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296 results for “Geography”
Dataset for "The Gobolitide (Al-Jibal) microregion: geography and settlement network evolution from Nabataean to Byzantine times"
<p>Dataset for: Kopij, K. and Bała, S. (2021). The Gobolitide (Al-Jibal) microregion: geography and settlement network evolution from Nabataean to Byzantine times. Polish Archaeology in the Mediterranean 30/2) (pp. 181–201). https://doi.org/10.31338/uw.2083-537X.pam30.2.28</p>
Data archive associated with "Landscape age as a major control on the geography of soil weathering" (https://doi.org/10.1029/2019GB006266)
<p>(1) Table including parameter values and weathering model outputs associated with NASGLP sampling locations (SLP_data.csv). </p> <p>(2) List of rivers used for calibrating erosion estimates (river_list.csv).</p> <p>(3) R workspace with same data as (1), plus a data frame of global parameter values ("gm") and spatial polygons giving continent boundaries ("con").</p> <p>(4) Scripts with functions for running the single-compartment weathering model at individual point locations or running a global sample of locations and computing summary statistics by continent (run_soilgenesis.R; soilgenesis.R). </p>
D-PLACE dataset derived from Wessel and Smith 2015 'Global Self-consistent, Hierarchical, High-resolution Geography Database'
<p>Cite the source of the dataset as:</p> <blockquote> <p>Wessel, P., and W. H. F. Smith (1996), A global, self-consistent, hierarchical, high-resolution shoreline database, J. Geophys. Res., 101(B4), 8741–8743, doi:10.1029/96JB00104. Wessel P, Smith, W. H. F. Global Self-consistent, Hierarchical, High-resolution Geography Database (GSHHS) v2.3.4 [Internet]. 2015. Available: https://www.ngdc.noaa.gov/mgg/shorelines/gshhs.html</p> </blockquote>
Data and analysis code from: Micro-scale geography of synchrony in a serpentine plant community
This package includes data and code to reproduce analyses of micro-scale geography of synchrony in the plant community at Jasper Ridge Biological Preserve. Plant cover and soil depth data come from long-term experimental plots established by Richard Hobbs. Plant cover is aggregated into 36 1m2 plots across three treatments (control, gopher exclosure, rabbit exclosure) from 1983 to 2015; included herein are data on the 6 most abundant species (Plantago erecta, Bromus hordeaceous, Lasthenia californica, Microseris douglasii, Vulpia microstachys, and Calycadenia multiglandulosa), total plant cover across all species, and records of gopher disturbance in the plots. The data package also includes time series of monthly precipitation and growing season Palmer’s Drought Severity Index for the same time period. An R Markdown file is included that reproduces all analyses described in the manuscript and reproduces all data figures. Data to support: Walter, Hallett et al. in review “Micro-scale geography of synchrony in a serpentine plant community
Data from: Climate drives the geography of marine consumption by changing predator communities
<p>The global distribution of primary production and consumption by humans (fisheries) is well-documented, but we have no map linking the central ecological process of consumption within food webs to temperature and other ecological drivers. Using standardized assays that span 105° of latitude on four continents, we show that rates of bait consumption by generalist predators in shallow marine ecosystems are tightly linked to both temperature and the composition of consumer assemblages. Unexpectedly, rates of consumption peaked at midlatitudes (25 to 35°) in both Northern and Southern Hemispheres across both seagrass and unvegetated sediment habitats. This pattern contrasts with terrestrial systems, where biotic interactions reportedly weaken away from the equator, but it parallels an emerging pattern of a subtropical peak in marine biodiversity. The higher consumption at midlatitudes was closely related to the type of consumers present, which explained rates of consumption better than consumer density, biomass, species diversity, or habitat. Indeed, the apparent effect of temperature on consumption was mostly driven by temperature-associated turnover in consumer community composition. Our findings reinforce the key influence of climate warming on altered species composition and highlight its implications for the functioning of Earth's ecosystems.</p>
The Literary Geographies of Christine de Pizan (geo-data)
<p>This geodata set gives the place names found in the corpus of writings of Christine de Pizan, woman writer of the late 14th and early 15th centuries. It accompanies an eponymous essay forthcoming in the Modern Language Association's Approaches to Teaching Christine de Pizan volume. </p> <p> </p>
