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90 results for “herbaria”
Linked collectors and determiners for: The University and Jepson Herbaria -- Algae.
Natural history specimen data linked to collectors and determiners held within, "The University and Jepson Herbaria -- Algae". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/e3dca178-5cef-456e-b3b0-6dc4b02bbd16">https://bionomia.net/dataset/e3dca178-5cef-456e-b3b0-6dc4b02bbd16</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/e3dca178-5cef-456e-b3b0-6dc4b02bbd16">https://gbif.org/dataset/e3dca178-5cef-456e-b3b0-6dc4b02bbd16</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: The University and Jepson Herbaria -- Vascular Plants.
Natural history specimen data linked to collectors and determiners held within, "The University and Jepson Herbaria -- Vascular Plants". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/83a49751-4282-481e-a847-1c5c224a0551">https://bionomia.net/dataset/83a49751-4282-481e-a847-1c5c224a0551</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/83a49751-4282-481e-a847-1c5c224a0551">https://gbif.org/dataset/83a49751-4282-481e-a847-1c5c224a0551</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: The University and Jepson Herbaria -- Bryophytes.
Natural history specimen data linked to collectors and determiners held within, "The University and Jepson Herbaria -- Bryophytes". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/5863759f-39ce-4575-b922-6c9c097fb93a">https://bionomia.net/dataset/5863759f-39ce-4575-b922-6c9c097fb93a</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/5863759f-39ce-4575-b922-6c9c097fb93a">https://gbif.org/dataset/5863759f-39ce-4575-b922-6c9c097fb93a</a>. Formatted as a Frictionless Data package.
F I G U R E 2 in Small and in-country herbaria are vital for accurate plant threat assessments: A case study from Peru
F I G U R E 2 The effect of including data from Peruvian herbaria upon estimated International Union for Conservation of Nature (IUCN) threat assessments. The percentage of species assessed as DD (Data Deficient, grey), LC (Least Concern, green), VU (Vulnerable, yellow), EN (Endangered, orange), and CR (Critically Endangered, red) based upon data from: Top, international herbaria, and bottom, Peruvian and international herbaria.
F I G U R E 3 in Small and in-country herbaria are vital for accurate plant threat assessments: A case study from Peru
F I G U R E 3 The effect of including data from different small and large herbaria upon estimated International Union for Conservation of Nature (IUCN) threat assessments. The percentage of species assessed as DD (Data Deficient, grey), LC (Least Concern, green), VU (Vulnerable, yellow), EN (Endangered, orange), and CR (Critically Endangered, red) based upon data from: top, large herbaria only (>1,000,000 sheets); middle, large and medium herbaria (>500,000 sheets); and bottom, large, medium, and small herbaria (all herbaria).
F I G U R E 1 in Small and in-country herbaria are vital for accurate plant threat assessments: A case study from Peru
F I G U R E 1 The proportion of specimens of Peruvian Begonia and Solanum held in Peruvian institutions (blue) versus international institutions (orange) in (a) the Global Biodiversity Information Facility (GBIF); (b) the Begonia Resource Centre and Solanaceae Source (see text for doi references for all datasets).
F I G U R E 4 in Small and in-country herbaria are vital for accurate plant threat assessments: A case study from Peru
F I G U R E 4 The effect of including data from herbaria in size order upon estimated International Union for Conservation of Nature (IUCN) threat assessments. (a) Percentage of species assessed as DD (Data Deficient, grey), LC (Least Concern, green), VU (Vulnerable, yellow), EN (Endangered, orange), and CR (Critically Endangered, red); (b) the size (number of accessions) of herbaria added (orange) and number of specimen records included (blue); (c) the mean range of species considered threatened when all data are considered. Dashed, vertical lines indicate the limits of large (>1,000,000 sheets) and medium (>500,000 sheets) herbaria. Grey shading indicates Peruvian herbaria. Selected herbaria are indicated in C. Herbarium abbreviations in panels B and C follow Thiers (2001).
