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349 results for “global distribution”
Data from: Climate change is predicted to impact the global distribution and richness of pines (genus Pinus) by 2070
<p>Aim: Climate change is altering habitat suitability for many organisms and modifying species ranges at a global scale. Here we explored the impact of climate change on 112 pine species (<em>Pinus</em>), fundamental elements of Northern terrestrial ecosystems.</p> <p>Location: Global.</p> <p>Methods: We applied a novel methodology for species distribution modelling that considers uncertainty in climatic projections and taxon sampling, and incorporates elements of species' recent evolutionary history. We based our niche calculations on climate and soil data and computed projections across multiple algorithms and IPCC scenarios, which were ensembled into one single suitability map. We then used phylogenetic methods to account for recent evolution in climatic requirements by estimating the evolution of climatic niche. Edaphoclimatic and evolutionary analyses were then combined to calibrate the projections in areas showing high uncertainty. We validated our models using naturalized occurrences of invasive pine species.</p> <p>Results: Our models predicted that by 2070 most pine species (58%) might face important reductions of habitat suitability, potentially leading to range losses and a decrease in species richness, particularly in some regions such as the Mediterranean Basin and South North America, albeit migration might mitigate these shifts in some cases. In contrast, our projections showed increased habitat suitability for approx. 20% of species, which may undergo range expansions under climate change. Moreover, the consideration of recent evolutionary trends modified projected scenarios, decreasing range loss and increasing range expansion for some species. The independent validation endorsed our models for many species and the influence of recent evolution in some cases.</p> <p>Conclusions: We predict that climate change will impose drastic changes in pine distribution and diversity across biogeographical regions, but the magnitude and direction of change will vary significantly across regions and taxa. Species-level responses are likely to be influenced by regional conditions and the recent evolutionary history of each taxon.</p>
GARD 1.7 - updated global distributions for all terrestrial reptiles
<p class="MsoNormal"><span>This is the updated version of the Global Assessment of Reptile Distributions (GARD; http://www.gardinitiative.org/) global distributions of all (10914 species) of terrestrial reptiles. Ranges are given in a polygonal shapefile format collated from various sources and had expert validation and curation.</span></p>
Evolution in response to climate in the native and introduced ranges of a globally distributed plant
<p><span>The extent to which species can adapt to spatiotemporal climatic variation in their native and introduced ranges remains unresolved. To address this, we examined how clines in cyanogenesis (HCN production—an antiherbivore defense associated with decreased tolerance to freezing) have shifted in response to climatic variation in space and time over a 60-year period in both the native and introduced ranges of <em>Trifolium repens</em>. HCN production is a polymorphic trait controlled by variation at two Mendelian loci (<em>Ac</em> and <em>Li</em>). Using phenotypic assays, we estimated within-population frequencies of HCN production and dominant alleles at both loci (i.e., <em>Ac</em> and <em>Li</em>) from 10,575 plants sampled from 131 populations on 5 continents, and then compared these frequencies to those from historical data collected in the 1950s. There were no clear relationships between changes in the frequency of HCN production, <em>Ac</em>, or <em>Li</em> and changes in temperature between contemporary and historical samples. We did detect evidence of continued evolution to temperature gradients in the introduced range, whereby the slope of contemporary clines for HCN and <em>Ac</em> in relation to winter temperature became steeper than historical clines and more similar to native clines. These results suggest that cyanogenesis clines show no clear changes through time in response to global warming, but introduced populations continue to adapt to their contemporary environments.</span></p>
Global distribution of oxygenated polycyclic aromatic hydrocarbons in mineral topsoils
