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FIGURE 2 in Functional responses of stream fish communities to rural and urban land uses
FIGURE 2 | Ternary diagram of land use/occupation in the 24 streams sampled in the state of Paraná, Brazil.
FIGURE 1 in Functional responses of stream fish communities to rural and urban land uses
FIGURE 1 | Location of the sampling sites in the 24 streams in the state of Paraná, Brazil. Codes and names of streams in S1.
FIGURE 4 in Fish functional responses to local habitat variation in streams within multiple land uses areas in the Amazon
FIGURE 4 | Relationships between the ecomorphological traits of fish species and environmental variables (land use and local habitat) in the streams evaluated in this study. Traits are represented by labels: relative head length (RHL), relative mouth width (RMW), relative height (RH), relative area of pectoral fin (RAPF) and relative caudal peduncle length (RCPL).
FIGURE 3 in Fish functional responses to local habitat variation in streams within multiple land uses areas in the Amazon
FIGURE 3 | Relationships between fish functional trophic groups and environmental variables (land use and local habitat) in the streams evaluated in this study. The groups are represented by the labels: Diurnal channel drift feeders (FTG 3), Diurnal backwater drift feeders (FTG 4), Diurnal surface pickers (FTG 7), Diggers (FTG 9) and Ambush and stalking predators (FTG 11). The FTG's with a correlation between 0.2 and -0.2 have been omitted for better visualization of the results.
FIGURE 2 in Fish functional responses to local habitat variation in streams within multiple land uses areas in the Amazon
FIGURE 2 | Ordination of the types of land use in the catchment areas of the study streams at the Capim River basin, eastern Amazon.
FIGURE 1 in Fish functional responses to local habitat variation in streams within multiple land uses areas in the Amazon
FIGURE 1 | Location of sampling streams (Middle Capim River basin, Pará State, Brazil). The characteristics of each land use class are described in the Material and Methods section.
FIGURE 1 in Body size responses to land use in stream fish: the importance of different metrics and functional groups
FIGURE 1 | Description of the four body size metrics used to investigate body size patterns in overall stream fish communities and in distinct functional groups. A. Skewness describes the tendency of value distribution being biased towards the right (negative-skewed) or left (positive-skewed). B. Kurtosis describes if the distribution of values is more flatted (platykurtic) or biased towards the center (narrow). Mean values can be the same for distinct kurtosis. Coefficient of variation (CV) describes the variation in values standardized to the mean.
FIGURE 3 in Body size responses to land use in stream fish: the importance of different metrics and functional groups
FIGURE 3 | Clusters of fish species based on ecomorphological and trophic traits, resulting in 11 functional groups (FG). Full species names by FG are available in S2.
FIGURE 2 in Body size responses to land use in stream fish: the importance of different metrics and functional groups
FIGURE 2 | Location of the 40 stream sites where fish communities were sampled in South Brazilian grassland biome (Pampa).
Drought stress triggers differential survival and functional trait responses in the establishment of Arnica montana seedlings
<ul> <li>The establishment and survival of seedlings are critical stages in the life cycle of plants and therefore usually well timed to humid and favourable conditions. Climate projections suggest that the threatened mountain grassland species <em>Arnica montana</em> may be increasingly exposed to drought stress. However, studies that focus on the species’ early development are missing. We evaluated impacts of drought-induced stress on <em>A. montana</em> seedlings in their early establishment phase and identified traits for the species’ fitness decline.</li> <li>In a greenhouse experiment, we tested the response of <em>A. montana</em> seedlings to different drought levels (moderate, strong, extreme). To assess their fitness under increasing drought, we evaluated the survival of the seedlings based on four senescence stages and measured the performance of above- and belowground morphological and physiological functional traits.</li> <li><em>Arnica montana</em> seedlings showed high resistance to drought. Senescence accelerated and survival declined only under strong and extreme drought conditions. However, the seedlings’ vegetative performance decreased even with moderate drought, as indicated by smaller values of most leaf traits and some root traits. Physiological trait response was less sensitive.</li> <li>Drought stress hinders the establishment and survival of <em>A. montana</em> seedlings. Following the functional trait responses to drought and their associations with survival, we suggest declining leaf length, leaf width, and leaf number as sensitive traits that can lead to a decline performance.</li> </ul>
