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1,840 results for “Representative”
Representing Model Uncertainty for Global Atmospheric CO2 Flux Inversions Using ECMWF-IFS-46R1
<p>Data used in the work "Representing Model Uncertainty for Global Atmospheric CO2 Flux Inversions Using ECMWF-IFS-46R1" - McNorton et al. (2020)</p> <p>All data generated using version 46R1 of the Integrated Forecast System based at the European Centre for Medium-Range Weather Forecasts, with work funded as part of the European Commission CO2 Human Emissions Project.</p> <p>Data includes global total standard errors for the total column CO2 mixing ratios at 3 hourly intervals for 2015 and both total column and surface transport errors at hourly intervals for January and July 2015, derived from a 50 member ensemble. It is suggested that the data are used by the inverse modelling community to account for transport model errors.</p> <p>Please view the README.txt file for a full description.</p> <p> </p> <p>###########################<br> ## EXPERIMENTAL SETUP ##<br> ###########################</p> <p># FLUXES #</p> <p>CHE-EDGAR-2015 EMISSIONS<br> CHE-TIER-2-FIRE/OCEAN<br> ONLINE CHTESSEL BIOGENIC FLUXES (FOR TRANSPORT ERROR THESE USE THE CONTROL MEMBER FLUXES)</p> <p># MODEL #</p> <p>IFS-CYCLE 46R1<br> RESOLUTION TCO399 (~25km)<br> 137 VERTICAL LEVELS<br> ALL DATA PROVIDED HERE ARE EITHER COLUMN INTEGRATED MIXING RATIO (XCO2) OR SURFACE (LEVEL 137)<br> ALL DATA PROVIDED HERE ARE STANDARD DEVIATION ACROSS 50 ENSEMBLE MEMBERS<br> </p>
Text-figure 1. Mormotomyia hirsuta Austen, 3. Greatly enlarged. in A Remarkable Semi-Apterous Fly (Diptera) found in a Cave in East Africa, and representing a new Family, Genus, and Species.
Text-figure 1. Mormotomyia hirsuta Austen, 3. Greatly enlarged.
Mormotomyia hirsuta Austen, d. Hind leg. Greatly enlarged. in A Remarkable Semi-Apterous Fly (Diptera) found in a Cave in East Africa, and representing a new Family, Genus, and Species.
Mormotomyia hirsuta Austen, d. Hind leg. Greatly enlarged.
Mormotomyia hirsuta Austen, 8. Wing. Greatly enlarged. in A Remarkable Semi-Apterous Fly (Diptera) found in a Cave in East Africa, and representing a new Family, Genus, and Species.
Mormotomyia hirsuta Austen, 8. Wing. Greatly enlarged.
Text-figure 4. Mormotomyia hirsuta Austen, 8. Wing. Greatly enlarged. in A Remarkable Semi-Apterous Fly (Diptera) found in a Cave in East Africa, and representing a new Family, Genus, and Species.
Text-figure 4. Mormotomyia hirsuta Austen, 8. Wing. Greatly enlarged.
Momnotomyia hirsuta Austen, 3. Greatly enlarged. in A Remarkable Semi-Apterous Fly (Diptera) found in a Cave in East Africa, and representing a new Family, Genus, and Species.
Momnotomyia hirsuta Austen, 3. Greatly enlarged.
Fig. 1 in A new species of Ocyale (Araneae, Lycosidae) from Madagascar, with first observations on the biology of a representative in the genus
Fig. 1. Type locality of Ocyale ghost Jocque M. & Jocqué R. sp. nov.
