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228 results for “light responsive”
Photosynthetic Light Response Curves in CRUI Land Use Project at Harvard Forest 1998
Ambient CO2 concentrations in terrestrial ecosystems vary substantially on several spatial and temporal scales as numerous soil, plant, and atmospheric processes respond to irradiance, temperature, moisture and wind. There is one widespread microhabitat in terrestrial ecosystems, the nearground zone, in which CO2 is naturally enhanced above average background levels. CO2 produced by soil respiration diffuses through the litter and boundary layers and dissipates fairly rapidly into the overlying bulk air. However, a marked vertical profile of nearground enriched CO2 (hereafter NEC) is usually present in the first 0-50 cm above ground. The degree of enrichment varies primarily with soil respiration rate and turbulent mixing, secondarily with photosynthesis by plants in the herbaceous stratum, and usually shows marked diel and seasonal variation. References to this CO2 "subsidy" and its effects on plants have occurred occasionally in the literature since 1939, but there have been few detailed studies of either the nearground profile or plant responses in the field, particularly for species that consistently occupy the nearground stratum. Considerable research over the last twenty years in both controlled and field environments has shown that co-occurring plant species may respond differently to artificially elevated CO2. But in contrast to light, temperature, water, and nutrients, plant community ecologists have generally not considered CO2 among the factors that regulate species’ distribution and abundance, except indirectly as it may affect water balance. We have documented differences in forest composition (woody and herbaceous), soil characteristics, microclimates, and nearground CO2 levels among six sites that were formerly plowed, pastured, or continuously forested woodlots in Prospect Hill. We selected three perennial herbaceous species (Aralia nudicaulis, wild sarsaparilla; Clintonia borealis, blue-bead lily; Medeola virginiana, Indian cucumber root) and two do
Brachypodium distachyon images used in the paper entitled "Led Color Gradient As A New Screening Tool For Rapid Phenotyping Of Plant Responses To Light Quality" by Pierre LEJEUNE et al.
<p>Brachypodium distachyon images used in the paper entitled "Led Color Gradient As A New Screening Tool For Rapid Phenotyping Of Plant Responses To Light Quality" by Pierre LEJEUNE, Anthony FRATAMICO, Frédéric BOUCHÉ, Samuel HUERGA-FERNÁNDEZ, Pierre TOCQUIN, Claire PÉRILLEUX</p>
Euphorbia peplus images used in the paper entitled "Led Color Gradient As A New Screening Tool For Rapid Phenotyping Of Plant Responses To Light Quality" by Pierre LEJEUNE et al.
<p>Euphorbia peplus images used in the paper entitled "Led Color Gradient As A New Screening Tool For Rapid Phenotyping Of Plant Responses To Light Quality" by Pierre LEJEUNE, Anthony FRATAMICO, Frédéric BOUCHÉ, Samuel HUERGA-FERNÁNDEZ, Pierre TOCQUIN, Claire PÉRILLEUX</p>
Arabidopsis thaliana images used in the paper entitled "Led Color Gradient As A New Screening Tool For Rapid Phenotyping Of Plant Responses To Light Quality" by Pierre LEJEUNE et al.
<p><em>Arabidopsis thaliana</em> images used in the paper entitled "Led Color Gradient As A New Screening Tool For Rapid Phenotyping Of Plant Responses To Light Quality" by Pierre LEJEUNE, Anthony FRATAMICO, Frédéric BOUCHÉ, Samuel HUERGA-FERNÁNDEZ, Pierre TOCQUIN, Claire PÉRILLEUX</p>
Oryza sativa images used in the paper entitled "Led Color Gradient As A New Screening Tool For Rapid Phenotyping Of Plant Responses To Light Quality" by Pierre LEJEUNE et al.
