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858 results for “monitoring data”
Data from: drones as a tool to study and monitor endangered Grey Crowned Cranes (Balaerica regulorum): behavioural responses and recommended guidelines
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Data from: Long term marine biodiversity monitoring in coastal Antarctica: Are fewer rare species recruiting?
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Data from: Repertoire-based individual acoustic monitoring of a migratory passerine bird with complex song as an efficient tool for tracking territorial dynamics and annual return rates
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Monitoring small mammal abundance using NEON data: Are calibrated indices useful?
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Data from: Monitoring vultures in the 21st century: the need for standardized protocols
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Data from: Monitoring a Norwegian freshwater crayfish tragedy - eDNA snapshots of invasion, infection and extinction
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Data from: Stock enhancement or sea ranching? Insights from monitoring the genetic diversity, relatedness and effective size in a seeded great scallop population (Pecten maximus)
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Data from: A comparison of breeding population estimators using nest and brood monitoring data
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Data from: Bioacoustic monitoring reveals details of tricolored blackbird breeding phenology
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Data for: A systematic review evaluating the performance of eDNA methods relative to conventional methods for biodiversity monitoring
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Monitoring data from a managed aquifer recharge system that collects stormwater runoff in central coastal California. Precipitation, runoff, infiltration, sediment, survey
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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).
Maine Department of Environment Protection lake monitoring and assessment, 1970s-2011, compiled all ME DEP programs for metadata unpublished data
Much of the lake monitoring in the state is done to assess "trophic state" or the productivity of the water. Our 30 year record includes data on over 1000 of our 5785 lakes, including parameters such as transparency, conductivity, alkalinity, total phosphorus and chlorophyll-a. These, along with extensive data sets from the University of Maine and clarity readings from volunteers, have produced one of the most comprehensive lake data sets in the country. DEP regular monitoring includes annual Baseline Sampling Program and special projects of one or more years’ duration. Each year between August 10 and September 10, we visit over 100 lakes and take a number of types of data. The timing coincides with the period when lakes usually show their worst water quality: lowest dissolved oxygen, lowest transparency and highest algae and phosphorus levels. Besides these measures, we sample for conductivity, alkalinity and acid neutralizing capacity (ANC), true and apparent color, and a variety of cations and anions. Lakes sampled generally include TMDL lakes, 33-50 lakes in the VLMP, lakes of special concern (e.g., anecdotal report of algal bloom), long-term monitoring lakes in ecoreserves and special project lakes.
Wisconsin Surface Water Integrated Monitoring System (SWIMS) Department of Natural Resources lake nutrient data, 1970-2011
The Wisconsin Surface Water Integrated Monitoring System (SWIMS) program is the state´s repository for water and sediment monitoring data collected for Clean Water Act work and is the source of data sharing through the federal Water Quality Exchange Network. DNR Fisheries and Water Quality Biologists use the system to locate monitoring stations, providing a gateway to final, reviewed fisheries management datasets housed at the U.S. Geological Survey. SWIMS is also the data system that citizen volunteers use to document water monitoring results for our state´s lakes, streams and wetlands. Parameters typically collected on lakes are total phosphorus, chlorophyll a and Secchi. Through the DNR Long-Term Trend monitoring program, additional parameters such as Nitrogen have been collected. Lake data in SWIMS generally goes back to the 1970s (1970s data was imported in from the EPA STORET database, where DNR laboratory results went historically). The database is updated daily.
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 –
Monitoring data for railway bridge KW51 in Leuven, Belgium, before, during, and after retrofitting
<p>This data set is obtained from a monitoring campaign of 15 months on a steel bowstring railway bridge in Leuven, Belgium. In this period, the connections of the diagonals to the bridge deck and the arches were strengthened after the observation of damage. The monitoring consists of measurements of acceleration on the bridge deck and the arches, strain on the bridge deck and the diagonals connecting the bridge deck with the arches, strain on the rails, displacement at the bearings, and temperature and relative humidity. Data is provided for two train passages and six periods of ambient vibration per day. In addition, the evolution of the identified modal characteristics over time is added. The data set is well-suited for the validation of vibration-based structural health monitoring methods, as it includes data for different states of the structure, i.e. before, during, and after the retrofitting. </p>
BES LTER Base Cation Data for Core Monitoring Streams across Land Use Gradient
<p>The Baltimore Ecosystem Study LTER has established a network of long-term biogeochemical hydrologic study sites. Sites range from suburban to highly urban. More site information can be found on the BESLTER page at www.beslter.org </p> <p>Descriptions of land use and further site descriptions can be found in Kaushal et al 2017. Tabs represent a different sites, listing the base cation concentrations, as well as a tab summarizing site averages as used in Kaushal et al. 2017.</p>
Application of spectral library prediction for parallel reaction monitoring of viral peptides_PRM_data
