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Text-fig. 2. Stratigraphic ranges of Microtoscoptini-bearing sites. Correlation of ELMA and NALMA with earth years is according to Hilgen et al. (2012). Localities of very broad stratigraphic range (e.g., the entire Turolian or Hemphillian, as for Vasilivka 1, Lobkove, Little Valley, Cambridge), do not contribute to detail the range, and are omitted in this figure. in Comments On The Age And Dispersal Of Microtoscoptini (Rodentia: Cricetidae)
Text-fig. 2. Stratigraphic ranges of Microtoscoptini-bearing sites. Correlation of ELMA and NALMA with earth years is according to Hilgen et al. (2012). Localities of very broad stratigraphic range (e.g., the entire Turolian or Hemphillian, as for Vasilivka 1, Lobkove, Little Valley, Cambridge), do not contribute to detail the range, and are omitted in this figure.
Text-fig. 1. Known geographic distribution of Microtoscoptini. 1 – Ertemte 1 and 2; 2 – Olan Chorea; 3 – Harr Obo 2; 4 – Shala; 5 – Baogeda Ula; 6 – Bilutu; 7 – Kholu (Southern Tuva); 8 – Sarayskoe (Olkhon Island); 9 – Hyargas-nuur; 10 – Petropavlovsk; 11 – Pavlodar; 12 – Akshauli; 13 – Selety 1A; 14 – Kedej 1A; 15 – Makovka; 16 – Cherevychne 3; 17 – Protopopovka 3; 18 – Verkhnya Krynytsa 2; 19 – Vasylivka 1; 20 – Lobkove; 21 – Rome; 22 – Bartlett Mountain; 23 – Bartlett Mountain (General); 24 – Juniper Creek; 25 – Little Valley; 26 – Stroud Claim; 27 – Kelley Road; 28 – Moonstone Formation; 29 – Lemoyne Quarry; 30 – Feltz Ranch; 31 – Cambridge; 32 – Rick Irwin Site; 33 – Rabbit Hole. in Comments On The Age And Dispersal Of Microtoscoptini (Rodentia: Cricetidae)
Text-fig. 1. Known geographic distribution of Microtoscoptini. 1 – Ertemte 1 and 2; 2 – Olan Chorea; 3 – Harr Obo 2; 4 – Shala; 5 – Baogeda Ula; 6 – Bilutu; 7 – Kholu (Southern Tuva); 8 – Sarayskoe (Olkhon Island); 9 – Hyargas-nuur; 10 – Petropavlovsk; 11 – Pavlodar; 12 – Akshauli; 13 – Selety 1A; 14 – Kedej 1A; 15 – Makovka; 16 – Cherevychne 3; 17 – Protopopovka 3; 18 – Verkhnya Krynytsa 2; 19 – Vasylivka 1; 20 – Lobkove; 21 – Rome; 22 – Bartlett Mountain; 23 – Bartlett Mountain (General); 24 – Juniper Creek; 25 – Little Valley; 26 – Stroud Claim; 27 – Kelley Road; 28 – Moonstone Formation; 29 – Lemoyne Quarry; 30 – Feltz Ranch; 31 – Cambridge; 32 – Rick Irwin Site; 33 – Rabbit Hole.
Fig. 3 in Assessing large mammal and bird richness from camera-trap records in the Hukaung Valley of Northern Myanmar
Fig. 3. Trend lines, correlations and p-values for the relationship between number of camera trap nights per season per area (effort) versus number of species photographed (diversity) in the Core study area (solid line & solid circle) and at and near camera trap locations Outside the Core area (dash line & hollow circle) in the Hukaung Valley, Myanmar (season [= year] data from Naing 2015).
