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70 results for “environmental quality”
Sacramento-San Joaquin Bay-Delta Continuous (15 Minute) water quality monitoring data collected by the Continuous Environmental Monitoring Program, DWR, 2005- ongoing.
The Continuous Environmental Monitoring Program (CEMP) plays an instrumental role in overseeing real-time water quality in the Sacramento-San Joaquin Delta (the Delta) and Suisun Bay. The program harnesses wireless telemetry to transmit crucial data to the California Data Exchange Center (CDEC), making high-resolution environmental data pertaining to the Delta and Suisun Bay publicly accessible. The extensive dataset captures information at 15-minute intervals from 15 monitoring stations, utilizing YSI 6600 and YSI EXO sondes to obtain standalone water quality measurements. This extensive dataset informs the operations of the California State Water Project, ensuring it adheres to mandated water quality standards set by Water Right Decision 1641. This data compilation incorporates all information since the transition to YSI multiparameter sondes in 2005. It is important to note that the commencement dates and subsequent upgrades vary between stations, leading to slight discrepancies in the dataset's date ranges. Since its inception in the mid-1980s, CEMP has progressively expanded its monitoring capabilities, consistently augmenting the number of monitoring locations and the array of water quality parameters assessed. Its commitment to utilizing the most advanced water quality monitoring technology reaffirms its position as an environmental monitoring leader in the Delta and Suisun Bay. Today, the program oversees 15 water quality stations that reliably capture data every 15 minutes, each day of the year, transmitting this data in real-time. The core tenents of CEMP: • to obtain consistent and accurate data in real-time at established monitoring stations • to provide data necessary to achieve compliance with salinity, flow, and dissolved oxygen standards • to perform data analyses for further understanding of estuarine ecology • to report information to other government agencies, as well as the public, for the purpose of management and conservation of the upper San F
Interagency Ecological Program: Discrete water quality monitoring in the Sacramento-San Joaquin Bay-Delta, collected by the Environmental Monitoring Program, 1975-2023
\<markdown\> The Interagency Ecological Program’s (IEP) Environmental Monitoring Program (EMP) was initiated in compliance with the Water Right Decision D-1379 (now mandated by Water Right Decision D-1641) and has monitored discrete water quality and nutrients in the upper San Francisco Estuary since 1975. The objectives of the EMP are to obtain consistent and accurate monthly data at established monitoring stations, provide and document information necessary to achieve compliance with salinity, flow, and dissolved oxygen standards, and to report this information for the purpose of management and conservation of the upper San Francisco Estuary. While the EMP also collects biological data, this dataset only includes the discrete water quality and nutrient data collected by the EMP from 1975-2021. Links to other EMP datasets can be found [here](https://emp-des.github.io/emp-reports/data-links.html) \</markdown\>
Atmospheric, hydrodynamic and water quality observations from environmental-quality stations, water level sensors, acoustic Doppler velocimeters, and meteorological stations located at the Guadalquivir river estuary (2008 - 2010)
<p>The dataset included in this repository was obtained during the project entitled “Propuesta metodológica para diagnósticar las consecuencias de las actuaciones humanas en el estuario del Guadalquivir” funded by the Autoridad Portuaria de Sevilla (APS), by the Consejería de Innovación, Ciencia y Empresa (Junta de Andalucía), CTM2011-22580, MedEX (CTM2008-04036-E) and PR11-RNM-7722. The data were collected in real time from 2008 until 2010 with a remote monitoring system installed by the Institute of Marine Sciences of Andalusia (ICMAN-CSIC) (Navarro et al., 2011).</p> <p> </p> <p>The environmental quality station recorded turbidity, temperature, conductivity, normalized turbidity, dissolved oxygen, oxygen, oxygen saturation, percentage of oxygen saturation, fluorescence, normalized fluorescence, and salinity every thirty minutes. Current data were measured every 15 minutes by means of acoustic current profilers. The former datasets were obtained at several depths and different locations along the Guadalquivir estuary. Water level sensors recorded the position of the free water surface every 10 minutes at several locations along the Guadalquivir estuary. Wind velocity and direction and solar radiation were measured every 10 minutes in a meteorological station at the mouth of the Guadalquivir estuary.</p> <p>Brief description of dataset.