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802 results for “urban data”
Figure 2. from Inventory of the Heteroptera (Insecta: Hemiptera) in Komaba Campus of the University of Tokyo, a highly urbanized area in Japan - Biodiversity Data Journal 3: e4981 (24 April 2015) https://doi.org/10.3897/BDJ.3.e4981
Figure 2. - The aerial photograph of the Komaba Campus (taken in 2009 by the Geospatial Information Authority of Japan).
Data for "Fractal analysis of urban catchments and their representation in semi-distributed models: imperviousness and sewer system"
<p>The data set corresponds the data used in the paper : “Fractal analysis of urban catchments and their representation in semi-distributed models: imperviousness and sewer system”, published in 2017 in the Journal “Hydrology and Earth System Sciences” (http://www.hydrol-earth-syst-sci.net/).</p> <p>More precisely it corresponds to the matrices that are used in the fractal and multi-fractal analysis of the ten urban areas investigated in the paper.</p> <p> </p> <p>For each catchment, it is organised as follow:</p> <p>- catchment_name_conduit.asc : the matrix describing the sewer system.</p> <p>- catchment_name_OSM.asc : the matrix describing the impervious areas (roads and buildings) obtained via Open Street Map (www.openstreetmap.org)</p> <p>- catchment_name_OSM_house_only.asc : the matrix describing the “building” areas obtained via Open Street Map (www.openstreetmap.org)</p> <p>- catchment_name_imperviousness.asc : the matrix describing the representation of imperviousness in operational semi-distributed models.</p> <p> </p> <p>More details can be found in the paper.</p>
Data: Greater local cooling effects of trees across globally distributed urban green spaces
<p>The dataset used for hierarchical linear mixed effects models in the R code during the study. </p><p>The description of the column names is provided in the readme file.</p>
Model simulations utilizing the latest urban underlying surface and anthropogenic heat data
<p>Based on numerical simulations utilizing the latest urban underlying surface and anthropogenic heat data over the Yangtze River Delta urban agglomeration, we find that LU change and AH emission can result in opposite effects on summer precipitation. The related model simulations are included in this dataset.</p>
Data from: Nine-banded Armadillo (Dasypus novemcinctus) occupancy and density across an urban to rural gradient
<p>The nine-banded Armadillo (<em>Dasypus novemcinctus</em>) is the only species of Armadillo in the United States and alters ecosystems by excavating extensive burrows used by many other wildlife species. Relatively little is known about its habitat use or population densities, particularly in developed areas, which may be key to facilitating its range expansion. We evaluated Armadillo occupancy and density in relation to anthropogenic and landcover variables in the Ozark Mountains of Arkansas along an urban to rural gradient. Armadillo detection probability was best predicted by temperature (positively) and precipitation (negatively). Contrary to expectations, occupancy probability of Armadillos was best predicted by slope (negatively) and elevation (positively) rather than any landcover or anthropogenic variables. Armadillo density varied considerably between sites (ranging from a mean of 4.88 – 46.20 Armadillos per km<sup>2</sup>) but was not associated with any environmental or anthropogenic variables.</p>
Data from: Geographic variations in eco-evolutionary factors governing urban birds: the case of university campuses in China
<ol> <li><span>Urbanization alters natural habitats, restructures biotic communities, and serves as a filter for selecting species from regional species pools. However, empirical evidence of the specific traits that allow species to persist in urban areas yields mixed results. More importantly, it remains unclear which traits are widespread for species utilizing urban spaces (urban utilizers) and which are environment-dependent traits. </span></li> <li><span>Using 745 bird species from 287 university/institute campuses in 74 cities and their species pools across China, we tested whether species that occur in urban areas are correlated with regards to their biological (body mass, beak shape, flight capacity, and clutch size), ecological (diet diversity, niche width, and habitat breadth), behavioral (foraging innovation), and evolutionary (diversification rate) attributes. </span></li> <li><span>We used Bayesian phylogenetic generalized linear mixed models to disentangle the relative roles of these predictors further and to determine the extent to which the effects of these predictors varied among different cities. </span></li> <li><span>We found that urban birds were more phylogenetically clustered than expected by chance, and were generally characterized by a larger habitat breadth, faster diversification rate, more behavioral innovation, and smaller body size. Notably, the relative effects of the attributes in explaining urban bird communities varied with city temperature and elevation, indicating that the filters used to determine urban species were environment-dependent. </span></li> <li><span>We conclude that, while urban birds are typically small-sized, generalists, innovative, and rapidly-diversifying, the key traits that allow them to thrive vary spatially, depending on the climatic and topographic conditions of the city. These findings emphasize the importance of studying species communities within specific cities to better understand the contextual dependencies of key traits that are filtered by urban environments.</span></li> </ol>
Data: On the role of water table depth, and urban and vegetation cover on groundwater dry period susceptibility
Open the record for dataset details and reuse information.