Fig. 2 in Assessing large mammal and bird richness from camera-trap records in the Hukaung Valley of Northern Myanmar
Fig. 2. Camera stations, and the composite areas within 3 km of each station, in the Core study area (A) and Outside of the Core area (B) in the Hukaung Valley Wildlife Sanctuary of Myanmar
Fig. 6 in Spatio-temporal segregation and size distribution of fish assemblages as related to non-native species occurrence in the middle rio Doce Valley, MG, Brazil
Fig. 6. Least-square means and 95% confidence intervals from ANCOVA of the first three environmental factors from PCA. Different markers represent significantly different means as detected by planned contrasts with 5% significance level, first comparing lakes with any non-native species with those without them, and then comparing the two categories of lakes with non-natives (non-piscivores vs. piscivores).
Fig. 4 in Spatio-temporal segregation and size distribution of fish assemblages as related to non-native species occurrence in the middle rio Doce Valley, MG, Brazil
Fig. 4. Scatterplot of species body size (mean standard length) vs. a relative index of native affinity to lakes containing piscivorous invaders (the proportion of biomass of a given native species in lakes with piscivorous invaders). The estimated regression line is also presented (Y = 0.044*X - 0.279; R2 = 0.443; p = 0.007). Species codes: ast = Astyanax sp.; aus = Australoheros facetus; cyp = Cyphocharax gilbert; cre = Crenicichla lacustris; geo = Geophagus brasiliensis; gym = Gymnotus gr. carapo; hop = Hoplias malabaricus; lep = Leporinus steindachneri; lor = Loricariidae (unidentified species); lyc = Lycengraulis sp.; moe = Moenkhausia doceana; oli = Oligosarcus solitarius; pac = Pachyurus adspersus; pro = Prochilodus vimboides; tra = Trachelyopterus striatulus.
Fig. 5 in Spatio-temporal segregation and size distribution of fish assemblages as related to non-native species occurrence in the middle rio Doce Valley, MG, Brazil
Fig. 5. Least-square means and 95% confidence intervals from ANCOVA of mean individual size and temporal turnover as related to the three lake categories. Different markers represent significantly different means as detected by planned contrasts with 5% significance level, first comparing lakes with any non-native species with those without them, and then comparing the two categories of lakes with non-natives (non-piscivores vs. piscivores).
Fig. 2 in Spatio-temporal segregation and size distribution of fish assemblages as related to non-native species occurrence in the middle rio Doce Valley, MG, Brazil
Fig. 2. Alpha (mean) and beta richness. a) Comparison among the temporal and spatial components of richness. b) Species richness for each lake. The alpha (mean) and beta richness were taken along the temporal component. Lake codes: No = Nova; Ca = Capim; Fe = Ferrugem; Cr = Crentes; Po = Poço Redondo; Ro = Romoalda; Ti = Timburé; Ag = Águas Claras; Pa = Palmeirinha; Ar = Ariranha. "Natives" represents lakes without non-native species; "Non-piscivores" represents lakes with non-piscivorous non-native species; "Piscivores" represents lakes with invasive piscivorous species.
MED-GOLD Indicators for the Wine pilot over Douro Valley based on High Resolution Climate projections
