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Fig. 1 in New Record of a Marine Fish Parasite Nerocila trichiura (Crustacea: Isopoda: Cymothoidae) from Japan, with its Confirmed Distribution in the Western North Pacific Ocean
Fig. 1. Nerocila trichiura, ovigerous female, NSMT-Cr 26315. A, Cypselurus hiraii (252 mm in total length) infested with N. trichiura (arrow); B, skin wound at attachment site; C, N. trichiura, dorsal view, fresh specimen. Scale bars: A, 50 mm; B, C, 10 mm.
Fig. 2 in New Record of a Marine Fish Parasite Nerocila trichiura (Crustacea: Isopoda: Cymothoidae) from Japan, with its Confirmed Distribution in the Western North Pacific Ocean
Fig. 2. Nerocila trichiura, ovigerous female, NSMT-Cr 26315. A, dorsal view; B, lateral view; C, cephalon and pereonite 1, dorsal view; D, pleotelson and right uropod, dorsal view; E, pereopod 7. Scale bars: A, B, 10 mm; C, E, 2 mm; D, 5 mm.
Fig. 3 in New Record of a Marine Fish Parasite Nerocila trichiura (Crustacea: Isopoda: Cymothoidae) from Japan, with its Confirmed Distribution in the Western North Pacific Ocean
Fig. 3. Map showing the localities where Nerocila trichiura was collected in the previous (circles) and present (star) studies. 1, 31°N, 76°W (Schioedte and Meinert 1881); 2, the West Indies (Trilles 1979); 3, Dakar Harbor, Senegal (Bruce and Harrison-Nelson 1988); 4, Banana and an unknown locality, Congo (Nierstrasz 1918; Monod 1931); 5, Durban, South Africa (Barnard 1955; Kensley 1978); 6, Comoro Islands (Kensley 2001); 7, Mauritius (type locality, Mier 1877; Bruce and Harrison-Nelson 1988); 8, 10°20′S, 70°00′E (Bruce and Harrison-Nelson 1988); 9, Great Chagos (Stebbing 1910); 10, Tamil Nadu coast, India (Trilles et al. 2013; Rameshkumar et al. 2013); 11, Zamboanga, Philippines (Schioedte and Meinert 1881); and 12, Kowaura Bay, Japan (this paper).
Fig. 1 in First Records of the Snailfish Careproctus lycopersicus (Cottoidei: Liparidae) from the Western North Pacific
Fig. 1. Careproctus lycopersicus from the Nemuro Strait, Hokkaido, Japan (A: FAKU 146593, 182.4 mm SL, fresh condition; B: FAKU 145976, 168.6 mm SL, preserved condition) and one of the paratypes from the Bering Sea (C: UW 119816, 113.5 mm SL, preserved condition).
Fig. 2 in First Records of the Snailfish Careproctus lycopersicus (Cottoidei: Liparidae) from the Western North Pacific
Fig. 2. Mandibular teeth (A) and right pectoral girdle (B) of Careproctus lycopersicus (FAKU 145977, 176.3 mm SL). Scale bars 1 mm (A) and 5 mm (B).