</p> <ul> <li> <p>velocities.csv (in m/s)</p> </li> <li> <p>Turbidity.csv (in Volts), temperature (in Celsius), conductivity (in Siemens/m), normalized turbidity (in FNU), dissolved oxygen (mg/L), oxygen (in Volts), fluorescence (in Volts), normalized fluorescence (in Volts), oxygen saturation (mg/L), percentage of oxygen saturation (%), salinity (in PSU).</p> </li> <li> <p>qual_Salmedina.csv, R_mean (mean radiative flux in W/m²), R_max (max radiative flux in W/m²), Rel_humidity (relative humidity in %), D_mean (wind mean direction in degrees), D_max (wind maximum direction in degrees), D_sig (standard deviation of the wind direction in degrees), V_mean (mean wind velocity in m/s), V_max (maximum wind velocity in m/s), V_sig (standard deviation of the wind velocity in m/s), P_atm_mean (mean atmospheric pressure in mbar), T_mean (mean air temperature in Celsius), T_max (maximum air temperature in Celsius), T_sig (standard deviation of the air temperature in Celsius).</p> </li> <li> <p>Sealevel.csv (in meters)</p> </li> </ul> <p>A wide description of the datasets can be found in Navarro et al (2011).</p> <p>Contact person: infogdfa@ugr.es (or mcobosb@ugr.es)</p>
Dataset: Environmental Impact on the Long-Term Connectivity and Link Quality of an Outdoor LoRa Network
<p>This repository contains the long-term connectivity and link quality dataset collected on <a href="https://chirpbox.github.io/">ChirpBox</a> over 4 months (May -- September 2021) in the city of Shanghai, China. </p> <p>In addition to the dataset itself, we provide evaluation scripts for data analysis and visualization, in order to facilitate data exploration and re-use. To make it clear how to use the scripts, we provide a <em>Jupyter notebook -- </em> <strong>dataset.ipynb</strong> for dataset visualization.</p> <p><strong>List of files:</strong></p> <ol> <li><em>dataset_03052021_15092021.csv</em> <ul> <li>The dataset includes LoRa connectivity and link quality, as well as environmental information, collected from May 3 to September 15, 2021.</li> </ul> </li> <li><em>data_analysis.py</em> <ul> <li>The script for dataset analysis and visualization. One can use the functions in this script to derive network-level statistics (e.g., in terms of average number of correctly-exchanged packets), link-level statistics (e.g., in terms of SNR, RSS, and PRR), and node-level statistics(e.g., in terms of number of neighbours and temperature evolution over time).</li> </ul> </li> <li><em>metadata_processing.py</em> <ul> <li>The script for pre-processing metadata into CSV files. One can use the functions in this script to convert metadata for each measurement saved in TXT and JSON formats to CSV files that include attributes such as link quality, connectivity, and environmental information, an example of which is <strong>dataset_03052021_15092021.csv</strong>.</li> </ul> </li> <li><em>dataset.ipynb </em> <ul> <li>The Jupiter notebook contains examples of visualization and metadata pre-processing of datasets with functions in <strong>data_analysis.py</strong> and <strong>metadata_processing.py</strong>.</li> </ul> </li> <li><em>topology_map.png</em> <ul> <li>The node deployment map used to create topology figures. A usage example is <strong>Figure 1</strong> shown in the notebook <strong>dataset.ipynb</strong>.</li> </ul> </li> <li><em>dataset_metadata.zip</em> <ul> <li>The dataset metadata is stored in TXT and JSON formats. Among them, link quality, connectivity and on-board sensor data are stored in TXT files and weather information are stored in JOSN files.</li> </ul> </li> <li><em>README.md</em> <ul> <li>The README.md explains all the files in this repository and gives some examples of how to use the provided scripts to analyze the dataset.</li> </ul> </li> </ol>
Indoor Environmental Quality in Schools: NOTECH Solution vs. Standard Solution - dataset
<p>Dataset for "Indoor Environmental Quality in Schools: NOTECH Solution vs. Standard Solution"</p>
Water quality data collected by the Citizen-Led Environmental Observatory (CLEO) from multiple nearshore sites in Lake Lillinonah, Connecticut, USA, 2010-current
Included in this data package are water quality data from the Citizen-Led Environmental, a Observatory (CLEO) volunteer water quality monitoring program run by Friends of the Lake (FOTL) and Fairfield University at Lake Lillinonah, Connecticut, USA. The program has been operational since 2008 (data available 2010-current). Trained volunteer monitors collect data from dock locations across the lake on water temperature, Secchi disk depth, water color, presence of floating woody debris, recreation potential, trash, particle type and surface scum. Volunteers collect data between 3:00 and 7:00 PM three times per week from Memorial Day through Labor Day. In addition to the variables listed above, CLEO volunteers collect routine water samples on a biweekly basis, as well as any time there is a notable algal bloom. The routine samples are analyzed for nutrient (total nitrogen and total phosphorus) concentrations as well as concentrations of the cyanobacterial toxin microcystin. The blooms samples are analyzed for microcystin only. These data are available in EDI packages EDI568 (nutrients) and EDI569 (toxins).