<p>Indicators of interest for the Wine sector over the Douro Valley using high resolution climate projections.</p> <ol> <li>GDD (Growing Degree Days) - summation of daily differences between daily temperature averages and 10 for the period April-October</li> <li>GST (Growing Season Temperature) - average of daily average temperatures for the period April-October</li> <li>SprR (Spring Rain) - Precipitation accumulated between 21st April-to 21st June,</li> <li>HarvR (Harvest Rain)-Precipitation accumulated between 21 August and 21 October</li> <li>SU35 -number of days with temperature higher than 35°C for the period April-October,</li> <li>WSDI (Warm Spell Duration Index) -days with at least 6 consecutive days when the daily temperature maximum exceeds its 90th percentile for the period April-October.</li> </ol> <p>The results are based on an sub-ensemble of five RCMs from the EURO-CORDEX modelling experiment which have been statistically downscaled to 1km x1km horizontal resolution using the PTHRES gridded dataset as the reference dataset. More details can be found in Raül Marcos-Matamoros, (2018). Report on the methodology followed to implement the wine pilot services. Zenodo. https://doi.org/10.5281/zenodo.4543337</p> <p>Datasets computed by National Observatory of Athens, in collaboration with SOGRAPE VINHOS S.A. in the framework of the European MED-GOLD project, funded from the European Union's Horizon 2020 Research and Innovation programme under Grant agreement No.776467</p> <p> </p> <p> </p>
Digital elevation models, ortho images and outlines of Yala Glacier, Langtang Valley, Nepal Himalaya
<p>Datasets related to article "Up-glacier propagation of surface lowering of Yala Glacier, Langtang Valley, Nepal Himalaya". The data includes three digital elevation models (DEM), two ortho images and five outlines of Yala Glacier between 1981 and 2015.<br> </p> <p>Description of files:<br> 1) DEM and ortho image</p> <p>- 1981Yala_dem_20_-10_bias_cor.tif: 10 m resolution digital elevation model derived from a map that was generated using ground phogogrammetry images that were acquired in 1981 (Yokoyama, 1984; Fujita and Nuimura).</p> <p>- 2007Yala_dem_0_-4_bias_cor.tif: 2 m resolution digital elevation model derived from 14 oblique photographs that were acquired by a private jet with handheld cameras in 2007.<br> - 2007Yala_ortho.tif: an ortho images derived by the same data in 2007.</p> <p>- 2015Yala_dem_0_0_bias_cor.tif: 1 m resolution digital elevation model derived from 519 photographs that were acquired by a UAV-based photogrammetric survey in 2015.<br> - 2015Yala_ortho.tif: an ortho images derived by the same data in 2015.<br> <br> 2) Glacier boundary (shapefile Files)</p> <p>- Yala_area_1981: <br> - Yala_area_2007:<br> - Yala_area_2009:<br> - Yala_area_2012:<br> - Yala_area_2015:<br> <br> <br> Please see the related journal article for details on datasets.<br> <br> Sunako, S., Fujita, K., Izumi, T., Yamaguchi, S., Sakai, A., & Kayastha, R. (2023). Up-glacier propagation of surface lowering of Yala Glacier, Langtang Valley, Nepal Himalaya. Journal of Glaciology, 69(274), 425-432. doi:10.1017/jog.2022.118<br> </p>
Fig. 1. A in Caridina clandestina, new species, an unusual new freshwater shrimp (Crustacea: Decapoda: Atyidae) from the remote high elevation Napu Valley of Sulawesi, Indonesia
Fig. 1. A, map of Sulawesi with the study area framed in red as shown on the detail map (B) of the Napu and Bada Valleys; B, the symbols show the sampling locations of Caridina clandestina, new species (black circles), C. sulawesi Cai & Ng, 2009 (white circles), C. parvidentata J. Roux, 1904 (square), and C. villadolidi Blanco, 1939 (diamond).
Fig. 4. A in Caridina clandestina, new species, an unusual new freshwater shrimp (Crustacea: Decapoda: Atyidae) from the remote high elevation Napu Valley of Sulawesi, Indonesia
Fig. 4. A, Lariang River, natural habitat of Caridina clandestina, new species; B, colouration of living specimen; C, specimen with chelae adapted for filter feeding.
Fig. 5. A in Caridina clandestina, new species, an unusual new freshwater shrimp (Crustacea: Decapoda: Atyidae) from the remote high elevation Napu Valley of Sulawesi, Indonesia
Fig. 5. A, scatterplot analysis of chelae morphology in both forms of Caridina clandestina, new species; B, chelae morphology in both forms of Caridina clandestina is not related to size of specimens.