Contributions of Anomalous Large-Scale Circulations to the Absence of Tropical Cyclones over the Western North Pacific in July 2020
<p>The datasets are for the article 'Contributions of Anomalous Large-Scale Circulations to the Absence of Tropical Cyclones over the Western North Pacific in July 2020', including the WRF Initial conditions (horizontal wind at 850 hPa, geopotential height at 850 and 200 hPa) of sensitivity experiments (CTRL, W_WNPSH, W_SAH, W_TUTT, and S_SASM) in July 2020, and the formation records of the simulated TC formation in all experiments.</p>
Catalog of low frequency earthquake beneath the Kaimanawa ranges, North Island of New Zealand
<p><strong>lfe_locations.csv</strong> contains the information relative to the 77 LFE candidates:</p> <p>1. Template name: name </p> <p>2. NonLinLoc location, error ellipsoid and uncertainties: lat, lon, depth, az1, dip1, len1, az2, dip2, len2, len3, rms, elat, elon, edepth</p> <p>3. GrowClust location and uncertainties lat_gc, lon_gc, depth_gc, gc_errorh, gc_error_z</p> <p><strong>detection.csv </strong>containes the information relative to the second-iteration catalog"</p> <p>1. Template name: name</p> <p>2. Detection time: time</p> <p>3. Sum of the correlation coefficient at the detection time: cc_sum</p> <p>4. Median Absolute Deviation at the detection time: mad</p>
Data set: "North Atlantic cooling is slowing down mass loss of Icelandic glaciers"
<p>This data set includes the materials required to reproduce the figures and tables presented in the study: "North Atlantic cooling is slowing down mass loss of Icelandic glaciers". The data consist of:</p> <p>1. Maps of annual surface mass balance (SMB) of Icelandic glaciers and ice caps (ICL) from RACMO2.3 at 500 m spatial resolution in NetCDF format.</p> <ul> <li><strong>smb_rec.1958-2019.RACMO2.3-ERA.ICL-0.5km.YY.nc</strong>: annual cumulative SMB of Icelandic glaciers and ice caps (kg m<sup>-2</sup> or mm w.e. per year) from RACMO2.3 forced by ERA reanalyses for the period 1958-2019, and further statistically downscaled to 500 m spatial resolution. Forcing includes ERA-40 (1958-1978), ERA-Interim (1979-2018) and ERA5 (2019) reanalyses.</li> <li><strong>smb_rec.1958-2099.RACMO2.3-CESM2-SSP85.ICL-0.5km.YY.nc</strong>: annual cumulative SMB of Icelandic glaciers and ice caps (kg m<sup>-2</sup> or mm w.e. per year) from RACMO2.3 forced by CESM2 for the historical period 1958-2014 and by CESM2 under a high-end warming scenario SSP5-8.5 for the period 2015-2099, further statistically downscaled to 500 m spatial resolution.</li> <li><strong>Topo_icemask_lsm_lon_lat_ICL-0.5km.nc</strong>: mask file including an ice mask, land/sea mask and surface topography derived from the ArcticDEM, and longitude/latitude coordinates on the 500 m grid.</li> </ul> <p><strong>NB</strong>: the NetCDF files above use a Polar Stereographic North (EPSG:3413) projection with a horizontal resolution of 500 m x 500 m. The reference point is located at 45ºW longitude and 70ºN latitude.</p> <p>2. Time series of annual ICL-integrated SMB components (Gigatons or Gt per year), annual mean 2 m air temperature above Icelandic glaciers and ice caps (T2m; K), annual mean sea surface temperature (SST) in the Northern Blue Blob. These time series are available in ASCII format for the RACMO2.3 simulation forced by ERA reanalyses (1958-2019) and the RACMO2.3 projection forced by CESM2 under a high-end warming scenario SSP5-8.5 (1958-2099).</p> <p><strong>RACMO2.3-ERA</strong></p> <ul> <li><strong>SMB-components-RACMO2.3-ERA-1958-2019.txt</strong>: time series of annual integrated SMB, snowfall, rainfall, runoff, total melt, refreezing and retention (Gt per year) from the ERA-forced RACMO2.3 simulation (1958-2019).</li> <li><strong>T2m-glacier-RACMO2.3-ERA-1958-2019.txt</strong>: time series of annual mean glacier T2m and anomalies relative to the period 1958-1994 (K) from the ERA-forced RACMO2.3 simulation (1958-2019).