Air phyto-cleaning by an urban meadow – Filling the winter gap - DATA
<p>Database of article: Air phyto-cleaning by an urban meadow – Filling the winter gap.</p>
Data from: Uniqueness of tree stand composition and soil microbial communities are related across urban spruce-dominated forests
<p>The dataset contains data obtained from urban spruce-dominated forests in southern Finland where we have measured tree stand composition, forest management history, soil chemical properties, and soil microbial communities. Data files include (1) microbial OTU tables describing microbial community composition (sequence read counts of Operational Taxonomic Units) across the study plots, (2) taxonomic assignments and other metadata related to OTUs, and (3) measured and calculated variables describing the characteristics of sites and their microbial assemblages (site metadata).</p>
Supporting Data for "Local exposure misclassification in national models: relationships with urban infrastructure and demographics"
<p><strong>Overview:</strong> This dataset accompanies the recent publication "Local exposure misclassification in national models: relationships with urban infrastructure and demographics" (DOI: 10.1038/s41370-023-00624-z). It provides essential data for replicating and extending the analysis conducted in the study. The script for the analysis is available at https://github.com/SEChambliss-AQ/LD-analysis. The dataset consists of four key files.</p> <p><strong>Files Included:</strong></p> <ol> <li> <p><strong>Gridded OSM and GSV Data (gridded_OSM_GSV.RDS):</strong></p> <ul> <li>This R object offers a 100mx100m grid covering select neighborhoods in the San Francisco Bay Area.</li> <li>Each grid cell includes average air pollution levels (Ultrafine Particle Count in thousand count per cubic meter; Nitrogen Dioxide in ppb) from mobile monitoring.</li> <li>The file also provides normalized z-scores of local density of urban infrastructure related to air pollutants based on OpenStreetMap (OSM) data.</li> <li>Further details can be found in the associated publication.</li> </ul> </li> <li> <p><strong>BartMachine Outputs (bartMachine R objects.zip):</strong></p> <ul> <li>A collection of R object outputs from the bartMachine package, an R-Java Bayesian Additive Regression Trees implementation.</li> <li>These objects, which can be regenerated using the provided script, are included to reduce computational requirements for future analyses.</li> <li>The script for generating these outputs is available at the above <a href="https://github.com/SEChambliss-AQ/LD-analysis">GitHub Repository</a>.</li> </ul> </li> <li> <p><strong>NO2 Predictions (CACES_criteria.csv):</strong></p> <ul> <li>Land Use Regression (LUR) data for Nitrogen Dioxide, provided by the Center for Air, Climate, and Energy Solutions.</li> <li>Methodologies for integrating these data with the gridded dataset are described in the publication and script.</li> </ul> </li> <li> <p><strong>UFP Predictions (CACES_UFP.csv):</strong></p> <ul> <li>Similar to the NO2 dataset, this file contains LUR data for Ultrafine Particle predictions.</li> <li>Methods for data integration are detailed in the publication and available script.</li> </ul> </li> </ol> <p><strong>Usage:</strong> These files are intended for researchers and analysts aiming to replicate or build upon the study's findings. They provide a source of data for exploring the complex interplay between air pollution, urban infrastructure, and demographic factors in urban environments. For detailed methodology and analysis, refer to the original publication and the accompanying GitHub repository.</p>
Biogeochemical data from urban ponds in Brussels
