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143 results for “urban landscape”
North Temperate Lakes LTER: Patterns of Soil Phosphorus Across an Urbanizing Agricultural Landscape 2000 - 2001
Understanding the magnitude and location of soil phosphorus (P) accumulation in watersheds is a critical step toward managing runoff of this pollutant to aquatic ecosystems. Here, we examined the usefulness of urban-rural gradients (URGs), an emerging paradigm in urban ecology, for predicting soil P concentrations across a rapidly urbanizing agricultural watershed in southern Wisconsin. We compared several measures of an urban-rural gradient to predictors of soil P such as soil type, slope, topography, land use, land cover, and fertilizer and manure use. Most of the factors that were expected to drive differences in soil P concentrations were not found to be good predictors of soil P; while there were several significant relationships, most explained only a small proportion of the variation. There was a significant relationship between soil P concentration and each of the urban-rural gradients, but these relationships explained only a small amount of the variation in soil P concentrations. Soil P concentration, unlike some other ecosystem properties, is not well predicted by urban-rural gradients Additional Chemical Analyses: These additional analyses were done to provide comparisons to Bray-1 P. Specifically, we wanted to know whether, in Dane County, there was a consistent relationship between total P and Bray-1 P. For sample sites on private property, specific site location information, such as GPS coordinates, is not included in these datasets. If you have a need for this information, please get in touch with the contact person listed above Number of sites: 334; 20 of these sites with additional chem analyses
Land cover, landscape metrics and typology of European cities for Urban Forest Ecosystem Services (UFES) evaluation
<p>The data refers to the paper "<em>Urban Forests as Regulating Ecosystems: Types and Ranking of European Cities</em>"</p> <p>The datasets provide a typology for 689 European urban areas, the land cover metrics and landscape metrics used to create the typology and the Urban Forest Ecosystem Services (UFES) indexes created from them.</p> <p>The typology of Urban Forest Ecosystem Services (UFES) presents 10 clusters of cities aggregated into 4 groups: Forest cities, Anthropogenic cities, Herbaceous cities and Standard European cities. The data can be used to support urban planning policies at local and regional scales; in urban forestry, urban form and ecosystem services work related at different spatial scales. The metrics used capture the spatial integration of different layers of natural, semi-natural and artificial land within functional urban areas.</p> <p> </p> <p>The datasets are a csv file (<code>Metrics.csv</code>) and a shapefile (<code>UFES.shp</code>) of polygons with attributes.</p> <ul> <li> <p><code>UFES.shp</code> attributes' are the following: FUA codes, country name, main city name, clusters and groups of FUAs resulting from the hierarchical cluster analysis (HCA), the R color codes used in the article, the five UFES budget indexes as well as an aggregated global UFES index for each FUA.</p> </li> <li> <p><code>Metrics.csv</code> contains the FUA codes, the land cover and landscape metrics used in the HCA.</p> </li> </ul> <p> </p>
Data and code from: "Building multidimensional tolerance landscapes to predict the population dynamics of bacteria exposed to antibiotics in urban sewers"
<p>City sewers harbor diverse bacterial communities exposed to various antibiotic residues resulting from human consumption and excretion. Although these residues typically occur at sub-inhibitory concentrations, they can still impact the growth rate and yield of susceptible wastewater bacteria. Many bacteria exhibit antibiotic tolerance through transient phenotypic changes. Antibiotic residues, combined with complex environmental factors like temperature and salinity, especially in coastal cities, contribute to non-additive interactions that modulate antibiotic tolerance and affect population dynamics.</p> <p>To better understand these interactions, we developed continuous multivariate tolerance landscapes for three bacterial species: <strong><em><span>Escherichia coli</span></em></strong>, the emerging pathogen <strong><em><span>Streptococcus suis</span></em></strong>, and the sewer-inhabiting <strong><em><span>Arcobacter cryaerophilus</span></em></strong>. We modeled their intrinsic growth rates and carrying capacities across complex environments, incorporating temperature, salinity, and concentrations of two antibiotics (ciprofloxacin and azithromycin).