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647 results for “historical data”
Figure 8 from: Faulwetter S, Pafilis E, Fanini L, Bailly N, Agosti D, Arvanitidis C, Boicenco L, Catapano T, Claus S, Dekeyzer S, Georgiev T, Legaki A, Mavraki D, Oulas A, Papastefanou G, Penev L, Sautter G, Schigel D, Senderov V, Teaca A, Tsompanou M (2016) EMODnet Workshop on mechanisms and guidelines to mobilise historical data into biogeographic databases. Research Ideas and Outcomes 2: e10445. https://doi.org/10.3897/rio.2.e10445
Figure 8 - Plazi workflow: from the publication through different levels of data processing to final availability of structured data.
Figure 5 from: Faulwetter S, Pafilis E, Fanini L, Bailly N, Agosti D, Arvanitidis C, Boicenco L, Catapano T, Claus S, Dekeyzer S, Georgiev T, Legaki A, Mavraki D, Oulas A, Papastefanou G, Penev L, Sautter G, Schigel D, Senderov V, Teaca A, Tsompanou M (2016) EMODnet Workshop on mechanisms and guidelines to mobilise historical data into biogeographic databases. Research Ideas and Outcomes 2: e10445. https://doi.org/10.3897/rio.2.e10445
Figure 5 - Biodiversity related articles and instructions to the authors available on the Biodiversity Literature Repository home page.
Figure 2 from: Faulwetter S, Pafilis E, Fanini L, Bailly N, Agosti D, Arvanitidis C, Boicenco L, Catapano T, Claus S, Dekeyzer S, Georgiev T, Legaki A, Mavraki D, Oulas A, Papastefanou G, Penev L, Sautter G, Schigel D, Senderov V, Teaca A, Tsompanou M (2016) EMODnet Workshop on mechanisms and guidelines to mobilise historical data into biogeographic databases. Research Ideas and Outcomes 2: e10445. https://doi.org/10.3897/rio.2.e10445
Figure 2 - Stations without coordinates (red box) are commonly listed, as well as non-SI units, here: depth as fathoms (based on a slide by Aglaia Legaki, Gabriella Papastefanou and Marilena Tsompanou).
Figure 4 from: Faulwetter S, Pafilis E, Fanini L, Bailly N, Agosti D, Arvanitidis C, Boicenco L, Catapano T, Claus S, Dekeyzer S, Georgiev T, Legaki A, Mavraki D, Oulas A, Papastefanou G, Penev L, Sautter G, Schigel D, Senderov V, Teaca A, Tsompanou M (2016) EMODnet Workshop on mechanisms and guidelines to mobilise historical data into biogeographic databases. Research Ideas and Outcomes 2: e10445. https://doi.org/10.3897/rio.2.e10445
Figure 4 - Complex natural language features that can lead to incorrect species-occurrence extraction (based on a slide by Aglaia Legaki, Gabriella Papastefanou and Marilena Tsompanou).
Figure 6 from: Faulwetter S, Pafilis E, Fanini L, Bailly N, Agosti D, Arvanitidis C, Boicenco L, Catapano T, Claus S, Dekeyzer S, Georgiev T, Legaki A, Mavraki D, Oulas A, Papastefanou G, Penev L, Sautter G, Schigel D, Senderov V, Teaca A, Tsompanou M (2016) EMODnet Workshop on mechanisms and guidelines to mobilise historical data into biogeographic databases. Research Ideas and Outcomes 2: e10445. https://doi.org/10.3897/rio.2.e10445
Figure 6 - Calman (1906) is available in BLR as https://zenodo.org/record/14941. The taxonomic treatment of Leucon longirostris G.O. Sars (shown above) extracted from this expedition document is also avaible in BLR: https://zenodo.org/record/14942. Both links have unique DOIs assigned to them and thus are also retrievable as https://doi.org/10.5281/zenodo.14941, and https://doi.org/10.5281/zenodo.14942, accordingly.