CTAO Instrument Response Functions - prod5 version v0.1
<p>CTAO Instrument Response Functions - prod5 version v0.1</p> <p>The CTA Observatory (CTAO) will provide very wide energy range and excellent angular resolution and sensitivity in comparison to any existing gamma-ray detector. Energies down to 20 GeV will allow CTAO to study the most distant objects. Energies up to 300 TeV will push CTAO beyond the edge of the known electromagnetic spectrum, providing a completely new view of the sky. This data repository provides access to performance evaluation and instrument response functions (IRFs) for CTA.</p> <ul> <li>IRF version: prod5 v0.1</li> <li>Telescope model and site configuration: <a href="https://zenodo.org/record/6218687">prod5-model</a></li> <li>Publication date: Sep 2021</li> <li>Archived webpage with performance figures included: <a href="/cta-science/montecarlo-results/public-irfs-zenodo/cta-prod5-zenodo/-/blob/preview/Website.md">CTAO Performance Description (file Website.md)</a></li> <li>Licence: this work is licensed under a <a href="/cta-science/montecarlo-results/public-irfs-zenodo/cta-prod5-zenodo/-/blob/preview/LICENSE">Creative Commons Attribution 4.0 International License</a>.</li> </ul> <p>Please use the contact address open-data@cta-observatory.org for any inquiries.</p> <p>Citation and Acknowledgements:</p> <p>In cases for which the CTA instrument response functions are used in a research project, we ask to add the following acknowledgement in any resulting publication:</p> <p>"This research has made use of the CTA instrument response functions provided by the CTA Consortium and Observatory, see <a href="https://www.cta-observatory.org/science/cta-performance/">https://www.ctao-observatory.org/science/cta-performance/</a> (version prod5 v0.1; [citation]) for more details."</p> <p>Please use the following BibTex Entry for [citation] in the reference section of your publication:<br> <a href="https://zenodo.org/record/5499840/export/hx">https://zenodo.org/record/5499840/export/hx</a></p> <p>Description</p> <p>Monte Carlo Simulations:</p> <p>The performance values are derived from detailed Monte Carlo (MC) simulations of the CTA instrument based on the CORSIKA air shower code (v7.71, with the hadronic interaction models QGSjet-II-04 and URQMD, [1]) and telescope simulation tool sim_telarray [2]. A power- law gamma-ray spectrum with photon index 2.62 was assumed in the calculations, although none of the instrument response functions (e.g. differential flux sensitivities, effective areas, angular or energy resolutions) depends on the assumed spectral shape of the gamma-ray source. Background cosmic-ray spectra of proton and electron/positron particle types are modelled according to recent measurements from cosmic-ray instruments.</p> <p>Nominal telescope pointing is assumed, with all telescopes pointing directions parallel to each other (performance estimation for other pointing modes, e.g. divergent pointing will be provided in the future). Performance estimations are available for three zenith angles (20 deg, 40 deg, and 60 deg), and for each zenith angle for two different azimuth angles (corresponding to pointing towards the magnetic North and South). There are significant performance differences found between the two azimuthal pointing directions (especially for the Northern site) as the impact of the geomagnetic field is large enough to influence notably the air shower development. For general studies, the use of the azimuth-averaged instrument response functions is recommended.</p> <p>Instrument Response Functions (IRFs):</p> <p>The analysis has been tuned to maximize the performance in terms of flux sensitivity. The optimal analysis cuts depend on the duration of the observation, therefore the IRFs are provided for 3 different observation times, from 0.5 to 50 h. IRFs are provided as binned histogram or FITS tables. It should be stressed, that the full potential of CTA in terms of angular and energy resolution is not revealed by these IRFS, due to the focus on the optimisation for best flux sensitivity.</p> <p>In general all histograms are binned with a 0.2-binning on the logarithmic energy axis (5 bins per decade); some selected histograms (e.g. effective areas or energy migration matrices) are provided with a finer binning. Effective area and energy migration matrix are available in a double version: one for the case in which there is no a priori knowledge of the true direction of incoming gamma rays (e.g. for the observation of diffuse sources), and another for observations of point-like objects (including among the analysis cuts one on the angle between the true and the reconstructed gamma-ray direction).</p> <p>IRFs are provided in ROOT format and as FITS tables. The FITS tables can be used directly as input to science analysis tools. The values of the IRFs are identical for the different file format, with one exception: the angular point-spread function is approximated by a Gaussian function for the FITS tables, while the ROOT files contain the full distribution.