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3,682 results for “ROOTS”

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edi48/100

Biogeography of root fungi in grasslands

Aim: Roots and rhizospheres host diverse microbial communities that can influence the fitness, phenotypes, and environmental tolerances of host plants. Documenting the biogeography of microbiomes can detect the potential for a changing environment to disrupt host-microbe interactions, particularly in cases where microbes, such as root-associated Ascomycota, buffer hosts against abiotic stressors. We evaluated whether root-associated fungi had poleward declines in diversity as occur for many animals and plants, tested whether microbial communities shifted near host plant range edges, and determined the relative importance of latitude, climate, edaphic factors, and host plant traits as predictors of fungal community structure. Location: North American plains grasslands Taxon: Foundation North American grass species ⎯ Andropogon gerardii, Bouteloua eriopoda, B. gracilis, B. dactyloides, and Schizachyrium scoparium and their root-associated fungi Methods: At each of 24 sites representing three replicate latitudinal gradients spanning 17° latitude, we collected roots from 12 individual plants per species along five transects spaced 10 m apart (40 m × 40 m grid). We used next-generation sequencing of the fungal ITS2 region, direct fungal culturing from roots, and microscopy to survey fungi associated with grass roots. Results: Root-associated fungi did not follow the poleward declines in diversity documented for many animals and plants. Instead, host plant identity had the largest influence on fungal community structure. Edaphic factors outranked climate or host plant traits as correlates of fungal community structure; however, the relative importance of these environmental predictors differed among plant species. As sampling approached host species range edges, fungal composition converged among individual plants of each grass species. Main conclusions: Environmental predictors of root-associated fungi depended strongly on host plant species identity. Biogeographic patte

openCC0Sep 2021View details →
edi48/100

Rapid root to leaf uptake of inorganic and amino acid nitrogen in three dryland plant species.

Our aim was to quantify inorganic and organic nitrogen (N) uptake and compare short-term nutrient acquisition patterns among three dryland plant species: Bouteloua eriopoda, Achnatherum hymenoides, and Gutierrezia sarothrae collected from a mixed grassland community in the Northern Chihuahuan Desert to better understand how asynchronous resource availability may influence biotic interactions and nutrient retention in these ecosystems. We collected living plants from two locations within the Sevilleta National Wildlife Refuge and transplanted them into pots maintained in the greenhouse with supplemental light and water for two months. We then conducted a greenhouse experiment using these species to compare nutrient uptake of 15N-labeled ammonium (NH4+), nitrate (NO3-), and glutamate (an amino acid) over 12 to 48 hours. Our study examined three main questions: (1) How rapidly do these dryland plants take up available soil N?, (2) Does leaf uptake differ among inorganic and amino acid N forms?, and (3) Do plant species differ in the speed or form of short-term N uptake?. In the greenhouse, we applied one of three isotopic 15N tracers directly to plant roots and quantified N uptake and recovery in leaves after 12, 24, and 48 hours. We found that plants took up inorganic and amino acid N to leaves as rapidly as 12 h following application, and N uptake more than doubled between 24 and 48 h. Inorganic N uptake was 3-4x higher than organic N uptake in all three species, and plants took up ammonium and nitrate at 2-3x faster rates than glutamate. On average, B. eriopoda had higher inorganic N recovery and uptake speeds, while G. sarothrae had the highest organic N uptake over time. A. hymenoides root to leaf uptake was ~50% lower than the other two species after 48 h. Plants showed similar patterns of short-term foliar uptake and recovery indicating a lack of niche partitioning by N form among the three dryland species measured. Our results suggest that soil inorganic N, par

openCC0Aug 2024View details →
edi48/100

Root distributions of coastal red cedars on Catlett Island, VA, 2018

This dataset contains the fall direction and root distributions of windthrown Juniperus virginiana on the Catlett Islands, VA. The distribution, number, length, and circumference of exposed roots are reported here. Additionally the aspect (direction of steepest slope) and fall direction were measured. Catlett Islands are a series of ridged islands on the York River, VA. See also: Messerschmidt, Tyler C.; Langston, Amy K.; and Kirwan, Matthew L., Asymmetric root distributions reveal press-pulse responses in retreating coastal forests (2021). Ecology.

openCustomMay 2022View details →
zenodo44/100

ds-uct-002: Root Canal Strain: X-Ray micro-CT of four teeth before and after root canal procedure.

