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40 results for “urban-rural”
Dust geochemistry and lead isotopes along an urban-rural transect in central Ohio, 2021
This data package contains geochemical concentrations and stable lead isotope ratios for dust samples collected along an urban-rural land use gradient in central Ohio during 2021. The purpose of the study was to characterize the geochemical and isotopic signatures of dust in relation to different land uses, to see how much dust varies across land use and by season. At four sites along an urban-rural transect in central Ohio, we collected weekly bulk deposition samples and analyzed the geochemical composition (47 elements including major elements, trace metals, and rare earth elements) and stable lead isotopes (208Pb, 207Pb, 206Pb, and 204Pb) of the particulate matter. This study demonstrates the tight connection between land use and anthropogenic dust composition in a region where land use is changing rapidly as development encroaches into farmland. This dataset is complete and will not be updated.
Air mass back-trajectory modeling output along an urban-rural transect in central Ohio, 2021
This data package contains modeled air parcel back-trajectories generated using the Stochastic Time-Inverted Lagrangian Transport model (STILT) via the R interface. The purpose of the study was to characterize the geochemical and isotopic signatures of dust in relation to different land uses, and to connect the geochemistry of deposited dust to air mass trajectories. Back-trajectories are three-dimensional paths of air parcels from a receptor site (the dust collection site) backwards in time and space for the duration of the tracking interval, calculated iteratively using wind fields from high-resolution gridded meteorological data. To calculate a probability of potential pathways, rather than a single back-trajectory, STILT introduces small random perturbations into the wind fields during each time step. For four sites along an urban-rural transect in central Ohio for June-July 2021, we generated weekly footprints of potential sources for the dust deposited at each site. These back-trajectories can be paired with geochemical data to establish a connection between land use and anthropogenic dust composition. This dataset is complete and will not be updated.
Urban-Rural Temperature Data-relation between land-cover and the Urban Heat Island in San Juan, Puerto Rico
Our objective in this study is to quantify the UHI created by the San Juan Metropolitan Area over space and time using temperature data collected by mobile and fixed-station measurements. We used the fixed-station measurements to examine the relation between average temperature at a given location and the density of vegetation located upwind. We then regressed temperatures against regional land-cover to predict future temperature with projected land-cover change. Our data show the existence of a nocturnal UHI, with average nighttime urban-rural temperature differences (ΔTU-R) of up to 3.02°C. Each of the stations listed in this excel file were used to calculate the urban heat island created by the San Juan Metropolitan Area. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
Thermal changes along the urban-rural continuums in Southeast Asia
<p>This research has been published in Environmental Research Letters. Please cite it as shown below when using this dataset:</p> <p>Citation:<strong> Zhu, Y., Myint, S., Chen, J., Fan, P., Seto, K., Jain, A. K., Qi, J., & Wang, J. (2025). Thermal changes along the urban-rural continuums in Southeast Asia. Environmental Research Letters. <a href="https://doi.org/10.1088/1748-9326/adcad2">https://doi.org/10.1088/1748-9326/adcad2</a>.</strong></p> <p> </p> <p>Our study focused on 19 cities across 8 countries: Cambodia, Indonesia, Lao PDR, Malaysia, Myanmar, Philippines, Thailand, and Vietnam. The cities included Phnom Penh, Siem Reap, Jakarta, Surabaya, Denpasar, Vientiane, Pakse, KL, Putrajaya, Yangon, NPT, Quezon City, Iloilo, Taytay, Bangkok, Chiang Rai, HCMC, Hanoi, Cantho. </p> <p>To assess the impact of urbanization over the past two decades, we examined the patterns of Land Surface Temperature (LST) changes with Land Use and Land Cover (LULC) changes across 19 cities in SEA along the urban-rural continuums (URCs). These cities include major urban hubs such as Jakarta, Bangkok, and Ho Chi Minh City, as well as medium and smaller cities like Vientiane and Chiang Rai, reflecting a diversity of urban environments and providing a comprehensive sample of SEA’s rapid urban expansion and associated thermal impacts. The boundaries of URCs for each city were defined as