</p> <p>Telescope layouts are preliminary and subject to change. The following array layouts (Alpha configuration) have been assumed:</p> <ul> <li> CTA South with 14 MSTs and 37 SSTs (see [figure](figures/CTA-Performance-prod5-v0.1-South-Alpha-Layout.png))</li> <li> CTA North with 4 LSTs and 9 MSTs (see [figure](figures/CTA-Performance-prod5-v0.1-North-Alpha-Layout.png))</li> </ul> <p>Two zip files are uploaded:</p> <ul> <li>full archive with IRFs in FITS and ROOT format: cta-prod5-zenodo-v0.1.zip</li> <li>partial archive with IRFs in FITS format only: cta-prod5-zenodo-fitsonly-v0.1.zip</li> </ul> <p>File Naming (examples):</p> <ul> <li>Prod5-North-40deg-AverageAz-4LSTs09MSTs.18000s-v0.1.root: IRF for CTA Northern site on La Palma, 40 deg zenith angle, azimuth-averaged pointing, optimised for 5 hours of observation time</li> <li>Prod5-South-20deg-AverageAz-14MSTs37SSTs.180000s-v0.1.fits.gz: IRF for CTA Southern site in Paranal, 20 deg zenith angle, azimuth-averaged pointing, optimised for 50 hours of observation time</li> </ul> <p>List of files:</p> <p>FITS format:</p> <ul> <li>fits/CTA-Performance-prod5-v0.1-North-20deg.FITS.tar.gz</li> <li>fits/CTA-Performance-prod5-v0.1-North-40deg.FITS.tar.gz</li> <li>fits/CTA-Performance-prod5-v0.1-North-60deg.FITS.tar.gz</li> <li>fits/CTA-Performance-prod5-v0.1-South-20deg.FITS.tar.gz</li> <li>fits/CTA-Performance-prod5-v0.1-South-40deg.FITS.tar.gz</li> <li>fits/CTA-Performance-prod5-v0.1-South-60deg.FITS.tar.gz</li> </ul> <p>ROOT format:</p> <ul> <li>root/CTA-Performance-prod5-v0.1-North-20deg.tar.gz</li> <li>root/CTA-Performance-prod5-v0.1-North-40deg.tar.gz</li> <li>root/CTA-Performance-prod5-v0.1-North-60deg.tar.gz</li> <li>root/CTA-Performance-prod5-v0.1-South-20deg.tar.gz</li> <li>root/CTA-Performance-prod5-v0.1-South-40deg.tar.gz</li> <li>root/CTA-Performance-prod5-v0.1-South-60deg.tar.gz</li> </ul> <p>IRFs for subarrays of e.g., MSTs only are in the files named MSTSubArray (similar for all other telescope types).</p> <p>References</p> <ul> <li>[1] <a href="https://www.ikp.kit.edu/corsika/">https://www.ikp.kit.edu/corsika/</a></li> <li>[2] Bernloehr, K. 2008, Astroparticle Physics, 30, 149</li> </ul> <p>Acknowledgements</p> <p>We would like to thank the computing centres that provided resources for the generation of the Prod 5 Instrument Response Functions (IRFs):</p> <ul> <li>CAMK, Nicolaus Copernicus Astronomical Center, Warsaw, Poland</li> <li>CIEMAT-LCG2, CIEMAT, Madrid, Spain</li> <li>CYFRONET-LCG2, ACC CYFRONET AGH, Cracow, Poland</li> <li>DESY-ZN, Deutsches Elektronen-Synchrotron, Standort Zeuthen, Germany</li> <li>GRIF, Grille de Recherche d’Ile de France, Paris, France</li> <li>IN2P3-CC, Centre de Calcul de l’IN2P3, Villeurbanne, France</li> <li>IN2P3-CPPM, Centre de Physique des Particules de Marseille, Marseille, France</li> <li>IN2P3-LAPP, Laboratoire d Annecy de Physique des Particules, Annecy, France</li> <li>INFN-FRASCATI, INFN Frascati, Frascati, Italy</li> <li>INFN-T1, CNAF INFN, Bologna, Italy</li> <li>INFN-TORINO, INFN Torino, Torino, Italy</li> <li>MPIK, Heidelberg, Germany</li> <li>OBSPM, Observatoire de Paris Meudon, Paris, France</li> <li>PIC, port d’informacio cientifica, Bellaterra, Spain</li> <li>prague_cesnet_lcg2, CESNET, Prague, Czech Republic</li> <li>praguelcg2, FZU Prague, Prague, Czech Republic</li> <li>UKI-NORTHGRID-LANCS-HEP, Lancaster University, United Kingdom</li> </ul>
Variation in biomass allocation and root functional parameters in response to fire history in Brazilian savannas
<p>Dataset associated with the manuscript "<strong>Variation in biomass allocation and root functional parameters in response to fire history in Brazilian savannas" </strong> (Le Stradic et al.). It includes 5 different datasets and for each one we provided metadata.</p> <p>above_below_b_SBI: it includes data related to aboveground and belowground biomass. Aboveground data were collected in circular plots of 0.5m2 and belowground biomass was collected using an auger of 5cm of diameter, every 10cm up to 40cm and every 20cm up to 1m depth. See the method section in the manuscript for full details.</p> <p>below_b_wet_all_SBII: it includes data related to belowground biomass (collected in the first 1m of soil, during the wet season, January-February 2018), including values for each soil depth.</p> <p>root_trait_SBI: it includes all root functional parameters for samples collected in the first 10 cm of soil.</p> <p>Sampling_data: it includes information associated with sampling areas (localization, GPS point, fire history).</p> <p>soil.expand.SBI: it includes all soil data.</p> <p> </p> <p><strong>Abstract</strong></p> <ol> <li>Fire is a fundamental ecological factor in savannas because it affects vegetation dynamics and ecosystem functioning. However, the effects of fire on belowground compartments, including biomass and root traits, and their regeneration remain poorly understood. In this study, we assess the variation of above- and belowground plant components along fire-history gradients in Brazilian open savannas and investigate whether vegetation and soil composition changes are associated with the responses of belowground biomass and root traits.