<p><strong>Summary</strong>:<br> .X-Ray micro-computed tomography (micro-CT) of four teeth before (TomoB) and after (TomoA) simulation of root canal treatment and retreatment procedures instrumented with strain-gauge, including reconstructions, for two different resolutions (TomoB and TomoA with voxel sizes of 20.0 &mu;m and 10.5 &mu;m, respectively).<br> .The 3D image was generated with an X-Ray micro-CT Scanner version Xradia Versa 510 from Zeiss performed by A Pereira at the UFF micro-CT Facility.<br> .For use of these data, please remember to cite the DOI of the Zenodo repository and relevant papers.</p> <p><strong>Details</strong>:<br> .Tomo1B/Tomo2B/Tomo3B/Tomo4B (1024) - Voxel size: 20.0 &mu;m; Sample-source: 45.0 mm; Sample-detector: 110 mm; Optical magnification: 0.4X; Filter: LE#1; Beam energy: 60 kV; Power: 5 W; Exposure time: 2.0 sec; Projections: 1600.<br> .Tomo1A/Tomo2A/Tomo3A/Tomo4A (2048) - Voxel size: 10.5 &mu;m; Sample-source: 48.2 mm; Sample-detector: 110 mm; Optical magnification: 0.4X; Filter: LE#2; Beam energy: 60 kV; Power: 5 W; Exposure time: 7.0 sec; Projections: 1600.</p> <p><strong>Contents</strong>:<br> ._info_ds-uct-002.txt<br> .ds-uct-002_root_canal_strain_tomo1b_20um_8bits.zip<br> .ds-uct-002_root_canal_strain_tomo2b_20um_8bits.zip<br> .ds-uct-002_root_canal_strain_tomo3b_20um_8bits.zip<br> .ds-uct-002_root_canal_strain_tomo4b_20um_8bits.zip<br> .ds-uct-002_root_canal_strain_tomo1a_10um_8bits.zip<br> .ds-uct-002_root_canal_strain_tomo2a_10um_8bits.zip<br> .ds-uct-002_root_canal_strain_tomo3a_10um_8bits.zip<br> .ds-uct-002_root_canal_strain_tomo4a_10um_8bits.zip<br> .PB_PARECER_CONSUBSTANCIADO_CEP_2650528.pdf</p>

opencc-by-4.0Jun 2020View details →
zenodo44/100

Modelled root zone storage capacities Hubbard Brook WS5

Modelled root zone storage capacities for the Hubbard Brook Experimental Forest - Watershed 5. Root zone storage capacities were derived based on a simple water balance based model (Nijzink et al. 2016). Long term equilibrium root zone storage capacities yearly root zone storage capacities were determined.

opencc-by-4.0Jun 2017View details →
zenodo44/100

Modelled root zone storage capacities HJ Andrews

Modelled root zone storage capacities for the HJ Andrews Experimental Forest - Watershed 1. Root zone storage capacities were derived based on a simple water balance based model (Nijzink et al. 2016). Long term equilibrium root zone storage capacities yearly root zone storage capacities were determined.

opencc-by-4.0Jun 2017View details →
zenodo44/100

Modelled root zone storage capacities Hubbard Brook

Modelled root zone storage capacities for the Hubbard Brook Forest - Watershed 2. Root zone storage capacities were derived based on a simple water balance based model (Nijzink et al. 2016). Long term equilibrium root zone storage capacities yearly root zone storage capacities were determined.

opencc-by-4.0Jun 2017View details →
zenodo44/100

Super-resolution analysis of the origins of the elementary events of ER calcium release in dorsal root ganglion neurons

<p>This is the data supplement for the paper entitled, "Super-resolution analysis of the origins of the elementary events of ER calcium release in dorsal root ganglion neurons"<br><br>There are two principal subdirectories within the enclosed zip file:</p><ol><li>10xEExM_data: The directory contains two exemplar datasets each of 10x Enhanced expansion microscopy images of IP3R1 and RyR immunolabelling in DRG soma, at the sub-plasmalemmal regions.<br>&nbsp;</li><li>Correlative Analysis: The directory contains two sub-directories of worked examples of data and correlative analysis of calcium sparks and dSTORM images of RyR and IP3R. The instructions for the code, run in IDL, are included in the Readme.txt enclosed within.</li></ol>

opencc-by-4.0Nov 2023View details →
zenodo44/100

Root phytohormone levels of mangrove seedlings grown in soils of low and high bulk density