<span> Using</span> these multivariate tolerance curves, we predicted microbial population dynamics in two sewers of Barcelona, highlighting the importance of environmental complexity in shaping microbial responses to antibiotic stressors.</p> <p> </p> <p><strong>Usage</strong></p> <p>Users can perform the analysis by running the R script (TC3D.R) after the installation of all</p> <p>package mentioned in the preamble,<span> </span></p> <p>This folder contains:</p> <p>- 3 datasets with OD measures for the 3 species:</p> <p><span> </span>* data_acrya.xlsx</p> <p><span> </span>* data_ecoli.xlsx</p> <p><span> </span>* data_ssuis.xlsx</p> <p>- 1 excel files with metadata (plate, well, species, environmental conditions)</p> <p><span> </span>* map_plate_all.xlsx</p> <p>- 4 datasets giving time series of the flow and several measures including <span> </span>conductivity and <span> </span>temperaturefor 2 sewers of Barcelona obtained from sample cabines <span> </span>set during the implementation of SCOREWATER (ID:820751)</p> <p><span> </span>* carmel_flow.csv</p> <p><span> </span>* carmel_quality.csv</p> <p><span> </span>* poblenou_flow.csv</p> <p><span> </span>* poblenou_quality.csv</p> <p>- 1 C++ script compiled and run with the R TMB package:</p> <p><span> </span>* fit_growth_r_K_SS_treatment.cpp : computes the negative loglikelihood for r and K, and state DOs, given the observed DO, for the populations under one same environmental treatment (salinity * temperature * antibiotic), and computes the density-dependence parameter alpha from r and K using the Delta Method.</p> <p><br><br></p>
UBGG-3m: Fine-grained urban blue-green-gray landscape dataset for 36 Chinese cities based on deep learning network
<p>The UBGG dataset provides easily access and leverage to researchers and analysts, which is stored in the following Zenodo repository (<a href="https://doi.org/10.5281/zenodo.8053333">https://doi.org/10.5281/zenodo.8352777</a>). The UBGG dataset consists of two main components:</p> <ul> <li><strong>UBGG-3m: the fine-grained UBGG map product of 36 metropolises in China.</strong> The UBGG-3m dataset captures the intricate urban landscape features with remarkable precision, providing a detailed representation at an impressive 3-meter resolution. Fig. 1 in User Guides shows the classification results for 36 Chinese metropolises. Researchers can delve into the nuances of the UBGG continuum, gaining invaluable insights into the interplay between the blue, green, and gray elements of urban environments in each metropolis.</li> </ul> <ul> <li><strong>UBGGset:</strong> <strong>the large-volume sample dataset to support the UBGG deep learning research.</strong> Complementing the UBGG-3m dataset, UBGGset serves as a large-volume sample dataset specifically tailored to support and foster UBGG research endeavors (Fig. 2). The UBGGset consists of 14,627 sample images (without data augmentation), with dimensions of 256 pixels in length and width, covering an urban area of approximately 2,272 km<sup>2</sup>. The UBGGset was constructed with co-registered pairs of 3 m Planet images and fine-annotated urban landscapes labeled on 1 m Google Earth image. This dataset encompasses 15 typical cities, offering researchers a rich and diverse resource to drive exploration, analysis, and innovation in the field of urban landscape studies.</li> </ul> <p> </p> <p><strong>Citation format for paper and dataset:</strong></p> <p>[1] Zhiyu Xu, Shuqing Zhao. Fine-grained urban blue-green-gray landscape dataset for 36 Chinese cities based on deep learning network. <em>Sci Data</em> 11, 266 (2024). https://doi.org/10.1038/s41597-023-02844-2</p> <p>[2] Zhiyu Xu, Shuqing Zhao, Fine-grained urban landscape mapping reveals broad-scale homogeneity in urban environments,<br>Science Bulletin, (2024). https://doi.org/10.1016/j.scib.2024.03.060</p> <p>[3] Zhiyu Xu, Shuqing Zhao. UBGG-3m: Fine-grained urban blue-green-gray landscape dataset for 36 Chinese cities based on deep learning network (v1.0) [Data set]. (2023). Zenodo. https://doi.org/10.5281/zenodo.8352777</p>
Data from: Quantifying nectar production by flowering plants in urban and rural landscapes