<p><em>Oryza sativa</em> images used in the paper entitled "Led Color Gradient As A New Screening Tool For Rapid Phenotyping Of Plant Responses To Light Quality" by Pierre LEJEUNE, Anthony FRATAMICO, Frédéric BOUCHÉ, Samuel HUERGA-FERNÁNDEZ, Pierre TOCQUIN, Claire PÉRILLEUX</p>
Solanum lycopersicum images used in the paper entitled "Led Color Gradient As A New Screening Tool For Rapid Phenotyping Of Plant Responses To Light Quality" by Pierre LEJEUNE et al.
<p><em>Solanum lycopersicum</em> images used in the paper entitled "Led Color Gradient As A New Screening Tool For Rapid Phenotyping Of Plant Responses To Light Quality" by Pierre LEJEUNE, Anthony FRATAMICO, Frédéric BOUCHÉ, Samuel HUERGA-FERNÁNDEZ, Pierre TOCQUIN, Claire PÉRILLEUX</p>
Ocimum basilicum images used in the paper entitled "Led Color Gradient As A New Screening Tool For Rapid Phenotyping Of Plant Responses To Light Quality" by Pierre LEJEUNE et al.
<p><em>Ocimum basilicum</em> images used in the paper entitled "Led Color Gradient As A New Screening Tool For Rapid Phenotyping Of Plant Responses To Light Quality" by Pierre LEJEUNE, Anthony FRATAMICO, Frédéric BOUCHÉ, Samuel HUERGA-FERNÁNDEZ, Pierre TOCQUIN, Claire PÉRILLEUX</p>
The DR-Train dataset: dynamic responses, GPS positions and environmental conditions of two light rail vehicles in Pittsburgh
<p><strong>Note: Downloading the large data file could have a timeout issue. If you cannot directly download it here, please use the following link as a complementary method for getting the data. </strong></p> <p><a href="https://drive.google.com/drive/folders/1oKn7IN7zznQuhwjDCDdjq8r9wHJYBEhj?usp=sharing">https://drive.google.com/drive/folders/1oKn7IN7zznQuhwjDCDdjq8r9wHJYBEhj?usp=sharing</a></p> <p> </p> <p>This dataset contains the dynamic responses (acceleration records) of two passenger trains with corresponding GPS positions, environmental conditions and track maintenance schedules for a light rail network in the city of Pittsburgh, Pennsylvania in the United States of America.</p> <p>In particular, two light rail vehicles were instrumented (identified as LRV4306 and LRV4313): <br> LRV 4306 has 5 acceleration channels, corresponding to the two uni-axial accelerometers inside the train and the three channels of the tri-axial accelerometer on the wheel truck.</p> <p><em>- The last digit of each acceleration file: 1, 2, 3, 4, 5<br> - Corresponding sensor channels: tri-axial x, tri-axial y, tri-axial z, front cabinet uni-axial, back cabinet uni-axial</em></p> <p><br> LRV 4313 has 8 acceleration channels, corresponding to the two uni-axial accelerometer and the two tri-axial accelerometers inside the train.</p> <p><em>- The last digit of each acceleration file: 1, 2, 3, 4, 5, 6, 7, 8<br> - Corresponding sensor channels: front cabinet uni-axial, back cabinet uni-axial, front tri-axial x, front tri-axial y, front tri-axial z, back tri-axial x, back tri-axial y, back tri-axial z.<br> - x longitudinal (vehicle moving direction); y-axis, transverse; z-axis, vertical.</em></p> <p>The dataset contained in this repository is a condensed version of the original raw data. While the accelerometers on the train were sampled continuously, this dataset contains only those measurements for when the train was actually moving along the track (i.e. not idling at a terminal).</p> <p>The data is stored in binary MAT-files (a MATLAB/Octave data format). These files contain MATLAB objects of the class "pass", which is defined in the file pass.m that can be found in the "code" folder. Specifically, two MAT-files named "obj_dic.mat", and found in the "LRV4306" and "LRV4313" folders, contain the "pass" objects of the two trains, respectively.