</li> <li><strong>SST-Northern-Blue-Blob-RACMO2.3-ERA-1958-2019.txt</strong>: time series of annual mean Northern Blue Blob SST and anomalies relative to the period 1958-1994 (K) derived from the ERA reanalyses (1958-2019).The reanalyses include ERA-40 (1958-1978), ERA-Interim (1979-2018) and ERA5 (2019).</li> </ul> <p><strong>RACMO2.3-CESM2</strong></p> <ul> <li><strong>SMB-components-RACMO2.3-CESM2-SSP85-1958-2099.txt</strong>: time series of annual integrated SMB, snowfall, rainfall, runoff, total melt, refreezing and retention (Gt per year) from the CESM2-forced RACMO2.3 projection under a SSP5-8.5 scenario (1958-2099).</li> <li><strong>T2m-glacier-RACMO2.3-CESM2-SSP85-1958-2099.txt</strong>: time series of annual mean glacier T2m and anomalies relative to the period 1958-1994 (K) from the CESM2-forced RACMO2.3 projection under a SSP5-8.5 scenario (1958-2099).</li> <li><strong>SST-Northern-Blue-Blob-RACMO2.3-CESM2-SSP85-1958-2099.txt</strong>: time series of annual mean Northern Blue Blob SST and anomalies relative to the period 1958-1994 (K) derived from the CESM2 projection under a SSP5-8.5 scenario (1958-2099).</li> </ul> <p>3. Time series of monthly ICL-integrated SMB (Gt per month) for the period 1958-2099. </p> <ul> <li><strong>SMB-monthly-RACMO2.3-1958-2099.txt</strong>: time series of monthly integrated SMB (Gt per month) combining RACMO2.3-ERA (January 1958 - December 2019) with RACMO2.3-CESM2 under a SSP5-8.5 scenario (January 2020 - December 2099) at 500 m horizontal resolution.</li> </ul> <p>The daily downscaled SMB data sets from the ERA-forced RACMO2.3 simulation and the CESM2-forced RACMO2.3 projection under a SSP5-8.5 scenario are freely available from the authors upon request and without conditions (contact: b.p.y.noel@uu.nl). Besides SMB, the data sets include daily total precipitation (snow and rain), snowfall, total melt (snow and ice), runoff, refreezing and retention, total sublimation (surface and drifting snow), snow drift erosion, as well as 2 m air temperature at 500 m horizontal resolution. </p> <p><strong>Abstract</strong>: Icelandic glaciers have been losing mass since the Little Ice Age in the mid-to-late 1800s, with higher mass loss rates in the early 21<sup>st </sup>century, followed by a slowdown since 2011. As of yet, it remains unclear whether this mass loss slowdown will persist in the future. By reconstructing the contemporary (1958-2019) surface mass balance of Icelandic glaciers, we show that the post-2011 mass loss slowdown coincides with the development of the Blue Blob, an area of regional cooling in the North Atlantic Ocean to the south of Greenland. This regional cooling signal mitigates atmospheric warming in Iceland since 2011, in turn decreasing glacier mass loss through reduced meltwater runoff. In a future high-end warming scenario, North Atlantic cooling is projected to mitigate mass loss of Icelandic glaciers until the mid-2050s. High mass loss rates resume thereafter as the regional cooling signal weakens. </p>
Figures 10–19 in New larval host plants and ecological observations on North American Cerambycidae (Coleoptera)
Figures 10–19. Larval host plants of Cerambycidae. 10) An old log of Quercus alba covered with lichens and mosses that harbored Typocerus lugubris, exit holes in the inset. 11–12) Quercus sp. stem girdled by Aneflomorpha fisheri. 13) Elongated future emergence hole of Aneflus paracalvatus in Prosopis velutina (holes of A. calvatus in Senegalia greggii are similar). 14) Fig. 13 after removal of a layer of wood – plug in the turn is visible, remnants of the tunnel leading to the plug can be seen due to their darker color. 15) Sclerotized terminal segment of Aneflus levettei larva (dorsal view). 16) Larva of Aneflus calvatus (ventral view) with the terminal segment bearing spikes but not having the area between them sclerotized. 17) Holes along a branch of Quercus emoryi through which Atylostagma glabra expelled frass. 18) Empty central tunnels of A. glabra (split branch from Fig. 17). 19). Future emergence holes of A. glabra on a branch of Quercus emoryi.
