Find research datasets worth reusing

opencc-by-4.0Dec 2016View details →

Fig. 1. Investigated 8 in The Relation Of Forest And Air Pollution With Human Health In Urban Territories Of Lithuania

Fig. 1. Investigated 8 urban territories of Lithuania (Alytus, Kaunas, Klaipeda, Palanga, Panevezys, Siauliai, Vilnius, Visaginas urban municipalities).

opencc-by-4.0Dec 2015View details →

Fig.1 in Natural And Historical Aspects Of The Origin And Functioning Of Urban Mammals In Western Siberia, Russia And Uzbekistan

Fig.1. Yamal - Tashkent Transect (70+5° E, ca. 2200 miles). The studied cities are marked with black circles, their size depending on the number of inhabitants.

opencc-by-4.0Dec 2015View details →

Fig. 2 in Natural And Historical Aspects Of The Origin And Functioning Of Urban Mammals In Western Siberia, Russia And Uzbekistan

Fig. 2. The similarity of small mammalian communities from different structural-functional zones of cities by species composition.

opencc-by-nc-4.0Jul 2021View details →

Hourly intra-urban temperature and relative humidity for Madrid

Description: This dataset contains intra-urban dry-bulb temperature and relative humidity measurements collected within the city of Madrid. This data was collected during the MODIFICA Project (2014-2017) and beyond, which aimed to investigate the impacts of urban heat on the buildings' energy performance. Methodology: The data collection followed the methodology detailed in <a href="https://doi.org/10.1016/j.uclim.2021.100921">this paper</a>. Briefly, 20 temperature and humidity sensors were deployed in Madrid's municipal area within the urban canopy layer. The sensors were protected using an aspirated radiation shield, and data were recorded every 30 minutes. All the metadata associated with the location of the sensors in included in the aforementioned paper. Data Structure: <ul> <li>Location ID: Identifier for the location where data were collected.</li> <li>Timestamp [Datetime]: Date and time of the measurement.</li> <li>Temperature (°C) [TEMP_IDXX]: Recorded temperature in degrees Celsius.</li> <li>Relative Humidity (%) [HR_IDXX]: Recorded relative humidity as a percentage.</li> </ul> Usage Notes: The dataset is suitable for studies on urban climate patterns, environmental monitoring, and related fields. The data here included is the raw data. No QC procedures nor gap filling techniques were applied to this dataset. Users should refer to the methodology section in the associated paper for detailed procedures and data handling practices. Funding and Acknowledgments: This research was funded by the FPU research grant FPU15/05052, from the Spanish Ministry of Science, Innovation and Universities. This research was also supported by the MODIFICA research project (BIA2013–41732-R), funded by the Spanish Ministry of Economy and Competitiveness. The authors would like to extend their gratitude to Luis Tejero Encinas and Juan Azcárate Luxán, from the Madrid City Council’ Subdivision of Energy and Climate Change, for their support with the urban measurements campaign. Citation: When using this dataset, please cite the following paper: Núñez-Peiró, M., Sánchez-Guevara Sánchez, C., & Neila González, F. J. (2021). Hourly evolution of intra-urban temperature variability across the local climate zones. The case of Madrid. Urban Climate, 39, 100921. <a href="https://doi.org/10.1016/j.uclim.2021.100921">https://doi.org/10.1016/j.uclim.2021.100921</a> Contact Information: For further inquiries, please contact Miguel Núñez-Peiró at miguel.nunez@upm.es.

opencc-by-4.0Dec 2019View details →

Figure 1 in Species richness of urban and rural fish assemblages in the Grijalva Basin floodplain, southern Gulf of Mexico

Figure 1. – Map of the study area in the floodplain of the Grijalva Basin. Sampling sites (ID), 1 = Gordiano, 2 = La Pólvora, 3 = Ilusiones, 4 = Costeñito and 5 = Loma de Caballo urban lagoons (circles); 6 = Campo, 7 = Manguito, 8 = Pucté, 9 = Maluco and 10 = Playa de Poza rural lagoons (stars); and 11 = González, 12 = Carrizal, 13 = Grijalva, 14 = Pichucalco and 15 = Samaria rivers (triangles) in rural sites. MR = Mezcalapa River; MvR = Mezcalapa Viejo River. Map modified of http:// antares.inegi.org.mx/analisis/red_ hidro/SIATL/#

opencc-by-4.0Nov 2022View details →

Figura 1. Gymnopilus pholiotoides. A in Gymnopilus pholiotoides (Agaricales, Basidiomycota), an unexpected new record from an urban area in Brazil

Figura 1. Gymnopilus pholiotoides. A. Basidiomes observed in side-view. B. Basidiomes showing pileus surface. Bars = 20 mm.

Fig. 2a, b in Morphological, ecological and toxicological aspects of Raphidiopsis raciborskii (Cyanobacteria) in a eutrophic urban subtropical lake in southern Brazil

Fig. 2a, b. Bar graphs indicating the relative percentages of different phytoplankton groups in the lake inflow (a) and outflow (b), sampled every month from November 2009 to November 2010.