<p>Floral resources (nectar and pollen) provide food for insect pollinators but have declined in the countryside due to land use change. Given widespread pollinator loss, it is important that we quantify their food supply to help develop conservation actions. While nectar resources have been measured in rural landscapes, equivalent data are lacking for urban areas, an important knowledge gap as towns and cities often host diverse pollinator populations.</p> <p>We quantified the nectar supply of urban areas, farmland and nature reserves in the UK by combining floral abundance and nectar sugar production data for 536 flowering plant taxa, allowing us to compare landscape types and assess the spatial distribution of nectar sugar among land uses within cities.</p> <p>The magnitude of nectar sugar production did not differ significantly among the three landscapes. In urban areas the nectar supply was more diverse in origin and predominantly delivered by non-native flowering plants. Within cities, urban land uses varied greatly in nectar sugar production. Gardens provided the most nectar sugar per unit area and 85% of all nectar at a city scale, while gardens and allotments produced the most diverse supplies of nectar sugar. Floral abundance, commonly used as a proxy for pollinators' food supply, correlated strongly with nectar resources, but left a substantial proportion of the variation in nectar supply unexplained.</p> <p>Synthesis. We show that urban areas are hotspots of floral resource diversity rather than quantity and their nectar supply is underpinned by the contribution of residential gardens. Individual gardeners have an important role to play in pollinator conservation as ornamental plants, usually non-native in origin, are a key source of nectar in towns and cities.</p>
Fig. 1 in Species Diversity And Ecology Of Amphibians And Reptiles In Urbanized Landscapes Of The City Of Minsk
Fig. 1 Location of the largest habitats and stable populations of amphibians and reptiles in the urbanized areas of the Minsk city.
Fig. 5 in Landuse Patterns, Air Quality And Bird Diversity In Urban Landscapes Of Delhi
Fig. 5. CCA plot showing the relationships of landuse patterns, air pollutants and bird species abundance.
Flying insect biomass is negatively associated with urban cover in surrounding landscapes
<p><strong>Aim</strong></p> <p>In this study, we assessed the importance of local to landscape-scale effects of land cover and land use on flying insect biomass. Our main prediction was that insect biomass would be lower within more intensely used land, especially in urban areas and farmland. Location Denmark and parts of Germany.</p> <p><strong>Methods</strong></p> <p>We used rooftop-mounted car nets in a citizen science project ('InsectMobile') to allow for large-scale geographic sampling of flying insects. Citizen scientists sampled insects along 278 five km routes in urban, farmland and semi-natural (grassland, wetland and forest) landscapes in the summer of 2018. The bulk insect samples were dried overnight to obtain the sample dry weight/biomass. We extracted proportional land use variables in buffers between 50 and 1000 m along the routes and compiled them into land cover categories to examine the effect of each land cover, and specific land use types, on insect biomass.</p> <p><strong>Results</strong></p> <p>We found a negative association between urban cover and insect biomass at a landscape-scale (1000 m buffer) in both countries. In Denmark, we also found positive effects of all semi-natural land cover types, i.e. protected grassland (largest at the landscape-scale, 1000 m) and forests (largest at intermediate scales, 250 m). Protected grassland cover had a more positive effect on insect biomass than forest cover. The positive association between insect biomass and farmland was not clearly modified by any variable associated with farmland use intensity. The negative association between insect biomass and urban land cover appeared to be lessened by increased urban green space.</p> <p><strong>Main conclusions</strong></p> <p>Our results show that land cover has an impact on flying insect biomass with the magnitude of this effect varying across spatial scales. However, the vast expanse of grey space in urbanised areas has a direct negative impact on flying insect biomass across all spatial scales examined.</p>
Nectar values from: Quantifying nectar production by flowering plants in urban and rural landscapes
<p>Floral resources (nectar and pollen) provide food for insect pollinators but have declined in the countryside due to land use change. Given widespread pollinator loss, it is important that we quantify their food supply to help develop conservation actions. While nectar resources have been measured in rural landscapes, equivalent data are lacking for urban areas, an important knowledge gap as towns and cities often host diverse pollinator populations.</p> <p>We quantified the nectar supply of urban areas, farmland and nature reserves in the UK by combining floral abundance and nectar sugar production data for 536 flowering plant taxa, allowing us to compare landscape types and assess the spatial distribution of nectar sugar among land uses within cities.