Figure 1 from: Faulwetter S, Pafilis E, Fanini L, Bailly N, Agosti D, Arvanitidis C, Boicenco L, Catapano T, Claus S, Dekeyzer S, Georgiev T, Legaki A, Mavraki D, Oulas A, Papastefanou G, Penev L, Sautter G, Schigel D, Senderov V, Teaca A, Tsompanou M (2016) EMODnet Workshop on mechanisms and guidelines to mobilise historical data into biogeographic databases. Research Ideas and Outcomes 2: e10445. https://doi.org/10.3897/rio.2.e10445
Figure 1 - Workflow depicting the process of manually extracting data from legacy literature workflow, as currently performed in in EMODnet WP4. Abbreviations: OCR = Optical Character Recognition; OBIS = Ocean Biogeographic Information System; DwC = Darwin Core; IPT = Integrated Publishing Toolkit; medOBIS = Mediterranean Ocean Biogeographic Information System, GBIF = Global Biodiversity Information Facility
Data of Building information modelling (BIM), Historic BIM (HBIM), Digital Twins and IoT
Open the record for dataset details and reuse information.
considered that it was present. Due to the lack of recent data and the limited information sup- plied by previous authors for Angolan specimens, the presence of L. viridis in Angola is questionable. MAP 74. Distribution of Leptopelis viridis in Angola. in Diversity and Distribution of the Amphibians and Terrestrial Reptiles of Angola Atlas of Historical and Bibliographic Records (1840-2017)
considered that it was present. Due to the lack of recent data and the limited information sup- plied by previous authors for Angolan specimens, the presence of L. viridis in Angola is questionable. MAP 74. Distribution of Leptopelis viridis in Angola.
Norte Pronvice. Cabinda: "Chinchoxo" [-5.10000, 12.10000] (Peters 1877a:615; Bocage 1895a:81); "Cabinda" [-5.55000, 12.18333] (Frade 1963:252). Lunda Norte: "Dundo" [-7.36667, 20.83333] (Laurent 1954:43; Thys van den Audenaerde 1966:32). Taxonomic and distributional notes: Kelly et al. (2011) provided molecular phylogenetic data to support the inclusion of this taxon along with the B. fuliginosus complex within a monophyletic Boaedon, separate from Lamprophis sensu stricto. MAP 289. Distribution of Boaedon olivaceus in Angola. in Diversity and Distribution of the Amphibians and Terrestrial Reptiles of Angola Atlas of Historical and Bibliographic Records (1840-2017)
Norte Pronvice. Cabinda: "Chinchoxo" [-5.10000, 12.10000] (Peters 1877a:615; Bocage 1895a:81); "Cabinda" [-5.55000, 12.18333] (Frade 1963:252). Lunda Norte: "Dundo" [-7.36667, 20.83333] (Laurent 1954:43; Thys van den Audenaerde 1966:32). Taxonomic and distributional notes: Kelly et al. (2011) provided molecular phylogenetic data to support the inclusion of this taxon along with the B. fuliginosus complex within a monophyletic Boaedon, separate from Lamprophis sensu stricto. MAP 289. Distribution of Boaedon olivaceus in Angola.
mapbiomas_lu_historical_data
<p>Brazilian land use data from 1985 to 2017 derived from Project MapBiomas - Collection 3.1 to be used as historical data in MAgPIE-Brazil.</p>
Data from: Phylogenetic covariance probability: confidence and historical associations
The correlation that exists among multiple cladograms is often taken as evidence of some underlying macroevolutionary phenomenon common to the histories of those clades and, thus, as an explanation of the patterns of association of the constituent taxa. Such studies have various forms, the most common of which are cladistic biogeography and host--parasite coevolution. The issue of confidence has periodically been a theoretical consideration of vicariance biogeographers but in practice has been largely ignored by others. Previous approaches to assessing confidence in historical associations are examined here in relation to the difference between simple-event and cumulative probabilities and in relation to the restrictiveness of joint hypothesis testing. The phylogenetic covariance probability (PCP) test, a novel approach to assessing confidence in hypotheses of historical association, employs the empirical protocol of Brooks parsimony analysis (BPA) in an iterative, computer-intensive randomization routine. The PCP value consists of the frequency with which a solution as efficient or more efficient than the observed hypothesis of correlated phylogeny is achieved with random associations (e.g., of parasites and hosts or of taxa and areas). Because only the associations, and not the contributing phylogenies, are subjected to randomization, the test is not prone to certain criticisms leveled at other cladistic randomization routines. The behavior of the PCP test is examined in relation to eight published studies of historical association. This test is appropriately sensitive to the degrees of freedom allowed by the number of contributing clades and the number of taxa in those clades, to the extent of noncorrelated associations in the observed hypothesis, and to the relative information content contributing to that hypothesis.
