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3,101 results for “Historical”
FIGURE 4 in History and historical DNA: Identity of Chelodina intergularis Fry, 1915 and type localities of C. intergularis and C. rugosa Ogilby, 1890
FIGURE 4. Comparison of (A) the holotype of Chelodina rugosa (AM R6256), (B) the holotype of C. intergularis (AM R6255) and (C) an individual of C. burrungandjii sensu stricto (UC 2101; redrawn from Thomson et al. 2000). Not to scale. Epidermal scutes (blue): G = gular; H = humeral; I = intergular; P = pectoral. Bony plates (black): Epi = epiplastron; Ent = entoplastron; Hyo = hyoplastron. In AM R6256 the bony sutures are visible at closer inspection through the translucent epidermal scutes. Drawings: S. Thomson.
FIGURE 2 in History and historical DNA: Identity of Chelodina intergularis Fry, 1915 and type localities of C. intergularis and C. rugosa Ogilby, 1890
FIGURE 2. Maximum Likelihood tree using near-complete mitogenomes of Chelodina species, rooted with Elseya flaviventralis. Numbers at nodes are bootstrap values and posterior probabilities from a Bayesian tree of the same topology. Asterisks indicate maximum support under both approaches. Species names do not imply validity or nomenclatural availability; accepted names of terminals on the right in bold. Sequences from type specimens are flagged; that of the C. intergularis type is highlighted in red. Codes following species names are GenBank/ENA accession numbers. For specimen/voucher tissue information, see Table 1. The mitogenomic phylogeny conflicts with subgenera and reflects a complex pattern of transspecific introgression and mitochondrial capture (Hodges 2015; Kehlmaier et al. 2019).
FIGURE 1 in History and historical DNA: Identity of Chelodina intergularis Fry, 1915 and type localities of C. intergularis and C. rugosa Ogilby, 1890
FIGURE 1. Holotype of Chelodina intergularis, Australian Museum, Sydney (AM R6255). Photos: G. Shea.
Figure 8 in Integrative taxonomy using historical specimens provides evidence for a single species of bushbuck, Tragelaphus scriptus (Mammalia: Bovidae)
Figure 8. Distribution of bushbuck crania according to size (log centroid size; A) and along the first three principal components of shape (B–D). Differences in size are non-significant between subclades and when assessed separately for males and females, despite the attainment of a larger maximum size in sylvaticus males. Differences in shape between subclades are significant, but only for males, not females.
Figure 5. A in Integrative taxonomy using historical specimens provides evidence for a single species of bushbuck, Tragelaphus scriptus (Mammalia: Bovidae)
Figure 5. A, plot of all specimens along the first two principal components (PCs) of shape. B, cranial outlines transformed via thin-plate spline from the mean shape to the extremes of PCs 1 and 2. Note the separation of subclades along PC1, which largely reflects sexual dimorphism and size allometry (see Fig. 3). The key is the same as that shown in Figure 1; labels refer to specimens in Table 1.
Figure 7 in Integrative taxonomy using historical specimens provides evidence for a single species of bushbuck, Tragelaphus scriptus (Mammalia: Bovidae)
Figure 7. Median-joining network of 28 sequences from bushbuck specimens, with missing and ambiguous sites removed. [Three sequences with many gaps (ZMB Mam 32456, ZMB Mam 40389 and ZMB Mam 107683) were removed before the analysis.] Branches are labelled with mutation distances; unlabelled branches have a distance of one. Note the structure, the long branch separating clades and the Tanzania/Nigeria haplogroup. One reference sequence was included from both clades (Table 2).
Figure 3 in Integrative taxonomy using historical specimens provides evidence for a single species of bushbuck, Tragelaphus scriptus (Mammalia: Bovidae)
Figure 3. Plots of size allometry examined via ln-transformed centroid size and principal component 1 (PC1) (A); or regression of shape (B). Note the strong influence of size on shape. The key is the same as that shown in Figure 1; labels refer to specimens in Table 1.