<p><strong>Project description: </strong></p> <p>A major part of the analysis of parallel reaction monitoring (PRM) data is the comparison of observed fragment ion intensities to a library spectrum. Classically, these libraries are generated by data-dependent acquisition (DDA). Here we test Prosit, a published deep neural network algorithm, for its applicability in predicting spectral libraries for PRM. For this purpose, we targeted 1,529 precursors derived from synthetic viral peptides and analyzed the data with Prosit and DDA-derived libraries. Additionally, we used a spectral library predicted by Prosit and a DDA library to identify SARS-CoV-2 peptides from a simulated oropharyngeal swab.</p> <p> </p> <p><strong>Sample processing protocol:</strong></p> <p>A total of 1,569 crude synthetic viral peptides were ordered in six pools from JPT (Berlin, Germany). Synthetic peptides were separated on a 200 cm μPAC™ column (PharmaFluidics) by using an EASY-nLC1200 system (Thermo Fisher Scientific) equipped with a μPAC™ trapping column (PharmaFluidics). The flow rate was set to 300 nL/min and a stepped linear 160 min gradient was applied: 3-10% B in 22 min, 10-33%B in 95 min, 33-49% B in 23 min, 49-80% B in 10 min and 80% B for 10 min. Solvent A was 0.1% (v/v) formic acid (FA) in water, solvent B consisted of 80% (v/v) acetonitrile in 0.1% (v/v) FA. The column temperature was set to 50 °C. The Q Exactive Plus (Thermo Fisher Scientific) operated in Full MS/dd-MS2 or unscheduled PRM mode. For MS/dd-MS2 the following parameters were used. MS1 resolution was 70.000 with an AGC target of 3x10<sup>6</sup>, max. injection time of 20 ms and a scan range of 300-1650 m/z. MS2 resolution was 17.500 with an AGC target of 10<sup>5</sup>, max. injection time of 50 ms and an isolation window of 2 m/z. The analysis parameters in PRM mode were set as follows. MS1 parameters were identical to DDA. MS2 resolution was 17.500 with an AGC target of 10<sup>6</sup>, max. injection time of 55 ms and an isolation window of 1.4 m/z.</p> <p>Potential SARS-CoV-2 target peptides belonging to the N protein were identified by DDA of SARS-CoV-2 infected Calu-3 cells. Peptides were diluted in 0.1% TFA (0.2 µg/µL) and 5 µL were separated on a 50 cm μPAC™ column (PharmaFluidics) using an EASY-nLC1200 system (Thermo Fisher Scientific). The flow rate was set to 800 nL/min and a stepped 30 min gradient was applied: 6-11% B in 2:58 min, 11-30% B in 17:10 min, 30-35% B in 2:41 min, 35-47% B in 3:11 min, 47-80% B for 0:10 min, 80% B for 1:50 min, 80-0% B in 0:10 min and 100% A for 1:50 min. Solvent A was 0.1% (v/v) formic acid (FA) in water, solvent B consisted of 80% (v/v) acetonitrile in 0.1% (v/v) FA. The column temperature was set to 50 °C. The Q Exactive HF (Thermo Fisher Scientific) operated in Full MS/dd-MS2 (Top20) using the following parameters. MS1 resolution was 60.000 with an AGC target of 3x10<sup>6</sup>, max. injection time of 20 ms and a scan range of 300-1650 m/z. MS2 resolution was 17.500 with an AGC target of 10<sup>5</sup>, max. injection time of 50 ms and an isolation window of 2 m/z.</p> <p> </p> <p>To simulate a SARS-CoV-2 positive patient sample, we spiked cell-culture derived virus in a negative oropharyngeal swab and targeted the N protein by PRM. LC parameters were identical to DDA analysis of SARS-CoV-2 infected Calu-3 cells. The PRM parameters of the The Q Exactive HF (Thermo Fisher Scientific) were set as follows. MS1 parameters were identical to DDA. MS2 resolution was 45.000 with an AGC target of 10<sup>6</sup>, max. injection time of 100 ms and an isolation window of 1.4 m/z.</p> <p> </p> <p> </p> <p><strong>Data processing protocol:</strong></p> <p>DDA Raw files were searched with MaxQuant against the respective virus database (UniProt) with a peptide FDR of 1%. Detailed MaxQuant parameters can be found in the parameters.txt files of the according results. MaxQuant .msms output files were used to generate spectral libraries with BiblioSpec implemented in the Skyline environment using a cut-off score of 0.95. Peptide identification of PRM runs was done in Skyline using the top 6 fragment ions of the DDA spectral library or according Prosit derived library (Prosit_2020_intensity_model).</p>
Data from: Pollinator Monitoring More than Pays for Itself
<p>Resilient pollination services depend on sufficient abundance of pollinating insects over time. Currently, however, most knowledge about the status and trends of pollinators is based on changes in pollinator species richness and distribution only.</p> <p>Systematic, long-term monitoring of pollinators is urgently needed to provide baseline information on their status, to identify the drivers of declines and to inform suitable response measures.</p> <p>We evaluated the full economic costs of implementing four potential national monitoring schemes in the United Kingdom, based on power analyses that estimated sample sizes required to detect a 30% national scale change in pollinator populations over 10 years: 1) professional pollinator monitoring, 2) professional pollination service monitoring, 3) volunteer collected pan-traps and 4) volunteer focal floral observations. These costs were compared to: i) the costs of implementing separate, expert-designed, research and monitoring networks and ii) the economic benefits of pollination services threatened by pollinator loss.</p> <p>Estimated scheme costs ranged from £6,159/year for a 75 site volunteer focal flower observation scheme to £2.7M/year for an 800 site professional pollination service monitoring network. The estimated research costs saved by using the site network as research infrastructure range from £1.46-17M/year. The economic value of UK crop yield lost following a 30% decline in pollinators was estimated at ~£188M/year.</p> <p><i>Synthesis and applications</i>. We evaluated the full costs of running pollinator monitoring schemes against the economic benefits to research and society they provide. The annual costs of monitoring are ≤0.02% of the estimated annual loss to UK crop production from a 30% decline in crop pollination services. Furthermore, by providing high quality scientific data, monitoring schemes would save at least £1.5 on data collection per £1 spent. Our findings demonstrate that long-term systematic monitoring can be a cost-effective tool for both addressing key research questions and setting action points for policy-makers. Careful consideration must be given to scheme design, the logistics of national-scale implementation and resulting data quality when selecting the most appropriate combination of surveyors, methods and site networks to deliver a successful scheme. </p>
ScienceDex guides
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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.