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Figs. 17-21. 17-20 in Taxonomic Review of Zavreliella Kieffer from East Asia
Figs. 17-21. 17-20 Zavreliella inawaheia Sasa, Kitami & Suzuki, 2001, male. 17 hypopygium 18 details of superior volsella 19 details of inferior volsella 20 color photograph of hypopygium. 21 Zavreliella shidai sp. n. color photograph of male hypopygium.
Figs. 1-9 in Taxonomic Review of Zavreliella Kieffer from East Asia
Figs. 1-9. Zavreliella shidai sp. n., male. 1 wing 2 abdominal marking, dorsal view 3 legs, showing marking pattern 4 forefemur 5 foretibial apex 6 mid tibial apex 7 hind tibial apex 8 hypopygium 9 details of superior volsella.
Figs. 10-16 in Taxonomic Review of Zavreliella Kieffer from East Asia
Figs. 10-16. Zavreliella shidai sp. n., pupa. 10 frontal apotome, with details of cephalic tubercles in upper corners 11 thoracic horn 12 thorax 13 details of basal ring 14 tergites 15 anal comb of VIII 16 anal lobe, showing male sac.
FIG. 1. — Clitoria ternatea L in Clitoria ternatea L. var. angustifolia Hochst. ex Baker (Fabaceae): new varietal record to Asia from India
FIG. 1. — Clitoria ternatea L. var. angustifolia Hochst. ex Baker f. from Machchu Dam 3 (India):A, habit (A', habit with flower); B, leaf with flower; C, leaf; D, E, flower; F, legume; G, seeds. Photos: P. K. Patel.
Figure 5 in Multiple mitogenomes indicate Things Fall Apart with Out of Africa or Asia hypotheses for the phylogeographic evolution
Figure 5. Molecular clades of A. mellifera mapped onto the first two PCA axes of morphometric ACMO space, redrawn afer Fig. 10.8 in Ref.8. Individual bees are identified to subspecies by the numeric color codes, and re-grouped to genetic clades as in Fig. 3, with additional color variants for Sub-Saharan taxa. Ruttner's four groups [African (A), European (C [Continental]), Mellifera (M), and Asian (O [Oriental]] correspond roughly to the four quadrants, clockwise from the upper lef as A, M, C, and O. Ŀe Levantine/Nilotic/Arabian clade overlays the Sub-Saharan clade, including local variants. Ŀe Asia Minor A. m. caucasia clade is distributed along the M → O axis, and is bisected by its Southeast European sister clade A. m. ligustica. Ŀe Afro-European Mediterranean clade overlies all three, as well as the basal A. m. mellifera clade.
Figure 2 in Multiple mitogenomes indicate Things Fall Apart with Out of Africa or Asia hypotheses for the phylogeographic evolution
Figure 2. Schematic maximum parsimony analysis of phylogenetic relationships among mtDNA genome sequences of 66 individual A. mellifera honey bees from 22 subspecies. Rooting as indicated by Fig. 1. Numbers above branches are inferred numbers of nucleotide substitutions; numbers in bold below branches are percent support in 3000 bootstrap replicates, with SPR branching swapping. Ŀe tree shown is one of nine minimum length trees that differ only by rearrangements at unresolved nodes. Sequences in the Sub-Saharan clade that make that subspecies paraphyletic are tagged in Roman font, as are two sequences referred to A. m. scutellata that are outside that clade. An additional 12 sequences from the Arabian series that are identical to the four shown are not included. Sequences curated as A. m. mellifera in GenBank15 are re-assigned their proper names in parentheses (J. M. Fuller, pers. comm). Subspecies represented by single sequences are indicated by (*). Named phylogeographic clades discussed in the text are indicated in color. Ŀe complete MP tree with GenBank accession numbers is given in Supplementary Fig. S1, along with those for Maximum Likelihood and Neighbor Joining methods (Supplementary Figs. S2 and S3, respectively).
