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13,117 results for “Maps”
Figure 8. Cocoon features mapped onto a in An overview of cocoon morphology of Sphecidae (Hymenoptera: Apoidea)
Figure 8. Cocoon features mapped onto a simplified phylogeny of Sphecidae, based on Bohart and Menke (1976), Ohl 1996 and Buys 2020.
Magnetic susceptibility-weighted imaging mapped the migratory route of a paragonimus in brain
<p>A 53-year-old man with a recent history of left temporal lobe hemorrhage presented with weakness of left upper limb for 4 days. Paragonimus eggs were detected in patient's sputum. Work up revealed paragonimiasis, a lung fluke worm infection endemic to East Africa, West Africa and South America which rarely involves in brain. Characteristic tunnel sign was visualized on brain MRI. Notably, susceptibility-weighted imaging revealed a migratory pattern of the parasite from the left temporal lobe to the right parietal lobe and resultant patchy hemorrhage. Treatment with praziquantel resulted in favorable outcome without residual deficits.</p>
Mapping scrub vegetation cover from photogrammetric point-clouds
<p>This dataset is derived from photogrammetric point cloud models of UAV imagery. It includes the Above ground models of vegetation as well as the isolated scrub vegetation.</p> <p>We illustrate the method with two case studies from the UK. The scrub cover at Daneway Banks, a calcareous grassland site in Gloucestershire was calculated at 21.8% of the site. The scrub cover at Flat Holm Island, a maritime grassland in the Severn Estuary was calculated at 7%. This approach enabled the scrub layer to be readily measured and if required, modelled to provide a visual guide of what a projected management objective would look like. This approach provides a new tool in reserve management, enabling habitat management strategies to be informed, and progress towards objectives monitored.</p>
Data from: A data-driven geospatial workflow to map species distributions for conservation assessments
<p>We developed a geospatial workflow that refines the distribution of a species from its extent of occurrence (EOO) to area of habitat (AOH) within the species range map. The range maps are produced with an inverse distance weighted (IDW) interpolation procedure using presence and absence points derived from primary biodiversity data (GBIF and eBird hotspots respectively). Here we provide sample data to run the geospatial workflow for nine forest species across Mexico and Central America.</p>
Distribution. SE Europe from Albania and Greece (including Crete) N to S Ukraine and S Russia, the Caucasus, Turkey, and N Iran, and through C Asia to W Mongolia, N, E & C China (including Hainan), and the Himalayas; isolated populations in S Croatia and Korea. Specimens collected from SW Syria may representjuvenile Geoffroy's Myotis (M. emarginatus) or a different form, and are not mapped here. in Vespertilionidae
Distribution. SE Europe from Albania and Greece (including Crete) N to S Ukraine and S Russia, the Caucasus, Turkey, and N Iran, and through C Asia to W Mongolia, N, E & C China (including Hainan), and the Himalayas; isolated populations in S Croatia and Korea. Specimens collected from SW Syria may representjuvenile Geoffroy's Myotis (M. emarginatus) or a different form, and are not mapped here.
Subspecies and Distribution. M.s.swillaTemminck,1840—MalayPeninsula(includingLangkawiI),Borneo,Suma-tra,Java,andthePhilippines(Luzon,Cebu,Mindanao,andPalawanIs). M. s. canescens Thomas, 1923 — Nias I, off W Sumatra. Apparently also in C Sulawesi, Peleng I, and New Guinea because these specimens are similar to this speciesin size, although they were originally identified as the Flores Tube-nosed Bat (M. florium). These records are not mapped here. in Vespertilionidae
Subspecies and Distribution. M.s.swillaTemminck,1840—MalayPeninsula(includingLangkawiI),Borneo,Suma-tra,Java,andthePhilippines(Luzon,Cebu,Mindanao,andPalawanIs). M. s. canescens Thomas, 1923 — Nias I, off W Sumatra. Apparently also in C Sulawesi, Peleng I, and New Guinea because these specimens are similar to this speciesin size, although they were originally identified as the Flores Tube-nosed Bat (M. florium). These records are not mapped here.
Subspecies and Distribution. M.l.leucogasterMilne-Edwards,1872—C&EChinaandNVietnam. M. l. rubex Thomas, 1916 — NE India (West Bengal); a record from Nepal is not supported by any voucher specimens and is not mapped here. in Vespertilionidae
Subspecies and Distribution. M.l.leucogasterMilne-Edwards,1872—C&EChinaandNVietnam. M. l. rubex Thomas, 1916 — NE India (West Bengal); a record from Nepal is not supported by any voucher specimens and is not mapped here.
