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Figs. 1-2 in Contribution to the knowledge of the genus Thaumaglossa Redtenbacher, 1867 from North and Central America (Coleoptera¡ Dermestidae¡ Megatominae).
Figs. 1-2.- Thaumaglossa cognatoi sp. nov. 1.- Terminal antennomere of male. 2.- Aedeagus.
PaleoDA South America reconstruction
<p>This repository contains the reconstruction data ase presented in "A continental reconstruction of hydroclimatic variability in South America during the past 2000 years", submitted to Climate of the Past in February 2024 [https://egusphere.copernicus.org/preprints/2024/egusphere-2024-545/]. The data can be used to reproduce the Figures of the manuscript using the code in the accompanying Github repository: https://github.com/mchoblet/paleoda_sa/tree/main</p> <p><strong>Origin of Files:</strong></p> <p>See paper_experiments.ipynb in https://github.com/mchoblet/paleoda_sa/</p> <p><strong>Structure:</strong></p> <p>The files were compressed for space reasons.</p> <p>Each ZIP files contains the reconstructions for a specic reconstruction configuration (normal error, same error, half error) and seasonality (annual, DJF). The error type refers to how the proxy record error was defined (see section 3.4 of the manuscript) and the seasonality</p> <p>The standard reconstruction is the annual normal error reconstruction. The Folder contains subfoldes for different types of reconstructions depending on the proxy data that was used as input (standard is all_proxies). Reconstructions have been performed for five different model priors (see input data here https://zenodo.org/uploads/10370001). <em>I recommend using the multi-model reconstruction mean</em>. 'Proxy_frac' indicates that in each Monte Carlo reconstruction (the mean of 50 iterations is saved) 80% of the proxy record data was used as input data. The structure of the files is relevant for the plotting scripts.</p> <p><strong>Revision in July 2024</strong>:</p> <p>Due to the inclusion of a dozen more proxy records (11 historical indices and 1 lake sediment record), the results have (slightly) changed and needed to be updated.</p>
Fig. 2 in First record of the painted bug Bagrada hilaris (Burmeister, 1835) (Heteroptera: Pentatomidae) in South America.
Fig. 2.- Nymph of B. hilaris in Quilicura.
Fig. 5 in First record of the painted bug Bagrada hilaris (Burmeister, 1835) (Heteroptera: Pentatomidae) in South America.
Fig. 5.- Bagrada hilaris, habitus.
Fig. 1 in First record of the painted bug Bagrada hilaris (Burmeister, 1835) (Heteroptera: Pentatomidae) in South America.
Fig. 1.- Mating pair of Bagrada hilaris in Quilicura.
Fig. 2 in First record of Silpha puncticollis Lucas, 1846 (Coleoptera¦ Silphidae, Silphinae) for North America.
Fig. 2.- Habitus of Silpha puncticollis Lucas, 1846 (♂).
Fig. 5 in New distributional records of the genus Tetragonoderus Dejean, 1829 from the United States of America, including an updated key to species (Coleoptera: Carabidae)
Fig. 5 – Tetragonoderus pallidus Horn, 1869: a, map of distribution; b, habitus.
Fig. 4 in New distributional records of the genus Tetragonoderus Dejean, 1829 from the United States of America, including an updated key to species (Coleoptera: Carabidae)
Fig. 4 – Tetragonoderus latipennis LeConte, 1874: a, map of distribution; b, habitus.
Fig. 1 in New distributional records of the genus Tetragonoderus Dejean, 1829 from the United States of America, including an updated key to species (Coleoptera: Carabidae)
Fig. 1 – Tetragonoderus fasciatus (Haldeman, 1843): a, map of distribution; b, habitus.
Fig. 3 in New distributional records of the genus Tetragonoderus Dejean, 1829 from the United States of America, including an updated key to species (Coleoptera: Carabidae)
Fig. 3 – Tetragonoderus laevigatus Chaudoir, 1876: a, map of distribution; b, habitus.
Fig. 2 in New distributional records of the genus Tetragonoderus Dejean, 1829 from the United States of America, including an updated key to species (Coleoptera: Carabidae)
Fig. 2 – Tetragonoderus intersectus (Germar, 1824): a, map of distribution; b, habitus.
Northern and central Walker Lane horizontal velocities in North America and Sierra Nevada reference frames.
