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113 results for “urban birds”
Seasonal and annual summary statistics of urbanization, vegetation, land surface temperature, and bioclimatic variables derived from remotely-sensed imagery in areas surrounding long-term bird monitoring locations in the greater Phoenix, Arizona, USA metropolitan area (1997-2023)
This data package consists of 26 years (1998-2023) of environmental data and 22 years (2000-2022) years of bioclimatic data associated with CAP-LTER long-term point-count bird censusing sites (https://doi.org/10.6073/pasta/4777d7f0a899f506d6d4f9b5d535ba09), temporally aggregated by year and by four meteorological seasons (Winter, Spring, Summer, Fall). The environmental variables include land surface temperature (LST), three spectral indices of vegetation and water – the normalized difference vegetation index (NDVI), the soil adjusted vegetation index (SAVI), and modified normalized difference water index (MNDWI) – and four spectral indices of impervious surface/urbanization. Impervious surface indices include the normalized difference built-up index (NDBI), the normalized difference impervious surface index (NDISI), the enhanced normalized differences impervious surface index (ENDISI), and the normalized impervious surface index (NISI). LST and all spectral indices were derived from annual and seasonal composites of 30-m resolution Landsat 5-9 Level-2 Surface Reflectance imagery. The seven bioclimatic variables (e.g., air temperature, precipitation) were sourced from 1-km resolution gridded estimates of daily climatic data from NASA Daymet V4. We created temporally-aggregated Daymet raster images by calculating mean pixel-values for each season and year, as well as seasonally and annually summed precipitation. We summarized the values of each environmental variable by generating variously-sized (100-m, 500-m, 1000-m) buffers around each bird point count location and extracting weighted mean values of each environmental variable, with each pixel's values weighted by the proportion of its area falling within the buffer. All imagery retrieval and data processing were completed with Google Earth Engine (Gorelick et al. 2017) and program R. A complete description of data processing methods, including the aggregation of imagery by year and season and the calculation of s
Raw data of the study: Categorizing urban avoiders, utilizers, and dwellers for identifying bird conservation priorities in a northern Andean city
<p>This datasheet contains raw data on bird count records made from 2016 and 2019. Data were taken in urban and adjacent non-urban areas of Medellín, Colombia. It was part of a collaborative sampling effort during environmental assessments and personal research, summarizing systematic information on 139 sampling points (124 within the city and 15 in adjacent non-urban areas). All points were sampled under the same protocol in order to facilited data for research; in all cases, sampling was in charge of ornithologist with at least 4 years of previous experience in bird surveys. This protocol consisted in sampling during 10 minutes, four times per point (i.e., repetitions), using a fixed radius of 25 m. </p> <p>Information on bird surveys (Count_Data within the corresponding datasheet tab) contains the ID of each site; whether corresponded to a urban or non-urban site; in what category of urban development the site was located, based on 1000, 500 and 200 m buffers (from the observer during bird counts: moderate, low or high); the taxonomic information of each species (order, family, scientific name); the number of recorded individuals; the repetition or number of the visit (1, 2, 3, or 4); the name of the project; the name of the observer, and the date of sampling. </p> <p>Information on categorization of bird species (Categorization within the corresponding datasheet tab) represents additional information on altitudinal ranges, trophic guilds, distribution, and others. In addition, information on frequency for each bird species is given, according to the location of each sampling site and the way it was grouped. This information was the base for categorizing bird species as urban avoider, utilizer, or dweller, under the calculations and decision rules that are also given within the corresponding cells of the datasheet.</p> <p>Any further information or questions about this data could be ask directly, writing to the e-mails: jgarizabal@unal.edu.co or njmacer@unal.edu.co.</p> <p> </p>
Patterns in bird and pollinator occupancy and richness in a mosaic of urban office parks across scales and seasons