Data from: Revisiting the Iberian honey bee (Apis mellifera iberiensis) contact zone: maternal and genome-wide nuclear variation provide support for secondary contact from historical refugia
Dissecting diversity patterns of organisms endemic to Iberia has been truly challenging for a variety of taxa, and the Iberian honey bee is no exception. Surveys of genetic variation in the Iberian honey bee are among the most extensive for any honey bee subspecies. From these, differential and complex patterns of diversity have emerged, which have yet to be fully resolved. Here, we used a genome-wide data set of 309 neutrally tested single nucleotide polymorphisms (SNPs), scattered across the 16 honey bee chromosomes, which were genotyped in 711 haploid males. These SNPs were analysed along with an intergenic locus of the mtDNA, to reveal historical patterns of population structure across the entire range of the Iberian honey bee. Overall, patterns of population structure inferred from nuclear loci by multiple clustering approaches and geographic cline analysis were consistent with two major clusters forming a well-defined cline that bisects Iberia along a northeastern–southwestern axis, a pattern that remarkably parallels that of the mtDNA. While a mechanism of primary intergradation or isolation by distance could explain the observed clinal variation, our results are more consistent with an alternative model of secondary contact between divergent populations previously isolated in glacial refugia, as proposed for a growing list of other Iberian taxa. Despite current intense honey bee management, human-mediated processes have seemingly played a minor role in shaping Iberian honey bee genetic structure. This study highlights the complexity of the Iberian honey bee patterns and reinforces the importance of Iberia as a reservoir of Apis mellifera diversity.
Genotype and individual data for genetic structure in Louisiana Iris species reveals patterns of recent and historical admixture
<p><b><span>Premise: </span></b><span>When divergent lineages come into secondary contact reproductive isolation may be incomplete, thus providing an opportunity to investigate how speciation is manifested in the genome. The Louisiana Irises (<i>Iris</i>, series <i>Hexagonae</i>) comprise a group of three or more ecologically and reproductively divergent lineages that can produce hybrids where they come into contact. In this study we sought to estimate standing genetic variation to understand the current distribution of population structure in the Louisiana Irises.</span></p> <p><b><span>Methods:</span></b><span> We used genotyping-by-sequencing techniques to sample the genomes of Louisiana Iris species across their ranges. Twenty populations were sampled (total n=632) across 11,249 loci. Population genetic data were assessed using ENTROPY and PCA models. </span></p> <p><b><span>Results: </span></b><span>We discovered evidence for interspecific gene flow in parts of the range and revealed patterns of population structure at odds with widely accepted nominal taxonomy. Undescribed hybrid populations were discovered that were designated as belonging to the <i>I. brevicaulis</i> lineage. <i>Iris nelsonii </i>shared significant ancestry with only one of the purported parent species, <i>I. fulva, </i>evidence inconsistent with a hybrid origin.</span></p> <p><b><span>Conclusions: </span></b><span>This study provides several key findings important to the investigation of standing genetic variation in the Louisiana Iris species complex. <i>Iris brevicaulis</i> has a large amount of genetic diversity within it relative to the other nominal species. In addition, this study has discovered a previously unknown hybrid zone between <i>I. brevicaulis </i>and <i>I. hexagona</i> along the Texas coast. Finally, <i>I. nelsonii</i> does not appear to have mixed ancestry from three parental taxa as has been the longstanding hypothesis. </span></p>
Figure 2 from: Amori G, Aloise G, Luiselli L (2014) Modern analyses on an historical data set: skull morphology of Italian red squirrel populations. ZooKeys 368: 79-89. https://doi.org/10.3897/zookeys.368.4691
Figure 2 - PCA of skull measurements (VARIMAX rotation applied) based on Cavazza's (1913) dataset. Eigenvalues: component 1 = 2.559; component 2 = 1.099.