</p> <p>Each category is described in detail. For more detail on the regions of the track, refer to the 'region.fig' file in this folder. The track was divided into distinct regions so that the data over specific sections of track could be compared. These regions were chosen for two reasons: <br> (1) within a region, the train always followed the same track and <br> (2) there are no tunnels in them so the GPS data is relatively consistent. </p> <p>To get started, using MATLAB or Octave try running "main_script.m" in the "code" folder.</p> <p>A data descriptor paper with details of the data collection process was published.</p> <p>Please cite as</p> <p><strong>Liu, J., Chen, S., Lederman, G., Kramer, D. B., Noh, H. Y., Bielak, J., Garrett, J. H., Kovačević, J., & Berges, M. Dynamic responses, GPS positions and environmental conditions of two light rail vehicles in Pittsburgh. Scientific Data, 6, 146. <a href="https://doi.org/10.1038/s41597-019-0148-9">https://doi.org/10.1038/s41597-019-0148-9</a>(2019)</strong></p> <p><strong>Liu, J., Chen, S., Lederman, G., Kramer, D. B., Noh, H. Y., Bielak, J., Garrett, J. H., Kovačević, J., & Berges, M. The DR-Train dataset: dynamic responses, GPS positions and environmental conditions of two light rail vehicles in Pittsburgh. Zenodo, <a href="https://doi.org/10.5281/zenodo.1432702">https://doi.org/10.5281/zenodo.1432702</a>(2018).</strong></p> <p>For questions or suggestions please e-mail Jingxiao Liu <liujx@stanford.edu></p>
Elevation modulates the phenotypic responses to light of four co-occurring Pyrenean forest tree species
<p>Data on plant water potential for seedlings of four Pyrenean tree species planted along an elevation gradient. The dataset contains three files:</p> <ol> <li><strong>Biomass.txt: </strong>Data on plant biomass per fraction (leaf, stem and roots) 4 years after plantation. Included variables:<br> - Piso (factor): elevational stage at which the seedling was planted. Two levels: montane (M) or subalpine (S)<br> - Luz (factor): whether the seedling was plantes at a gap or in the understory. Two levels: gap (O) or understroy (T)<br> - N (numeric): number of plant in that plot<br> - Sp (factor): species. Four levels: BEPE (Betula pendula) / PISY (Pinus sylvestris) / PIUN (Pinus uncinata) / ABAL (Abies alba)<br> - Planta (factor): code to identify uniquely each plant<br> - File (factor): code to identify uniquely each plant<br> - GLI (num): Global Light Index, the amount of irradiance that receives each seedling<br> - Code (factor): code to identify uniquely each plant<br> - PLB (numeric): total plant biomass (g)<br> - LFB (numeric): leaf biomass (g)<br> - STB (numeric): stem biomass (g)<br> - RTB (numeric): root biomass (g)<br> - LMF (numeric): leaf mass fraction (LFB/PLB)<br> - SMF (numeric): stem mass fraction (STB/PLB)<br> - RMF (numeric): root mass fraction (RTB/PLB)<br> - SLA (numeric): specific leaf area<br> - H (numeric): plant height (mm)<br> - D (numeric): plant diameter at root collar (mm)<br> - PB2 (numeric): total plant biomass without considering leaves (g)<br> - SF2 (numeric): stem mass fraction without considering leaves (STB/PB2)<br> - RF2 (numeric): root mass fraction without considering leaves (RTB/PB2)</li> <li><strong>init_biomass.txt:</strong> for biomass at the moment of plantation<br> - Piso (factor): elevational stage at which the seedling was planted. Two levels: montane (M) or subalpine (S)<br> - N (numeric): number of plant<br> - Sp (factor): species. Four levels: BEPE (Betula pendula) / PISY (Pinus sylvestris) / PIUN (Pinus uncinata) / ABAL (Abies alba)<br> - Planta (factor): code to identify uniquely each