Figure 6 in Multiple mitogenomes indicate Things Fall Apart with Out of Africa or Asia hypotheses for the phylogeographic evolution
Figure 6. Comparison of Boardman et al.11 and Tihelka et al.20 meta-analyses with Fig. 2. Ŀe base phylogram is a Maximum Parsimony analysis calculated as in Fig. 2, with the addition of two problematic sequences mentioned in the text, KY926882 and KY926883, attributed to A. m. syriaca and A. m. intermissa, respectively. Ŀe 17 sequences used by Boardman et al. are marked "B" and the 16 sequences used by Tihelka et al. "T", with the 11 sequences common to both sets "TB". Note the anomalous pairwise placements of two sequences attributed to KY026882 and KY926883 with respect to their nominal sister subspecies (* and *, respectively).
Figure 1 in Multiple mitogenomes indicate Things Fall Apart with Out of Africa or Asia hypotheses for the phylogeographic evolution
Figure 1. Maximum Parsimony analysis of phylogenetic relationships among mtDNA genomes sequences of nine species of Apis honey bees. (a) Ŀe tree is rooted with a bumblebee Bombus ignitus as outgroup. A. m. mellifera (KY926884) is the basal-most member of that species and the alignment reference. Numbers above branches are inferred numbers of nucleotide substitutions; numbers in bold below branches are percent support in 3000 bootstrap replicates. Identical branching order and substantially similar bootstrap support are given by Maximum Likelihood and Neighbor Joining methods. (b) As above, with removal of Bombus and addition of key subspecies of A. mellifera (cf. Fig. 2).
Figure 4 in Multiple mitogenomes indicate Things Fall Apart with Out of Africa or Asia hypotheses for the phylogeographic evolution
Figure 4. An mtDNA-based molecular clock for within- and among-subspecies divergences of A. mellifera. Sequences are coded as in Fig. 2: only one representative each of A. m. scutellata and A. m. capensis is included (n = 37). Divergence times are calculated from a linearized ML model with A. m. mellifera sequences as the designated outgroup (cf. Supplementary Fig. S2). Ŀe clock is calibrated from the mean linearized nucleotide subs/site distances to each node (Relative Time) at 0.0115 subs/site/Myr (see text for sample calculation). See Supplementary Fig. S4 for the clock of A. mellifera within Apis, with Bombus as the designated outgroup.
Figure 3 in Multiple mitogenomes indicate Things Fall Apart with Out of Africa or Asia hypotheses for the phylogeographic evolution
Figure 3. Phylogeographic evolution in context of geographic distribution2 of subspecies of A. mellifera as inferred from mitogenomic data. Numbered symbols indicate five clades described in the text and in Fig. 2. Dark and light green circles indicate respectively subspecies in the Southeast European and Asia Minor clades included within the Eurasian superclade. Blue symbols indicate the Levantine (circles), Nilotic (squares), and Arabian (A. m. jemenitica) (diamonds) clades. Light and dark purple circles indicate independent A. m. simensis and A. m. unicolor lineages, respectively. Light orange symbols indicate subspecies in the Mediterranean clade. Red circles indicate the paraphyletic assemblage of A. m. scutellata and A. m. capensis, including A. m. adansonii (light red) and A. m. monticola (brown). Base map modified from [https://commons. wikimedia.org/wiki/File:BlankMap-World.svg].