</p> <p>The magnitude of nectar sugar production did not differ significantly among the three landscapes. In urban areas the nectar supply was more diverse in origin and predominantly delivered by non-native flowering plants. Within cities, urban land uses varied greatly in nectar sugar production. Gardens provided the most nectar sugar per unit area and 85% of all nectar at a city scale, while gardens and allotments produced the most diverse supplies of nectar sugar. Floral abundance, commonly used as a proxy for pollinators' food supply, correlated strongly with nectar resources, but left a substantial proportion of the variation in nectar supply unexplained.</p> <p>Synthesis. We show that urban areas are hotspots of floral resource diversity rather than quantity and their nectar supply is underpinned by the contribution of residential gardens. Individual gardeners have an important role to play in pollinator conservation as ornamental plants, usually non-native in origin, are a key source of nectar in towns and cities.</p>
Fig. 3 in Ixodid Ticks (Acari, Ixodidae) In Urban Landscapes. A Review
Fig. 3. Diagram of indexes of references of mass hard tick species that adapted to European urban landscapes (including Russia).
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>
Habitat specialization by wildlife reduces pathogen spread in urbanizing landscapes
<p>Urban areas are expanding globally, with far-reaching ecological consequences, including for wildlife-pathogen interactions. Wildlife show tremendous variation in their responses to urbanization; even within a single population, some individuals can specialize on urban or natural habitat types. This specialization could alter pathogen impacts on host populations via changes to wildlife movement and aggregation. Here, we build a mechanistic model to explore how habitat specialization in urban landscapes affects interactions between a mobile host population and a density-dependent specialist pathogen that confers no immunity. We model movement on a network of resource-stable urban sites and resource-fluctuating natural sites, where hosts are either urban specialists, natural specialists, or generalists that use both patch types. We find that, for generalists, natural and partially urban landscapes produce the highest infection prevalence and mortality, driven by high movement rates at natural sites and high densities at urban sites. However, habitat specialization protects hosts from these negative effects of partially urban landscapes by limiting movement between patch types. These findings suggest that habitat specialization can benefit populations by reducing infectious disease transmission, but by reducing movement between habitat types could also carry the cost of reducing other movement-related ecosystem functions such as seed dispersal and pollination.</p>
Urban tree pests can support biological control services in landscape shrubs
<p>Scale insects are common tree pests in urban ecosystems. Although severe scale infestations can worsen tree condition, trees can tolerate moderate scale densities. Scale insects are prey for many arthropod natural enemies that also feed on plant pests throughout urban landscapes. Because scale-infested trees support natural enemy communities, they may support biological control services on nearby plants and function analogously to banker plants in greenhouse production systems. In this study, we tested if sentinel insect prey were more likely to be removed on shrubs below scale-infested trees compared to scale-uninfested trees. We conducted several biological control experiments from 2019–2021 using fruit flies, aphids, and caterpillars in potted and planted holly shrubs below scale-infested and scale-uninfested oak trees. We found that caterpillars in potted shrubs and fruit flies in planted landscape shrubs were more likely to be removed underneath scale-infested trees compared to scale-uninfested trees. Caterpillars were also more likely to be removed from landscape <em>Ilex</em> <em>vomitoria</em> shrubs compared to <em>I</em>. <em>cornuta</em> shrubs. In all other experiments, we found no effect of scale infestation status or shrub species on prey removal. Our results suggest that scale-infested trees can support biological control services in shrubs below them but that this effect can vary depending on prey and shrub species. The natural enemy communities in urban trees and shrubs appear to be linked and tolerating tree pests can favor conservation biological control services in urban landscapes.</p>
Data from: Insects in the city: Determinants of a contained aquatic microecosystem across an urbanized landscape