an area centered within a 30 km radius from its city center point. This ensured that all cities had the same extent so that the URCs could make the comparison. The city center point was defined as either the center of the central business district or the geometric center of the city’s administrative limits (Estoque et al., 2017). We created 30 ring buffer zones around each city center point at 1 km intervals to analyze LULC and the associated LST change gradient along the URCs. After establishing these buffer zones, we excluded (1) large water bodies or oceans, (2) continuous urban areas beyond the city boundaries—for cities located close to one another, such as Kuala Lumpur and Putrajaya, and Quezon City and Taytay, the city’s URCs were adjusted to exclude overlapping administrative boundaries from neighboring cities, ensuring that the analysis was confined to each city’s specific URCs, and (3) mountains with elevations exceeding 100 m above the mean elevation of each city buffer to minimize the confounding effects of topography on LST variations to ensure that the LST changes we observed were more directly attributable to urban development rather than elevation-related climatic variations. (C. Wang et al., 2016; Z. Wang et al., 2020). These exclusions were implemented to ensure a fair comparison, avoid confusion, and reduce the influence of elevation on the analysis.</p> <p>For URCs, we retrieved LST and NDVI data for the summer months (June, July, and August) between 2000 and 2022 at a 30-meter resolution based on the Google Earth Engine Platform. This period was chosen due to peak heat-related mortality and morbidity (Hsu et al., 2021; Johnson et al., 2009). A total of 5,805 Landsat 5/7/8/9 scenes were collected to ensure full coverage of all 19 cities. Contaminated pixels (e.g., clouds and cloud shadows) were removed via quality assessment bands and Landsat-7 SLC-off stripes were eliminated. NDVI was calculated from the surface reflectance of the Red and Near-Infrared (NIR) bands. LST retrieval from Landsat data was conducted using the Statistical Mono-Window (SMW) algorithm developed by the Climate Monitoring Satellite Application Facility (CM-SAF) (Duguay-Tetzlaff et al., 2015; Freitas et al., 2013; Sun et al., 2004). Further details are provided in the Supplemental materials.</p> <p>The final datasets are LST in 2022, LST Sen's Slope (2000-2022), and NDVI Sen's Slope (2000-2022) and are shared.</p>
Comparison of Urban-Rural Tree Growth Response to Climate in the Eastern U.S. for the years 1990-2014
Climate is an important driver of tree growth in forests of the eastern U.S. Urbanization can augment the growing conditions of trees in ways that could change the sensitivity of radial growth to climate stressors such as excessive heat and water stress. This dataset include tree ring chronologies (1990-2014) in the form of basal area increment for canopy oak and maples trees from paired urban and nearby rural reference forest sites in Baltimore, Maryland, New York City, New York, and Boston, Massachusetts. Also included are metrics of heat stress and water stress from 1990-2014.
Urban-rural life tables for Scotland, 1861-1910
<p>This data set contains the life tables the were computed for the study presented in: Torres, C., V. Canudas-Romo, and J. Oeppen (2019) 'The contribution of urbanization to changes in life expectancy in Scotland, 1861–1910', <em>Population Studies</em>, 73:3, 387-404, DOI: 10.1080/00324728.2018.1549746</p> <p>The life tables are by sex and urban-rural category. For reasons explained in the paper, the tables cover periods of different lengths, from 1861 to 1910.</p> <p><strong>Example of how to load the data in R:</strong></p> <p>LT <- read.table("Urban-Rural-LifeTables-Scotland-1861-1910.txt", header = T, sep = ";")</p> <p><strong>Description of each column:</strong><br> Period: time-interval, including the first and excluding the last indicated years (e.g., [1861,1866) corresponds to the years from 1861 to 1865). Available periods: 1861-1865, 1866-1870, 1871-1874, 1875-1877, 1878-1880, 1881-1885, 1886-1890, 1891-1892, 1893-1896, 1897-1900, 1901-1905, 1906-1910.<br> Population: Rural, Semi-Urban, Urban, or Total population (see definitions in Torres et al. 2019)<br> Sex: Female or Male<br> x : Age (from 0 to 110+, by single ages)<br> nmx: Death rate in the age interval [x, x+n)<br> nax: average number of person-years lived in the age interval [x, x+n) by those who die in that interval<br> nqx: Probability of dying in the age interval [x, x+n)<br> lx: number of survivors at exact age x, or probability of surviving until exact age x<br> ndx: Life-table deaths in the age interval [x, x+n)<br> nLx: Person-years lived in the age interval [x, x+n)<br> Tx: Person-years lived above age x<br> ex: Remaining life expectancy at age x</p> <p>For more information about life tables in general, see: Preston, S., Heuveline, P., and Guillot, M. (2001). <em>Demography: Measuring and Modeling Population Processes</em>. Wiley-Blackwell</p>