<p>These data contain information on root traits and concentrations of multiple hormones in root tissue of two mangrove species grown under low and high soil bulk density conditions. Inhibitors were used to assess the role of the phytohormone ethylene.</p> <h2>Description of the data and file structure</h2> <p>The root trait file contains total root length (cm), mean root length (cm), root dry weight (g), and root number data for two mangrove species (Avicennia marina, Rhizophora stylosa) grown under two different soil bulk densities: 0.2 and 1.0 g cm^-3. Treatment refers to the application of ethylene inhibitors (CoCl2: cobalt chloride, AIB: aminoisobutyric acid, control).</p> <p>The phytohormone file contains the root tissue concentrations (all in ng g^-1) for multiple hormones (ABA: abscisic acid, ACC: 1-aminocyclopropane-1-carboxylic acid, GAx: gibberellins, IAA: indole-3-acetic acid, iP: isopentenyl adenine, JA: jasmonic acid, SA: salicylic acid, tZ: cytokinin <em>trans</em>-zeatin) of two mangrove species (Avicennia marina, Rhizophora stylosa) grown under two different soil bulk densities: 0.2 and 1.0 g cm^-3. Treatment refers to the application of ethylene inhibitors (CoCl2: cobalt chloride, AIB: aminoisobutyric acid, control).</p> <p>&nbsp;</p> <p>&nbsp;</p>

opencc-by-4.0Dec 2023View details →
zenodo44/100

Global rooting zone water storage capacity and rooting depth estimates

<p>Global rooting zone water storage capacity (<em>S</em><sub>CWDX80</sub>, mm) and rooting depth (<em>z</em><sub>CWDX80</sub>, mm) estimates from Stocker et al., (2023).&nbsp;</p> <p>Additional global maps for rooting zone water storage capacity and rooting depth are provided and may be used as vegetation model forcing. These are created using the code from <code>whc_forcing_map.Rmd</code> , available&nbsp;<a href="https://github.com/geco-bern/mct/blob/master/whc_forcing_map.Rmd">here</a> (Zenodo entry: https://doi.org/10.5281/zenodo.7429129). The following steps were taken for creating these maps:</p> <ol> <li>The relationship between vegetation height and rooting depth was fitted using quantile regression (lower 10%) and data from Tumber-Davila et al. (2023). This yields a lower-bound rooting depth.</li> <li>A global map of vegetation height (Simard et al., 2011) was used for predicting the lower-bound rooting depth distribution globally.</li> <li>The lower-bound rooting depth was converted into a lower-bound root zone water storage capacity following methods as described in Stocker et al. (2023).</li> <li>The maximum of the lower-bound rooting depth and the inferred rooting depth (<em>z</em><sub>CWDX80</sub>) from Stocker et al., (2023) was determined for each grid cell. This is what's in the file <code>zroot_cwdx80_forcing.nc</code>. Anaologusly for <code>cwdx80_forcing.nc</code>.</li> </ol> <p>Please cite published paper:</p> <div> <div>Stocker, B. D., Tumber-D&aacute;vila, S. J., Konings, A. G., Anderson, M. C., Hain, C., and Jackson, R. B.: Global patterns of water storage in the rooting zones of vegetation, Nat. Geosci., 1&ndash;7, <a href="https://doi.org/10.1038/s41561-023-01125-2">https://doi.org/10.1038/s41561-023-01125-2</a>, 2023.</div> </div> <p>&nbsp;</p>

opencc-by-4.0Sep 2021View details →
zenodo44/100

How is tree growth rate linked to root functional traits in phylogenetically related poplar hybrids?

<p>Fine roots play a crucial role in soil nutrient and water acquisition, significantly contributing to tree growth. Fine roots with a high specific root length (SRL) and small diameter are often considered to help trees grow fast. However, inconsistencies in the literature do not provide a clear basis on the effect of root functional traits, such as SRL or root mass density (RMD), on tree growth rate in phylogenetically related trees. Our aim was to examine relationships between tree growth rate and root functional traits, using clones displaying different growth rates in a hybrid poplar plantation located in New Liskeard, ON, Canada. Fine roots (diameter &lt; 2 mm) samples were collected using soil cores at depths of 0&ndash;20, 20&ndash;40 and 40&ndash;60 cm, and analyzed for morphological, chemical and architectural traits. High SRL and thin fine roots were associated with the least productive clones, which is not consistent with the root economics spectrum (RES) theory. However, the most productive clone had larger fine root diameter and higher root lignin concentrations, probably reducing root construction and maintenance costs and C losses. Therefore, at the 0&ndash;20 and 20&ndash;40 cm depths, tree growth rates showed positive correlations with root diameter and root lignin concentrations, but negative correlations with SRL and root soluble compounds concentration. Increasing RMD at the 0&ndash;20 cm depth promoted tree growth rates, showing the importance of soil exploration in the topsoil for tree growth. We conclude that fine root variation does not always follow the RES hypothesis and argue that the rapid growth rate of trees may also be driven by fine root growth in diameter and mass in phylogenetically related trees.</p>