Figure 1 from: Amori G, Aloise G, Luiselli L (2014) Modern analyses on an historical data set: skull morphology of Italian red squirrel populations. ZooKeys 368: 79-89. https://doi.org/10.3897/zookeys.368.4691
Figure 1 - Map of Italy showing the localities where squirrels were collected according to Cavazza (1913). 1 Porlezza 2 Lanzo 3 Central Alps 4 Alpi Piemontesi 5 Biellese 6 Lugano 7 Bassano del Grappa 8 Buggiolo 9 Lombardia 10 Emilia 11 Tuscany 12 Liguria 13 Neapolitan (Campania) 14 Calabria.
Figure 3 from: Amori G, Aloise G, Luiselli L (2014) Modern analyses on an historical data set: skull morphology of Italian red squirrel populations. ZooKeys 368: 79-89. https://doi.org/10.3897/zookeys.368.4691
Figure 3 - Neighbor joining dendrogram of skull measurements (with 10,000 bootstraps) based on Cavazza's (1913) dataset.
Figure 6 from: Faulwetter S, Pafilis E, Fanini L, Bailly N, Agosti D, Arvanitidis C, Boicenco L, Capatano T, Claus S, Dekeyzer S, Georgiev T, Legaki A, Mavraki D, Oulas A, Papastefanou G, Penev L, Sautter G, Schigel D, Senderov V, Teaca A, Tsompanou M (2016) EMODnet Workshop on mechanisms and guidelines to mobilise historical data into biogeographic databases. Research Ideas and Outcomes 2: e9774. https://doi.org/10.3897/rio.2.e9774
Figure 6 - Calman 1906 is available in BLR as https://zenodo.org/record/14941. The taxonomic treatment of Leucon longirostris G.O. Sars (shown above) extracted from this expedition document is also avaible in BLR: https://zenodo.org/record/14942. Both links have unique DOIs assigned to them and thus are also retrievable as https://doi.org/10.5281/zenodo.14941, and https://doi.org/10.5281/zenodo.14942, accordingly.
Figure 2 from: Faulwetter S, Pafilis E, Fanini L, Bailly N, Agosti D, Arvanitidis C, Boicenco L, Capatano T, Claus S, Dekeyzer S, Georgiev T, Legaki A, Mavraki D, Oulas A, Papastefanou G, Penev L, Sautter G, Schigel D, Senderov V, Teaca A, Tsompanou M (2016) EMODnet Workshop on mechanisms and guidelines to mobilise historical data into biogeographic databases. Research Ideas and Outcomes 2: e9774. https://doi.org/10.3897/rio.2.e9774
Figure 2 - Stations without coordinates (red box) are commonly listed, as well as non-SI units, here: depth as fathoms (based on a slide by Aglaia Legaki, Gabriella Papastefanou and Marilena Tsompanou).
Figure 9 from: Faulwetter S, Pafilis E, Fanini L, Bailly N, Agosti D, Arvanitidis C, Boicenco L, Capatano T, Claus S, Dekeyzer S, Georgiev T, Legaki A, Mavraki D, Oulas A, Papastefanou G, Penev L, Sautter G, Schigel D, Senderov V, Teaca A, Tsompanou M (2016) EMODnet Workshop on mechanisms and guidelines to mobilise historical data into biogeographic databases. Research Ideas and Outcomes 2: e9774. https://doi.org/10.3897/rio.2.e9774
Figure 9 - Top: to retrieve a scanned BHL book document from BHL click on the "Download Contents" icon on the top-right and select to browse the corresponding web page on the Internet Archive ("View at Internet Archive"). Bottom: The link to the jpeg2000 (JP2) image is found on the bottom right. Sources: top: http://biodiversitylibrary.org/page/9663476; bottom: https://archive.org/details/mittheilungenaus17staz.
Figure 8 from: Faulwetter S, Pafilis E, Fanini L, Bailly N, Agosti D, Arvanitidis C, Boicenco L, Capatano T, Claus S, Dekeyzer S, Georgiev T, Legaki A, Mavraki D, Oulas A, Papastefanou G, Penev L, Sautter G, Schigel D, Senderov V, Teaca A, Tsompanou M (2016) EMODnet Workshop on mechanisms and guidelines to mobilise historical data into biogeographic databases. Research Ideas and Outcomes 2: e9774. https://doi.org/10.3897/rio.2.e9774
Figure 8 - Plazi workflow: from the publication through different levels of data processing to final availability of structured data.
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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.