Accounting for imperfect detection in data from museums and herbaria when modeling species distributions: Combining and contrasting data-level versus model-level bias correction
The digitization of museum collections as well as an explosion in citizen science initiatives has resulted in a wealth of data that can be useful for understanding the global distribution of biodiversity, provided that the well-documented biases inherent in unstructured opportunistic data are accounted for. While traditionally used to model imperfect detection using structured data from systematic surveys of wildlife, occupancy models provide a framework for modelling the imperfect collection process that results in digital specimen data. In this study, we explore methods for adapting occupancy models for use with biased opportunistic occurrence data from museum specimens and citizen science platforms using 7 species of Anacardiaceae in Florida as a case study. We explored two methods of incorporating information about collection effort to inform our uncertainty around species presence: (1) filtering the data to exclude collectors unlikely to collect the focal species and (2) incorporating collection covariates (collection type, time of collection, and history of previous detections) into a model of collection probability. We found that the best models incorporated both the background data filtration step as well as collector covariates. Month, method of collection and whether a collector had previously collected the focal species were important predictors of collection probability. Efforts to standardize meta-data associated with data collection will improve efforts for modeling the spatial distribution of a variety of species.
Genus Aconitum in Slovakia: a phenetic approach. S29: Database of specimens deposited in Slovakian herbaria
<p>This is full database of analyzed specimens of genus Aconitum deposited in Slovakian herbaria. The IDs correspond to number of photo made during the investigation (this is not a herbarium voucher ID!) and each of these photos can be requested from author for free.</p>
Accounting for imperfect detection in data from museums and herbaria when modeling species distributions: Combining and contrasting data-level versus model-level bias correction
Open the record for dataset details and reuse information.
Fig. 2 in Herbaria are a major frontier for species discovery
Fig. 2. Fraction of specimens remaining to be discovered against discovery time (I), for data from Kew Bulletin (blue lines) and Monographs (red lines). For each series, the central line shows the mean and the upper and lower lines show the 95% confidence limits on the mean. (A) All data: Mean I (and 95% confidence limits) to describe half the species is 23 y (22–25 y) for Kew and 28 y (25–34 y) for Monographs. (B) Specimens collected 1956 (the mean of C), fitted using Cox proportional hazards models: Mean I (and 95% confidence limits) to describe half the species is 32 y (31–33 y) for Kew Bulletin and 31 y (29–35 y) for Monographs. Note that the scales on the abscissa in A and B differ.
FIGURE 4 in Generic delimitation between Fragariocoptes and Sierraphytoptus (Acari: Eriophyoidea: Phytoptidae) and a supplementary description of Fragariocoptes gansuensis with remarks on searching for mummified eriophyoid mites in herbaria under UV light
FIGURE 4. Images showing the same mummy of Fragariocoptes gansuensis under white light (A) and ultraviolet light with wavelength 395 nm (B) and 365 nm (C). Scale bar = 200 µm. Note: brightness and contrast have not been digitally adjusted, so the images correctly indicate the observed differences; same focus and adjustments of video camera in all three images.
FIGURE 3 in Generic delimitation between Fragariocoptes and Sierraphytoptus (Acari: Eriophyoidea: Phytoptidae) and a supplementary description of Fragariocoptes gansuensis with remarks on searching for mummified eriophyoid mites in herbaria under UV light
FIGURE 3. CLSM images of a male (A) and a female (B & C) of Fragariocoptes setiger (Nalepa, 1894). A & C—ventral aspect; B—dorsal aspect. Scale bar = 30 µm.
FIGURE 7 in Generic delimitation between Fragariocoptes and Sierraphytoptus (Acari: Eriophyoidea: Phytoptidae) and a supplementary description of Fragariocoptes gansuensis with remarks on searching for mummified eriophyoid mites in herbaria under UV light
FIGURE 7. CLSM (A−F) and DICLM (J−I) images showing variation of the prodorsal shield ornamentation in males (A & B) and females (C−I) of Fragariocoptes gansuensis. Note: Images A−F represent specimens from Astrakhan, whereas images J−I correspond to specimens from herbarium. Scale bar = 10 µm.