opencc-by-4.0Apr 2024View details →
zenodo44/100

Noccaea root and soil metagenomes

<p>Datasets comprise metagenomic data of hyperaccumulating <em>Noccaea praecox</em> and <em>N. caerulescens</em> from bulk soil, rhizosphere, and root compartments.</p>

opencc-by-4.0Apr 2025View details →
zenodo44/100

Data and statistical analysis scripts for manuscript on wheat root response to nitrate using X-ray CT and OpenSimRoot

<p>Data and statistical analysis scripts for manuscript on wheat root response to nitrate using X-ray CT and OpenSimRoot</p> <blockquote> <p><strong>X-ray CT reveals 4D root system development and lateral root responses to nitrate in soil </strong>- [<a href="https://doi.org/10.1002/ppj2.20036">https://doi.org/10.1002/ppj2.20036</a>]</p> </blockquote> <p>The ZIP file&nbsp;contains:</p> <ul> <li><code>MCT1_Rcode.R</code>&nbsp;- Statistics script for candidate single-timepoint experiment. Requires all CSV data files in the directory. User needs to set working directory to location of this script and the CSV data files before running.</li> <li><code>MCT1... .csv</code>&nbsp;- 3&nbsp;CSV data files required by the R script.</li> <li><code>MCT2_Rcode.R</code>&nbsp;- Statistics script for time-series experiment. Requires all CSV data files in the directory. User needs to set working directory to location of this script and the CSV data files before running.</li> <li><code>MCT2... .csv</code>&nbsp;- 3&nbsp;CSV data files required by the R script.</li> <li><code>R_RooThProcessing.R</code> - R code for aggregating root traits from RooTh software.</li> <li><code>Modelling folder</code> - OpenSimRoot with model parameters and root data used in manuscript.</li> </ul>

opencc-by-4.0Jan 2022View details →
zenodo44/100

Raw data: Diversity in root architecture of durum wheat at stem elongation under drought stress

<p>Raw data&nbsp;on above and below ground traits from a greenhouse drought stress experiment with six&nbsp;durum wheat varieties performed at Tuscia University, Viterbo, Italy. Measurements were performed at stem elongation stage; recorded traits: plant shoot length, dry weight, number of leaves and tillers; total root length, root surface area, mean diameter, volume, number of tips, forks, crossings, root dry weight and root angle. Root measurments were performed on the whole root system and the topsoil area (upper 5 cm).&nbsp;</p>

opencc-by-4.0Jan 2022View details →
zenodo44/100

Scanned images of monocultures and mixtures of six grassland plant species roots, and of simulated fine roots

<p>Soil core samples were taken from a multi-species grassland experiment with field plots of monocultures and mixtures of six grassland plant species: <em>Lolium perenne</em> L. (PRG),<em> Phleum pratense</em> L. (TIM), <em>Trifolium pratense</em> L. (RC), <em>Trifolium repens</em> L. (WC), <em>Cichorium intybus </em>L. (CHIC), and <em>Plantago lanceolata </em>L.. The multi-species plots had a two species mixture with <em>Trifolium repens </em>L. and<em> Lolium perenne</em> L. (PRGWC), and a 6 species mixture with all species mentioned above. The cores were separated into soil depths of 0-10 cm, 10-15 cm and 15-20 cm and the roots separated from the soil.</p> <p>A ground-truth image set was created to simulate fine roots using fishing line. The fishing line used was a clear copolymer monofilament (Greys<sup>TM</sup> Greylon Tippet Material 3 lb), measured using a scanning electron microscope (Hitachi SU8200) to be 0.14 mm in diameter. The fishing line was used in its clear colour or coloured black using a permanent marker to simulate unstained and stained fine roots respectively. The fishing line was cut into lengths of 30 cm or 5 cm.&nbsp;</p> <p>Roots and fishing line were scanned using an Epson Perfection V800 flatbed scanner at 600 dpi.&nbsp;</p> <p>The Roots ZIP file&nbsp;contains a folder for the scanned root images&nbsp;and the Line zip file contains a folder&nbsp;with the scanned fishing line. The excel spreadsheet describes the naming convention for the images.</p> <p>Further details about the root sampling and image acquisition can be found in the publication that analyses these images: <a href="https://doi.org/10.1002/ppj2.20034">https://doi.org/10.1002/ppj2.20034</a></p>

opencc-by-4.0Mar 2022View details →
zenodo44/100

Alkanna tinctoria (L.) Tausch roots in different soils and developmental stages, HPLC peak areas of alkannins/shikonins