Data from: Using Landsat time-series to investigate nearly 50 years of tree canopy cover change across an urban-rural landscape in southern Ontario
<p><strong>Paper Abstract:</strong></p> <p>Canadian urban and adjacent landscapes have been dynamic over the last 50 years due to land management, land cover alternations, climate change, and disturbances. Remote sensing, particularly the Landsat archive, provides the only means to spatially quantify these long-term dynamics locally. Here, we explore the utility of Landsat, including the often-forgotten MSS sensor, for investigating percent tree canopy cover (TCC) change between 1972 and 2020 in a Canadian urban-rural context. We build a TCC time-series by training random forest models using visually interpreted TCC from high-resolution imagery. Predictors include topographic and yearly LandsatLinkr-harmonized and LandTrendr-fitted tasseled cap indices. Yearly binary TCC maps are built to mask consistently treeless areas and limit noise. To increase confidence in observed TCC change without historical reference imagery, we investigate multiple temporal validation options. Our TCC time-series (R2: 0.89, RMSE: 10.7%), quantifies TCC dynamics while limiting erroneous change and predictor space extrapolation. We explore TCC changes across landscapes, revealing periods of gain and loss associated with agricultural reforestation (1978-1996), housing development (on-going), drought (late 1990s), emerald ash borer (2010s), an ice storm (2013), and other drivers. Results demonstrate how long-term Landsat time-series can be used to better understand historical tree canopy change at local-regional scales. </p> <p> </p> <p><strong>Dataset details:</strong></p> <p>See paper. </p> <ul> <li>cc_72to20.tif: Yearly tree CC predictions (1972-2020)</li> <li>always_nonforest10_nowater.tif: continuous-non-canopy mask</li> <li>water.tif: water mask</li> <li>Yearly.zip: Annual predictors (including CC10) and asc outputs</li> </ul> <p> </p> <p>See code on GitHub: <a href="https://github.com/ZZMitch/PredictTreeCC_Landsat_1972to2020">ZZMitch/PredictTreeCC_Landsat_1972to2020: Code from the portion of my PhD about using Landsat time-series to predict tree canopy cover from 1972 - 2020. Code will be released as papers are published. (github.com)</a></p>
Predicting the strength of urban-rural clines in a Mendelian polymorphism along a latitudinal gradient
Cities are emerging as models for addressing the fundamental question of whether populations evolve in parallel to similar environments. Here, we examine the environmental factors that drive the evolution of parallel urban-rural clines in a Mendelian trait—the cyanogenic antiherbivore defense of white clover (Trifolium repens). Previous work suggested urban-rural gradients in frost and snow depth could drive the evolution of reduced hydrogen cyanide (HCN) frequencies in urban populations. Here, we sampled over 700 urban and rural clover populations across 16 cities along a latitudinal transect in eastern North America. In each population, we quantified changes in the frequency of genotypes that produce HCN, and in a subset of the cities we estimated the frequency of the alleles at the two genes (CYP79D15 and Li) that epistatically interact to produce HCN. We then tested the hypothesis that cold climatic conditions are necessary for the evolution of cyanogenesis clines by comparing the strength of clines among cities located along a gradient of winter temperatures and frost exposure. Overall, half of the cities exhibited urban-rural clines in the frequency of HCN, whereby urban populations evolved lower HCN frequencies. Clines did not evolve in cities with the lowest temperatures and greatest snowfall, supporting the hypothesis that snow buffers plants against winter frost and constrains the formation of clines. By contrast, the strongest clines occurred in the warmest cities where snow and frost are rare, suggesting that alternative selective agents are maintaining clines in warmer cities. Some clines were driven by evolution at only CYP79D15, consistent with stronger and more consistent selection on this locus than on Li. Together, our results demonstrate that urban environments often select for similar phenotypes, but different selective agents and targets underlie the evolutionary response in different cities.