Figure 2 in Integrative taxonomy using historical specimens provides evidence for a single species of bushbuck, Tragelaphus scriptus (Mammalia: Bovidae)
Figure 2. Surface model of Tragelaphus scriptus cranium in dorsal, lateral and ventral views, with points representing 53 digitized landmarks used to characterize cranial shape (22 blue landmarks mirrored on left and right sides; 9 orange medial landmarks). See the Supporting Information (Table S1) for anatomical descriptions of the locations of landmarks.
Figure 6 in Integrative taxonomy using historical specimens provides evidence for a single species of bushbuck, Tragelaphus scriptus (Mammalia: Bovidae)
Figure 6. Phylomorphospace shows poor correspondence between mitogenomic relationships and morphological differences. Axes refer to the first and second principal components (PC1 and PC2) of the geometric morphometric analysis. The key is the same as that shown in Figure 1; labels refer to specimens in Table 1. Note that this figure includes only specimens for which mitochondrial DNA was extracted.
Figure 1 in Integrative taxonomy using historical specimens provides evidence for a single species of bushbuck, Tragelaphus scriptus (Mammalia: Bovidae)
Figure 1. Map of specimens with location information used in this study (39 individuals; four additional specimens did not have location information and are not shown here). Mitochondrial subclade designations (scriptus and sylvaticus) are based on the molecular phylogeny, and are designated NA (grey) where this could not be determined. Location coordinates are based on locality information on historical specimens and were estimated as closely as possible. The modern range of the bushbuck is shown in grey (IUCN SSC Antelope Specialist Group 2016). See Supporting Information, Fig. S2 for a map labelled with specimen numbers and countries.
DIVINE: Andalusia Agroclimatic Information Network Historic Datasets - CADIZ - (June 23 - May 24)
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DIVINE: Andalusia Agroclimatic Information Network Historic Datasets - HUELVA - (June 23 - May 24)
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DIVINE: Andalusia Agroclimatic Information Network Historic Datasets - CORDOBA - (June 23 - May 24)
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DIVINE: Andalusia Agroclimatic Information Network Historic Datasets - SEVILLA - (June 23 - May 24)
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DIVINE: Andalusia Agroclimatic Information Network Historic Datasets - GRANADA - (June 23 - May 24)
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DIVINE: Andalusia Agroclimatic Information Network Historic Datasets - ALMERIA - (June 23 - May 24)
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DIVINE: Andalusia Agroclimatic Information Network Historic Datasets - JAEN - (June 23 - May 24)
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Haplotype analysis of the mitochondrial DNA d-loop region reveals the maternal origin and historical dynamics among the indigenous goat populations in east and west of the Democratic Republic of Congo (DRC)
<p><span>This study aimed at assessing haplotype diversity and population dynamics of three Congolese indigenous goat populations that included Kasai goat (KG), small goat (SG), and dwarf goat (DG) of the Democratic Republic of Congo (DRC). The 1,169 bp <em>d-loop</em> region of mitochondrial DNA (mtDNA) was sequenced for 339 Congolese indigenous goats. The total length of sequences was used to generate the haplotypes and evaluate their diversities, whereas the hypervariable region (HVI, 453 bp) was analyzed to define the maternal variation and the demographic dynamic. A total of 568 segregating sites that generated 192 haplotypes were observed from the entire <em>d-loop</em> region (1,169 bp <em>d-loop</em>). Phylogenetic analyses using reference haplotypes from the six globally defined goat mtDNA haplogroups showed that all the three Congolese indigenous goat populations studied clustered into the dominant haplogroup A, as revealed by the Neighbor-joining (NJ) tree and median-joining (MJ) network. Nine haplotypes were shared between the studied goats and goat populations from Pakistan (1 haplotype), Kenya, Ethiopia and Algeria (1 haplotype), Zimbabwe (1 haplotype), Cameroon (3 haplotypes), and Mozambique (3 haplotypes). The population pairwise analysis (<em>F<sub>ST</sub></em>) indicated a weak differentiation between the Congolese indigenous goat populations. Negative and significant (<em>p</em>-value < 0.05) values for <em>F</em>u's <em>F</em>s (-20.418) and Tajima's (-2.189) tests showed the expansion in the history of the three Congolese indigenous goat populations. These results suggest a weak differentiation and a single maternal origin for the studied goats. This information will contribute to the improvement of the management strategies and long-term conservation of indigenous goats in DRC</span><span>.</span></p>