Distribution. NC, C & SW China (Tibet [= Xizang], Qinghai, Gansu, Ningxia, and Sichuan), Bangladesh (Sylhet Division), NE India (Meghalaya and Mizoram), and NW Thailand; possibly N Myanmar (although this record has been mapped dubiously). in Vespertilionidae
Distribution. NC, C & SW China (Tibet [= Xizang], Qinghai, Gansu, Ningxia, and Sichuan), Bangladesh (Sylhet Division), NE India (Meghalaya and Mizoram), and NW Thailand; possibly N Myanmar (although this record has been mapped dubiously).
Subspecies and Distribution. P.r.rusticusTomes,1861—scatteredrecordsfromWAfricafromSenegaltoEEthiopiaalongwithNUgandaandWCKenya. P. r. marrensis Thomas & Hinton, 1923 — S Africa in SE Angola, Zambia, NE Namibia, N Botswana, Zimbabwe, and NE South Africa; perhaps also Malawi, although specimens from that region need to be reexamined and are not mapped here. There is also a record from E Tanzania, although its subspecific identity is uncertain. in Vespertilionidae
Subspecies and Distribution. P.r.rusticusTomes,1861—scatteredrecordsfromWAfricafromSenegaltoEEthiopiaalongwithNUgandaandWCKenya. P. r. marrensis Thomas & Hinton, 1923 — S Africa in SE Angola, Zambia, NE Namibia, N Botswana, Zimbabwe, and NE South Africa; perhaps also Malawi, although specimens from that region need to be reexamined and are not mapped here. There is also a record from E Tanzania, although its subspecific identity is uncertain.
Bibliometric appendix for the paper "The application domains of systematic mapping studies: A mapping study of the first decade of practice with the method"
<p>Bibliometric appendix for the paper "The application domains of systematic mapping studies: A mapping study of the first decade of practice with the method"</p>
Ecological impacts of photosynthetic light harvesting in changing aquatic environments: A systematic literature map
<p>Underwater light is spatially as well as temporally variable and directly affects phytoplankton growth and competition. Here we systematically (following the guidelines of PRISMA-EcoEvo) searched and screened the published literature resulting in 640 individual articles. We mapped the conducted research for the objectives of (1) phytoplankton fundamental responses to light, (2) effects of light on the competition between phytoplankton species and (3) effects of climate change induced changes in the light availability in aquatic ecosystems. Among the fundamental responses of phytoplankton to light, the effects of light intensity (quantity, as measure of total photon or energy flux) were investigated in most identified studies. The effects of the light spectrum (quality) that via species-specific light absorbance result in direct consequences on species competition emerged more recently. Complexity in competition arises due to variability and fluctuations in light which effects are sparsely investigated on community level. Predictions regarding future climate change scenarios included changes in in stratification and mixing, lake and coastal ocean darkening, UV radiation, ice melting as well as light pollution which affect the underwater light-climate. Generalization of consequences is difficult due to a high variability, interactions of consequences as well as a lack in sustained timeseries and holistic approaches. Nevertheless, our systematic literature map, and the identified articles within, provide a comprehensive overview and shall guide prospective research.</p>
Distribution. Scattered localities in NE Venezuela, S Guyana, Suriname (unknown locality, not mapped), NE Ecuador, E Peru, and Brazil. in Molossidae
Distribution. Scattered localities in NE Venezuela, S Guyana, Suriname (unknown locality, not mapped), NE Ecuador, E Peru, and Brazil.