<p>Table of peak areas of alkannins detected in the HPLC-UV/Vis analysis of extracts of <em>Alkanna tinctoria</em>&nbsp;(L.) Tausch root samples cultivated in the greenhouse in various soils. Samples come from four different stages of plant growth.</p>

opencc-by-4.0Mar 2022View details →
zenodo44/100

Root symbionts alter the volatile profile of herbivore-infested tomato plants and aid the attraction of a predator

<p>Beneficial root microbes are among the most frequently used biocontrol agents in cropping systems, since they have been shown to promote plant growth and crop yield. Moreover, they are able to enhance protection against pathogens and insect herbivores by activating plant resistance mechanisms. Plant defense responses against herbivorous insects include the induction of metabolic pathways involved in the synthesis of defense-related metabolites. These metabolites include volatile organic compounds (VOCs), which attract natural enemies of the herbivores as a form of indirect resistance. Considering that beneficial root microbes may affect direct herbivore resistance, we hypothesized that also indirect resistance may be affected. We tested this hypothesis in a study system composed of tomato, the arbuscular mycorrhizal fungus <em>Rhizophagus irregularis</em>, the growth-promoting fungus <em>Trichoderma harzianum</em>, the generalist chewing herbivore <em>Spodoptera exigua </em>and the omnivorous predator<em> Macrolophus pygmaeus</em>. Using a Y-tube olfactometer we found that <em>M. pygmaeus</em> preferred plants with <em>S. exigua </em>herbivory, but microbe-inoculated plants more than non-inoculated ones. We used a targeted GC-MS approach to assess the impact of beneficial microbes on the emission of volatiles twenty-four hours after herbivory to explain the choice of <em>M. pygmaeus</em>. We observed that the volatile composition of the herbivore-infested plants differed from that of the non-infested plants, which was driven by the higher emission of green leaf volatile compounds, methyl salicylate, and several monoterpenes and sesquiterpenes. Inoculation with microbes had only a marginal effect on the emission of some terpenoids in our experiment. Gene expression analysis showed that the marker genes involved in the jasmonic and salicylic acid pathways were differentially expressed in the microbe-inoculated plants after herbivory. Our results pinpoint the role of root symbionts in determining plant-microbe-insect interactions up to the third trophic level, and elucidates their potential to be used in plant protection.</p>

opencc-by-4.0Aug 2022View details →
zenodo44/100

Supplementary material 3 from: Bongard C, Butler K, Fulthorpe R (2013) Investigation of fungal root colonizers of the invasive plant Vincetoxicum rossicum and co-occurring local native plants in a field and woodland area in Southern Ontario. Nature Conservation 4: 55-76. https://doi.org/10.3897/natureconservation.4.3578

Supplementary material 3 from: Bongard C, Butler K, Fulthorpe R (2013) Investigation of fungal root colonizers of the invasive plant Vincetoxicum rossicum and co-occurring local native plants in a field and woodland area in Southern Ontario. Nature Conservation 4: 55-76. https://doi.org/10.3897/natureconservation.4.3578

opencc-by-4.0Jun 2013View details →
zenodo44/100

Soil pH, developmental stages and geographical origin differently influence the root metabolomic diversity and root-related microbial diversity of Echium vulgare from native habitats

<p>R Studio codes and ASV table used to analyze the microbiome data of our Echium vulgare microbial ecology experiment.&nbsp;</p>

opencc-by-4.0May 2024View details →
zenodo44/100

SNDATA_ROOT for SNANA software

<p>Environment for the Supernova Analysis software package (https://github.com/RickKessler/SNANA). This environment&nbsp;Includes public light curve&nbsp;data sets, filter transmissions, primary SEDs, calibration files, models for SNIa &amp;&nbsp;CC, cadence and host-galaxy&nbsp;libraries for simulations, etc ...</p>

opencc-by-4.0Apr 2021View details →

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