<p>Urbanization is a leading cause of global biodiversity loss, yet cities can provide resources required by many species throughout the year. In recognition of this, cities around the world are adopting strategies to increase biodiversity. These efforts would benefit from a robust understanding of how natural and enhanced features in urbanized areas influence various taxa. We explored seasonal and spatial patterns in occupancy and taxonomic richness of birds and pollinators among office parks in Santa Clara County, California, USA, where natural features and commercial landscaping have generated variation in conditions across scales. We surveyed birds and insect pollinators, estimated multi-species occupancy and species richness, and found that spatial scale, season, and urban sensitivity were all important for understanding how communities occupied sites. Features at the landscape- and local-scale (i.e., distance to streams or baylands and tree canopy, shrub, or impervious cover, respectively) were the strongest predictors of avian occupancy in all seasons. The pollinator richness index was influenced by local tree canopy and impervious cover in spring, and distance to baylands in early and late summer. We predicted relative contributions of different spatial scales to annual bird species richness by assigning values to simulated sites representing "good" and "poor" quality, based on influential covariates returned by models. Shifting from poor to good quality conditions locally increased annual avian richness by up to 6.8 species with no predicted effect of the quality of the neighborhood. Conversely, sites of poor local- and neighborhood-scale quality in good quality landscapes were predicted to harbor 11.5 more species than sites of good local- and neighborhood-scale quality in poor quality landscapes. Finally, more urban sensitive bird species were gained at good quality sites relative to urban tolerant species, suggesting that urban natural features at the local- and landscape-scales disproportionately benefited them.</p>
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.
Fig. 12 in Breeding Bird Assemblage In A Mosaic Of Urbanized Habitats In A Cenral European City
Fig. 12. Distribution of occupied territories of Cuculus canorus, Oriolus oriolus, Phasianus colchicus and Dendrocopos major.
Fig. 7 in Breeding Bird Assemblage In A Mosaic Of Urbanized Habitats In A Cenral European City
Fig. 7. Distribution of occupied territories of Acrocephalus plustris, A. Arundinaceus and A. scirpaceus.
Fig. 4 in Breeding Bird Assemblage In A Mosaic Of Urbanized Habitats In A Cenral European City
Fig. 4. Distribution of occupied territories of Serinus Fig. 5. Distribution of occupied territories of serinus, Phylloscopus collybita, P. trochilus and Phoenicurus ochruros. P. sibilatrix.
Fig. 2 in Breeding Bird Assemblage In A Mosaic Of Urbanized Habitats In A Cenral European City
Fig. 2. Distribution of occupied territories of Sylvia Fig. 3. Distribution of occupied territories of Sylvia communis. curruca.
Fig. 1 in Breeding Bird Assemblage In A Mosaic Of Urbanized Habitats In A Cenral European City
Fig. 1. Location of the study area (surrounded with a broken line) in the city of Wroclaw: A — borders of the study area; B — rivers; C — main roads; D — loosely built-up areas; E —densely built-up areas.
Fig. 3 in Glass Buildings As Bird Feeders: Urban Birds Exploit Insects Trapped By Polarized Light Pollution
Fig. 3. Timing of foraging visits of European magpie (Pica pica) to the northern building of the Eötvös University as detected by a web camera from 17:00 h on 16 May to 20:00 h on 23 May in 2007. Arrow lengths represent the proportion of all visits made during a particular hour over the
Fig. 2 in Glass Buildings As Bird Feeders: Urban Birds Exploit Insects Trapped By Polarized Light Pollution
Fig. 2. (A) Hovering white wagtail (Motacilla alba) catching caddis flies from a window. (B) House sparrow (Passer domesticus) capturing caddis flies from a vertical glass surface. (C) Great tit (Parus major) standing on a window's edge and catching caddis flies. (D) European magpie (Pica pica) on
Fig. 1 in Glass Buildings As Bird Feeders: Urban Birds Exploit Insects Trapped By Polarized Light Pollution
Fig. 1. (A) The southern (left arrow) and northern (right arrow) building of the Faculty of Natural Sciences of the Eötvös University in Budapest seen from the river Danube. (B) Mass-swarming caddis flies (Hydropsyche pellucidula, white dots) at the vertical glass surfaces of the northern building. (C) "Well-laid table" for urban birds: caddis fly imagoes (black dots) landed on white (untinted) and black (tinted) vertical glass surfaces. (D) An adult caddis fly landed on the outside surface of a window photographed from outside. (E) A copulating caddis fly pair on the outside surface of a window
Figure. CCA ordination of bird species. The eigenvalue of the first axis is 0.164 and of the second axis is 0.127. Species abbreviations are the first 3 letters of their genus followed by the first 3 letters of the species epithet. in Birds and small urban parks: a study in a high plateau city
Figure. CCA ordination of bird species. The eigenvalue of the first axis is 0.164 and of the second axis is 0.127. Species abbreviations are the first 3 letters of their genus followed by the first 3 letters of the species epithet.