<p>The hazardous oxygenated polycyclic aromatic hydrocarbons (OPAHs) originate from combustion (primary sources) or post-emission conversion of PAHs (secondary sources). We evaluated the global distribution of up to 15 OPAHs in 195 mineral topsoils from 33 study sites (covering 52°N-47°S, 71°W-118°E), to identify indications of primary or secondary sources of OPAHs. The sums of the (frequently measured 7 and 15) OPAH concentrations correlated with those of the Σ16EPA-PAHs. The relationship of the Σ16EPA-PAHs concentrations with the Σ7OPAHs/Σ16EPA-PAHs concentration ratio (a measure of the variable OPAH sources) could be described by a power function with a negative exponent <1, leveling off at a Σ16EPA-PAHs concentration of ca. 400 ng g<sup>-1</sup>. We suggest that below this value, secondary sources contributed more to the OPAHs burden in soil than above, where primary sources dominated the OPAHs mixture. This was supported by a negative correlation of the Σ16EPA-PAHs concentrations with the contribution of the more readily biologically produced highly polar OPAHs (octanol-water partition coefficient, log K<sub>OW</sub> <3) to the Σ7OPAHs concentrations. We identified mean annual precipitation (Spearman-r = 0.33, p <0.001, n = 143) and clay concentrations (r = 0.55, p <0.001, n = 33) as important drivers of the Σ7OPAHs/Σ16EPA-PAHs concentration ratios. Our results indicate that at low PAH contamination levels, secondary sources contribute considerably and to a variable extent to total OPAH concentrations, while at Σ16EPA-PAHs contamination levels >400 ng g<sup>-1</sup>, there was a nearly constant ratio of Σ7OPAHs/Σ16EPA-PAHs (0.08±standard error 0.005, n = 80) determined by their combustion sources.</p>
Global distribution and evolutionary transitions of floral symmetry in angiosperms
<p><span>Floral symmetry plays a crucial role in plant-pollinator interactions and has remarkable impacts on angiosperm evolution. However, the spatiotemporal patterns in floral symmetry and drivers of these patterns </span><span>remain poorly known</span><span>. Here, using global distributions and </span><span>floral symmetry data </span><span>of 280,140 angiosperm species, we presented the global geographic and evolutionary patterns of floral symmetry </span><span>composition and demonstrated the climatic drivers of these patterns</span><span>. We found that the frequency of actinomorphic (radial) species increased with latitude, while that of </span><span>zygomorphic</span><span> (</span><span>bilateral</span><span>) species decreased</span><span>.</span><span> Solar radiation, present-day temperature and Quaternary temperature change explained the geographic variation in floral symmetry. Evolutionary transitions from actinomorphy to</span><span> zygomorphy dominated floral symmetry evolution, although the rate of this transition decreased through the Cenozoic associated with decreasing </span><span>paleo-temperature</span><span>. </span><span>Our study </span><span>provides novel insights into the ecology and evolution of angiosperm floral symmetry and suggests that climate change may influence species distributions via its effect on floral symmetry.</span></p>
Modelling the potential global distribution of suitable habitat for the biological control agent Heterorhabditis indica
<p class="MsoNoSpacing">Entomopathogenic nematode (EPN) <em>Heterorhabditis indica</em> is a promising biocontrol candidate. Despite the acknowledged importance of EPN in pest control, no extensive data sets or maps have been developed on their distribution at global level. This study is the first attempt to generate Ecological Niche Models (ENM) for <em>H. indica</em> and its global Habitat Suitability Map (HSM) to generate biogeographical information and predicts its global geographical range of prospective areas for its exploration and to help identify the suitable release areas for biocontrol purpose. The aim of the modelling exercise was to access the influence of temperature and soil moisture on the biogeographical patterns of <em>H. indica</em> at the global level. CLIMEX software was used to model the distribution of <em>H. indica</em> and access to the influence of environmental variable on its global distribution. In total, 162 records of <em>H. indica</em> occurrence from 27 countries over 25 years was combined to generate the known distribution data. The model was further fine-tuned using the direct experimental observations of the <em>H. indica</em>'s growth response to temperature and soil moisture. Model predicts much of the tropics and subtropics has suitable climatic conditions for <em>H. indica</em>. It further predicts that <em>H. indica</em> distribution can extends into warmer temperate climates. Examination of the model output, predictions maps at a global level indicate that <em>H. indica</em> distribution may be limited by cold stress, heat stress and dry stresses in different areas. However, cold stress appears to be the major limiting factor. This study, highlighted an efficient way to construct HSM for EPN potentially useful in the search/release of target species in new locations. The study showed that <em>H. indica</em> which is known as warm adapted EPN generally found in tropics and subtropics can potentially establish itself in warmer temperate climates as well. The model can also be used to decide the release timing of EPN by adjusting with season for maximum growth. The model developed in the current study clearly identified the value and potential of Habitat Suitability Map (HSM) in planning of future surveys and application of <em>H. indica.</em></p>