A downscaled 0.05-Degree Monthly Solar-Induced Chlorophyll Fluorescence Product derived using AVHRR Data in East Asia (1995-2003)
<p>Downscaling techniques offer the opportunity to utilize coarse-spatial-resolution SIF products for investigating carbon cycles and ecological processes at finer resolutions. Here, we generated a new monthly SIF product, DSIF_EA0.05, at a resolution of 0.05° in East Asia from July 1995 to June 2003. The random forest kriging (RFK) approach was employed, incorporating GOME SIF, AVHRR data, ERA5 climate data, and using the optimal explanatory variables. The unit of SIF is mW m<sup>-2</sup> nm<sup>-1</sup> sr<sup>-1</sup>. The selected variables were daily maximum values of air temperature (T<sub>air</sub>), skin temperature (T<sub>skin</sub>), fraction of absorbed photosynthetically active radiation (fPAR), near-infrared reflectance of vegetation (NIRv), downward shortwave radiation (SR<sub>down</sub>), and precipitation. To verify the reliability of DSIF_EA0.05 and the advantages over original GOME SIF, this dataset has been validated with the original GOME SIF, ground gross primary productivity (GPP) data from eight flux sites, and two other SIF products at 1-degree and 0.05-degree resolutions from SCIAMACHY SIF and downscaled SCIAMACHY SIF datasets.</p>
ELITE land surface temperature: hourly seamless 0.02° LST over East Asia (2021)
<p>The <strong>E</strong>ssential therma<strong>L</strong> <strong>I</strong>nfrared remo<strong>T</strong>e s<strong>E</strong>nsing (<strong>ELITE</strong>) product suite currently has four types of products, including land surface temperature (LST: clear-sky and all-sky), emissivity (NBE: narrowband emissivity; BBE: broadband emissivity; and spectral emissivity), the component of surface radiation and energy budget (SLUR: surface longwave upwelling radiation; SLDR: surface longwave downward radiation SLDR; SLNR: surface longwave net radiation), and the component of Earth’s radiation budget (OLR; outgoing longwave radiation; RSR: reflected solar radiation). The spatial-temporal resolutions of the ELITE products are mainly determined by the employed satellite data sources. For more information about ELITE products, please refer to the website (<a href="https://elite.bnu.edu.cn">https://elite.bnu.edu.cn</a>).</p> <p>This dataset is the ELITE hourly seamless 0.02 ° LST dataset over East Asia (2016-2021). Firstly, the iTES algorithm is employed to retrieve the Himawari-8/AHI LST. Secondly, the CLDAS LST is corrected to eliminate its system deviation. Finally, the multi-scale Kalman filter is employed to fuse Himawari-8/AHI LST and the bias-corrected CLDAS LST to generate 0.02 ° hourly seamless LST. The in situ validation results show that the root mean square error (RMSE) of the seamless LST is about 3k. The temporal resolution and spatial resolution of this dataset are 1 hour and 0.02°, respectively.</p> <p>This is the seamless LST dataset in 2021. Please<a href="../records/10668883" target="_blank" rel="noopener"> <strong><em>click here</em></strong></a> to download the ELITE LST product in Januray-June, 2022.</p> <p><strong>Dataset Characteristics:</strong></p> <ul> <li>Spatial Coverage: East Asia (0-60°N, 80°E-140°E)</li> <li>Temporal Coverage: 2021</li> <li>Spatial Resolution: 0.02 °</li> <li>Temporal Resolution: one hour</li> <li>Data Format: Geotiff</li> <li>Scale: 0.01</li> </ul> <p><strong>Citation </strong>(Please cite these papers when using the data)<strong>:</strong></p> <ol> <li>Dong, S., Cheng, J., Shi, J., Shi, C., Sun, S., & Liu, W. (2022). A Data Fusion Method for Generating Hourly Seamless Land Surface Temperature from Himawari-8 AHI Data. Remote Sensing, 14, 5170</li> <li>Zhou, S., & Cheng, J. (2020). An Improved Temperature and Emissivity Separation Algorithm for the Advanced Himawari Imager. IEEE Transactions on Geoscience and Remote Sensing, 58(10), 7105-7124.</li> </ol> <p>If you have any questions, please contact Prof. Jie Cheng (Jie_Cheng@bnu.edu.cn).</p>