Effects of genetic vs. environmental quality on condition-dependent morphological and life history traits in a neriid fly
<p>Condition is assumed to reflect both genes and environment, enabling condition-dependent signals to reveal genetic quality. However, because the phenotypic effects of variation in genetic quality could be masked by environmental heterogeneity, the contribution of genetic quality to phenotypic variation in fitness-related traits and condition-dependent signals remains unclear. We compared effects of ecologically relevant manipulations of environmental quality (nutrient dilution in the larval diet) and genetic quality (one generation of inbreeding) on male and female morphology, life history and reproductive performance in the neriid fly <em>Telostylinus angusticollis</em>. We found that larval diet quality had strong, positive effects on male and female body size, male secondary sexual traits, and aspects of male and female reproductive performance. By contrast, inbreeding had weak effects on most traits, and no trait showed clear and consistent effects of both environmental and genetic quality. Indeed, inbreeding effects on body size and male competitive performance were of opposite sign in rich vs. poor larval diet treatment groups. Our results suggest that environmental quality strongly affects condition, but the effects of genetic quality are subtle and environment-dependent in this species. These findings raise questions about the genetic architecture of condition and the potential for condition-dependent traits to function as signals of genetic quality.</p>
Dataset: Environmental conditions and male quality traits simultaneously explain variation of multiple colour signals in male lizards
<p>Dataset and R code associated with the following publication:</p> <p>Badiane et al. (2022), Environmental conditions and male quality traits simultaneously explain variation of multiple colour signals in male lizards. Journal of Animal Ecology, in press</p> <p>This dataset includes the following files:</p> <p>- An excel file containing the reflectance spectra of all individuals from all the study populations</p> <p>- An excel file containing the variables collected at the individual and population levels</p> <p>- Two R scripts corresponding to the analyses performed in the publication</p>
FIGURE 1 in Trophic strategies of the invasive Twospot livebearer (Pseudoxiphophorus bimaculatus, Teleostei: Poeciliidae) in a gradient of environmental quality in central Mexico
FIGURE 1 | Geographic location of study area and sampling sites located in the Lerma-Chapala River basin and Pánuco River basin in central Mexico. XOT = El Xote; CHI = El Charco del Ingenio; GAL = Los Galvanes; PRC = Presa del Carmen; PVA = Paso de Vaqueros; OAS = Oasis; EXT = Extoraz; BUC = Bucareli.
FIGURE 2 in Trophic strategies of the invasive Twospot livebearer (Pseudoxiphophorus bimaculatus, Teleostei: Poeciliidae) in a gradient of environmental quality in central Mexico
FIGURE 2 | Physicochemical parameters of water in each study site in central Mexico: temperature (°C), TDS= Total dissolved solids (g/L) and DO= Dissolved oxygen (mg/L). XOT = El Xote; CHI = El Charco del Ingenio; GAL = Los Galvanes; PRC = Presa del Carmen; PVA = Paso de Vaqueros; OAS = Oasis; EXT = Extoraz; BUC = Bucareli.
Fig. 2 in Saproxylic weevils and edaphic beetles as indicators of environmental quality of relict forests in Piedmont lowlands (Coleoptera)
Fig. 2 – Map of Parco della Partecipanza, completely surrounded by agroecosystems. Map data: Google Earth, Maxar Technologies, used according to Google Earth Terms of Service.
Fig. 1 in Saproxylic weevils and edaphic beetles as indicators of environmental quality of relict forests in Piedmont lowlands (Coleoptera)
Fig. 1 – The collecting sites. Map data: Google Earth, Maxar Technologies, used according to Google Earth Terms of Service.
Fig. 5 in Saproxylic weevils and edaphic beetles as indicators of environmental quality of relict forests in Piedmont lowlands (Coleoptera)
Fig. 5 – Some of the weevils collected in the research. a, Kyklioacalles navieresi (Boheman, 1837); b, Kyklioacalles aubei (Boheman, 1837); c, Acalles echinatus (Germar, 1824); d, Echinodera hypocrita (Boheman, 1837). From Stüben (2014-2020), used with permission.
Figure 1 in Using of fluctuating asymmetry in adult Pelophylax ridibundus (Amphibia: Anura: Ranidae) meristic traits as a method for assessing developmental stability of population and environmental quality of their habitat: industrial area in southern Bulgaria
Figure 1. An indicative map of the sites in southern Bulgaria where P. ridibundus individuals were captured in 2019.