<p>The dataset comprises two files, each containing geo-referenced information with corresponding timestamps.The names of the ponds are written in French according to the official name defined by Brussels Environment (BE).</p> <ul> <li>Brussels_ponds_all.xlsx contains pH, Conductivity, dissolved oxygen saturation, CO2, CH4, N2O dissolved concentrations, chlorophyll-a concentrations, inorganic nutrients (NO3-, NO2-, NH4+, PO43-) concentrations, total phosphorus and total suspended matter concentrations collected during four surveys (November 2021, February 2022, May 2022 and August 2022) on 22 ponds</li> <li>Brussels_ponds_Chla_temporal.xlsx contains chlorophyll-a concentration of two ponds monitored on a recurring basis (1-2 times a month) from June 2021 to December 2022.</li> </ul> <p>All ponds have pontoons, raised above the water surface, which allow sampling at least 2m further from the banks. Water pH, temperature, conductivity and oxygen saturation level (%O<sub>2</sub>) were measured by a VWR MU 6100 H probe. Water was collected in 2L polypropylene bottles for subsequent analysis of chlorophyll a (Chl-a), total suspended matter (TSM) and dissolved nutrients (ammonium (NH<sub>4</sub><sup>+</sup>), nitrite (NO<sub>2</sub><sup>-</sup>), nitrate (NO<sub>3</sub><sup>-</sup>), soluble reactive phosphorus (SRP)). Three 50mL falcons were filled with unfiltered water and stabilised with 200µL HNO<sub>3</sub> (65%) for total phosphorus (Ptot) analysis.</p> <p>Filtration on Whatman filters 0.7µm GF/F glass microfibres with diameter of 47mm was carried out. For TSM, 1 pre-weighed filter was weighed after drying at 100°C for 48h in order to obtain the TSM concentration. For Chl-a, a filter was placed after filtration in 90% acetone to extract the Chl-a, which was then measured by fluorimetry (Kontron SFM 25 model) at an excitation length of 430nm and emission length of 664nm (Yentsch and Menzel, 1963). Nutrient concentrations were determined spectrophotometrically (Perkin-Elmer Lambda 650 S model) by coloration of the filtrates obtained after filtration through 0.7µm Whatman GF/F filters. NH<sub>4</sub><sup>+</sup> was determined by coloration with nitroprusside-hypochlorite-phenol (Grasshoff and Johannsen, 1972) at 630nm. NO<sub>2</sub><sup>-</sup> and NO<sub>3</sub><sup>-</sup> are determined before and after reduction of NO<sub>3</sub><sup>-</sup> to NO<sub>2</sub><sup>-</sup> by passage through a cadmium-copper column. The NO<sub>2</sub><sup>-</sup> is then reacted with Griess' reagent in acidic medium (Grasshoff et al., 1983) at 540nm. The SRP is determined after colorimetric reaction with ammonium molybdate, ascorbic acid and potassium antimony tartrate (Koroleff, 1983) at 885nm.</p> <p>Ptot was determined by inductively coupled plasma spectroscopy (ICP) on an ICP-OES Perkin Elmer Avio 200 model. The assay protocol was based on the US EPA (1994) method 200.7 for analysis of metals and trace elements in water by ICP with prior microwave acid digestion based on US EPA, (2007) method 3015A.</p> <p>CO<sub>2</sub> measurements were carried out on the field with a Li-Cor Li-840 IR-CO<sub>2</sub>/H<sub>2</sub>O gas analyser calibrated before each campaign, using the headspace technique with 4 polypropylene syringes (Abril et al., 2015). Samples for CH<sub>4</sub> and N<sub>2</sub>O were collected via a silicone tube into 60mL borosilicate serum bottles and poisoned with 200µL of saturated HgCl<sub>2</sub> solution. The vials were sealed with a butyl stopper and crimped with an aluminium cap. Measurements were carried out using the headspace technique (Weiss, 1974) and a gas chromatography measurement (model SRI 8610C) with a flame ionisation detector (FID) for CH<sub>4</sub> and an electron capture detector (ECD) for N<sub>2</sub>O.</p> <p> </p> <p> </p> <p>References:</p> <p>Abril, G., Bouillon, S., Darchambeau, F., Teodoru, C.R., Marwick, T.R., Tamooh, F., Omengo, Ochieng Omengo, F., Geeraert, N., Deirmendjian, L., Polsenaere, P., Borges, A.V., (2015). Technical Note : Large overestimation of p CO<sub>2</sub> calculated from pH and alkalinity in acidic , organic-rich freshwaters Biogeosciences 12, 67–78. <a href="https://doi.org/10.5194/bg-12-67-2015">https://doi.org/10.5194/bg-12-67-2015</a></p> <p>Grasshoff, K., & Johannsen, H. (1972). A new sensitive and direct method for the automatic determination of ammonia in sea water. <em>ICES Journal of Marine Science</em>, <em>34</em>(3), 516-521. <a href="https://doi.org/10.1093/icesjms/34.3.516">https://doi.org/10.1093/icesjms/34.3.516</a></p> <p>Grasshoff, K., Kremling, K., & Ehrhardt, M. (Eds.). (1983). <em>Methods of seawater analysis : </em>Determination of nitrite. John Wiley & Sons</p> <p>Koroleff, J. (1983). Determination of total phosphorus by alkaline persulphate oxidation. <em>Methods of Seawater Analysis. Verlag Chemie, Wienheim</em>, 136-138.