Figures 1–7 in New larval host plants and ecological observations on North American Cerambycidae (Coleoptera)
Figures 1–7. Larval host plants of Cerambycidae. 1–2) Decayed branches of Fagus grandifolia utilized by Sphenostethus taslei, emergence hole is in Fig. 1, exposed larva in a gallery in Fig. 2. 3–4) Stump of Prunus serotina with emergence holes from Lepthorhabdium pictum. 5) Quercus falcata with a basidiocarp of Phellinus everhartii and an emergence hole from Stenelytrana emarginata (enlarged in the inset). 6) Quercus emoryi with resupinate basidiocarp of Inonotus andersonii. 7) Old emergence holes of Stenelytrana splendens in an oak with an old resupinate basidiocarp of Inonotus andersonii.
Figures 20–26 in New larval host plants and ecological observations on North American Cerambycidae (Coleoptera)
Figures 20–26. Larval host plants of Cerambycidae. 20) Galleries of Haplidus laticeps in Vachelia constricta. 21) One sealed opening in a branch of Quercus used by larvae of Metaleptus batesi to expel frass (enlarged in inset). 22) Exit holes of Obrium rubidium on a dead limb of Robinia pseudoacacia (enlarged in inset). 23) Galleries of O. rubidium on a cross-section. 24) Elongated exit holes of Smodicum cucujiforme in a scar on living Quercus (enlarged in the inset). 25) A pile of yellow granular frass around a base of living Mimosa expelled by larvae of Stenaspis solitaria. 26) Pink pupa of Sternidius alpha.
Annual mean TROPOMI-derived ground-level NO2 mixing ratio (2019 - North America v1)
<p>Annual mean ground-level NO2 mixing ratio for 2019 inferred from the TROPOMI satellite instrument over North America at 0.025x0.03125 degree resolution. Included is 2019 annual mean and 1.5 year mean spanning July 2018 – December 2019.</p> <p><strong>Reference:</strong></p> <p>Cooper, M.J., R.V. Martin, C.A. McLinden, and J.R. Brook (2020), Inferring ground-level nitrogen dioxide concentrations at fine spatial resolution applied to the TROPOMI satellite instrument, Env. Res. Lett., DOI:10.1088/1748-9326/aba3a5</p>
Figure 1: Study area: A Digital Elevation Model of the North Island and the Manawatū-Whanganui dune field
<p>Figure 1 of article: Managing coastal sand drift in the Anthropocene: A case study of the Manawatū-Whanganui Dune Field, New Zealand, 1800s-2020s; authors: Sampath, Ruwan; Beattie, James; Freitas, Joana Gaspar; journal Environment & History [forthcoming]</p> <p>an article accepted in June 29, 2021</p> <p>https://zenodo.org/badge/DOI/10.5281/zenodo.5075980.svg</p>
Geodetic displacement data near North Brawley Geothermal Field, 2009-2019
<p>Supplementary Dataset for Materna, Barbour, Jiang, and Eneva (2022), "Detection of aseismic slip and poroelastic reservoir deformation at the North Brawley Geothermal Field from 2009–2019". The 2009-2019 downsampled and processed displacements for modeling, shown in their Figure 3, are presented in this repository. Processing methods are included in detail in the paper. Also included are the fault geometries used for modeling and the surface rupture trace of the M4.7 normal faulting earthquake in the 2012 Brawley Swarm, traced from a UAVSAR interferogram. </p> <p>TerraSAR-X data were ordered from the German Space Agency (DLR), using funding from grant GEO-10-001 awarded to Imageair Inc. by the California Energy Commission (CEC). InSAR/SqueeSAR processing of these data was done by TRE Altamira in Canada and Italy under CEC grant GEO-16-003 to Imageair Inc. Leveling data were obtained from the Imperial County Department of Public Works (https://publicworks.imperialcounty.org) and processed under the same grant. The Copernicus Sentinel-1 data were processed by the European Space Agency (ESA) and retrieved from the Alaska Satellite Facility (ASF) (https://search.asf.alaska.edu/). Sentinel-1 displacement time series were derived from interferograms processed in Jiang and Lohman (2021) through the support of Southern California Earthquake Center (SCEC) award 20139. SCEC is funded by NSF Cooperative Agreement EAR-1600087 & USGS Cooperative Agreement G17AC00047. UAVSAR data can be downloaded at https://uavsar.jpl.nasa.gov/. Quadtree downsampling was performed with the Kite library (Isken et al., 2017).</p>