Dietary diversification of an insect predator along an urban-rural gradient
<p>Here we provide the raw data and R scripts of our study "Dietary diversification of an insect predator along an urban-rural gradient"</p> <p><span>Abstract: Urbanisation generally leads to a loss of taxonomic and functional diversity in almost all animal taxa, yet a mosaic of highly variable habitats within the urban matrix could offer a diversity of insect prey to highly mobile predators such as bats. We therefore asked if insect-feeding bats change in trophic interactions along rural-urban gradients. </span><span>We predicted that the diet of common noctule bats (<em>Nyctalus noctula</em>) diversifies with increasing levels of urbanisation and that urban bats include more pest and nuisance insect species than rural conspecifics.</span><span>Using metabarcoding of faecal samples over three years of sampling, we observed a more diverse diet in urban compared with rural noctule bats. Furthermore, urban bats consumed more than twice as many agricultural pests and six times as many nuisance insects as their rural conspecifics. Finally, insect species richness in the diet decreased with increasing levels of sealed surface and vegetation cover at the sampling site.</span><span>We argue that a highly mobile bat species such as the noctule bat compensate for the lower abundance of insects in urban areas by foraging over relatively large spatial scales, including adjacent rural areas. A high proportion of pest and nuisance insects highlights the importance of urban bats for providing important ecosystem services to humans. Urban planning needs to consider maintaining and establishing dark flight corridors and a diversity of habitats to support urban bat populations. </span></p>
Temporal data from camera trap captures of raccoons (Procyon lotor) and coyote (Canis latrans) across urban-rural gradient Michigan 2015-2020
<p>Temporal data and trap success for raccoons (<em>Procyon lotor</em>) and coyotes (<em>Canis latrans</em>) across an urban-rural gradient in Michigan, from 2015 to 2020. These data are associated with the article "Temporal refuges of a subordinate carnivore vary across rural-urban gradient" in the journal Ecology and Evolution. </p>
Wave-Cascade Nested Model: The Urban-rural Diffusion Model of Suzhou(Essays on Linguistics 2025(1))
<p>This is the high-resolution images (Figure 3) from published paper entitled Wave-Cascade Nested Model: The Urban-rural Diffusion Model of Suzhou (Essays on Linguistics 2025(1)) (in Chinese 波浪-级联嵌套模型”:苏州城乡方言的扩散模式 (《语言学论丛》2025年第1期)) . </p> <p>Given the journal doesn't provide color printing or needs to compress images due to size limitations, it offers readers access to the high-quality and full-color image.</p> <p>If you have any question, please contact me without any hesitation! Thank you very much!</p>
Data from: Rural selection drives the evolution of an urban-rural cline in coat color in gray squirrels
<div> <p><span>Phenotypic differences between urban and rural populations are well-documented, but the evolutionary processes driving trait variation along urbanization gradients are often unclear. We combined spatial data on abundance, trait variation, and measurements of fitness to understand cline structure and test for natural selection on heritable coat color morphs (melanic, gray) of eastern gray squirrels (Sciurus carolinensis) along an urbanization gradient. Population surveys using remote cameras and visual counts at 76 sites along the urbanization gradient revealed a significant cline in melanism, decreasing from 48% in the city center to <5% in rural woodlands. Among 76 squirrels translocated to test for phenotypic selection, survival was lower for the melanic than gray morph in rural woodlands, whereas there was no difference in survival between color morphs in the city. These results suggest the urban-rural cline in melanism is explained by natural selection favoring the gray morph in rural woodlands combined with relaxed selection in the city. Our study illustrates how trait variation between urban and rural populations can emerge from selection primarily in rural populations rather than adaptation to novel features of the urban environment. </span>This reposotory contains a) occupancy data, point count data, and R code used to estimate the urban-rural cline in melanism, and b) radiotelemetry data and R code used to estimate differential survival between color morphs in urban and rural environments.</p> </div>
Predicting the strength of urban-rural clines in a Mendelian polymorphism along a latitudinal gradient
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Data from: Rural selection drives the evolution of an urban-rural cline in coat color in gray squirrels
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Temporal data from camera trap captures of raccoons (Procyon lotor) and coyote (Canis latrans) across urban-rural gradient Michigan 2015-2020
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Data from: Plant radiocarbon across an urban-rural CO2 gradient matches surface and column CO2 observations
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Land use effects on temperature and humidity along an urban-rural transect gradient in central Arizona-Phoenix
This study examines the effects of land use on microclimate along several commercial-to-rural land use transects in the greater Phoenix metropolitan area.