Machine learning reveals that climate, geography, and cultural drift all predict bird song variation in coastal Zonotrichia leucophrys
<p>Previous work has demonstrated that there is extensive variation in the songs of White-crowned Sparrow (<em>Zonotrichia leucophrys</em>) throughout the species range, including between neighboring (and genetically distinct) subspecies <em>Z. l. nuttalli </em>and <em>Z. l. pugetensis</em>. Using a machine learning approach to bioacoustic analysis, we demonstrate that variation in song is correlated with year of recording (representing cultural drift), geographic distance, and climatic differences, but the response is subspecies- and season-specific. Automated machine learning methods of bird song annotation can process large datasets more efficiently, allowing us to examine 1,913 recordings across ~60 years. We utilize a recently published artificial neural network to automatically annotate White-crowned Sparrow vocalizations. By analyzing differences in syllable usage and composition, we recapitulate the known pattern where <em>Z. l. nuttalli </em>and <em>Z. l. pugetensis </em>have significantly different songs. Our results are consistent with the interpretation that these differences are caused by the changes in characteristics of syllables in the White-crowned Sparrow repertoire. This supports the hypothesis that the evolution of vocalization behavior is affected by the environment, in addition to population structure.</p>
GSHHG: Global Self-consistent Hierarchical High-resolution Geography
<p><a href="http://www.soest.hawaii.edu/pwessel/gshhg/"><strong>Global Self-consistent, Hierarchical, High-resolution Geography Database (GSHHG)</strong></a> is a high-resolution geography data set, amalgamated from two databases: World Vector Shorelines (WVS) and CIA World Data Bank II (WDBII). The former is the basis for shorelines while the latter is the basis for lakes, although there are instances where differences in coastline representations necessitated adding WDBII islands to GSHHG. The WDBII source also provides political borders and rivers. GSHHG data have undergone extensive processing and should be free of internal inconsistencies such as erratic points and crossing segments. The shorelines are constructed entirely from hierarchically arranged closed polygons.<br><br>GSHHG combines the older GSHHS shoreline database with WDBII rivers and borders, available in either ESRI shapefile format or in a native binary format. Geography data are in five resolutions: crude(c), low(l), intermediate(i), high(h), and full(f). Shorelines are organized into four levels: boundary between land and ocean (L1), boundary between lake and land (L2), boundary between island-in-lake and lake (L3), and boundary between pond-in-island and island (L4). Datasets are in WGS84 geographic (simple latitudes and longitudes; decimal degrees).</p> <p>GSHHG is released under the <a title="external link to GNU license" href="http://www.gnu.org/licenses/lgpl.html">GNU Lesser General Public license</a>, and is developed and maintained by Dr. Paul Wessel, SOEST, University of Hawai'i, and Dr. Walter H. F. Smith, NOAA Laboratory for Satellite Altimetry. <strong>Please notify Dr. Paul Wessel and Dr. Walter H.F. Smith if any changes are made to the GSHHG data set for commercial use.</strong></p> <p><strong>Processing and assembly of the GSHHG data:<br></strong>Wessel, P., and W. H. F. Smith (1996), A global, self-consistent, hierarchical, high-resolution shoreline database, J. Geophys. Res., 101(B4), 8741–8743, <a href="https://doi.org/10.1029/96JB00104">doi:10.1029/96JB00104.</a></p>
Data and scripts for: Island geography drives evolution of rattan palms in tropical Asian rainforests
<p>This repository contains data and scripts for the research paper "<strong>Island geography drives evolution of rattan palms in tropical Asian rainforests</strong>".</p> <p><strong>Authors</strong>: Benedikt G. Kuhnhäuser, Christopher D. Bates, John Dransfield, Connie Geri, Andrew Henderson, Sang Julia, Jun Ying Lim, Robert J. Morley, Himmah Rustiami, Rowan J. Schley, Sidonie Bellot, Guillaume Chomicki, Wolf L. Eiserhardt, Simon J. Hiscock, William J. Baker</p> <p>Corresponding authors: <a href="mailto:b.kuhnhaeuser@kew.org">b.kuhnhaeuser@kew.org</a>, <a href="mailto:w.baker@kew.org">w.baker@kew.org</a></p> <h3> </h3> <p>The repository contains the following data, scripts, supplementary figures, and supplementary tables:</p> <p>1. Phylogenomic analyses<br>- Alignments<br>- Gene trees<br>- Species trees<br>- README file</p> <p>2. Divergence time estimation<br>- .xml files (containing both sequence data and analysis parameters)<br>- dated trees<br>- README file</p> <p>3. Ancestral range estimation<br>- input data<br>- scripts<br>- input data, intermediate data and scripts for the best model<br>- README file</p> <p>4. Downstream biogeographic analyses<br>- input data<br>- script<br>- README file</p> <p>5. Supplementary Figures</p> <p>6. Supplementary Tables</p>