Data from: The weight of the crust: biomass of crustose lichens in tropical dry forest represents more than half of foliar biomass
In recent years, our ecological knowledge of tropical dry forests has increased dramatically. However, the functional contributions of whole ecosystem components, such as lichens, remain mostly unknown. In these forests, the abundance of epiphyte crustose lichens is responsible for the characteristic white bark on most woody plants, conspicuous during the dry season, but the amount of resources that the lichen component represents remains unexplored. We estimated lichen biomass in a Mexican tropical dry forest using the bark area of trees, the dry mass of lichens per unit area and the percentage of bark covered by lichens, together with previously known tree densities. The lowest 2.5 m of the forests main trunks contained 188 kg/ha of lichen biomass, with lichens covering 85% of the available bark for trees <12 cm DBH and 38% for trees >12 cm. Total epiphytic lichen biomass was 1.34–1.99 Mg/ha. Lichen biomass represented 61% of the foliar biomass in the forest. To our knowledge, this is the first time that a lichen biomass estimate is provided for an ecosystem in which crustose lichens are the dominant lichen growth form. Crustose lichens are typically considered to contribute little to the total lichen biomass and to be difficult to include in ecological analyses. The high lichen biomass in this ecosystem implies a significant ecological role which so far is unexplored. We suggest the crustose lichen component should not be underestimated a priori in ecological studies, especially in ecosystems with abundant lichen cover.
Data Set of Interviews with Industry Representatives on Smart Dust
<p>Data Set of Interviews with Industry Representatives on Smart Dust</p> <p>This data set comprises the following documents:</p> <ul> <li>Coding scheme</li> <li>Model development</li> <li>Interview guideline</li> </ul>
Geometric morphometric wing analysis represents a robust tool to identify female mosquitoes (Diptera: Culicidae) in Germany
<p>Accurate species identification is the prerequisite to assess the relevance of mosquito specimens, but is often hindered by missing or damaged morphological features. The present study analyses the applicability of wing geometric morphometrics as a low-cost and practical alternative to identify native mosquitoes in Germany. Wing pictures were collected for 502 female mosquitoes of five genera and 19 species from 80 sampling sites. The reliable species identification based on interspecific wing geometry of 18 landmarks per specimen was tested. Leave-one-out cross validation revealed an overall accuracy of 99% for the genus and 90% for the species identification. Misidentifications were mainly due to three pairings of <i>Aedes</i> species: <i>Aedes annulipes</i> vs. <i>Aedes cantans</i>, <i>Aedes cinereus</i> vs. <i>Aedes rossicus</i> and <i>Aedes communis </i>vs. <i>Aedes punctor.</i> Cytochrome oxidase subunit I (COI) gene region was sequenced to validate the morphological and morphometric identification. Similar to the results of the morphometric analysis, the same problematic three <i>Aedes</i>-pairs clustered, but most other species could be well separated. Overall, our study underpins that morphometric wing analysis is a robust tool for reliable mosquito identification, which reach the accuracy of COI barcoding.</p>
Data from: The Chord-Normalized Expected Species Shared (CNESS)-distance represents a superior measure of species turnover patterns
<p>1. Measures of β-diversity characterizing the difference in species composition between samples are commonly used in ecological studies. Nonetheless, commonly used dissimilarity measures require high sample completeness, or at least similar sample sizes between samples. In contrast, the Chord-Normalized Expected Species Shared (CNESS) dissimilarity measure calculates the probability of collecting the same set of species in random samples of a standardized size, and hence is not sensitive to completeness or size of compared samples. To date, this index has enjoyed limited use due to difficulties in its calculation and scarcity of studies systematically comparing it with other measures.</p> <p>2. Here, we developed a novel R function that enables users to calculate ESS (Expected Species Shared)-associated measures. We evaluate the performance of the CNESS index based on simulated datasets of known species distribution structure, and compared CNESS with more widespread dissimilarity measures (Bray-Curtis index, Chao-Sørensen index, and proportionality based Euclidean distances) for varying sample completeness and sample sizes.