Supplementary material to 'Collapse fragility analysis of historical masonry buildings considering in-plane and out-of-plane response of masonry walls'
<p>This repository provides the numerical models of buildings developed in OpenSees and the selected ground motions to perform IDAs referred to in the manuscript "<em>Collapse fragility analysis of historical masonry buildings considering in-plane and out-of-plane response of masonry walls</em>" submitted for publication in <em>Engineering Structures</em>.</p>
Historical snowfall precipitation data in the Apennine Mountains, Italy
<p>This database includes a large collection of quality-controlled and homogenized historical snow records measured in the 1951-2001 period in the Central and Southern Apennine Mountains (Italy). Such data have been manually digitized from the Hydrological Yearbooks of the Italian National Hydrological and Mareographic Service (hereafter, NHMS), the institution that managed the hydro-meteorological data collection in Italy from 1917 to 2002. More specifically, the rescued dataset includes the monthly observations of three different variables:</p> <p>· The snow cover duration (SCD), which is defined as total number of days in a given month with snow depth on the ground >=1 cm. This variable is available for 110 stations between 288 and 1430 m above the sea level (ASL).</p> <p>· The number of days with snowfall (NDS), which is total number of days in a given month on which the accumulated snowfall (i.e. the amount of fresh snow with respect to the previous observations) is at least 1 cm. This variable is available for 114 stations between 288 and 1430 m ASL.</p> <p>· The height of new snow (HN), which is defined as the monthly amount of fresh snow (expressed in cm). The monthly value is intended as the sum of daily HN data observed in a determined month. This variable is available for 120 stations between 288 and 1750 m ASL.</p> <p>Note that for HN variable, the data availability is restricted to the period 1971-2001.</p> <p>The considered dataset has been subjected to an accurate quality control consisting of several statistical tests: the gross error test, which flags the data that are above or below acceptable physical limits, the consistency test, which involves an inter-variable check, and the tolerance test, which is focused on the outlier detection. In addition, the homogeneity of the rescued time series has been checked using Climatol method (Guijarro, 2018). The latter is based on the Standard Normal Homogeneity Test (Alexandersson, 1986) for the identification of the breaks and on a linear regression approach for the adjustments (Easterling and Peterson, 1995). Climatol has been also employed for the filling of missing values.</p> <p>The database is structured into three different folders (one for each variable). In a determined folder, the user finds two files, one containing the main information regarding the available stations (code, station name, latitude and longitude (in decimal degrees) and altitude ASL (in m)), the other one the monthly time series for the considered variable.</p> <p>Note that the original data sources of this database, the Hydrological Yearbooks of the NHMS, are freely accessible in printed version (i.e. as scanned images in portable document format) through the Italian Institute for Environmental Protection and Research (ISPRA) website (http://www.bio.isprambiente.it/annalipdf).</p> <p>Additional information about the data rescue processing can be found in the preprint “Historical snowfall measurements in the Central and Southern Apennine Mountains: climatology, variability and trend”, open for discussion in The Cryosphere journal (https://doi.org/10.5194/egusphere-2024-1056).</p> <p> </p> <p><strong>References</strong></p> <p>Alexandersson, H.: A homogeneity test applied to precipitation data, J. Climatol., 6, 661–675, 1986.</p> <p>Easterling, D. R. and Peterson, T.C.: A new method for detecting and adjusting for undocumented discontinuities in climatological time series, International Journal Climatol.,15, 369–377, https://doi.org/10.1002/joc.3370150403, 1995.</p> <p>Guijarro, J. A.: Homogenization of climatic series with Climatol, Climatol manual, https://www.climatol.eu/homog_climatolen.pdf (last access: 15 February 2024), 2018.</p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
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