Fig. 1 in Bird diversity in an urban ecosystem: the role of local habitats in understanding the effects of urbanization
Fig. 1. Bird species richness and overall abundance recorded in point counts (surveyed on September 2013) in the municipality of Canoas, Rio Grande do Sul, Brazil.
Fig. 2 in Bird diversity in an urban ecosystem: the role of local habitats in understanding the effects of urbanization
Fig. 2. Ordination diagram presenting the first two axes of the Canonical Correspondence Analysis (CCA) (percent of explained variability: axis I = 7.1%, axis II = 1.9%) based on the distribution of species abundance in 118 sample units (dots) in the urban area of Canoas, Rio Grande do Sul, Brazil, and its correlation with seven explanatory variables (arrows). The first axis shows the urbanization gradient (negatives values on left = more urbanized regions; positive values on right = less urbanized regions). All axes were significant (Monte Carlo test with 9,999 permutations: P <0.001). Species names are given in full in Appendix 1. Variables are described in Tab. I.
Invasion success and tolerance to urbanization in birds
<p>Cities are considered hotspot of biological invasions, yet it remains unclear why non-indigenous species are so successful in environments that most local native species do not tolerate. Here, we explore the intriguing possibility that humans may be unintentionally introducing species preadapted to persist in such environments. Combining data on historical introductions with information of avian assemblages along urban-wildland gradients, we found that avian species that in their native range proliferate in human-altered environments have been more likely to be transported and introduced to new locations than species confined to the wildland. We also found that such urban dwellers had higher chances to become established because they already had adaptations to cope with novel environments. These findings suggest that the pathway of introduction selects for species preadapted to persist in novel environments, providing an explanation for why non-indigenous birds are so successful in cities. Because the tendency to introduce species associated with human-altered environments continues, there is an urgent need to develop new regulations to prevent future introductions.</p>
Patterns in bird and pollinator occupancy and richness in a mosaic of urban office parks across scales and seasons
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Data from: The city and forest bird flock together in a common garden: Genetic and environmental effects drive urban phenotypic divergence
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Invasion success and tolerance to urbanization in birds
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Ecophysiological and behavioral adaptations of birds to rapid urbanization of a desert environment in central Arizona-Phoenix, from 2006 to 2008.
We used Sonoran desert species that have adapted to urbanization to various degrees to investigate relations between endocrine parameters, in particular plasma corticosterone in response to acute stress, and aspects of the immune system, parasite infections, and body condition. Desert residents generally suppressed their endocrine response to acute stress during the breeding season and underwent marked seasonal changes in body condition. By contrast, conspecific urban residents tended to maintain an acute stress response throughout the year and showed subdued seasonal changes in body condition. We surmise that this difference is related to differences between desert and urban environments in food resources that birds use to sustain themselves. The goal of upcoming studies will be to test this hypothesis. In addition, we are carrying out studies aimed at elucidating the neuroendocrine mechanisms that mediate differential stress responses seen in birds residing in rural vs. urban habitats. We are also developing experiments examining relation between the stress response and the activity of the immune and reproductive system. The data that we have already collected, and those to be collected in the coming year, will provide the most extensive set of data to date on effects of urbanization on wild vertebrates and on the mechanisms that are responsible for these effects.
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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.
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.