Competition and geography underlie speciation and morphological evolution in Indo-Australasian monitor lizards
<p>How biotic and abiotic factors act together to shape biological diversity is a major question in evolutionary biology. The recent availability of large datasets and development of new methodological approaches provide new tools to evaluate the predicted effects of ecological interactions and geography on lineage diversification and phenotypic evolution. Here, we use a near complete phylogenomic-scale phylogeny and a comprehensive morphological dataset comprising more than a thousand specimens to assess the role of biotic and abiotic processes in the diversification of monitor lizards (Varanidae). This charismatic group of lizards shows striking variation in species richness among its clades and multiple instances of endemic radiation in Indo-Australasia (i.e., the Indo-Australian Archipelago and Australia), one of Earth's most biogeographically complex regions. We found heterogeneity in diversification dynamics across the family. Idiosyncratic biotic and geographic conditions appear to have driven diversification and morphological evolution in three endemic Indo-Australasian radiations. Furthermore, incumbency effects partially explain patterns in the biotic exchange between Australia and New Guinea. Our results offer insight into the dynamic history of Indo-Australasia, the evolutionary significance of competition, and the long-term consequences of incumbency effects.</p>
Dataset for Aqueous habitats and carbon inputs shape the microscale geography and interaction ranges of soil bacteria
<p>This repository hosts data for the paper entitled: "<em>Aqueous habitats and carbon inputs shape the microscale geography and interaction ranges of soil bacteria</em>" by Samuel Bickel and Dani Or.</p> <p>The following files are provided:</p> <p><strong>Microcosm experiment:</strong></p> <p>- Fluorescence microscopy images of the microcosm experiment (*.tif)</p> <p>- Code used for extracting cell locations from images (image_analysis.py)</p> <p><strong>Global model estimates from the bacterial interactions heuristic model:</strong></p> <p>- Maps of estimated cell density and proportion of biomass associated with anoxic cell clusters (*.nc)</p> <p> </p>
Figure 2 in Global diversity and geography of planktonic marine fungi
Figure 2: Shotgun sequencing data sourced from MG-RAST and manually binned into various oceanographic regions of the world. (Top) Relative abundances (using annotation e-value of 10−8) of fungal genera. Numbers across the top of histogram bars denote the number of datasets used in the analysis. Numbers at top of histogram do not match the total number of databases analyzed, as many samples had no fungal sequences remaining after subsampling. GOM is Gulf of Mexico. (Bottom left) Rarefaction curves showing the number of fungal genera detected as a function of the number of fungal sequences analyzed before database normalization. (Bottom right) Genera-based non-metric multidimensional scaling (NMDS) spatial analysis with indicator taxa displayed, illustrating overlapping, similar fungal communities.
Figure 4 in Global diversity and geography of planktonic marine fungi
Figure 4: Shotgun sequencing data analyzed from metagenomic rapid annotations using subsystems technology (MG-RAST) of deposited datasets plotting richness and diversity as a function of latitude. Red colors depict open ocean samples. Black colors depict coastal samples.
Figure 3 in Global diversity and geography of planktonic marine fungi
Figure 3: 18S rRNA amplicon sequencing of global high-throughput sequencing datasets. Number at top of histogram indicates the number of samples used in this analysis. Numbers at top of histogram do not match the total number of databases analyzed, as many samples had no fungal sequences remaining after subsampling. (Top) Histogram of lowestlevel classification of marine fungal taxa using SILVA-classified datasets from various regions of the world. (Bottom left) Non-metric multidimensional scaling (NMDS) spatial analysis of normalized sequencing datasets displaying color-coded sites with embedded colors representing sites from deeper (>35 m) and shallower depths. (Bottom right) Rarefaction curves showing the number of fungal genera detected as a function of the number of fungal sequences analyzed before database normalization.