FIGURE 8 in Generic delimitation between Fragariocoptes and Sierraphytoptus (Acari: Eriophyoidea: Phytoptidae) and a supplementary description of Fragariocoptes gansuensis with remarks on searching for mummified eriophyoid mites in herbaria under UV light
FIGURE 8. DICLM (A) and CLSM (B–G) images of seven females of F. gansuensis. A, B – coxigenital area; C—genital area; D—genital aperture; E, F and G—epigynium. Scale bar = 10 µm. Notation: a—ear-like flaps; b—suboral plate; c—rod-like apodeme; d—genital cuticle; e—thickened edge of genital cuticle; f—putative external opening of spermathecal tube; g – genital rim; h—postspermathecal part of longitudinal bridge; i—medial ramus of coxal apodeme; j—genital slit; k—genital coveflap.
FIGURE 2 in Generic delimitation between Fragariocoptes and Sierraphytoptus (Acari: Eriophyoidea: Phytoptidae) and a supplementary description of Fragariocoptes gansuensis with remarks on searching for mummified eriophyoid mites in herbaria under UV light
FIGURE 2. CLSM (A,B,D,E) and SEM (C) images of four females of Sierraphytoptus alnivagrans Keifer 1939. Scale bar: A−C = 15 µm; D and E = 30 µm. Note: in E, the cuticle anterior to the epigynium is damaged, therefore the corresponding area is dark; images C and D indicate the real direction of setae ve and sc, whereas in images A and B the setae changed their direction during slide making.
FIGURE 6 in Generic delimitation between Fragariocoptes and Sierraphytoptus (Acari: Eriophyoidea: Phytoptidae) and a supplementary description of Fragariocoptes gansuensis with remarks on searching for mummified eriophyoid mites in herbaria under UV light
FIGURE 6. CLSM images of two males of Fragariocoptes gansuensis. A – ventral view of anterior half of body; B and D— genital area; C—coxigenital area. Scale bar: A = 15 µm; B, C and D = 10 µm. Note: images A and B represent one male, images C and D represent another male.
FIGURE 1 in Generic delimitation between Fragariocoptes and Sierraphytoptus (Acari: Eriophyoidea: Phytoptidae) and a supplementary description of Fragariocoptes gansuensis with remarks on searching for mummified eriophyoid mites in herbaria under UV light
FIGURE 1. Growth abnormalities caused by Fragariocoptes gansuensis on Potentilla bifurca. A—dried plant material from old herbaria and the corresponding collection label, В, C, D—live damaged plants. Note: B, C—images courtesy of L.F. Nepomenko, D—image courtesy of L. Moskalenko. Scale bar = 30 mm.
FIGURE 5 in Generic delimitation between Fragariocoptes and Sierraphytoptus (Acari: Eriophyoidea: Phytoptidae) and a supplementary description of Fragariocoptes gansuensis with remarks on searching for mummified eriophyoid mites in herbaria under UV light
FIGURE 5. Semischematic line drawings of a female of Fragariocoptes gansuensis. A—lateral view, B—coxigenital area, C—prodorsal shield, D—tarsal solenidion, I, E—empodium I, F—leg I, G—leg II, H—microtubercules on opisthosomal annuli. Scale bar: A = 60 µm; B and C = 10 µm; D and E = 5 µm; F and G = 15 µm; H = 10 µm.
FIGURE 9 in Generic delimitation between Fragariocoptes and Sierraphytoptus (Acari: Eriophyoidea: Phytoptidae) and a supplementary description of Fragariocoptes gansuensis with remarks on searching for mummified eriophyoid mites in herbaria under UV light
FIGURE 9. PCLM (A) and CLSM images (B—surface rendering; C—volume rendering, same female) of the internal genitalia of two females of Fragariocoptes gansuensis. Scale bar = 10 µm. Notation: a—spermatheca, b—distal segment of spermathecal tube, c—postspermathecal part of longitudinal bridge, d—prespermathecal part of longitudinal bridge, e—genital channel, f—remnants of genital chamber, g—anterior genital apodeme, i—zigzag-shaped hinge, j—anterodorsal extremity of anterior genital apodeme. Note: in images B and C internal structures viewed from dorsal aspect.
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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.