</p> <p>3. Simulation results indicated that for small sample size (m) values, CNESS chiefly reflects similarities in dominant species, while selecting large m values emphasizes differences in the overall species assemblages. Permutation tests revealed that CNESS has a consistently low CV (coefficient of variation) even where sample completeness varies, while the Chao-Sørensen index has a high CV particularly for low sampling completeness. CNESS distances are also more robust than other indices with regards to undersampling, particularly when chiefly rare species are shared between two assemblages.</p> <p>4. Our results emphasize the superiority of CNESS for comparisons of samples diverging in sample completeness and size, which is particularly important in studies of highly mobile and species-rich taxa where sample completeness is often low. Via changes in the sample size parameter m, CNESS furthermore cannot only provide insights into the similarity of the overall distribution structure of shared species, but also into the differences in dominant and rare species, hence allowing additional, valuable insights beyond the capability of more widespread measures.<br> </p>
Data from: Unhatched eggs represent the invisible fraction in two wild bird populations
<p>Prenatal mortality is typically overlooked in population studies, which biases evolutionary inference by confounding selection and inheritance. Birds represent an opportunity to include this 'invisible fraction' if each egg contains a zygote but whether hatching failure is caused by fertilisation failure versus prenatal mortality is largely unknown. We quantified fertilisation failure rates in two bird species that are popular systems for studying evolutionary dynamics in the wild. over three years, finding that overwhelming majorities (99.9%) of laid eggs were fertilised. These systems thus present opportunities to eliminate the invisible fraction from life-history data.</p>
Supporting data: Structure-based Markov random field model for representing evolutionary constraints on functional sites
<p>Supporting data for the paper:</p> <p>Chan-Seok Jeong, Dongsup Kim. Structure-based Markov random field model for representing evolutionary constraints on functional sites. Submitted. (2015)</p> <p>See 'README' for a description of the contents.</p>
Representative structures for Trypsin-Benzamidine conformation-space network
<p>These structures were used for the analysis presented in the paper "Multiple Ligand Unbinding Pathways and Ligand-Induced Destabilization Revealed by WExplore" published in Biophysical Journal, 112, February 28, 2017. There is a tar ball (allframes.tgz) containing 4000 structures in PDB format, as well as a PDF file of the network with labels for each of the 4000 states (network_labels.pdf). Unpack the tar ball with: "tar xzf allframes.tgz".</p> <p> </p>
Figure 2. - Phylogenetic relationships among Dicronocephalus species reconstructed with Bayesian inference using COI sequences. Numbers above branches indicate ML bootstrap values and Bayesian posterior probabilities. Numbers below branches are bootstrap, symmetric resampling, and jacknife support from parsimony searches, respectively. Scale bar represents 10% nucleotide mutation rate.
Figure 2. - Phylogenetic relationships among Dicronocephalus species reconstructed with Bayesian inference using COI sequences. Numbers above branches indicate ML bootstrap values and Bayesian posterior probabilities. Numbers below branches are bootstrap, symmetric resampling, and jacknife support from parsimony searches, respectively. Scale bar represents 10% nucleotide mutation rate.
Figure 2. - Bayesian (GTR+Γ+I and HKY+Γ models) and maximum likelihood 50% majority-rule consensus tree. Numbers in the nodes represent posterior probabilities (GTR+Γ+I and HKY+Γ, respectively), and bootstrap value for maximum likelihood and parsimony analyses, respectively. c1–Bragança, Pará; c2–Santa Maria do Pará, Pará; c3–National Forest of Amapá, Amapá; c4–Belém, Pará; i1–Solimões River, near Manaus, Amazonas; i2–Xingu River, Altamira, Pará; i3 and i4–Itacoatiara, Amazonas. MYBP–million years before present.
Figure 2. - Bayesian (GTR+Γ+I and HKY+Γ models) and maximum likelihood 50% majority-rule consensus tree. Numbers in the nodes represent posterior probabilities (GTR+Γ+I and HKY+Γ, respectively), and bootstrap value for maximum likelihood and parsimony analyses, respectively. c1–Bragança, Pará; c2–Santa Maria do Pará, Pará; c3–National Forest of Amapá, Amapá; c4–Belém, Pará; i1–Solimões River, near Manaus, Amazonas; i2–Xingu River, Altamira, Pará; i3 and i4–Itacoatiara, Amazonas. MYBP–million years before present.