Figure 1 in Global diversity and geography of planktonic marine fungi
Figure 1: Global map displaying high-throughput sequencing data sampling sites in red that were used in this review for analysis. Some points represent multiple datasets.
Fig. 2 in Botanical geography correspondence between Alexander von Humboldt and Filippo Parlatore (1851-1852)
Fig. 2 - Alexander von Humboldt in his studio (1848). Lithograph by J. Bardtenschlager from a watercolor by Eduard Hildebrandt. / Alexander von Humboldt nel suo studio (1848). Litografia di J. Bardtenschlager da un acquerello di Eduard Hildebrandt. 32,30 cm x 41,80 cm. Inv.-Nr.: HU 01/8 DR. © Courtesy of Stiftung Stadtmuseum Berlin.
Fig. 3 - Parkinsonia aculeata L in Botanical geography correspondence between Alexander von Humboldt and Filippo Parlatore (1851-1852)
Fig. 3 - Parkinsonia aculeata L. (Fabaceae). American species collected in 1832 at Matamoros (Chihuahua, Mexico) by the FrancoMexican botanist J.-L. Berlandier (courtesy of the Department of Botany in the Natural History Museum of the University of Florence). / Parkinsonia aculeata L. (Fabaceae). Specie americana raccolta nel 1832 presso Matamoros (Chihuahua, Messico) dal botanico francomessicano J.-L. Berlandier (per gentile concessione del Dipartimento di Botanica del Museo di Storia Naturale dell'Università di Firenze).
Fig. 7 - Polemonium caeruleum L in Botanical geography correspondence between Alexander von Humboldt and Filippo Parlatore (1851-1852)
Fig. 7 - Polemonium caeruleum L. (Polemoniaceae). Arctic-Alpine plant collected in Sweden (Jämtland County) by J. Emanuel Wikström in 1844 (courtesy of the Department of Botany in the Natural History Museum of the University of Florence). / Polemonium caeruleum L. (Polemoniaceae). Pianta artico-alpina (raccolta in Svezia (Contea di Jämtland) da J. Emanuel Wikström nel 1844 (per gentile concessione del Dipartimento di Botanica del Museo di Storia Naturale dell'Università di Firenze).
Fig. 6 - Erigeron alpinus L in Botanical geography correspondence between Alexander von Humboldt and Filippo Parlatore (1851-1852)
Fig. 6 - Erigeron alpinus L. (Asteraceae). Italian collection of brothers A. and C. Perini made in Trentino, plant received by Parlatore in September 1844 (courtesy of the Department of Botany in the Natural History Museum of the University of Florence). / Erigeron alpinus L. (Asteraceae). Raccolta italiana dei fratelli A. e C. Perini effettuata in Trentino, pianta ricevuta da Parlatore nel Settembre del 1844 (per gentile concessione del Dipartimento di Botanica del Museo di Storia Naturale dell'Università di Firenze).
Fig. 1 in Botanical geography correspondence between Alexander von Humboldt and Filippo Parlatore (1851-1852)
Fig. 1 - Filippo Parlatore (1816-1877) in a photographic portrait by Gustavo Matucci (187?). Handwritten title on the recto, where the following note also appears: R. Tod. [Todaro Collection]. Mounted on 165 x 105 mm cardboard. 1 photo: albumin; 137 x 97 mm. University of Padua. Library of the Botanical Garden (IB.FF.8). Creative Commons license CC BY-NC-SA 4.0. / Filippo Parlatore (1816-1877) in un ritratto fotografico di Gustavo Matucci (187?). Titolo manoscritto sul recto, dove compare anche la nota: R. Tod. [Raccolta Todaro]. Montata su cartoncino 165 x 105 mm. 1 fotografia: albumina; 137 x 97 mm. Università di Padova. Biblioteca dell'Orto Botanico (IB.FF.8). Licenza Creative Commons CC BY-NC-SA 4.0.
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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.