capture subtle dynamic variation in the plant.</p>
Systematics of a Neotropical clade of dead-leaf-foraging antwrens (Aves: Thamnophilidae; Epinecrophylla)
<p>The stipple-throated antwrens of the genus <i>Epinecrophylla</i> (Aves: Thamnophilidae) are represented by eight species primarily found in the lowlands of the Amazon Basin and the Guiana Shield. The genus has a long and convoluted taxonomic history, with many attempts made to address the taxonomy and systematics of the group. Here we employ massively parallel sequencing of thousands of ultraconserved elements (UCEs) to provide both the most comprehensive subspecies-level phylogeny of <i>Epinecrophylla</i> antwrens and the first population-level genetic analyses for most species in the genus. Most of our results are robust to a diversity of phylogenetic and population genetic methods, but we show that even with thousands of loci we are unable to fully resolve the relationships between some western Amazonian species in the <i>haematonota </i>group. We uncovered phylogenetic relationships between taxa and patterns of population structure that are discordant with both morphology and current taxonomy. For example, we found deep genetic breaks between taxa in the <i>ornata </i>group that are currently regarded as species, and in the <i>haematonota </i>and <i>leucophthalma</i> groups we found paraphyly at the species and subspecies levels, respectively. As has been found in many Amazonian taxa, our phylogenetic results show that the major river systems of the Amazon Basin appear to have an effect on the genetic structure and range limits within <i>Epinecrophylla</i>. Our population genetics analyses showed extensive admixture between some taxa despite their deep genetic divergence. We present a revised taxonomy for the group and suggest areas for further study.</p>
Quantification of plant morphology and leaf thickness with optical coherence tomography
<p>The uploaded scripts and data are used to obtain the figures 2, 4, 5, 6 and 7 in the publication. </p> <p>The code has been run with Python 3.7 in Spyder (Anaconda).</p> <p>There are three scripts, each needing specific datasets to run the code.</p> <p>1. The core is the segmentation of the leaf surface and this is subsequently used to calculate leaf thickness and obtain en-face images.</p> <p><a href="https://zenodo.org/api/files/89412f06-4c84-4516-9e7d-113796b42834/3D_segmentation_thickness_enface.py">3D_segmentation_thickness_enface.py</a>: This file loads the 3D processed OCT data, does the leaf surface segmentation and calculates the en face images. It needs the files processed_3Ddata.npy and videoim.npy</p> <p><a href="https://zenodo.org/api/files/89412f06-4c84-4516-9e7d-113796b42834/processed_3Ddata.npy">processed_3Ddata.npy</a>: This file contains the processed 3D OCT dataset (linear amplitude data), with respectively dimensions z,x,y. The data is saved as uint16 to save memory, and should be converted to double before further processing, as done in the script.</p> <p><a href="https://zenodo.org/api/files/89412f06-4c84-4516-9e7d-113796b42834/videoim.npy">videoim.npy</a>: This file contains the RGB image of Fig. 6(a) as image matrix.</p> <p>2. The non-infiltrated and infiltrated image (Figure 4)</p> <p><a href="https://zenodo.org/api/files/89412f06-4c84-4516-9e7d-113796b42834/2D_fig4.py">2D_fig4.py</a>: This script produces Figure 4 of the paper and also shows the two RGB images that indicate the scan location on the leaf. It needs the files OCTdata_figure4.npy (containing OCT data) and videoimages_figure4.npy</p> <p><a href="https://zenodo.org/api/files/89412f06-4c84-4516-9e7d-113796b42834/OCTdata_figure4.npy">OCTdata_figure4.npy</a>: This file contains the processed 2D OCT dataset (linear amplitude data), with respectively dimensions (a/b),z,x. The data is saved as uint16 to save memory, and should be converted to double before further processing, as done in the script.</p> <p><a href="https://zenodo.org/api/files/89412f06-4c84-4516-9e7d-113796b42834/videoimages_figure4.npy">videoimages_figure4.npy</a> This file contains the two RGB images that show the scan area of the data in Figure 4.</p> <p>3. The calculation of the refractive index and making Figure 5</p> <p><a href="https://zenodo.org/api/files/89412f06-4c84-4516-9e7d-113796b42834/refractiveindex_fig5.py">refractiveindex_fig5.py</a>: this script segments the cuvette wall and leaf surface on 2D images and calculates the refractive index by evaluating equation 1 of the publication. It needs the file images_refractiveindex.npy</p> <p><a href="https://zenodo.org/api/files/89412f06-4c84-4516-9e7d-113796b42834/images_refractiveindex.npy">images_refractiveindex.npy</a>: This file contains the processed 2D OCT dataset (linear amplitude data), with respectively dimensions (leaf/empty),z,x. The data is saved as uint16 to save memory, and should be converted to double before further processing, as done in the script.</p>
Figure 3 in Mites associated with egg masses of the viburnum leaf beetle Pyrrhalta viburni (Paykull) on Viburnum tinus L.