ELITE land surface temperature: hourly seamless 0.02° LST over East Asia (2020)
<p>The <strong>E</strong>ssential therma<strong>L</strong> <strong>I</strong>nfrared remo<strong>T</strong>e s<strong>E</strong>nsing (<strong>ELITE</strong>) product suite currently has four types of products, including land surface temperature (LST: clear-sky and all-sky), emissivity (NBE: narrowband emissivity; BBE: broadband emissivity; and spectral emissivity), the component of surface radiation and energy budget (SLUR: surface longwave upwelling radiation; SLDR: surface longwave downward radiation SLDR; SLNR: surface longwave net radiation), and the component of Earth’s radiation budget (OLR; outgoing longwave radiation; RSR: reflected solar radiation). The spatial-temporal resolutions of the ELITE products are mainly determined by the employed satellite data sources. For more information about ELITE products, please refer to the website (<a href="https://elite.bnu.edu.cn">https://elite.bnu.edu.cn</a>).</p> <p>This dataset is the 0.02 ° hourly seamless LST dataset over East Asia (2016-2021). Firstly, the iTES algorithm is employed to retrieve the Himawari-8/AHI LST. Secondly, the CLDAS LST is corrected to eliminate its system deviation. Finally, the multi-scale Kalman filter is employed to fuse Himawari-8/AHI LST and the bias-corrected CLDAS LST to generate 0.02 ° hourly seamless LST. The in situ validation results show that the root mean square error (RMSE) of the seamless LST is about 3k. The temporal resolution and spatial resolution of this dataset are 1 hour and 0.02°, respectively.</p> <p>This is the ELITE seamless LST product in 2020. Please <a href="https://zenodo.org/record/8260245"><strong><em>click here</em></strong></a> to download the ELITE LST product in 2019 and <a href="https://zenodo.org/record/8260240"><strong><em>click here</em></strong></a> to download the ELITE LST product in 2021.</p> <p><strong>Dataset Characteristics:</strong></p> <ul> <li>Spatial Coverage: East Asia (0-60°N, 80°E-140°E)</li> <li>Temporal Coverage: 2020</li> <li>Spatial Resolution: 0.02 °</li> <li>Temporal Resolution: one hour</li> <li>Data Format: Geotiff</li> <li>Scale: 0.01</li> </ul> <p><strong>Citation </strong>(Please cite these papers when using the data)<strong>:</strong></p> <ol> <li>Dong, S., Cheng, J., Shi, J., Shi, C., Sun, S., & Liu, W. (2022). A Data Fusion Method for Generating Hourly Seamless Land Surface Temperature from Himawari-8 AHI Data. Remote Sensing, 14, 5170</li> <li>Zhou, S., & Cheng, J. (2020). An Improved Temperature and Emissivity Separation Algorithm for the Advanced Himawari Imager. IEEE Transactions on Geoscience and Remote Sensing, 58(10), 7105-7124.</li> </ol> <p>If you have any questions, please contact Prof. Jie Cheng (Jie_Cheng@bnu.edu.cn).</p> <p> </p>
ELITE land surface temperature: hourly seamless 0.02° LST over East Asia (2018)
<p>The <strong>E</strong>ssential therma<strong>L</strong> <strong>I</strong>nfrared remo<strong>T</strong>e s<strong>E</strong>nsing (<strong>ELITE</strong>) product suite currently has four types of products, including land surface temperature (LST: clear-sky and all-sky), emissivity (NBE: narrowband emissivity; BBE: broadband emissivity; and spectral emissivity), the component of surface radiation and energy budget (SLUR: surface longwave upwelling radiation; SLDR: surface longwave downward radiation SLDR; SLNR: surface longwave net radiation), and the component of Earth’s radiation budget (OLR; outgoing longwave radiation; RSR: reflected solar radiation). The spatial-temporal resolutions of the ELITE products are mainly determined by the employed satellite data sources. For more information about ELITE products, please refer to the website (<a href="https://elite.bnu.edu.cn">https://elite.bnu.edu.cn</a>).