Ground temperature timeseries (2014-2021) and cryostratigraphy from Villum Research Station, Station Nord, eastern North Greenland (81° N)
<p>This dataset contains ground temperature timeseries (2014-2021) and cryostratigraphy data from two 20 m deep boreholes located at Villum Research Station (VRS), Station Nord, eastern North Greenland. The cryostratigraphy data includes split permafrost core photographs and values for the following parameters: gravimetric moisture content, salinity, and freezing point depression. A complete sample inventory and information on sample quality and recovery is also included. Please read the file "Readme_Strandetal2021_V2" for the necessary background information and overview of the dataset contents (file structure and description of each file). This is the second version of the dataset; the ground temperature timeseries in this version are 2.5 years longer than in the first version, and meteorology data from the same period as the ground temperature data is provided.</p>
MPAS-Albany Land Ice model simulations of Humboldt Glacier, North Greenland, from 2007–2100
<p>This dataset contains model input and output in netCDF format, model code, and analysis scripts for simulations of Humboldt Glacier, North Greenland, through the 21st century (Hillebrand et al., 2022) using the MPAS-Albany Land Ice model (Hoffman et al., 2018). We calibrate parameters controlling basal traction, iceberg calving, and submarine melt against observations from 2007–2017. We then explore the glacier’s sensitivity to climate forcing, iceberg calving, and basal conditions in an ensemble of 24 simulations from 2007–2100. We further explore its sensitivity to uncertainties in ice-shelf melt, bed topography, and calving rate limits in targeted sensitivity experiments. Input files include surface mass balance, ocean thermal forcing, and subglacial runoff forcings provided by ISMIP6 (Nowicki et al., 2020; Slater et al., 2020). Output includes basal traction optimization solutions for the year 2007; annual 2D ice speed, basal shear and driving stresses, and geometry; annual 3D temperature; and grounded, floating, and global mass budgets at every timestep.</p> <p>References:</p> <p>Hillebrand, T. R., Hoffman, M. J., Perego, M., Price, S. F., and Howat, I. M. (2022): The contribution of Humboldt Glacier, northern Greenland, to sea-level rise through 2100 constrained by recent observations of speedup and retreat, The Cryosphere, 16, 4679–4700, <a href="https://doi.org/10.5194/tc-16-4679-2022">https://doi.org/10.5194/tc-16-4679-2022</a>.</p> <p>Hoffman, M. J., Perego, M., Price, S. F., Lipscomb, W. H., Zhang, T., Jacobsen, D., et al. (2018). MPAS-Albany Land Ice (MALI): a variable-resolution ice sheet model for Earth system modeling using Voronoi grids. <em>Geoscientific Model Development</em>, <em>11</em>(9), 3747–3780.<a href="https://doi.org/10.5194/gmd-11-3747-2018"> https://doi.org/10.5194/gmd-11-3747-2018</a></p> <p>Nowicki, S., Goelzer, H., Seroussi, H., Payne, A. J., Lipscomb, W. H., Abe-Ouchi, A., et al. (2020). Experimental protocol for sea level projections from ISMIP6 stand-alone ice sheet models. <em>The Cryosphere</em>, <em>14</em>(7), 2331–2368.<a href="https://doi.org/10.5194/tc-14-2331-2020"> https://doi.org/10.5194/tc-14-2331-2020</a></p> <p>Slater, D. A., Felikson, D., Straneo, F., Goelzer, H., Little, C. M., Morlighem, M., et al. (2020). Twenty-first century ocean forcing of the Greenland ice sheet for modelling of sea level contribution. <em>The Cryosphere</em>, <em>14</em>(3), 985–1008.<a href="https://doi.org/10.5194/tc-14-985-2020"> https://doi.org/10.5194/tc-14-985-2020</a></p>