</p> <p>U.S. EPA. 1994. “Method 200.7: Determination of Metals and Trace Elements in Water and Wastes by Inductively Coupled Plasma-Atomic Emission Spectrometry,” Revision 4.4. Cincinnati, OH. <a href="https://www.epa.gov/esam/method-2007-determination-metals-and-trace-elements-water-and-wastes-inductively-coupled">https://www.epa.gov/esam/method-2007-determination-metals-and-trace-elements-water-and-wastes-inductively-coupled</a></p> <p>U.S. EPA. 2007. “Method 3015A (SW-846): Microwave Assisted Acid Digestion of Aqueous Samples and Extracts,” Revision 1. Washington, DC <a href="https://www.epa.gov/esam/epa-method-3015a-microwave-assisted-acid-digestion-aqueous-samples-and-extracts"><em>https://www.epa.gov/esam/epa-method-3015a-microwave-assisted-acid-digestion-aqueous-samples-and-extracts</em></a></p> <p>Weiss, R. (1974). Carbon dioxide in water and seawater: the solubility of a non-ideal gas. <em>Marine chemistry</em>, <em>2</em>(3), 203-215. <a href="https://doi.org/10.1016/0304-4203(74)90015-2">https://doi.org/10.1016/0304-4203(74)90015-2</a></p> <p>Yentsch, C. S., & Menzel, D. W. (1963, July). A method for the determination of phytoplankton chlorophyll and phaeophytin by fluorescence. In <em>Deep Sea Research and Oceanographic Abstracts</em> (Vol. 10, No. 3, pp. 221-231). Elsevier. <a href="https://doi.org/10.1016/0011-7471(63)90358-9">https://doi.org/10.1016/0011-7471(63)90358-9</a></p>
Data and Code for "Urban socioeconomic variation influences the ecology and evolution of trophic interactions"
<p>Data and code required for all analyses in <em>Urban socioeconomic variation influences the ecology and evolution of trophic interactions</em>. </p> <p><a href="../api/files/5ca97a29-9947-482a-9095-5a54c40c57f0/Gall_Data_2022_new.csv">Gall_Data_2022_new.csv</a> contains data for gall predation and diameter measurements. <a href="../api/files/5ca97a29-9947-482a-9095-5a54c40c57f0/Goldrod_Gall_Density.csv">Goldrod_Gall_Density.csv</a> contains goldenrod and gall density measurements for each site. <a href="../api/files/5ca97a29-9947-482a-9095-5a54c40c57f0/GallSitesFinal.csv">GallSitesFinal.csv</a> contains location data for all study sites. <a href="../api/files/5ca97a29-9947-482a-9095-5a54c40c57f0/DisseminationAreaCodes.csv">DisseminationAreaCodes.csv</a> contains codes for each site location needed to obtain census data. Full descriptions of data are included in <a href="../api/records/10702694/draft/files/README.txt/content" target="_blank" rel="noopener noreferrer">README.txt</a></p> <p>The script <a href="../api/records/10640975/draft/files/DataCleaning.R/content" target="_blank" rel="noopener noreferrer">DataCleaning.R</a> assembles the above four datasets with environmental and census data to produce the final dataset: <a href="../api/files/5ca97a29-9947-482a-9095-5a54c40c57f0/MartinElGalmady%26Johnson2023_cleandataset.csv">MartinElGalmady&Johnson2023_cleandataset.csv</a> and the supplemental dataset with galls with early larval death removed: <a href="../api/records/10640975/draft/files/NoELD_dataset.csv/content" target="_blank" rel="noopener noreferrer">NoELD_dataset.csv</a></p> <p><a href="../api/records/10640975/draft/files/Analysis.R/content" target="_blank" rel="noopener noreferrer">Analysis.R</a> provides the code for conducting analyses and producing figures using the <a href="../api/files/5ca97a29-9947-482a-9095-5a54c40c57f0/MartinElGalmady%26Johnson2023_cleandataset.csv">MartinElGalmady&Johnson2023_cleandataset.csv</a> dataset (or the <a href="../api/records/10640975/draft/files/NoELD_dataset.csv/content" target="_blank" rel="noopener noreferrer">NoELD_dataset.csv</a> for supplemental analyses with early larval death removed).</p> <p>Detailed descriptions of the final dataset are included in <a href="../api/records/10702694/draft/files/cleandataset_metadata.csv/content" target="_blank" rel="noopener noreferrer">cleandataset_metadata.csv</a> (NoELD_dataset has the same rows and columns as the full dataset). </p> <p>All code was run in R verison 4.2.2</p>
Data from: Evolutionary change in flight-to-light response in urban moths comes with changes in wing morphology