</li> <li>The study was conducted in eight sampling areas of open savanna (<em>campo sujo</em>) the Cerrado (Brazilian savannas), located along a gradient of time since the last fire (1–34 years); the number of fires that occurred within the past 34 years (0–9 fires) varied by sampling area. In each sampling area, we measured above- and belowground biomass, root depth distribution, root functional parameters, and nutrient levels in the upper soil layers (0–10 cm).</li> <li>Rapid recovery of aboveground live biomass after a fire was primarily due to resprouting of graminoids. This recovery was associated with an increase in absorptive root biomass in the upper soil layer in the most recently burnt sites, whereas root biomass was unaffected in deeper layers. Root parameters remained constant regardless of fire history but responded to variations in vegetation structure and soil resources. Specific root length (SRL) decreased with K, Mg<sup>2+</sup>, Al<sup>3+</sup>, N, and C and increased with P concentration. In contrast, root tissue density (RTD) and absorptive root proportion were negatively correlated with soil P. RTD was strongly associated with the aboveground biomass of graminoids. Soil texture impacted the root system: the proportion of absorptive root increased with fine sand content in the soil, inversely to transport root biomass. The relationship between fire and soil composition was insignificant.</li> <li><em>Synthesis</em>. In savannas, fire stimulates absorptive root biomass in response to the higher demand for belowground resources. This response is correlated with shoot regrowth after a fire. Variations in morphological root parameters are not directly associated with fire history; instead, they reflect differences in soil chemistry, especially soil P and graminoid biomass changes.</li> </ol>
Dataset: Core excitations and ionizations of uranyl in Cs2UO2Cl4 from relativistic embedded damped response time-dependent density functional theory and equation of motion coupled cluster calculations
<p>This dataset collects the unprocessed (= outputs from calculations) results discussed in the paper titled "Core excitations and ionizations of uranyl in Cs2UO2Cl4 from relativistic embedded damped response time-dependent density functional theory and equation of motion coupled cluster calculations", by Wilken Aldair Misael and Andre Severo Pereira Gomes. It also contains the figures used in the manuscript.</p>
Data from: Measuring leaf and root functional traits uncovers multidimensionality of plant responses to arbuscular mycorrhizal fungi
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Emergence and function of cortical offset responses in sound termination detection
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Data and code from: Species interactions amplify functional group responses to elevated CO2 and N enrichment in a 24-year grassland experiment
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Data from: Differential responses of community-level functional traits to mid- and late-season experimental drought in a temperate grassland
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Geo-referenced crop-nutrient response function dataset for Tropical Africa
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Plant and soil organic matter responses to ten years of nutrient enrichment in the Nutrient Network:Nutrient Network. A cross-site investigation of bottom-up control over herbaceous plant community dynamics and ecosystem function
This experiment is one implementation of a globally distributed experiment, known as the Nutrient Network. At Cedar Creek, as in over 70 other sites in grasslands around the world, the experiment aims to describe impacts of increased nutrients (nitrogen, phosphorus, potassium, sulfur and other metals) and decreased herbivory (removal of mammals by fencing). Two overarching questions are being explored with these manipulations: 1. To what extent are plant production and diversity co-limited by multiple nutrients in herbaceous-dominated communities? 2. Under what conditions do grazers or fertilization control plant biomass, diversity, and composition? By utilizing identical protocols at diverse grassland sites around the world, NutNet aims to uncover both the generalities in ecosystem functioning, and the contingencies or differences which can obscure those common mechanisms. In addition to the standard NutNet protocol, e247 includes an additional low Nitrogen gradient (1 gram Nitrogen per meter squared per year and 5 grams Nitrogen per meter squared per year in addition to the standard 10 grams Nitrogen per meter squared per year).
Dataset for "Analytic High-order Geometric Derivatives with Polarizable Embedding in a Response Function Framework"
<p>This dataset contains data for the article "Analytic High-order Geometric Derivatives with Polarizable Embedding in a Response Function Framework"</p>
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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.