plant<br> - File (numeric): code to identify uniquely each plant<br> - PB (numeric): total plant biomass (g)<br> - LB (numeric): leaf biomass (g)<br> - SB (numeric): stem biomass (g)<br> - RB (numeric): root biomass (g)</li> <li><strong>WaterPot.txt</strong>: data on plant water potential for seedlings of four Pyrenean tree species planted along an elevation gradient during a period of intense drought<br> - Piso (factor): elevational stage at which the seedling was planted. Two levels: montane (M) or subalpine (S)<br> - Luz (factor): whether the seedling was plantes at a gap or in the understory. Two levels: gap (O) or understroy (T)<br> - N (numeric): number of plant <br> - Parcela (factor): identifier ofthe plot<br> - Sp (factor): species. Four levels: BEPE (Betula pendula) / PISY (Pinus sylvestris) / PIUN (Pinus uncinata) / ABAL (Abies alba)<br> - Estacion (factor): the moment for the measurement. One level: September<br> - GLI (numeric): global light index, the ration of total irradiance received by the plant at the moment of plantation<br> - WPt (numeric): water potential (bars)</li> </ol>
Light and confocal micrographs on the response of Mesotaenium endlicherianum SAG 12.97 to a bifactorial environmental gradient, the accumulation of lipid droplets, and the heterologous expression and localisation of signature LD protein homologs to tobacco pollen tubes
<p>These micrographs accompany the work "Environmental gradients reveal stress hubs predating plant terrestrialization", posted as a pre-print on bioRxiv https://doi.org/10.1101/2022.10.17.512551 </p> <p>The light and confocal micrographs show the response of Mesotaenium endlicherianum SAG 12.97 to a bifactorial environmental gradient, especially their accumulation of lipid droplets (LDs); in confocal micrographs, LDs appeared as distinct structures upon staining with BODIPY.</p> <p>Further confocal micrographs show the heterologous expression and localisation of signature LD protein homologs detected in Mesotaenium endlicherianum SAG 12.97; heterologous expression was carried out in tobacco pollen tubes were also stained with BODIPY and proteins were tagged with mCherry.</p>
Dataset about response of some ciliate species to resources and light
<p>Communities of seven species of ciliates were grown at 10 different levels of resources and four levels of light. The two treatments were manipulated factorially. Most treatment combinations were replicated once, some twice. The dataset contains the abundances of the seven ciliate species after seven days of growth at the respective levels of resources and light.</p>
Light response curves measured from shoots harvested at three levels in the canopy from 19 1m x 1m plots dominated by S. pulchra or B. nana shrubs near LTER Shrub plots at Toolik Field Station, AK the summer of 2012.
This dataset contains light response curves and modeled light curve parameters from shoots clipped from low, mid, and the top parts of tall, shrub canopies dominated either by Salix pulchra or Betula nana. Six shoots were harvested from each 1m x 1m plot, two from each level in the canopy in plots located near the LTER shrub plots at Toolik Field Station, AK the summer of 2012. The species harvested were chosen based on the species present in each plot, thus the species from each segment of the canopy may not be the same. Additional information about each shoot can be found in the "2012_GS_ITEX_PF_ShootA-CiData" and "2012_GS_ITEX_PF_ShootHarvestData" pages, regarding the A-Ci response, area, mass, leaf area index, and leaf nitrogen content of each shoot. The file "2012_GS_ITEX_PercentCover" contains the species cover data for each plot.