Species and foliar biochemical trait maps for Blackhawk Island, Wisconsin May-October 2018
<p class="MsoNormal">Foliar biochemical traits are important indicators of ecosystem functioning and health that are impractical to characterize at large spatial and temporal scales using traditional measurements. However, comprehensive inventories of foliar traits are important for understanding ecosystem responses to anthropogenic and natural disturbances, as inputs into ecosystem process models, and for quantifying spatial variation in functional diversity. Imaging spectroscopy has been demonstrated as a valuable tool for developing maps of ecologically important foliar traits at large scales, but its application to mapping foliar traits over the course of the growing season has been limited. We collected high-resolution imaging spectroscopy data over Blackhawk Island, Wisconsin, USA at eight time points during the 2018 growing season (May – October). Using partial least squares regression (PLSR) we developed predictive models applicable to all dates to produce canopy-level maps of eight traits related to ecophysiological function: chlorophyll content, leaf mass per area and concentrations of calcium, nitrogen, phosphorus, potassium, phenolics and lignin. The accuracy of our models varied across traits (R<sup>2</sup>: 0.25-0.86); traits with well-defined absorption features were retrieved with high accuracy including chlorophyll (R<sup>2</sup>: 0.86; %RMSE: 11.0) and total phenolics (R<sup>2</sup>: 0.86; %RMSE: 11.0). We also assessed how well our models estimated biochemistry on novel species and new dates using a cross-validation analysis. Chlorophyll and total phenolics were well estimated across withheld dates and species, whereas calcium was estimated poorly on both withheld species (R<sup>2</sup>: 0.08) and dates (R<sup>2</sup>: 0.07). Our canopy-level maps of macronutrients (N, P and K) showed general trends of decreasing concentration over the course of the year, reflecting dilution by carbon-rich compounds during the growing season and resorption during senescence.</p>
Rapid increase in China's industrial ammonia emissions: evidence from unit-based mapping
<p>Ammonia (NH<sub>3</sub>) is an important precursor of secondary inorganic aerosols and greatly impacts nitrogen deposition and acid rain. Previous studies have mainly focused on the agricultural NH<sub>3</sub> emissions, while recent research has noted that industrial sources could be significant in China. However, detailed estimates of NH<sub>3</sub> emitted from industrial sectors in China are lacking. Here we established an unprecedented high-spatial-resolution dataset of China's industrial NH<sub>3</sub> emissions using up-to-date measurements of NH<sub>3</sub> and point source-level information covering eight major industries and 27 subdivided process categories. We found that China emitted 798 (90% confidence interval: 668–933) gigagrams of industrial NH<sub>3</sub> to the atmosphere in 2019, equivalent to 44±20% of the industrial emissions worldwide; this flux is three-fold larger than that in 1998 and has fluctuated since 2014. Furthermore, although fertilizer production is responsible for approximately half of the emissions in China, the emissions from cement production and coal-fired power plants increased dramatically from near zero to 164 and 41 gigagrams, respectively, in the past two decades, primarily due to the NH<sub>3</sub> escape caused by the large-scale application of the denitration process. Our results reveal that, unlike other major air pollutants, China's industrial NH<sub>3</sub> emission control is still in a critical period, and stricter NH<sub>3</sub> emission standards and innovation in pollution control technologies are highly desirable.</p>
Map 2 in On some Lomechusini of the Palaearctic and Oriental regions (Coleoptera: Staphylinidae: Aleocharinae)
Map 2: Distribution of Tetrabothrus clavatus based on revised material and reliable literature records taken from MARYUAMA & KISHIMOTO (1999) and YAN & LI (2015b) (filled circles), as well as on a female-based record from Australia and localities of suspected synonyms (T. canescens, T. neoguineensis) (open circles).
FIGURES 15–18. Distribution maps for the Metallactus taeniatellus species group. M in Revision of the Metallactus taeniatellus species group (Coleoptera: Chrysomelidae: Cryptocephalinae)
FIGURES 15–18. Distribution maps for the Metallactus taeniatellus species group. M. planipennis (15); M. quadrinus (16); M. superbiens (17); M. taeniatellus (18). Striped squares: two possible (alternative) locations for the type locality of M. planipennis due to the ambiguous report in the original description (see text for further information).
FIGURES 11–14. Distribution maps for the Metallactus taeniatellus species group. M in Revision of the Metallactus taeniatellus species group (Coleoptera: Chrysomelidae: Cryptocephalinae)
FIGURES 11–14. Distribution maps for the Metallactus taeniatellus species group. M. cultus (11); M. insitivus (12); M. latiusculus (13); M. multicolor (14). Grey squares: generic localization for specimens briefly labeled as coming from "Venezuela" and "Suriname".
FIGURES 19–20. Distribution maps for the Metallactus taeniatellus species group. M in Revision of the Metallactus taeniatellus species group (Coleoptera: Chrysomelidae: Cryptocephalinae)
FIGURES 19–20. Distribution maps for the Metallactus taeniatellus species group. M. geiseri (19); M. uncinatus (20).