Fig. 3. A–C, F, G, J–O in Caridina clandestina, new species, an unusual new freshwater shrimp (Crustacea: Decapoda: Atyidae) from the remote high elevation Napu Valley of Sulawesi, Indonesia
Fig. 3. A–C, F, G, J–O, Caridina clandestina, new species, paratype male filter feeding morph (CL 5.6 mm) (ZMB 30207a), Lariang River, Central Sulawesi; D, E, H, I, Caridina clandestina, new species, paratype male short chelae morph (CL 4.7 mm) (ZMB 30203b), Napu Valley, stream, tributary of Lariang River, Central Sulawesi. A, third maxilliped; B, first pereiopod; C, fingers of first pereiopod; F, second pereiopod; G, fingers of second pereiopod; J, third pereiopod; K, dactylus of third pereiopod; L, fifth pereiopod; M, dactylus of fifth pereiopod; N, endopod of male's first pleopod; O, endopod and appendix masculina on second pleopod. Scale bars: A–F, H–J, L, N, O = 1.0 mm; G, K, M = 0.5 mm.
Fig. 2. A, C–N in Caridina clandestina, new species, an unusual new freshwater shrimp (Crustacea: Decapoda: Atyidae) from the remote high elevation Napu Valley of Sulawesi, Indonesia
Fig. 2. A, C–N, Caridina clandestina, new species, paratype male filter feeding morph (CL 5.6 mm) (ZMB 30207a), Lariang River, Central Sulawesi; B, Caridina clandestina, new species, paratype male short chelae morph (CL 4.7 mm) (ZMB 30203b), Napu Valley, stream, tributary of Lariang River, Central Sulawesi. A, cephalothorax and cephalic appendages; B, rostrum; C, telson; D, distal part of telson; E, preanal carina; F, uropodal diaeresis; G, antennular peduncle; H, scaphocerite; I, distal part of mandible; J, maxillula; K, maxilla; L, first maxilliped; M, palp of first maxilliped; N, second maxilliped. Scale bars: A–C, G–I, K–N = 1.0 mm; D, E, F, J = 0.5 mm.
Fig. 6 in Caridina clandestina, new species, an unusual new freshwater shrimp (Crustacea: Decapoda: Atyidae) from the remote high elevation Napu Valley of Sulawesi, Indonesia
Fig. 6. Molecular phylogeny of all described endemic species of Caridina from Sulawesi. Topology based on BI analysis of concatenated dataset of two mitochondrial gene fragments (16S and COI). Numbers on branches are, from the top, Bayesian posterior probabilities (>0.9) and ML/MP bootstrap values (>70). An asterisk indicates nodes with full support (1/100/100). The scale bar indicates the substitution rate.
Particle–hole symmetry protects spin-valley blockade in graphene quantum dots
<p> Experimental data and python scripts used to evaluate the data and to perform simulations for the publication</p> <p>" Particle-hole symmetry protects spin-valley blockade in graphene quantum dots " in Nature.</p> <p>https://doi.org/10.1038/s41586-023-05953-5</p> <p> </p>
FIG. 3. — TWINSPAN classification for the 23 in The Epiphytic Bryophyte Vegetation of Buxus sempervirens L. forests in the Fırtına Valley (Rize, Turkey)
FIG. 3. — TWINSPAN classification for the 23 relevés carried out in the studied area and 31 taxa found.
FIG. 1 in The Epiphytic Bryophyte Vegetation of Buxus sempervirens L. forests in the Fırtına Valley (Rize, Turkey)
FIG. 1. — Location of the study area. The red point indicates the Fırtına Valley. The black rectangle indicates the Rize Province, and the black points indicate the Rize districts. The numbers indicate the nine localities sampled (see Table 1).
Automated mapping and classification of valleys beneath the Greenland Ice Sheet: Datasets
<p><strong>Valley morphology and classification: training dataset and full dataset for Greenland</strong></p> <p>This dataset contains:</p> <ul> <li>TrainingDataValleys.csv: A .csv file of the training dataset used to classify valleys in Greenland as 'fluvial' or 'glacial'. These valleys were extracted from the Copernicus 90 m global digital elevation model.</li> <li>GreenlandValleys.csv: A .csv file of the locations, morphometrics, and class of Greenland valleys identified in Operation IceBridge and CReSIS radio-echo sounding data. These valleys have been classified using a random forest model trained using the above training dataset.</li> </ul>
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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.