Global warming pushes the distribution range of the two alpine 'glasshouse' Rheum species north- and upwards in the Eastern Himalayas (EH) and the Hengduan Mountains (HM)
<p><span>Alpine plants' distribution is being pushed higher towards mountaintops due to global warming, finally diminishing their range and thereby increasing the risk of extinction. Plants with specialized 'glasshouse' structures have adapted well to harsh alpine environments, notably to the extremely low temperatures, which makes them vulnerable to global warming. </span><span>How</span><span>ever, their response to global warming is quite unexplored. Therefore, by compiling occurrences and several environmental strata, we utilized multiple ensemble species distribution modeling (eSDM) to estimate the historical, present-day, and future distribution of two alpine 'glasshouse' species <em>Rheum nobile</em> Hook. f. & Thomson and <em>R. alexandrae</em> Batalin. <em>Rheum nobile</em> was predicted to extend its distribution from the Eastern Himalaya (EH) to the Hengduan Mountains (HM), whereas <em>R. alexandrae</em> was restricted exclusively in the HM. Both species witnessed a northward expansion of suitable habitats followed by a southerly retreat in the HM region. Our findings reveal that both species have a considerable range shift under different climate change scenarios, mainly triggered by precipitation rather than temperature. The model predicted northward and upward migration for both species since the last glacial period which is mainly due to expected future climate change scenarios. Further, the observed niche overlap between the two species presented that they are more divergent depending on their habitat, except for certain regions in the HM. However, relocating appropriate habitats to the north and high elevation may not ensure the species' survival, as it needs to adapt to the extreme climatic circumstances in alpine habitats. Therefore, we advocate for more conservation efforts in these biodiversity hotspots.</span></p>
HR-GLDD: A globally distributed high resolution landslide dataset
<p> HR-GLDD, a high-resolution (HR) dataset for landslide mapping composed of landslide instances from ten different physiographical regions globally: South and South-East Asia, East Asia, South America, and Central America. The dataset contains five rainfall triggered and five earthquake-triggered multiple landslide events that occurred in varying geomorphological and topographical regions.</p>
The confluence of traits and environmental factors driving diversification and niche expansion in the globally distributed order Myrtales
<p>Supplementary files for the article: <strong>The confluence of traits and environmental factors driving diversification and niche expansion in the globally distributed order Myrtales</strong></p>
Data Supporting Global Distribution of Geothermal Gradients in Sedimentary Basins
<p>This dataset contains a global compillation of geothermal gradient estimates in boreholes from sedimentary basins all over the world. The data largely supports the analysis in the <em>Geoscience Frontiers</em> publication: <strong><em>Kolawole & Evenick (2023), Global distribution of geothermal gradients in sedimentary basins</em></strong>, doi.org/10.1016/j.gsf.2023.101685. An exception in the data is the proprietary data sourced from FrogTech SEEBASE reports (https://www.geognostics.com/frogtech-seebase-studies) that is not inlcuded in this release.</p> <p>Kolawole, F., Evenick, J.C. (2023). Global Distribution of Geothermal Gradients in Sedimentary Basins. Geoscience Frontiers, 14(6), p.101685. Doi: 10.1016/j.gsf.2023.101685.</p> <p>The here in attached zip folder contains:<br>1. Global geothermal gradient database as described above, provided in .csv and .txt formats. Each data entry includes: Reference Number (same as in Data Sources file), API/UWI (where available), Longitude (Decimal Degrees), Latitude (Decimal Degrees), Region, Country, Well Name (where available), Geothermal Gradient (°C/km), Data Source.<br>2. List of data sources and their references, provided in excel .xlsx format</p> <p>Acknowledgement:<br>We thank the Exploration Technology Center (ETC) of BP Exploration, Houston, U.S. for supporting the implementation of this research project during the time F. Kolawole and J. C. Evenick worked there, the release of the public domain portion of the compilled geothermal gradient database, and for the permission to publish the database.</p> <p><br>For further questions or comments, contact:<br>Folarin Kolawole, Ph.D.<br>Assistant Professor of Geology,<br>Department of Earth & Env. Sciences,<br>Columbia University,<br>New York, USA<br>Tel: +1 (646) 661-7143<br>Email: fola@ldeo.columbia.edu<br>Website: http://www.folarinkolawole.com</p>
Plant diversity darkspots for global collection priorities: time-to-event datasets per botanical country as defined by the World Geographical Scheme for Recording Plant Distributions (WGSRPD).