Figure 4. - Phylogenetic relationships among Dicronocephalus species reconstructed with Bayesian inference using COI and 16S rRNA sequences. Numbers above branches indicate ML bootstrap values and Bayesian posterior probabilities. Numbers below branches are bootstrap, symmetric resampling, and jacknife support from parsimony searches, respectively. Scale bar represents 10% nucleotide mutation rate.
Figure 4. - Phylogenetic relationships among Dicronocephalus species reconstructed with Bayesian inference using COI and 16S rRNA sequences. Numbers above branches indicate ML bootstrap values and Bayesian posterior probabilities. Numbers below branches are bootstrap, symmetric resampling, and jacknife support from parsimony searches, respectively. Scale bar represents 10% nucleotide mutation rate.
Figure 3. - Phylogenetic relationships among Dicronocephalus species reconstructed with Bayesian inference using 16S rRNA sequences. Numbers above branches indicate ML bootstrap values and Bayesian posterior probabilities. Numbers below branches are bootstrap, symmetric resampling, and jacknife support from parsimony searches, respectively. Scale bar represents 10% nucleotide mutation rate.
Figure 3. - Phylogenetic relationships among Dicronocephalus species reconstructed with Bayesian inference using 16S rRNA sequences. Numbers above branches indicate ML bootstrap values and Bayesian posterior probabilities. Numbers below branches are bootstrap, symmetric resampling, and jacknife support from parsimony searches, respectively. Scale bar represents 10% nucleotide mutation rate.
Figure 1. - World map representing all the locations mentioned in the dataset. Areas of particular interest are represented with the same colour (⬤ Madagascar, ⬤ Western Indian Ocean, ⬤ Papuasia, ⬤ New Caledonia, ⬤ South Pacific). Grey spots gather all the other locations.
Figure 1. - World map representing all the locations mentioned in the dataset. Areas of particular interest are represented with the same colour (⬤ Madagascar, ⬤ Western Indian Ocean, ⬤ Papuasia, ⬤ New Caledonia, ⬤ South Pacific). Grey spots gather all the other locations.
Figure 1. - Representative specimens of the nine Epicephala species in Japan. Wing pattern of Epicephalaparasitica is sexually dimorphic, so specimens of both sexes are shown for this species. A Epicephalaanthophilia (Amami Island, Kagoshima, ♀, holotype) B Epicephalabipollenella (Henoko, Okinawa, ♀) C Epicephalalanceolatella (Cape Hedo, Okinawa, ♀, holotype) D Epicephalaperplexa (Cape Hedo, Okinawa, ♀, holotype) E Epicephalaobovatella (Tomogashima, Wakayama, ♂, paratype) F Epicephalacorruptrix (Takae, Okinawa, ♀, holotype) G Epicephalavitisidaea (Yona, Okinawa, ♀) H Epicephalaparasitica (Yonaguni Island, Okinawa, ♀, holotype) I Epicephalaparasitica (Hateruma Island, Okinawa, ♂) J Epicephalanudilingua (Watarase-yusuichi, Tochigi, ♀, holotype). Scale bar: 5 mm.
Figure 1. - Representative specimens of the nine Epicephala species in Japan. Wing pattern of Epicephalaparasitica is sexually dimorphic, so specimens of both sexes are shown for this species. A Epicephalaanthophilia (Amami Island, Kagoshima, ♀, holotype) B Epicephalabipollenella (Henoko, Okinawa, ♀) C Epicephalalanceolatella (Cape Hedo, Okinawa, ♀, holotype) D Epicephalaperplexa (Cape Hedo, Okinawa, ♀, holotype) E Epicephalaobovatella (Tomogashima, Wakayama, ♂, paratype) F Epicephalacorruptrix (Takae, Okinawa, ♀, holotype) G Epicephalavitisidaea (Yona, Okinawa, ♀) H Epicephalaparasitica (Yonaguni Island, Okinawa, ♀, holotype) I Epicephalaparasitica (Hateruma Island, Okinawa, ♂) J Epicephalanudilingua (Watarase-yusuichi, Tochigi, ♀, holotype). Scale bar: 5 mm.
ScienceDex guides
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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.