</p> <p>This dataset is the 0.02 ° hourly seamless LST dataset over East Asia (2016-2021). Firstly, the iTES algorithm is employed to retrieve the Himawari-8/AHI LST. Secondly, the CLDAS LST is corrected to eliminate its system deviation. Finally, the multi-scale Kalman filter is employed to fuse Himawari-8/AHI LST and the bias-corrected CLDAS LST to generate 0.02 ° hourly seamless LST. The in situ validation results show that the root mean square error (RMSE) of the seamless LST is about 3k. The temporal resolution and spatial resolution of this dataset are 1 hour and 0.02°, respectively.</p> <p>This is the ELITE seamless LST product in 2018. Please <a href="https://zenodo.org/record/8266456"><strong><em>click here</em></strong></a> to download the ELITE LST product in 2017 and <a href="https://zenodo.org/record/8260245"><strong><em>click here</em></strong></a> to download the ELITE LST product in 2019.</p> <p><strong>Dataset Characteristics:</strong></p> <ul> <li>Spatial Coverage: East Asia (0-60°N, 80°E-140°E)</li> <li>Temporal Coverage: 2018</li> <li>Spatial Resolution: 0.02 °</li> <li>Temporal Resolution: one hour</li> <li>Data Format: Geotiff</li> <li>Scale: 0.01</li> </ul> <p><strong>Citation </strong>(Please cite these papers when using the data)<strong>:</strong></p> <ol> <li>Dong, S., Cheng, J., Shi, J., Shi, C., Sun, S., & Liu, W. (2022). A Data Fusion Method for Generating Hourly Seamless Land Surface Temperature from Himawari-8 AHI Data. Remote Sensing, 14, 5170</li> <li>Zhou, S., & Cheng, J. (2020). An Improved Temperature and Emissivity Separation Algorithm for the Advanced Himawari Imager. IEEE Transactions on Geoscience and Remote Sensing, 58(10), 7105-7124.</li> </ol> <p>If you have any questions, please contact Prof. Jie Cheng (Jie_Cheng@bnu.edu.cn).</p> <p> </p>
ELITE land surface temperature: hourly seamless 0.02° LST over East Asia (2019)
<p>The <strong>E</strong>ssential therma<strong>L</strong> <strong>I</strong>nfrared remo<strong>T</strong>e s<strong>E</strong>nsing (<strong>ELITE</strong>) product suite currently has four types of products, including land surface temperature (LST: clear-sky and all-sky), emissivity (NBE: narrowband emissivity; BBE: broadband emissivity; and spectral emissivity), the component of surface radiation and energy budget (SLUR: surface longwave upwelling radiation; SLDR: surface longwave downward radiation SLDR; SLNR: surface longwave net radiation), and the component of Earth’s radiation budget (OLR; outgoing longwave radiation; RSR: reflected solar radiation). The spatial-temporal resolutions of the ELITE products are mainly determined by the employed satellite data sources. For more information about ELITE products, please refer to the website (<a href="https://elite.bnu.edu.cn">https://elite.bnu.edu.cn</a>).</p> <p>This dataset is the 0.02 ° hourly seamless LST dataset over East Asia (2016-2021). Firstly, the iTES algorithm is employed to retrieve the Himawari-8/AHI LST. Secondly, the CLDAS LST is corrected to eliminate its system deviation. Finally, the multi-scale Kalman filter is employed to fuse Himawari-8/AHI LST and the bias-corrected CLDAS LST to generate 0.02 ° hourly seamless LST. The in situ validation results show that the root mean square error (RMSE) of the seamless LST is about 3k. The temporal resolution and spatial resolution of this dataset are 1 hour and 0.02°, respectively.