<p>Datasets used to predict the number of plant species remaining to be described and/or geolocated within a botanical country, which represents the third level of subdivision (generally equating to a political country) used by WGSRPD for recording plant distributions. The folder is composed of two subfolders <em>has_coords</em> and <em>has_no_coords</em> containing the time-to-event data for species with valid and no (invalidated) occurrence records within a given botanical country respectively<em>.</em></p> <ul> <li>Each folder contains a<strong> </strong>list of 361 botanical countries with the following 16 fields:</li> </ul> <pre><strong>species:</strong> species name<br><strong>time_ofdescription:</strong> year of the (first) description<br><strong>time_ofcollection:</strong> year of the collection of the earliest record<br><strong>family:</strong> species family name<br><strong>lifeform_description: </strong>the life form categorised into 4 classes <br><strong>CHELSA_bio_1: </strong>annual mean temperature (°C)<br><strong>CHELSA_bio_12:</strong> annual precipiation (mm)<br><strong>CHELSA_bio_15</strong>: temperature seasonality (-)<br><strong>CHELSA_bio_4</strong>: precipitation seasonality (-)<br><strong>elevation</strong>: elevation (m)<br><strong>range_size_area:</strong> total area of the botanical countries encompassing the species' native range <br>according to the World Checklist of Vascular Plants (WCVP) (km^2) <br><strong>taxo_activity</strong>: taxonomic activity calculated as the number of named authors in the World Checklist of Vascular Plants<br>describing species from the same family during the year of description of the species,<br>divided by the number of species described within the given family that year. <br><strong>num_records_per_year:</strong> geographic activity calculated as the number of occurrence records<br>collected within the native range of the species, divided by the number of years between <br>the earliest and the lastest (first) record collected within this range.<br><strong>num_uses</strong>: number of human uses<br><strong>time_todescription:</strong> number of years between the (first) description and 1753<br><strong>time_tocollection:</strong> number of years between the (first) description and the collection of the first record of the species<br><br></pre> <p> </p>
Local optima and global optimum distribution
<p>We understand the reviewer's concern regarding the distribution of local optima and global optimum. Here we address these concerns via the following two additional results, which were not presented in the main text.</p> <ul> <li><strong>Figure 1, local optima distribution: </strong>This plot presents exactly the analysis that the reviewer suggested on LLVM-W1. Specifically, for all local optima configurations in this landscape, we count the percentage of the on/off (note that all options considered in LLVM are binary) of each option, and plot them in a stacked bar chart. From the results, we can clearly see that for all options, nearly 50% times each option is on/off. This then further consolidates our finding that local optima are uniformly distributed across the landscape. </li> <li><strong>Figure 2, gobal optimum distribution: </strong>This plot visually depicts the distribution of the global optimum (purple star) of each workload of LLVM in the entire landscape. This is achieved by using UMAP dimensionality reduction to project each configurations to a 2D space. From the plot, we can see that the global optimum of each workload tends to be far from each other. <ul> <li>While this provides a qualitative intuition, we also report strict numerical distances here. The average distance for global optimum of different workloads in LLVM, SQLite and Apache is $9.44 \pm 2.48$, $12.54 \pm 3.67$, and $9.64 \pm 2.14$, respectively. These distances are relatively lower than the respective radius of each landscape, but are still considerably high for a direct transfer. </li> </ul> </li> </ul> <p>We sincerely hope these additional results can address the reviewer's concern. </p>
The role of external inputs and internal cycling in shaping the global ocean cobalt distribution: insights from the first cobalt biogeochemical model
<p>Model output for cobalt biogeochemistry model on ORCA2 grid.</p>
Fig. 1. Geographic distribution of bogidiellid amphipods. Large map: type localities of: 1, Bogidiella veneris n. sp.; 2, Bogidomma australis; 3, Xystriogidiella capricornea; and 4, Xystriogidiella juliani on the Australian continent (with kind permission of demis.nl). Insert map: global distribution of Bogidiellidae and several, possibly closely related taxa (modified after Koenemann and Holsinger, 1999).