Figure 3 Timing of mite infestation experiment 2017. (a) abundance and (b) diversity of mites found on V. tinus twigs depending on the number of intactP. viburni egg masses present on the twigs (mean ± SE). Data are pooled in three categories: twigs with 0 to 4 intact egg masses (n = 81), twigs with 5 to 9 intact egg masses (n = 13), and twigs with ≥ 10 intact egg masses (n = 8); (c) abundance of mites found onV. tinus twigs depending on the number of damagedP. viburni egg masses present on the twigs. Data are pooled in three categories: twigs with 0 to 4 damaged egg masses (n = 62), twigs with 5 to 9 damaged egg masses (n = 24), and twigs with ≥ 10 damaged egg masses (n = 16).
Figure 2 Observational study 2016 in Mites associated with egg masses of the viburnum leaf beetle Pyrrhalta viburni (Paykull) on Viburnum tinus L.
Figure 2 Observational study 2016. (a) abundance and (b) diversity of mites foundV. tinus on twigs depending onP. viburni infestation: twigs
Figure 1 in Mites associated with egg masses of the viburnum leaf beetle Pyrrhalta viburni (Paykull) on Viburnum tinus L.
Figure 1 Pictures of (a) four intact Pyrrhalta viburni egg masses along a Viburnum tinus twig, with the protective "egg cap" visible; (b) one damagedP. viburni egg mass following plant wounding response, with the egg cap removed and the egg mass cavity partially covered by wounding tissue; (c) twoP. viburni eggs; (d) Detritivorous miteTrichoribates trimaculatus nymph; (e) T. trimaculatus adult; (f) predatory mite Anystis baccarum. Photo credit: (a)(b) Gaylord Desurmont; (c)(d)(e)(f) Elven Kerdellant.
FIGURE 2 in Description of a new species of Ovaticoccus Kloet (Hemiptera: Coccoidea, Eriococcidae) from Belize, with remarkably large hind coxae and causing leafcurl galls
FIGURE 2. Ovaticoccus amplicoxae sp. nov., unmounted adult female in alcohol, with large hind coxa prominent.
Leaf growth response to mild drought: natural variation sheds light on trait architecture
<p>Plant growth and crop yield are negatively affected by a reduction in water availability. However, a clear understanding of how growth is regulated under non-lethal drought conditions is lacking. Recent advances in genomics, phenomics and transcriptomics allow in-depth analysis of natural variation. In this study, we conducted a detailed screening of leaf growth responses to mild drought in a worldwide collection of <em>Arabidopsis thaliana</em> accessions. </p> <p>The raw phenotyping can be found in:<br> - cellularData.txt -> mature (23 days after stratification; DAS) leaf epidermis (third leaf) analysed for cell area, cell number, pavement cell area, pavement cell number, stomatal index and leaf area of the analysed leaf.</p> <p>- leaf3AreaMaturity.txt -> area of the third leaf at maturity (23DAs) in mm<sup>2.</sup></p> <p>- leaf3AreaProliferation.txt -> area of the third leaf at proliferation (last day of full cell proliferation; 8-10 DAS) in mm<sup>2</sup>.</p> <p>- rosetteArea Maturity.txt -> projected rosette area at maturity (22DAS)</p> <p>The phenotyping results have been normalised for batch effects ('experiment' in raw data)</p> <p>- allPhenotypesNormalised.txt -> contains the normalised data for all the measured phenotypes</p> <p>All datafiles indicate the accession name ('Accession'), the unique identifier for each accessions ('Ecotype_ID') as used in the 1001genomes project (www.1001genomes.org) and the treatment ('C' indicate well-watered plants, 'S' the mild-drought treated plants).</p> <p>These results and methodological results are described in Clauw et al. (2016, The Plant Cell).</p> <p>Citation:</p> <p><strong>Clauw, Pieter, Frederik Coppens, Arthur Korte, Dorota Herman, Bram Slabbinck, Stijn Dhondt, Twiggy Van Daele, et al. 2016. “Leaf Growth Response to Mild Drought: Natural Variation in Arabidopsis Sheds Light on Trait Architecture.” The Plant Cell, October. doi:10.1105/tpc.16.00483.</strong></p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p>
FIGURES 209 – 212 in Leaf-mining Nepticulidae (Lepidoptera) from record high altitudes: documenting an entire new fauna in the Andean páramo and puna
FIGURES 209 – 212. Male genitalia of Stigmella lobata Remeikis & Stonis, sp. nov. 209, holotype, genitalia slide no. RA 553, capsule with phallus removed; 210, same, uncus and gnathos; 211, paratype, genitalia slide no. RA 559, capsule with phallus removed; 212, same, phallus (ZMUC).
FIGURES 196 – 199 in Leaf-mining Nepticulidae (Lepidoptera) from record high altitudes: documenting an entire new fauna in the Andean páramo and puna
FIGURES 196 – 199. Male genitalia of Stigmella kristenseni Diškus & Stonis, sp. nov., holotype, genitalia slide no. AD 670. 196, valvae; 197, uncus, gnathos and transtilla; 198, basal part of valvae and ventral plate of vinculum; 199, apex of phallus (ZMUC).
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