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108 results for “environmental monitoring”
Data from: Weather conditions determine attenuation and speed of sound: environmental limitations for monitoring and analysing bat echolocation
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Data from: Environmental DNA analysis of river herring in Chesapeake Bay: a powerful tool for monitoring threatened keystone species
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Monitoring the birds and the bees: Environmental DNA metabarcoding of flowers detects plant–animal interactions
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Data from: Development and testing of an environmental DNA (eDNA) assay for endangered Atlantic sturgeon to assess its potential as a monitoring and management tool
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The use of environmental DNA to monitor impacted coastal estuaries
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New Jersey Department of Environmental Protection Ambient Lake Monitoring Program, 2005-2009
This project was developed as a monitoring program that would address both the deficiencies cited in the 1999 USEPA's Office of Inspector General's Audit Report and the needs of the watershed management and water quality assessment (305(b)/303(d)) programs. This approach comports with the guidance provided in USEPA's publication, "Elements of a State Water Monitoring and Assessment Program," March 2003, which requires that states develop and implement long-term strategies that include monitoring of all state water body types including lakes. Data is collected to evaluate trophic status of selected lakes and assess the ecological health of the State's lentic water resources. This data is not expected to be compared with any existing data and is not expected to be used for any permitting, enforcement or TMDL development activities. Target population for monitoring was all lakes, man-made or natural, excepting water supply reservoirs, wholly or partially within the State of NJ political boundaries. A lake is defined as a permanent body of water of at least two hectares in surface, and a minimum depth of one meter. Lakes were selected randomly, using the USEPA - Generalized Random Tessellation Stratified (GRTS) survey design, but in a manner that equalizes selections over all Omernik level III ecoregions (6 within state). The New Jersey GIS coverage containing approximately 870 named lakes, meeting the design criteria, was used for the selection process. A total of 200 lakes were sampled, each sampled once every five years, with 40 lakes sampled per year.
NH Department of Environmental Services (NHDES) Watershed Management Bureau Biology Section: Lake Trophic Survey Environmental Monitoring data, 1995-2014
This program was initially established in 1975 in order to identify the trophic state of NH lakes and ponds, as required by Section 314(a) of PL 92-500 (the Federal Water Pollution Control Act Amendments of 1972). The purpose of the program is to determine lake trophic class and monitor physical, chemical and biological water quality parameters. Each year, 40 different lakes and ponds are surveyed, once in the summer and once in the winter. The surveys are comprehensive physical, chemical and biological surveys, including electronic depth soundings, macrophyte identifications and abundance ratings, shoreline bacteria sampling and at the deep spot a temperature/dissolved oxygen/percent saturation profile, Secchi disk transparency reading, samples for chlorophyll, Ca, Mg Na, and K in the upper water layer, phytoplankton and zooplankton net hauls for identification and counts and discrete water samples at two or three depths for pH, acid neutralization capacity, apparent color, conductivity, TP, Total Kjeldahl nitrogen, nitrite+nitrate nitrogen, chloride, and sulfate. The surveys are designed to assess current baseline conditions and compliance with water quality criteria, identify the lake’s trophic status, determine acid rain impacts and the existence of exotic aquatic plants and provide information for gross long-term trend analyses.
Weather Data, 1940-2016, Adirondack Long-Term Ecological Monitoring Program by Adirondack Ecological Center of the State University of New York College of Environmental Science and Forestry, Newcomb, New York, USA
These datasets include information collected from 1940 to 2016 in or around Huntington Wildlife Forest at the Adirondack Ecological Center in Newcomb, New York. Data were collected daily and include minimum and maximum daily temperature, precipitation, snowfall, and sometimes additional measurements (e.g., wind direction, weather events). These data were collected as part of the Adirondack Long Term Ecological Monitoring Program (ALTEMP).
NH Department of Environmental Services (NHDES) Watershed Management Bureau Biology Section: Volunteer Lake Assessment Program (VLAP) Environmental Monitoring data, 1995-2014
The New Hampshire Volunteer Lake Assessment Program was initiated in 1985 in response to an expressed desire of lake associations to be involved in lake protection and watershed management. VLAP is a cooperative program between volunteer monitors and the DES which leads to local awareness of land use and human practices that may be detrimental to lake quality and also empowers communities in their decision-making regarding lake management issues. The three major partners are the NHDES Biology Section, numerous volunteer monitors located throughout the state, and the VLAP satellite laboratories. Sara Steiner, NHDES VLAP Coordinator (who reports directly to Jody Connor, the Limnology Center Director and VLAP Program Manager), has the overall responsibility for training the volunteer monitors throughout the state in sample collection and watershed monitoring, conducting annual site visits and training interns to conduct annual site visits. NHDES and the volunteer monitors will collect samples from their lake/pond and its watershed, and will then bring samples to the NHDES Limnology Center, the Lake Sunapee Region Laboratory at Colby Sawyer College in New London, or the Environmental Research Laboratory at Plymouth State University in Plymouth. The purpose of VLAP is to assess the chemical and biological characteristics of the lakes and ponds throughout the state to determine overall health of the system. Environmental results are measured by making comparisons to established means and ranges of water quality for the state of New Hampshire. Chemical, biological, and physical parameters are measured and compared to lakes throughout the state. This data is provided to NHDES and the volunteer monitors. The data is used by the NHDES for assessment, education, and reporting purposes. The data are used by the volunteer monitors for educational purposes and for guiding local lake management activities. Volunteers collect water at least once per month during the summer (June –
Figure 2 in Terrestrial isopods as bioindicators for environmental monitoring in olive groves and natural ecosystems
Figure 2. Occurrence of isopod species per studied site.