Light micrographs on the morphological response to heat stress in the filamentous Zygnematophyceae Mougeotia sp. and Spirogyra pratensis
<p>Herein are the light micrographs of <em>Mougeotia</em> sp. and <em>Spirogyra pratensis</em> that were used to obtain the quantitative information for Figure 1 in the article "Heat stress response in the closest algal relatives of land plants reveals conserved stress signaling circuits" published in The Plant Journal, doi: 10.1111/tpj.14782</p>
Pupillary response to representations of light in paintings
<p>“.mat” files contain:</p> <ul> <li><strong>BUF2:</strong> Recording during fixation slide (column 1: time; column 2: right pupil width; column 3: right pupil height; column 4: left pupil width; column 5: left pupil height; column 6: glint data from right eye; column 7: glint data from right eye; column 8: image number)</li> <li><strong>BUF</strong>: Recording during stimulus presentation (same columns of BUF2)</li> <li><strong>c</strong>: block’s specifics (eye-tracker information, trials number and duration, start and end times of eye-tracker registrations)</li> <li><strong>smile</strong>: images code</li> <li><strong>Response</strong>: block’s information (first column: stimulus presentation time; variable number of other columns: smile variable; last column: trials number);</li> </ul> <p> </p>
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>
Adaptation to numerosity affects the pupillary light response
<p>The dataset reports per participant and condition averages of peak pupil constrictions (columns P_...) and reported numerosity (columns B_...) from two experiments run with 12 and 13 participants (rows) in "Adaptation to numerosity affects the pupillary light response" (Scientific Reports, 2024) by Caponi, Castaldi, Burr and Binda.</p> <p>Pupil constrictions and numerosity reports were elicited by 500 ms long stimuli of constant luminance but variable numerosity, presented following two types of adapters: low numerosity or high numerosity. Column headers identify the measure (P for pupil constriction and B for behavioural responses), the adaptation condition (low and high) and the numerosity of the array (10, 14, 20, 28 and 40). The averages of these values are reported in Figure 2A-B of the publication.</p> <p>Columns "B_lmh40" and "P_hmlALL" correspond to the data in Figure 2C, quantifying the adaptation effect on reported numerosity and on pupil constrictions respectively.</p>
Data from: Annual species' experimental germination responses to light and temperature do not correspond with their microhabitat associations in the field
<p>Annual species have evolved sets of germination cues that are thought to be predictive of the post-germination environment. In naturally patchy environments, germination microsites often vary considerably in the amount of light they receive and in the diurnal temperature fluctuations they experience. However, whether species' differential germination responses to light and temperature are associated with their spatial patterns of occurrence remains largely untested.</p> <p>We surveyed species' occurrences in annual plant communities in 150 quadrats across gradients of canopy cover and litter cover. Nineteen species recorded in this survey were then included in a germination experiment that manipulated (1) Light vs. Dark (12h light or continuous dark) approximating seeds near the soil surface versus those covered by litter and (2) Cold vs. Warm temperature regimes (7/18 °C and 7/24 °C) approximating diurnal fluctuations experienced in shaded versus sun-exposed microsites, respectively.</p> <p>In the germination experiment, six species had highest germination probabilities in the Light treatment (regardless of temperature), five in <em>Cold</em> + <em>Light</em>, one in <em>Warm</em> + <em>Light</em>, two were indifferent to the treatments, and four did not germinate at all. Binomial linear mixed-effects models showed that species' maximum responses to light and temperature did not explain their spatial distributions along canopy cover and litter cover gradients, contrary to theoretical expectations of germination being a strong driver of species' occurrences.</p> <p>Despite variation in species' responses to experimental treatments, no association was found with their field microsite associations. Germination strategies in our system were wider than expected for Mediterranean systems. Our results support that germination cues are not strong drivers of microhabitat associations in this system.</p>
Fig. 1 in The response of Phyllophaga brevidens and Phyllophaga lenis (Coleoptera: Scarabaeidae) to methyl 2-(methylthio) benzoate and light
Fig. 1. Numbers of Phyllophaga brevidens and Phyllophaga lenis adults trapped per species, sex, and treatment during 2 sampling periods in Tlaltizapan, Morelos, Mexico. A = attractant, L= light, C = control, M = males, F = females, nd = not determined.
Fig. 1 in Halyomorpha halys (Hemiptera: Pentatomidae) response to pyramid traps baited with attractive light and pheromonal stimuli
Fig. 1. Standard black pyramid trap with PHER lure (A) and modified pyramid trap with narrow blue fluorescent light (B).
A new and highly robust light-responsive Azo-UiO-66 for highly selective and low energy post-combustion CO2 capture and its application in a mixed matrix membrane for CO2/N2 separation
<p>Supporting information for publication in Journal of Materials Chemistry A, <a href="https://dx.doi.org/10.1039/C8TA03553A">https://dx.doi.org/10.1039/C8TA03553A </a></p>
ScienceDex guides
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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.