<p>Moths and other insects are attracted by artificial light sources. This flight-to-light behaviour disrupts their general activity focused on finding essential habitat resources, such as mating partners, and increases predation risk. It thus has substantial fitness costs. In illuminated urban areas, spindle ermine moths <em>Yponomeuta cagnagella</em> were reported to have evolved a reduced flight-to-light response. Yet, the specific mechanism remained unknown, and was hypothesized to involve either changes in visual perception or general flight ability or overall mobility traits. Here, we test whether spindle ermine moths from urban and rural populations—with known differences in flight-to-light response—differ in flight-related morphological traits. Urban individuals were found to have on average smaller wings than rural moths, which in turn correlated with a lower probability of being attracted to an artificial light source. Our finding supports the reduced mobility hypothesis, which states that reduced mobility in urban areas is associated with specific morphological changes in the flight apparatus.</p>
Data from: Effects of microclimate on disease prevalence across an urbanization gradient
<p>Increased temperatures associated with urbanization (the "urban heat island" effect) have been shown to impact a wide range of traits across diverse taxa. At the same time, climatic conditions vary at fine spatial scales within habitats due to factors including shade from shrubs, trees, and built structures. Patches of shade may function as microclimate refugia that allow species to occur in habitats where high temperatures and/or exposure to ultraviolet radiation would otherwise be prohibitive. However, the importance of shaded microhabitats for interactions between species across urbanized landscapes remains poorly understood. Weedy plants and their foliar pathogens are a tractable system for studying how multiple scales of climatic variation influence infection prevalence. Powdery mildew pathogens are particularly well suited to this work, as these fungi can be visibly diagnosed on leaf surfaces. We studied the effects of shaded microclimates on rates of powdery mildew infection on <em>Plantago</em> host species in (1) "pandemic pivot" surveys in which undergraduate students recorded shade and infection status of thousands of plants along road verges in urban and suburban residential neighborhoods, (2) monthly surveys of plant populations in 22 parks along an urbanization gradient, and (3) a manipulative field experiment directly testing effects of shade on growth and transmission of powdery mildew. Together, our field survey results show strong positive effects of shade on mildew infection in wild <em>Plantago</em> populations across urban, suburban, and rural habitats. Our experiment suggests that this relationship is causal, where microclimate conditions associated with shade promote pathogen growth. Overall, infection prevalence increased with urbanization despite a negative association between urbanization and tree cover at the landscape scale. These findings highlight the importance of taking microclimate heterogeneity into account when establishing links between macroclimate or land use context and the prevalence of disease.</p>
Data from: Beyond the metropolis: street tree communities and resident perceptions on ecosystem services in small urban centers in India
<p>This dataset includes road transect characteristics, tree data and interview data (linked through transect number) from two cities in India - Kochi and Panjim, collected in 2019-2020 as part of the study:</p> <p>Beyond the metropolis: street tree communities and resident perceptions on ecosystem services in small urban centers in India</p> <p> </p> <p> </p>
Data used in manuscript Direct CO2 emissions and uptake at neighbourhood scale over the urban area of Beijing