Land use effects on temperature and humidity along an urban-rural transect gradient in central Arizona-Phoenix, 1999
These data result from a study that examined the effects of land use on microclimate along several commercial-to-rural land use transects in the greater Phoenix metropolitan area.
Anthropogenic noise reduces avian feeding efficiency and increases vigilance along an urban-rural gradient regardless of species' tolerances to urbanisation
<p>Anthropogenic noise can adversely impact urban bird populations by interfering with vocal communication. Less research has addressed if anthropogenic noise masks the adventitious sounds that birds use to aid predator detection, which may lead to increased vigilance and reduced feeding efficiency. We test this hypothesis using a controlled playback experiment along an urban-rural gradient in Sheffield (UK). We also test the related predictions that anthropogenic noise has the greatest impacts on vigilance and feeding efficiency in rural populations, and on species that are more sensitive to urbanisation. We focus on six passerines, in order from most to least urbanised (based on how urbanisation influences population densities): blue tit Cyanistes caeruleus, robin Erithacus rubeculla, great tit Parus major, chaffinch Fringilla coelebs, coal tit Periparus ater and nuthatch Sitta europaea. We used play-back of anthropogenic urban noise and a control treatment at 46 feeding stations located along the urban-rural gradient. We assess impacts on willingness to visit feeders, feeding and vigilance rates. Exposure to anthropogenic noise reduced visit rates to supplementary feeding stations, reduced feeding rates and increased vigilance. Birds at more urban sites exhibit less marked treatment induced reductions in feeding rates, suggesting that urban populations may be partially habituated or adapted to noisy environments. There was no evidence, however, that more urbanised species were less sensitive to the impacts of noise on any response variable. Our results support the adventitious sound masking hypothesis. Urban noise may thus interfere with the ability of birds to detect predators, reducing their willingness to use food rich environments and increase vigilance rates resulting in reduced feeding rates. These adverse impacts may compromise the quality of otherwise suitable foraging habitats in noisy urban areas. They are likely to be widespread as they arise in a range of species including common urban birds.</p>
Data from: Functional diversity of phyllostomid bats in an urban-rural landscape: a scale-dependent analysis
<p>Urbanization is one of the most pervasive landscape transformational processes responsible for novel selection agents promoting functional community homogenization. Bats may persist in those human environments, but the mechanisms responsible for their adaptability and the spatial scales in which landscape imposes environmental filtering remain poorly studied in the Neotropics. We tested the hypothesis that landscape composition interacts with the spatial scale to affect the functional diversity of phyllostomids in an urban-rural gradient. Based on functional traits, we calculated indices of functional richness, divergence, evenness, community-weighted means of morphological traits, and classified species into functional groups. We evaluated the changes of those variables in response to forest, grassland, and urbanized areas at 0.5, 1.25 and, 2 km scales. The number of functional groups, functional richness, and functional evenness tended to be higher in areas far from cities and with higher forest cover, whereas functional divergence increased in more urbanized areas. Our results show that the mean value of wing loading in the assemblage was negatively associated to landscape transformation at several spatial scales. However, environmental filtering driven by grass cover was particularly robust at the 500 m scale, affecting big-sized species with long pointed wings. Retaining natural forest in cattle ranging systems at ~12 km<sup>2</sup> appears to favor bat abundance evenness among functional types in the urban-rural landscape. Recognizing the scale of the effect on phyllostomid functional responses appears to be a fundamental issue for elucidating the spatial extent to which phyllostomid conservation planning in urban-rural landscapes should be addressed.</p>
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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.
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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.