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858 results for “monitoring data”
Monitoring data second-life battery at Cloverleaf
<p>Dataset consisting of monitoring data on the second-life battery system that was implemented in the context of Circusol:</p> <p>- Round Trip Efficiency<br> - State of Health evolution<br> - Typical Day V I & Vcell</p>
Monitoring data second-life battery Cloverleaf demonstrator Circusol
<p>This dataset includes monitoring data on the second-life battery system that was implemented in the Cloverleaf demonstrator in the context of Circusol.</p> <p>The following data are included:<br> - State of Health evolution<br> - Round trip Efficiency<br> - Typical day V I<br> - Typical day Vcell</p>
T a b l e 1 in Citizen Science Assisted Monitoring Provides New Data Concerning the Distribution of the Bulgarian Bent-toed Gecko, Mediodactylus danilewskii (Gekkonidae, Squamata), in North-East Bulgaria
T a b l e 1. Coordinates of the newly recorded specimens of M. danilewskii in North East Bulgaria
Fig. 2 in Citizen Science Assisted Monitoring Provides New Data Concerning the Distribution of the Bulgarian Bent-toed Gecko, Mediodactylus danilewskii (Gekkonidae, Squamata), in North-East Bulgaria
Fig. 2. Schematic map of the confirmed and new sites of
Data from: Passive acoustic monitoring provides reliable under-estimates of population size and longevity in wild Savannah Sparrows
<p>Many breeding birds produce conspicuous sounds, providing tremendous opportunities to study free-living birds through acoustic recordings. Traditional methods for studying population size and demographic features depend on labour-intensive field research. Passive acoustic monitoring provides an alternative method for quantifying population size and demographic parameters, but this approach requires careful validation. To determine the accuracy of passive acoustic monitoring for estimating population size and demographic parameters, we used autonomous recorders to sample an island-living population of Savannah Sparrows (<em>Passerculus sandwichensis</em>) over a six-year period. Using the individually distinctive songs of males, we estimated male population size as the number of unique songs detected in the recordings. We analyzed songs across six years to estimate birth year, death year, and longevity. We then compared the estimates to field data in a blind analysis. Estimates of male population size through passive acoustic monitoring were, on average, 72% of the true male population size, with higher accuracy in lower-density years. Estimates of demographic rates were lower than true values by 29% for birth year, 23% for death year, and 29% for longevity. This is the first investigation to estimate longevity with passive acoustic monitoring, and adds to a growing number of studies that have used passive acoustic monitoring to estimate population size. Although passive acoustic monitoring under-estimated true population parametersfeatures, likely due to the high similarity among many male songs, our findings suggest that autonomous recorders can provide reliable estimates of population size and demographic characteristicslongevity in a wild songbird.</p>
Six years of wild bee monitoring collections data using Blue Vane traps in Southern Pennsylvania, USA
<p><span><span>Turley NE, Biddinger DJ, Joshi NK, López-Uribe MM. 2022. Six years of wild bee monitoring shows changes in biodiversity within and across years and declines in abundance. Ecology and Evolution. </span></span></p> <p><span>Wild bees form diverse communities that pollinate plants in both native and agricultural ecosystems making them both ecologically and economically important. The growing evidence of bee declines has sparked increased interest in monitoring bee community and population dynamics using standardized methods. Here, we studied the dynamics of bee biodiversity within and across years by monitoring wild bees adjacent to four apple orchard locations in Southern Pennsylvania, USA. We collected bees using passive Blue Vane traps continuously from April to October for six years (2014-2019) amassing over 26,000 bees representing 144 species. We quantified total abundance, richness, diversity, composition, and phylogenetic structure. There were large seasonal changes in all measures of biodiversity with month explaining an average of 72% of the variation in our models. Changes over time were less dramatic with years explaining an average of 44% of the variation in biodiversity metrics. We found declines in all measures of biodiversity especially in the last 3 years, though additional years of sampling are needed to say if changes over time are part of a larger trend. Analyses of population dynamics</span> <span>over time for the 40 most abundant species indicate that about one third of species showed at least some evidence for declines in abundance. Bee family explained variation in species-level seasonal patterns but we found no consistent family-level patterns in declines, though bumble bees and sweat bees were groups that declined the most. Overall, our results show that season-wide standardized sampling across multiple years can reveal nuanced patterns in bee biodiversity, phenological patterns of bees, and population trends over time of many co-occurring species. These datasets could be used to quantify the relative effects that different aspects of environmental change have on bee communities and to help identify species of conservation concern</span><span>. </span></p>