<p>This dataset provides the data used in the manuscript "<em>Direct CO2 emissions and uptake at neighbourhood scale over the urban area of Beijing</em>".</p> <p>The folders are:</p> <p><strong>1. Modelled_CO2_Flux</strong><br> This folder contains a portion of modelled CO2 fluxes generated by SUEWS. Fc is the net CO2 flux, FcPhoto the CO2 uptake by vegetation, FcRespi the CO2 release from soil and vegetation respiration, FcMetab the CO2 emissions from human metabolism, FcBuild the CO2 emissions from the local fuel combustion in buildings. Longitudes and latitudes denote the centroid of grid.<br> <strong>1.1 Fc_annual_2016_g_C_m-2_yr-1.nc</strong> is the annual CO2 fluxes in g C m-2 year-1.<br> <strong> 1.2 Fc_monthly_2016_g_C_m-2_mon-1.nc</strong> is the monthly CO2 fluxes in g C m-2 month-1.<br> <strong>1.3 Fc_annual_2016_g_C_m-2_yr-1.tiff</strong> is the annual Fc (g C m-2 year-1) provided in GeoTiff format.<br> <strong>1.4 6_ring_EPSG4326</strong> contains the ESRI Shapefile defining the study area (with the 6th Ring Road in Beijing as the boundary).</p> <p><strong>2. ModelRun</strong><br> This folder includes SUEWS source code (Järvi et al., 2011; Ward et al., 2016; Järvi et al., 2019) and a model run sample.<br> <strong>2.1 SUEWS_SourceCode</strong> is a folder including SUEWS V2020b source Fortran codes. For detailed descriptions, readers are referred to SUEWS webpage (https://suews.readthedocs.io/en/latest/). Enter "make" through the command line and a SUEWS executive will be built under ".../ModelRun/Release".<br> <strong>2.2 EvaluationRun</strong> is a folder including the SUEWS run for model performance evaluation. To conduct a quick model run to reproduce the results demonstrated in the manuscript, use command line "./SUEWS_V2020b". </p> <p><strong>3. Observations</strong><br> The unit for CO2 flux (Fc) is μmol m-2 s-1 under this folder.<br> <strong>3.1 co2_flux_140m_2016_rm_QC.csv</strong> is the Fc observations after quality control and resampled to hourly resolution.<br> <strong>3.2 Fc_gapfilled_with_MeanDC.csv</strong> is the Fc time series for the year 2016 gap-filled with the Mean Diurnal Cycle method on a seasonal basis.</p> <p> </p> <p>Contact information: zhengyingqi@mail.iap.ac.cn</p> <p><br><strong>[References]</strong><br>Järvi, L., Grimmond, C. S. B., & Christen, A. (2011). The surface urban energy and water balance scheme (SUEWS): Evaluation in Los Angeles and Vancouver. Journal of Hydrology, 411(3-4), 219-237.<br>Ward, H. C., Kotthaus, S., Järvi, L., & Grimmond, C. S. B. (2016). Surface Urban Energy and Water Balance Scheme (SUEWS): development and evaluation at two UK sites. Urban Climate, 18, 1-32.<br>Järvi, L., Havu, M., Ward, H. C., Bellucco, V., McFadden, J. P., Toivonen, T., ... & Grimmond, C. S. B. (2019). Spatial modeling of local‐scale biogenic and anthropogenic carbon dioxide emissions in Helsinki. Journal of Geophysical Research: Atmospheres, 124(15), 8363-8384.</p>
Data from: Contrasting heat tolerance of evergreen and deciduous urban woody species during heat waves
<p>The increasing frequency and intensity of heat waves caused significant damages to urban woody species, and the different leaf structures between evergreen and deciduous species may be closely related to leaf heat tolerance. However, whether the different leaf structural traits of evergreen and deciduous plants contribute to their different responses under heat waves is still unclear.</p> <p>During the record-breaking and long-lasting 2022 summer heat waves in China, we investigated the relationships between leaf thermal indices and leaf structural traits of 36 urban woody species in four cities along the Yangtze River.</p> <p>We found that all the four thermal indices were significantly but weakly related with leaf damage status. The critical temperature that causes the initial 15% damage to photosystem II (Tcrit) may serve as a sensitive measure of heat tolerance. Evergreen species suffered less leaf damage during the heat waves and exhibited higher leaf heat tolerance, thicker leaves than deciduous species. Tcrit was significantly correlated with leaf mass per area, leaf thickness and thickness of spongy tissue.</p> <p><em>Synthesis</em>:<em> </em>Urban woody species with high Tcrit, leaf mass per area, and leaf thickness tend to be more tolerant to heat stress. This study provides insights for predicting leaf heat tolerance of urban woody plants in subtropical China and their physiological and ecological responses to severe heat waves.</p>