Rapeseed Map Example data
<p>This dataset provides 30m-grid rapeseed map example data.</p> <p>*** The data file is in “.tif" format</p> <p>*** Temporal Resolution: Yearly</p> <p>*** Pixel size: 30 m</p> <p>*** Projection information: EPSG: 4326</p>
African Digital Research Repositories: Mapping the Landscape
<p>This data set accompanies the text at doi <a href="https://doi.org/10.5281/zenodo.3732273">10.5281/zenodo.3732273</a>. // Correspondence: JH: <a href="mailto:info@africarxiv.org">info@africarxiv.org</a>, SK: <a href="mailto:sk111@soas.ac.uk">sk111@soas.ac.uk</a></p> <p><strong>Visual Map: </strong><a href="https://kumu.io/access2perspectives/african-digital-research-repositories"><strong>https://kumu.io/access2perspectives/african-digital-research-repositories</strong></a><strong> <br> Dataset: </strong><a href="https://tinyurl.com/African-Research-Repositories"><strong>https://tinyurl.com/African-Research-Repositories</strong></a><br> <strong>Archived at </strong><a href="https://info.africarxiv.org/african-digital-research-repositories/"><strong>https://info.africarxiv.org/african-digital-research-repositories/</strong></a><strong> <br> Submission form: </strong><a href="https://forms.gle/CnyGPmBxN59nWVB38"><strong>https://forms.gle/CnyGPmBxN59nWVB38</strong></a></p> <p> </p> <p><strong>Licensing</strong>: Text and Visual Map – CC-BY-SA 4.0 // Dataset – CC0 (Public Domain) // The licensing of each database is determined by the database itself</p> <p>Preprint doi: <a href="https://doi.org/10.5281/zenodo.3732273">10.5281/zenodo.3732273</a>. <br> Data set doi: <a href="http://doi.org/10.5281/zenodo.3732172">10.5281/zenodo.3732172</a> // available in different formats (pdf, xls, ods, csv)</p> <p> </p> <p><strong><a href="https://info.africarxiv.org">AfricarXiv</a> in collaboration with the <a href="https://www.internationalafricaninstitute.org">International African Institute </a>(IAI) presents an interactive map of African digital research literature repositories. This drew from IAI’s earlier work from 2016 onwards to identify and list Africa-based institutional repositories that focused on identifying repositories based in African university libraries. Our earlier resources are available at </strong><a href="https://www.internationalafricaninstitute.org/repositories"><strong>https://www.internationalafricaninstitute.org/repositories</strong></a><strong>.</strong></p> <p><strong>The interactive map extends the work of the IAI to include organizational, governmental, and international repositories. It also maps the interactions between research repositories. In this dataset, we focus on institutional repositories for scholarly works, as defined by Wikipedia contributors (March 2020).</strong><br> </p> <p><strong>Objective</strong></p> <p>The map of African digital repositories was created as a resource to be used in activities addressing the following aims:</p> <ol> <li> <p>Improving the discoverability of African research and publications </p> </li> <li> <p>Enhance the interoperability of existing and emerging African repositories</p> </li> <li> <p>Identify ways through which digital scholarly search engines can enhance the discoverability of African research</p> </li> </ol> <p>We promote the dissemination of research-based knowledge from African repositories as part of a bigger landscape that also includes online journals, research data repositories, and scholarly publishers to enhance the interconnectivity and accessibility of such repositories across and beyond the African continent and to contribute to a more granular understanding of the continent’s scholarly resources. </p> <p> </p> <p><strong>Data archiving and maintenance</strong></p> <p>The map and corresponding dataset are hosted on the AfricArXiv website under ‘Resources’ at <a href="https://info.africarxiv.org/african-digital-research-repositories/">https://info.africarxiv.org/african-digital-research-repositories/</a>. The listing is not exhaustive and therefore we encourage any repositories relevant for the African continent not listed here to the <strong>submission form at </strong><a href="https://forms.gle/CnyGPmBxN59nWVB38"><strong>https://forms.gle/CnyGPmBxN59nWVB38</strong></a>, or to notify the International African Institute (email <a href="mailto:sk111@soas.ac.uk">sk111@soas.ac.uk</a>). Both AfricArXiv and IAI will continue to maintain the list of repositories as a resource for African researchers and other stakeholders including international African studies communities.</p>
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.