Figure 2 in Using of fluctuating asymmetry in adult Pelophylax ridibundus (Amphibia: Anura: Ranidae) meristic traits as a method for assessing developmental stability of population and environmental quality of their habitat: industrial area in southern Bulgaria
Figure 2. Photos of some asymmetric P. ridibundus individuals from site 1: the Chaya River in southern Bulgaria. Legend: a–d: asymmetric morphological traits on the back of the body and hind limbs of frogs, e–f: asymmetric morphological traits on the fingers of frogs. Trait 1 – number of stripes on the dorsal side of the thigh (femur); trait 2 – number of spots on the dorsal side of the thigh; trait 3 – number of stripes on the dorsal side of the shank (crus); trait 4 – number of spots on the dorsal side of the shank; trait 5 – number of stripes on the foot (pes); trait 6 – number of spots on the foot; trait 7 – number of stripes and spots on the back (dorsum); trait 8 – number of white spots on the ventral side of the second finger of the hind leg; trait 9 – number of white spots on the ventral side of the third finger of the hind leg; trait 10 – number of white spots on the ventral side of the fourth finger of the hind leg.
Supplementary data for "Individual quality and environmental factors interact to shape reproduction and survival in a resident bird of prey"
<p><strong>Abstract</strong></p> <p>The archive contains data file and R-Script to reproduce the results presented in the paper “Individual quality and environmental factors interact to shape reproduction and survival in a resident bird of prey” published in Royal Society Open Science.</p> <p><strong><span> </span></strong></p>
China's historical 1km resolution eco-environmental quality data (CHEQ)
<p>The China's High-resolution Eco-Environmental Quality (CHEQ) dataset provides 1-km historical eco-environmental quality (EEQ) during years 2001-2019. This dataset archived in TIFF format was jointly developed by Beijing Normal University, Southern University of Science and Technology and Peking University based on multi-source remote sensing data. The dataset covers the entire land of China with a yearly temporal resolution. The existing validation results show that the CHEQ dataset was highly consistent with the environmental index (EI) provided by the Ministry of Ecology and Environment of China. The CHEQ fills the research gap in the field of EEQ monitoring in China.<br> </p>
Benefits and limitations of environmental magnetism for completing citizen science on air quality: a case study in a street canyon.
<p>Inside a street canyon in Montpellier (France) a total of 72 deposimeters were deployed in 29 households for a period of 3 months to measure local air quality. This street canyon was chosen because dwellers were already mobilized against the street traffic, and because they were in conflict on this issue with policy makers. The project aimed to include all the stakeholders through co-construction. The closure of the street during the metrological campaign and the absence of agreement curbed their involvement and motivation. However, the feedbacks from the citizen partners promote the fact that this study supported their claims and brought them a deeper understanding on the micro-scale air quality monitoring. Indeed, it is increasingly difficult for citizens, who seemed specifically interested in what is happening right outside their front door, to understand this measure with the emergence of ever more low-cost sensors. For that reason, we examined the citizen’s degree of confidence in magnetic monitoring of air quality and how can this technique be useful in their claims. The results show that magnetism can be a measurement technique favorable to citizen participation because it provides a large amount of data at the micro-scale of the street level, while the data from the certified associations for monitoring air quality requires a spatial interpolation to map variations on a neighborhood scale. In this study, we proposed a magnetic air quality index to standardize and democratize the magnetic monitoring of air quality to facilitate the dialogue with all stakeholders.</p>
Dataset for "Exposure and environmental engagement: A pilot integrating wearable sensors, air quality and citizen science"
<p>The dataset contains anonymised readings of 7 citizens taking air quality measurements using PlumeLabs Flow 2 monitor. Data is for Falmouth/Penryn, and Bristol and it was collected between January 26, 2022 and March 9, 2022.</p> <p>CSV file:</p> <ul> <li>latitude: unit degrees, positive values indicate North hemisphere.</li> <li>longitude, unit degrees, positive values indicate East.</li> <li>AQI: PlumeLabs' Air Quality Index.</li> <li>site: A refers to Falmouth/Penryn(UK), B refers to Bristol (UK).</li> <li>count: auxiliary variable that indicates that the record was comprised of a single reading.</li> </ul> <p>Jupyter notebook: The air quality analysis was conducted with Python 3.9.16 alongside numpy 1.24.3, pandas 2.0.2, matplotlib 3.7.1, and cartopy 0.21.1 (background tiles by OpenStreetMaps).</p>
Effects of genetic vs. environmental quality on condition-dependent morphological and life history traits in a neriid fly
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