PM10, SO2, and NO2 Ambient Air Quality Monitoring Data from India's National Ambient Monitoring Program (NAMP) 2011-2015
<p>India's Central Pollution Control Board (CPCB) operates and maintains the National Ambient Monitoring Program (<a href="https://cpcb.nic.in/about-namp/">NAMP</a>) which includes both continuous and manual ambient monitoring stations. This dataset is a collation of manual monitoring data by day for years 2011, 2012, 2013, 2014, and 2015 for PM10, SO2, and NO2. These stations collect for a maximum of 104 days in a year. This cleaned dataset was utilized for understanding trends and conducting comparisons with modeled concentrations under the APnA city program, published <a href="https://doi.org/10.1016/j.uclim.2018.11.005">here</a> (<a href="https://doi.org/10.1016/j.uclim.2018.11.005">Urban Climate, 2019</a>).<br> <br> Data format - year, month, day, SO2, NO2, PM10, Stn Code, State, City<br> All units - micro-gm/m3 (ug/m3)</p> <p>Official annual summary reports (PDFs) are available <a href="https://cpcb.nic.in/namp-data/">here</a>.</p> <p>For guidelines for ambient and emissions monitoring, summaries of available data, and other resources on monitoring in India, visit <a href="https://urbanemissions.info/resources-energy-emissions-analysis-in-india/#monitoring">https://urbanemissions.info/resources-energy-emissions-analysis-in-india</a></p>
Improving citizen science data for long-term monitoring of plant species
<p>In 2012, a new volunteer-based recording scheme for vascular plants was launched in the Netherlands. Its purpose is to track the changes in the number of occupied 1-km grid cells for as many native plant species as possible between survey rounds of 8 years. We did not prescribe a strict field protocol to minimize variation in observer effort, but instead chose to statistically correct for this variation with occupancy models. These models require replicated visits to a grid cell per season, which was implemented by having two independent observers survey grid cells and record all plant species observed. Now that a first survey round has ended (2012–2019), we evaluate our approach, i.e. we tested whether the scheme has the potential to produce proper trend estimates. The number of occupied grid cells in the first round was estimated per species, using an occupancy model with day of year, visit duration and observer experience as covariates for detection. The detection probability, which was 0.43 on average, strongly depended on visit duration and day of year. It was possible to estimate the number of occupied grid cells quite precisely for several hundreds of species, such that the statistical power is expected to be high enough to detect changes of 10% between survey rounds. For rare species, however, the power to detect changes is expected to be quite low. We conclude that the approach works well, but further improvements are suggested.</p>
Data and code for "A decade of monitoring micropollutants in urban wet-weather flows: what did we learn?"
<p><strong>Data and code for publication</strong></p> <p><em>Lena Mutzner, Viviane Furrer, Hélène Castebrunet, Ulrich Dittmer, Stephan Fuchs, Wolfgang Gernjak, Marie-Christine Gromaire, Andreas Matzinger, Peter Steen Mikkelsen, William R. Selbig, Luca Vezzaro,<br> A decade of monitoring micropollutants in urban wet-weather flows: what did we learn?<br> Water Research, 2022.<br> https://doi.org/10.1016/j.watres.2022.118968</em></p> <p><strong>Data</strong></p> <p>Micropollutants concentrations in µg/l (incl. heavy metals) for 77 wet-weather discharge sites (36 combined sewer overflows, 41 stormwater outlets). The provided data set is a collection of raw data sets based on publications referenced below. The data description is provided in the folder Data\AA_DataDescription.txt</p> <p><strong>Abstract</strong></p> <p>Urban wet-weather discharges from combined sewer overflows (CSO) and stormwater outlets (SWO) are a potential pathway for micropollutants (trace contaminants) to surface waters, posing a threat to the environment and possible water reuse applications. Despite large efforts to monitor micropollutants in the last decade, the gained information is still limited and scattered. In a metastudy we performed a data-driven analysis of measurements collected at 77 sites (683 events, 297 detected micropollutants) over the last decade to investigate which micropollutants are most relevant in terms of 1) occurrence and 2) potential risk for the aquatic environment, 3) estimate the minimum number of data to be collected in monitoring studies to reliably obtain concentration estimates, and 4) provide recommendations for future monitoring campaigns. We highlight micropollutants to be prioritized due to their high occurrence and critical concentration levels compared to environmental quality standards. These top-listed micropollutants include contaminants from all chemical classes (pesticides, heavy metals, polycyclic aromatic hydrocarbons, personal care products, pharmaceuticals, and industrial and household chemicals). Analysis of over 30,000 event mean concentrations shows a large fraction of measurements (> 50%) were below the limit of quantification, stressing the need for reliable, standard monitoring procedures. High variability was observed among events and sites, with differences between micropollutant classes. The number of events required for a reliable estimate of site mean concentrations (error bandwidth of 1 around the “true value) depends on the individual micropollutant. The median minimum number of events is 7 for CSO (2 to 31, 80%-interquantile) and 6 for SWO (1 to 25 events, 80%-interquantile). Our analysis indicates the minimum number of sites needed to assess global pollution levels and our data collection and analysis can be used to estimate the required number of sites for an urban catchment. Our data-driven analysis demonstrates how future wet-weather monitoring programs will be more effective if the consequences of high variability inherent in urban wet-weather discharges are considered.</p>
Data on three-year flowering intensity monitoring in an apple orchard
<p>The present dataset contains UAV images during the full blooming period of an apple orchard for three consecutive years, 2018, 2019, and 2020. It is directly linked to a research article entitled “Feasibility assessment of tree-level flower intensity quantification from UAV RGB imagery: A triennial study in an apple orchard”. The data collection site was an apple orchard located at Randwijk, Overbetuwe, The Netherlands (51.938, 5.7068 in WGS84 UTM 31U). This dataset aims to support researchers focussing on remote sensing, machine vision, deep learning, and image classification, and the stakeholders interested in precision horticulture and orchard management. It can be used for flowering intensity estimation and prediction, and spatial and temporal flowering variability mapping by using digital photogrammetry and 3D reconstruction.</p>
Compilation of chemical pollution monitoring data for the water of mountain lakes
<p>Compilation of chemical pollution monitoring data for the water of mountain lakes. Includes data for wide variety of chemical pollutants and mountain lakes from all over the world. A toxic unit (TU) based approach was used to assess the mixture toxic risks of the compiled monitoring data for each respective lake.Data will be part of an review investigating the risk for mountain lakes by chemical pollution.</p>
A synchronized estimation of hourly ground-level concentrations of six criteria air pollutants in China using data from the first geostationary air-quality monitoring satellite
<p>This dataset provides the ground-level concentrations of six criteria air pollutants estimated from the first geostationary air quality monitoring satellite GEMS with a multi-output random forest model.</p>
2021 Soil and nutrient loss monitoring data of Sunjiagou sub-watershed
<p><span>This dataset observes soil and nutrient loss from runoff plots at a monitoring station in the black soil area in 2021. The details of the runoff plots are as follows: A1: 3°, smooth monopoly, planted with soybeans; A2: 3°, cross monopoly, planted with soybeans; A3: 3°, bare ground; B1: 5°, smooth monopoly, planted with soybeans; B2: 5°, cross monopoly, planted with soybeans and planted with purple acacia as a plant hedge; B3: 5°, bare ground.</span></p>
Data from high throughput SNP-chip as cost effective new monitoring tool for assessing invasion dynamics in the comb jelly Mnemiopsis leidyi
<p class="MsoNormal"><span>High throughput low-density SNP arrays provide a cost-effective solution for population genetic studies and monitoring of genetic diversity as well as population structure commonly implemented in real time stock assessment of fish species. However, the application of high throughput SNP arrays for monitoring of invasive species has so far not been implemented. We developed a species-specific SNP array for the invasive comb jelly <em>Mnemiopsis leidyi</em> based on whole genome resequencing data. Initially, </span><span>a total of</span><span> </span><span>1,</span><span>395</span><span> </span><span>high quality </span><span>SNPs</span><span> were identified</span><span> </span><span>u</span><span>sing stri</span><span>ngent</span><span> filtering criteria</span><span>. From those, 192 assays were designed and validated, resulting in the final panel of 116 SNPs. Markers were diagnostic between the northern and southern <em>M. leidyi</em> lineages and highly polymorphic to distinguish populations. Despite using a reduced representation of the genome, our SNP panel yielded comparable results to using a whole genome resequencing approach (832,323 SNPs), recovering similar values of genetic differentiation between samples and detecting the same clustering groups when performing Structure analyses. The resource presented here provides a cost-effective, high throughput solution for population genetic studies, allowing to routinely genotype large number of individuals. Monitoring of genetic diversity and effective population size estimations in this highly invasive species will allow for the early detection of new introductions from distant source regions or hybridization events. Thereby, this SNP chip represents an important management tool in order to understand invasion dynamics and </span><span>opens the door for implementing such methods for a wider range of alien invasive species.</span></p> <div></div>