</p> <p>This is the ELITE seamless LST product in 2019. Please <a href="https://zenodo.org/record/8256087"><strong><em>click here</em></strong></a> to download the ELITE LST product in 2018 and <a href="https://zenodo.org/record/8264798"><strong><em>click here</em></strong></a> to download the ELITE LST product in 2020.</p> <p><strong>Dataset Characteristics:</strong></p> <ul> <li>Spatial Coverage: East Asia (0-60°N, 80°E-140°E)</li> <li>Temporal Coverage: 2019</li> <li>Spatial Resolution: 0.02 °</li> <li>Temporal Resolution: one hour</li> <li>Data Format: Geotiff</li> <li>Scale: 0.01</li> </ul> <p><strong>Citation </strong>(Please cite these papers when using the data)<strong>:</strong></p> <ol> <li>Dong, S., Cheng, J., Shi, J., Shi, C., Sun, S., & Liu, W. (2022). A Data Fusion Method for Generating Hourly Seamless Land Surface Temperature from Himawari-8 AHI Data. Remote Sensing, 14, 5170</li> <li>Zhou, S., & Cheng, J. (2020). An Improved Temperature and Emissivity Separation Algorithm for the Advanced Himawari Imager. IEEE Transactions on Geoscience and Remote Sensing, 58(10), 7105-7124.</li> </ol> <p>If you have any questions, please contact Prof. Jie Cheng (Jie_Cheng@bnu.edu.cn).</p> <p> </p>
Fig. 1 in First record of Bolitophila japonica (Diptera: Bolitophilidae) for continental Asia
Fig. 1. Bolitophila japonica – male terminalia, dorsal view, tergite IX is not visible (specimen from Nepal, microphotography).
Figure Data for "Continuous Estimates of Glacier Mass Balance in High Mountain Asia Based on ICESat-1,2 and GRACE/GRACE Follow-On"
<p>Figure Data for "Continuous Estimates of Glacier Mass Balance in High Mountain Asia Based on ICESat-1,2 and GRACE/GRACE Follow-On" Data" </p>
44 Block--63k or 50k scale Maps of South Asia
<p>320 maps of the Survey of India covering block 44.</p> <p>In the time since this first batch of maps (see the list below) was posted additional maps of Block 44 have become available. These additional maps are posted on a separate page, and can be reached by clicking the link(s) below. Included in the final set of additional maps is an Index Map showing the total 63k/50k holdings in Block 44.</p> <table> <tbody> <tr> <td><a href="../records/10460244">63k/50k Maps of South Asia--Block 44--additional 1--20240105</a></td> </tr> <tr> <td><a href="../records/10460247">63k/50k Maps of South Asia--Block 44--additional 2--20240105</a></td> </tr> </tbody> </table>
41 Block--63k or 50k scale South Asia Maps
<p>175 maps of the Survey of India covering block 41.</p> <p>In the time since this first batch of maps (see the list below) was posted additional maps of Block 41 have become available. These additional maps are posted on a separate page, and can be reached by clicking the link(s) below. Included in the final set of additional maps is an Index Map showing the total 63k/50k holdings in Block 41.</p> <table> <tbody> <tr> <td><a href="../records/10460221">63k/50k Maps of South Asia--Block 41--additional 1--20240105</a></td> </tr> </tbody> </table>
43 Block--63k or 50k scale Maps of South Asia
<p>293 maps of the Survey of India covering block 43.</p> <p>In the time since this first batch of maps (see the list below) was posted additional maps of Block 43 have become available. These additional maps are posted on a separate page, and can be reached by clicking the link(s) below. Included in the final set of additional maps is an Index Map showing the total 63k/50k holdings in Block 43.</p> <table> <tbody> <tr> <td><a href="../records/10460235">63k/50k Maps of South Asia--Block 43--additional 1--20240105</a></td> </tr> <tr> <td><a href="../records/10460240">63k/50k Maps of South Asia--Block 43--additional 2--20240105</a></td> </tr> </tbody> </table>
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.