<p>Cities can have profound impacts on ecosystems, yet our understanding of these impacts is currently limited. First, the effects of socioeconomic dimensions of human society are often overlooked. Second, correlative analyses are common, limiting our causal understanding of mechanisms. Third, most research has focused on terrestrial systems, ignoring aquatic systems that also provide important ecosystem services. Here we compare the effects of human population density and low-income prevalence on the macroinvertebrate communities and ecosystem processes within water-filled artificial tree holes. We hypothesized that these human demographic variables would affect tree holes in different ways via changes in temperature, water nutrients, and the local tree hole environment. We recruited community scientists across Greater Vancouver (Canada) to provide host trees and tend 50 tree holes over 14 weeks of colonization. We quantified tree hole ecosystems in terms of aquatic invertebrates, litter decomposition, and chlorophyll-a. We compiled potential explanatory variables from field measurements, satellite images, or census databases. Using structural equation models, we showed that invertebrate abundance was affected by low-income prevalence but not human population density. This was driven by cosmopolitan species of Ceratopogonidae (Diptera) with known associations to anthropogenic containers. Invertebrate diversity and abundance were also affected by environmental factors, such as temperature, elevation, water nutrients, litter quantity, and exposure. By contrast, invertebrate biomass, chlorophyll-a, and litter decomposition were not affected by any measured variables. In summary, this study shows that some urban ecosystems can be largely unaffected by human population density. Our study also demonstrates the potential of using artificial tree holes as a standardized, replicated habitat for studying urbanization. Finally, by combining community science and urban ecology, we were able to involve our local community in this pandemic research pivot. </p> <p>This abstract is quoted from the original article "Insects in the city: Determinants of a contained aquatic microecosystem across an urbanized landscape" in Ecology (2023) by DS Srivastava et al.</p>
"I was the class teacher at that time. It was a class trip, usually organized near the end of the schoolterm in summer. The pupils went there by bike to have a barbecue at the sandy banks of the river Rhine near Dusseldorf. The landscape around is mostly dominated by agriculture and glasshouse cultures. You find a mixture of former villages nowadays completely suburbanized. The population finds jobs in the nearby urban centers like Dusseldorf, Neuss and other big cities. The reason why Irecorded the scene is simply because Iam interested in collecting sounds in general by doing recordings in different surroundings like nature, cities and everything between. My memories about the event are that it was a relaxing and funny atmosphere, which is not always the case while teaching in a classroom" [Reinhard/reinsamba]15 in Collecting Sounds. Online Sharing of Field Recordings as Cultural Practice
"I was the class teacher at that time. It was a class trip, usually organized near the end of the schoolterm in summer. The pupils went there by bike to have a barbecue at the sandy banks of the river Rhine near Dusseldorf. The landscape around is mostly dominated by agriculture and glasshouse cultures. You find a mixture of former villages nowadays completely suburbanized. The population finds jobs in the nearby urban centers like Dusseldorf, Neuss and other big cities. The reason why Irecorded the scene is simply because Iam interested in collecting sounds in general by doing recordings in different surroundings like nature, cities and everything between. My memories about the event are that it was a relaxing and funny atmosphere, which is not always the case while teaching in a classroom" [Reinhard/reinsamba]15
Habitat specialization by wildlife reduces pathogen spread in urbanizing landscapes
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Data from: Quantifying nectar production by flowering plants in urban and rural landscapes
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Urban landscapes with more natural greenspace support higher pollinator diversity
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Flying insect biomass is negatively associated with urban cover in surrounding landscapes
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Data from: Insects in the city: Determinants of a contained aquatic microecosystem across an urbanized landscape
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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.