<p>The data in this file contains east and north velocities covering the northern and central sections of the Walker Lane, USA. The velocities were obtained from GPS time series, available at Nevada Geodetic Laboratory (NGL): http://geodesy.unr.edu/NGLStationPages/gpsnetmap/GPSNetMap.html (24 hour final solutions). The position time series were manually screened and corrected for offsets, and a local common-mode filter was applied following the methodology of Kreemer & Blewitt (2021, https://doi.org/10.1007/s00190-020-01466-5). Velocities in the North America frame were obtained using MIDAS, a robust median trend estimator (Blewitt et al., 2016, https://doi.org/10.1002/2015JB012552). Two sets of stations were used to rotate the velocities into the Sierra Nevada frame: CAOV, CAPV, P140, P276, P310 for the northern section and CMBB, P245, P305, P308, P512 for the central section.</p> <p>The file contains the following columns:</p> <ul> <li>sta: station ID</li> <li>lon: longitude of station (decimal degree)</li> <li>lat: latitude of station (decimal degree)</li> <li>ve_NA: east velocity in North America frame (mm/yr)</li> <li>vn_NA: north velocity in North America frame (mm/yr) </li> <li>ve_SN: east velocity in Sierra Nevada frame (mm/yr) </li> <li>vn_SN: north velocity in Sierra Nevada frame (mm/yr) </li> <li>region: denotes whether the set of stations used to rotate the velocities into the Sierra Nevada frame are located in the northern (N) or central (C) Walker Lane</li> <li>sve: east velocity uncertainty (mm/yr)</li> <li> svn: north velocity uncertainty (mm/yr)</li> <li>network: who operates the station</li> </ul>
CLDF dataset derived from Blum et al.'s (2024) "A Comparative Wordlist for Investigating Distant Relations Among Languages in Lowland South America"
<p>Cite the source of the dataset as:</p> <blockquote> <p>Blum, Frederic and Barrientos, Carlos and Zariquiey, Roberto and List, Johann-Mattis. 2024. A Comparative Wordlist for Investigating Distant Relations Among Languages in Lowland South America. *Scientific Data* 11(92). https://doi.org/10.1038/s41597-024-02928-7</p> </blockquote>
Land facet data for North America at 100m resolution.
<p>We developed a dataset categorizing the North American continent into physical habitat types at 100m resolution. The input data used included elevation and soil type. Further details on methodology are available <a href="http://www.cacpd.org/Facets/landfacetmethods.pdf">here</a>. The data is provided via a link to a zipfile containing TIFF (.tif) format files that can be imported into ArcGIS or other GIS applications. Projection information is available <a href="http://www.cacpd.org/Facets/lazea.prj">here</a>.</p> <p>One potential strategy for protecting biodiversity in a changing climate is based on the idea of protecting the diversity of abiotic conditions that influence patterns of biodiversity. In this strategy, conservation features (the “targets” considered in the conservation planning process) are derived from data on physical features such as topography, soils, and geology. The approach has been described as “conserving the ecological stage” or protecting “land facets” or “enduring features”. Species distributions, communities, ecosystems, and broader patterns of biodiversity are clearly influenced by abiotic drivers such as soils, geology, topography, and climate. Although climates will change relatively rapidly over the coming century, soils, geology, and topography will not. Thus, local, and some regional, climate patterns and gradients influenced by topography will persist (e.g., higher elevations will still be cooler than lower elevations, although both will likely be warmer) as climates change. The hypothesis underlying use of land facets in climate adaptation planning is that by protecting a diversity of land facets, it may be possible to protect areas that will foster a diversity of biota in the future, albeit different biota than those areas would protect today. Although land facets are clearly an imperfect coarse-filter surrogate for biodiversity, physical habitat diversity may still represent a useful additional source of data that can augment biodiversity data in conservation planning processes.</p>
Fig. 2 in A new genus in the dipterous family Cyrtidae from South America
Fig. 2. Wing of Lasia sp., nomenclature according to the Comstock system.
1. CAMPOSELLA INSIGNATA, N in A new genus in the dipterous family Cyrtidae from South America
1. CAMPOSELLA INSIGNATA, N. GEN. ET SP. 2. LASIA SR-COLE.
Thermal regimes, but not mean temperatures, drive patterns of rapid climate adaptation at a continent-scale: evidence from the introduced European earwig across North America
<p>Full data set + R script</p>
Fig. 30 in Synopsis of the extinct Batrachia, Reptilia and Aves of North America
Fig. 30.
Fig. 33 in Synopsis of the extinct Batrachia, Reptilia and Aves of North America
Fig. 33.
Fig. 32 in Synopsis of the extinct Batrachia, Reptilia and Aves of North America
Fig. 32.
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.