Fig. 1. Geographic distribution of bogidiellid amphipods. Large map: type localities of: 1, Bogidiella veneris n. sp.; 2, Bogidomma australis; 3, Xystriogidiella capricornea; and 4, Xystriogidiella juliani on the Australian continent (with kind permission of demis.nl). Insert map: global distribution of Bogidiellidae and several, possibly closely related taxa (modified after Koenemann and Holsinger, 1999).
Datasets associated with: Comparing temperature data sources for use in species distribution models: From in-situ logging to remote sensing. Global Ecology and Biogeography
<p>Data associated with the paper 'Comparing temperature data sources for use in species distribution models: From in-situ logging to remote sensing. Global Ecology and Biogeography' by Lembrechts JJ et al., published in Global Ecology and Biogeography.</p> <p>Contains a dataset containing all extracted and measured temperature variables for all 106 measurement plots (climatedata), as well as the climate and species data used in the Species Distribution Models (SDMs). </p> <p>For details on the content of the table, see the readme-file, for details on methodology, see the original paper. </p>
Eulerian modelling of the three-dimensional distribution of seven popular microplastic types in the global ocean dataset
<p>Dataset for the paper "Eulerian modelling of the three-dimensional distribution of seven popular microplastic types in the global ocean" by A. S. Mountford and M. A. Morales Maqueda.</p> <p>ORCA2_5d_00010101_00011231_ptrc_T_con.nc<a href="https://zenodo.org/api/files/c6c9cbac-d5db-452a-aade-fd852db07351/ORCA2_5d_00010101_00011231_ptrc_T_con.nc"> </a> - control experiment (year 50)</p> <p>ORCA2_5d_00010101_00011231_ptrc_T_30m.nc - 30 m year<sup>-1</sup> piston velocity sensitivity experiment (year 50)</p> <p>ORCA2_5d_00010101_00011231_ptrc_T_90m.nc - 90 m year<sup>-1</sup> piston velocity sensitivity experiment (year 50)</p> <p>ORCA2_5d_00010101_00011231_ptrc_T_50.nc - neutrally buoyant sensitivity simulation (year 50)</p> <p>plastic_1_ts.nc - positively buoyant time series</p> <p>plastic_2_ts.nc - neutrally buoyant time series</p> <p>plastic_3_ts.nc - negatively buoyant time series</p> <p>plastic_input_ORCA2.nc - plastic input data file</p> <p>ORCA2_5d_00010101_00011231_grid_U.nc & ORCA2_5d_00010101_00011231_grid_V.nc - ocean velocity files</p>
Figure 1 in Soil BON Earthworm - A global initiative on earthworm distribution, traits, and spatiotemporal diversity patterns
Figure 1. Summary of essential steps of the earthworm sampling protocol.
Fig. 2 in From wildlife to humans: The global distribution of Trichinella species and genotypes in wildlife and wildlife-associated human trichinellosis
Fig. 2. Global distribution of Trichinella spiralis in wildlife reported in this review.
Impact of a Bimodal Dust Distribution on the 2018 Martian Global Dust Storm with the NASA/Ames Mars Global Climate Model
<p>This dataset is simulation data from the NASA Ames Mars GCM, produced for the research article titled "Impact of a Bimodal Dust Distribution on the 2018 Martian Global Dust Storm with the NASA/Ames Mars Global Climate Model." It is presented in NetCDF format.</p>
Spatiotemporal distribution of global peatland area during the Holocene
<p>The global peatland area dataset comprises netCDF files, which consist of 13 sets of maps showing the global extent of peatlands at a spatial resolution of 0.5° × 0.5°. All maps are provided at 1,000-year time intervals between 12 and 0 ka BP. The peatland area files named “Global_peatland_area_BA_*” were reconstructed using the BA method, and the files named “Global_peatland_area_IDW_*” were reconstructed using the IDW method. The global peatland records included data on location, latitude, longitude, peat type, basal ages, and end ages. The global pollen of <em>Sphagnum</em> records included latitude, longitude,<em> Sphagnum</em> content, and peat basal and end ages.</p>
ScienceDex guides
Understand access before you commit
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.