Dataset: Long-term Change in Metabolism Phenology in North Temperate Lakes
<p>Scripts, model configurations and outputs to process the data and recreate the figures from Ladwig, R., Appling, A., Delany, A., Dugan, H.A., Gao, L., Lottig, N., Stachelek, J., Hanson, P.C.: Long-term Change in Metabolism Phenology in North-Temperate Lakes.</p> <p>This repository includes the setup and output from the metabolism model ran on the lakes Allequash, Big Muskellunge, Crystal, Fish, Mendota, Monona, Sparkling and Trout. Scripts to run the model are located under /src (odem_min_indexed_sed.stan, run_odem_chtc_sed.R, stan_utility.R, stan_utility_chtc.R) together with the scripts to create the driver data, 0_Model_Input.R, and the processed results for the discussion of the paper, 1_Postprocessing.R. Addtionally, all scripts to recreate the figures from the manuscript are also included in /src.</p> <p>The figures are located under /Figures and processed output under /Processed_Output.</p>
Research dat for: "Active Tectonics of the North Tunisian Continental Margin"
<p>The data are the figures in high-resolution for the article: "Active Tectonics of the North Tunisian Continental Margin"</p>
Characterization of legacy persistent organic pollutants (POPs) in northern bottlenose whales of the Western North-Atlantic
<p>Dataset associated with the Canadian Technical Report of Fisheries and Aquatic Sciences entitled "Characterization of legacy persistent organic pollutants (POPs) in northern bottlenose whales of the Western North-Atlantic". Presents lipid weight corrected persistent organic pollutant concentrations (microgram per gram) in the blubber of northern bottlenose whales samples in the western North Atlantic. </p>
Characterizing North American Ipomoea grandifolia (Convolvulaceae), a member of Ipomoea series batatas
<p>Species in the genus <em>Ipomoea </em>are often difficult to identify due to their similar morphologies and their ability to hybridize with one another. An undescribed North American <em>Ipomoea </em>morphotype in series <em>Batatas</em>, referred here as <em>Ipomoea</em> Carolina morphotype, was found to be morphologically, genetically, and reproductively isolated from other locally co-occurring <em>Ipomoea </em>species. A previous phylogenetic analysis that included a broader sampling of species in <em>Ipomoea</em> series <em>Batatas</em> suggested that <em>Ipomoea </em>Carolina morphotype may be <em>Ipomoea grandifolia</em>, a species described as found only in South America<em>.</em> To evaluate these findings, we tested intrinsic cross-compatibility between <em>Ipomoea </em>Carolina morphotype and <em>I. grandifolia</em> as well as with three other co-localizing North American <em>Ipomoea </em>species – <em>Ipomoea cordatotriloba</em>,<em> Ipomoea lacunosa</em>, and <em>Ipomoea leucantha</em>. We also examined genetic differentiation using single nucleotide polymorphisms from leaf transcriptomes from multiple individuals of all five species and several outgroup species. We find no cross-incompatibility and little genetic differentiation between <em>Ipomoea </em>Carolina morphotype and <em>Ipomoea grandifolia</em>, suggesting that<em> Ipomoea </em>Carolina morphotype is a representative of <em>Ipomoea grandifolia</em>. This finding raises additional questions about the origins of <em>Ipomoea grandifolia</em> in North America and how its disjunct distribution could play a role in the divergence of <em>Ipomoea grandifolia</em> in the future.</p>
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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.