Data for "Willingness of rural and urban citizens to undertake pollinator conservation actions across three contrasting European countries"
<p>Data for: "Willingness of rural and urban citizens to undertake pollinator conservation actions across three contrasting European countries" by Costanza Geppert, Cristiano Franceschinis, Thijs P.M. Fijen, David Kleijn, Jeroen Scheper, Ingolf Steffan-Dewenter, Mara Thiene, Lorenzo Marini (2024) <em>People and Nature</em>. This dataset was obtained by administering an online questionnaire in Germany, Italy, and the Netherlands.</p>
Data: Exploring the Drivers and Dynamics of Urban Waters: A Case Study of Wuhan from 1980 to 2060
<p>The dataset comprises three main folders: "lulc," "factors," and "results."</p> <p><span>1. </span><strong><span>lulc (Land Use/Land Cover)</span></strong>: This folder contains raster data spanning from 1980 to 2020, representing land use and land cover dynamics. The data is stored in TIFF format, with values ranging from 1 to 6 denoting different land cover classes: farmland (1), woodland (2), grassland (3), waters (4), settlements (5), and unused land (6).</p> <p><span>2. </span><strong><span>factors</span></strong>: This folder includes various driving factors influencing water dynamics. It encompasses eleven raster datasets, including Digital Elevation Models (DEM), annual precipitation data, and other relevant variables. The temporal coverage of these factors spans from 1980 to 2020. Additionally, demographic factors such as population data and economic indicators like GDP are available, covering the period from the 1990s to 2020. All datasets are stored in TIFF format with a spatial resolution of 30 meters.</p> <p><span>3. </span><strong><span>results</span></strong>: This folder contains the outcomes of the analysis conducted using the PLUS (Patch Landscape and Urban Growth Model) framework. The results include outputs from the Landscape Ecological Assessment Protocol (LEAP) and the Cellular Automata for Regional Simulation (CARS) modeling. These results offer insights into the spatial and temporal patterns of water dynamics in the study area.</p> <p>The data structure follows a systematic organization to facilitate access and analysis. Each folder contains raster datasets stored in TIFF format, ensuring compatibility and ease of use with common GIS software. The temporal consistency of the datasets allows for longitudinal analysis of water dynamics, while the inclusion of various driving factors provides a comprehensive understanding of the underlying processes. Overall, this dataset offers valuable insights into land-water interactions and their implications for urban planning and water resource management strategies.</p>
Data from: neglected puzzle pieces of urban green infrastructure: richness, cover, and composition of insect-pollinated plants in traffic-related green spaces
<p>Insect-pollinated vascular plants in spontaneous vegetation provide essential ecosystem services and benefit wildlife. However, floral communities associated with traffic-related green spaces are rarely considered valuable elements of urban green infrastructure (UGI). The dataset contains information on species-based floral communities of vascular insect-pollinated plants in traffic-related green spaces in three highly populated Finnish cities. Those are Helsinki (665 558 inhabitants), Tampere (244 029 inhabitants), and Turku (175 645 inhabitants). Data were collected during the mean flowering phenophase of vascular plants in July-August 2022 from two types of locations: (i) urban (city centers) and (ii) suburban (city outskirts), and from three types of traffic-related green spaces: (i) traffic islands, (ii) parking lots, (iii) road verges. The dataset contains information for the 93 vascular insect-pollinated plant species flowering during the survey. Sampling campaign was conducted in 90 sampling sites, and the dataset contains information on the location coordinates. In addition, the dataset possesses information on the amount of garbage pieces (cigarette filters, plastic boxes, or scraps) revealed for each sampling point in traffic-related green spaces.</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.