Supplementary material 1 from: Crookes S, Heer T, Castañeda RA, Mandrak NE, Heath DD, Weyl OLF, MacIsaac HJ, Foxcroft LC (2020) Monitoring the silver carp invasion in Africa: a case study using environmental DNA (eDNA) in dangerous watersheds. NeoBiota 56: 31-47. https://doi.org/10.3897/neobiota.56.47475
Table 1
Accompanying dataset for: "A Bayesian method for predicting background radiation at environmental monitoring stations"
<h3>Physical parameters included</h3> <ul> <li>Ten-minute-averaged ambient dose equivalent rates (nSv/h) observed by the Immission Monitors for Ring area (IMR stations) at the sites of the SCK CEN and the Doel NPP for selected periods in time</li> </ul> <h3>Geographic locations</h3> <ul> <li>Belgian Nuclear Research Centre (SCK CEN) in Mol, Belgium: 18 IMR stations</li> <li>Nuclear Power Plant in Doel, Belgium: 16 IMR stations</li> </ul> <h3>Periods</h3> <ul> <li>6 through 13 August 2022</li> <li>30 August through 1 September 2022</li> <li>10 through 12 September 2022</li> </ul> <h3>Description of data</h3> <p>The zipped folder contains three sub folders for the different periods of interest. Each sub folder contains 34 files. Files are either named IMR-D##.txt to indicate Doel-based or IMR-M##.txt to indicate SCK CEN-based stations. Exact locations (WGS84) are included in the headers. Time stamps (referred to as 'local_time' in the files) are given in Central European Summer Time (UTC+2), and the ambient dose equivalent rates (referred to as 'value' in the files) in nanosievert per hour (nSv/h).</p> <h3>Acknowledgements</h3> <p>The authors thank François Menneson from FANC-ACFN for providing access to the Telerad data.</p>
Accompanying software for: "A Bayesian method for predicting background radiation at environmental monitoring stations"
<h3>Introduction</h3> <p>This software accompanies: "A Bayesian Method for predicting background radiation at environmental monitoring stations". The software is written in Python and depends (besides on standard packages like numpy) on the PyMC package for Bayesian inference. A brief user manual is provided that will allow to install the necessary prerequisites in a conda environment, and describes how to perform the inferences that are described in the paper. This requires additionally downloading the dataset that we have also made available on this platform (<a href="https://doi.org/10.5281/zenodo.12581795" target="_blank" rel="noopener">10.5281/zenodo.12581795</a>). </p> <h3>Description of files</h3> <ul> <li><em>manual.pdf</em> describes how to install the necessary packages in conda, and how to perform inferences from the paper.</li> <li><em>main.py</em> is the main script, which contains the input parameters and calls the relevant functions.</li> <li><em>bayesian_inference.py</em> contains the beating heart of the software. Here, the Bayesian problems for calibration and predictions are set up and solved using the PyMC package.</li> <li><em>data_paper_interface.py </em>is only necessary when reproducing the data from the paper. It contains the different cases that were used in the paper, and can be used to parse data from the accompanying dataset.</li> </ul>
Supplementary material 10 from: Ushio M, Murakami H, Masuda R, Sado T, Miya M, Sakurai S, Yamanaka H, Minamoto T, Kondoh M (2018) Quantitative monitoring of multispecies fish environmental DNA using high-throughput sequencing. Metabarcoding and Metagenomics 2: e23297. https://doi.org/10.3897/mbmg.2.23297
Abundance of some common fish species obtained by the direct visual census
Supplementary material 2 from: Ushio M, Murakami H, Masuda R, Sado T, Miya M, Sakurai S, Yamanaka H, Minamoto T, Kondoh M (2018) Quantitative monitoring of multispecies fish environmental DNA using high-throughput sequencing. Metabarcoding and Metagenomics 2: e23297. https://doi.org/10.3897/mbmg.2.23297
Primer, index and probe sequences used in the study
Supplementary material 1 from: Ushio M, Murakami H, Masuda R, Sado T, Miya M, Sakurai S, Yamanaka H, Minamoto T, Kondoh M (2018) Quantitative monitoring of multispecies fish environmental DNA using high-throughput sequencing. Metabarcoding and Metagenomics 2: e23297. https://doi.org/10.3897/mbmg.2.23297
The numbers of sequence reads remaining (filtered) in data processing steps
Supplementary material 7 from: Ushio M, Murakami H, Masuda R, Sado T, Miya M, Sakurai S, Yamanaka H, Minamoto T, Kondoh M (2018) Quantitative monitoring of multispecies fish environmental DNA using high-throughput sequencing. Metabarcoding and Metagenomics 2: e23297. https://doi.org/10.3897/mbmg.2.23297
Results of quantitative PCR for total fish eDNA, Japanese anchovy and Japanese jack mackerel
Supplementary material 3 from: Ushio M, Murakami H, Masuda R, Sado T, Miya M, Sakurai S, Yamanaka H, Minamoto T, Kondoh M (2018) Quantitative monitoring of multispecies fish environmental DNA using high-throughput sequencing. Metabarcoding and Metagenomics 2: e23297. https://doi.org/10.3897/mbmg.2.23297
Descriptions of TaqMan probe specificity test and supplementary Table S1 and S2
Comparison of an extracellular vs. total DNA extraction approach for environmental DNA-based monitoring of sediment biota
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Standardized Evaluation of Subcutaneous Glucose Monitoring Systems Under Routine Environmental Conditions
ClinicalTrials.gov study NCT02614768. IPD Sharing: Not stated. Countries: 0. Publications: 0.
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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.