Fig. 6 in Morphological, ecological and toxicological aspects of Raphidiopsis raciborskii (Cyanobacteria) in a eutrophic urban subtropical lake in southern Brazil

Fig. 6. Principal Component Analysis (PCA) ordination of the sampling units (P1) = water inflow and (P2) = water outflow, and of the physical and chemical variables analyzed. The sampling units are listed by month abbreviated as follows: Jan = January; Feb = February; Mar = March; Apr = April; May = May; Jun = June; Jul = July; Aug = August; Sept = September; Oct = October; Nov = November; Dec = December. T = Temperature; Transp = Transparency; Cond = Conductivity; DO = Dissolved oxygen; NH4 = Ammonium; OM = Organic material.

Fig. 4a-c in Morphological, ecological and toxicological aspects of Raphidiopsis raciborskii (Cyanobacteria) in a eutrophic urban subtropical lake in southern Brazil

Fig. 4a-c. Photomicrographs of Raphidiopsis raciborskii bloom from the studied lake demonstrating: a. general aspect of the bloom; c. part of a trichome with a heterocyte and an akinete; c. part of a trichome with only an akinete. Bars =10µm.

Fig. 1 in Morphological, ecological and toxicological aspects of Raphidiopsis raciborskii (Cyanobacteria) in a eutrophic urban subtropical lake in southern Brazil

Fig. 1. Map of the studied lake, showing the two sampling sites (I = water inflow and O = water outflow).

Figure 2 in Culex quinquefasciatus predominance during integrated mosquito surveillance in an urban area of the Brazilian Amazon

Figure 2. Nasci Aspirator (A) and a plastic pot (B) with a screen (C) adapted for electric vacuuming. Open pot (D) and pot with a lid (E) in the nozzle of the aspirator.

Figure 1 in Culex quinquefasciatus predominance during integrated mosquito surveillance in an urban area of the Brazilian Amazon

Figure 1. Map of the study area, Porto Velho city in Rondônia State, Brazil, demonstrating the location of each residence of collect (represented by a black circle).

Figure 6 in Far from urban areas: plastic uptake in fish populations of subtropical headwater streams

Figure 6. Median plastic particle distribution in fishes per sample site (whiskers = min - max values, dots = outliers, stars = extreme outliers, horizontal line = median, box = 50% tile).

Figure 3 in Far from urban areas: plastic uptake in fish populations of subtropical headwater streams

Figure 3. Plastic particles abundances in benthic and water column feeders (whiskers = min - max values, dots outliers, stars extreme outliers, horizontal line median, box 50% tile).

Figure 1. Study area. A. South America and Brazil. B in Far from urban areas: plastic uptake in fish populations of subtropical headwater streams

Figure 1. Study area. A. South America and Brazil. B. Brazil and the state of Rio Grande do Sul. C. Rio Grande do Sul and the Sinos River Basin. D. The numbers from 1 to 7 in the white dots show the sampling sites in the upper section of the Sinos River basin. The colour gradient represents the terrain elevation (light green elevations of 30m altitude and dark brown elevations of 980m). The red polygons are the urban areas.

Figure 5 in Far from urban areas: plastic uptake in fish populations of subtropical headwater streams

Figure 5. Total abundances of food items per category in comparison with ingested plastic particles abundances. (Pla=Pastics, Dip=Diptera, Hem=Hemiptera, Tri=Tricoptera, Lep=Lepidoptera, Eph=Ephemeroptera, Ple=Plecoptera, Col=Coleoptera, Gas=Gastropoda, Odo=Odonata, Veg= Plant).

Figure 4 in Small mammals in the diet of Barn Owls (Tyto furcata) in an urban area in Rio de Janeiro state, Brazil, with a new record of the dwarf mouse opossum (Cryptonanus)

Figure 4. Labial views of the second lower molars of the didelphid marsupials (A) Cryptonanus sp. (this study, Campos dos Goytacazes, Rio de Janeiro state), (B) Gracilinanus microtarsus (NPM 1682, Macaé, Rio de Janeiro state), and (C) Monodelphis iheringi (NPM 1010, Macaé, Rio de Janeiro state), showing the variation in the entoconid size.

Figure 3 in Small mammals in the diet of Barn Owls (Tyto furcata) in an urban area in Rio de Janeiro state, Brazil, with a new record of the dwarf mouse opossum (Cryptonanus)

Figure 3. Manipulation and identification of the pellets collected below the artificial nest of the Tyto furcata pair. (A) Separation of bone material; (B) Selection of craniums and mandibles for morphological identification.

Figure 1 in Small mammals in the diet of Barn Owls (Tyto furcata) in an urban area in Rio de Janeiro state, Brazil, with a new record of the dwarf mouse opossum (Cryptonanus)

Figure 1. Satellite image showing nesting site of the T. furcata couple and the surrounding area in Campos dos Goytacazes, Rio de Janeiro. Adapted from Google Earth®.

Figure 2 in Prevalence of cestodes infection among school children of urban parts of Lower Dir district, Pakistan

Figure 2. Tapeworm species eggs. (A) Taenia saginata; (B) Hymenolepis nana; (C) Hymenolepis diminuta.