Mosquito Lagoon Watershed Livingshoreline monitoring data
<p><strong>PROJECT NAME: </strong>Implementing and evaluating the effectiveness of native vegetative buffers at controlling nonpoint source pollution and as a tool for public education along the Indian River Lagoon</p> <p> </p> <p><strong>PROJECT LOCATION AND WATERSHED CHARACTERISTICS:</strong> </p> <p>Geographic Location (city and county): New Smyrna Beach, FL and nearby cities</p> <p>Size of Project Impact: North Indian River Lagoon Stakeholder zone (A Project Zone)</p> <p>Size of Area Being Treated: approx. 100,000 sq ft (9300 sq. m)</p> <p>Latitude (decimal degrees): approx. 29 N</p> <p>Longitude (decimal degrees): 80.9 W</p> <p>12 Digit Hydrologic Unit Code: 030802020400</p> <p>WBID<strong>:</strong> 2924B2, 2924B1</p> <p>Impaired Water Body Affected: Indian River Lagoon Basin Northern Indian River Lagoon (North A)</p> <p>TMDL Status and Name: Nutrient TMDLs (TN: 177,220 lbs/yr; TP: 9320 lbs/yr)</p> <p>TMDL Impairment; indicate the parameters in the TMDL: Water quality conditions necessary for seagrass regrowth at water depth limits where seagrass historically grew in the basin (a 10% reduction in the target seagrass depth)</p> <p>Impairments to be Addressed by Project: Dissolved oxygen, Nutrients (TN, TP), Un-Ionized Ammonia, turbidity, seagrass depth limits</p> <p><strong> </strong></p> <p><strong>PROJECT OVERVIEW:</strong> The primary objective of this project is to reduce nonpoint source pollution along the Mosquito Lagoon (ML), a northern sub-lagoon of the Indian River Lagoon (IRL) system, by (1) transforming artificially landscaped turfgrass dominated shorelines and retention ponds into living shorelines of native Florida plants that are known to be better filters of nonpoint source nutrients and (2) engaging the public and enhancing awareness of their role in contribution to BMPs for nonpoint source pollution impacting the system.</p>
Changes Monitoring in Hongjiannao Lake from 1987-2023 using Google Earth Engine and Analysis of Climatic and Anthropogenic Forces (Climatic Data)
<p>This dataset presents temporal (1987 to 2023) climatic data for the weather station near Hongjiannao Lake.</p>
Data coverage, biases, and trends in a global citizen-science resource for monitoring avian diversity
<p><strong>Aim:</strong> Understanding and addressing the global biodiversity crisis requires ecological information compiled continuously from across the globe. Data from citizen science initiatives are useful for quantifying species' ecological niches and geographical distributions but can be difficult to apply towards biodiversity monitoring. The presence of fixed geographical locations reduces the opportunistic nature of citizen science data, allowing for more reliable and nuanced trend estimation. The eBird citizen-science programs contains predefined locations whose bird assemblages are sampled across years ('hotspots'). For hotspots to function as a biodiversity monitoring resource, issues related to data coverage, biases, and trends need to be addressed.</p> <p><strong>Location:</strong> Global.</p> <p><strong>Methods:</strong> We estimated the survey completeness of species richness at 300,500 eBird hotspots during the years 2002 to 2022. We documented sampling biases at eBird hotspot and non-hotspot locations during 2022 based on protection status, temperature, precipitation, and landcover.</p> <p><strong>Results:</strong> A total of 10,410 bird species (<em>ca</em>. 96.9% of total) were recorded at hotspots. The number hotspots and the quantity of data and unique participants and quality of species richness estimates has increased worldwide with the Nearctic containing the strongest and most consistent trends. Compared to non-hotspots, hotspots over sampled areas with higher protection status. Hotspots and non-hotspots over sampled warmer and wetter locations in the Antarctic, Nearctic, and Palearctic, and cooler locations in the Afrotropics, Australasia, and the Neotropics. Hotspots and especially non-hotspots over sampled urban areas. Hotspots and non-hotspots under sampled shrublands in Australasia. Hotspots and especially non-hotspots under sampled forests in the Afrotropics, Indomalaya, Neotropics, and Oceania.</p> <p><strong>Main conclusions:</strong> Hotspots have captured a large component of the world's avian diversity but have done so inconsistently across space and time. Data quantity and quality are increasing in many regions, but the presence of sampling biases and spatial uncertainty needs to be addressed when applying the data.</p>
Open Data in German Forest Information Systems: Towards an EU Forest Resilience Monitor (Collection of Forest Resilience Indicators)
<p>This dataset represents the collection of forest indicators for my Master's Thesis in the pioneer master programme at the Universities of Münster, Tallinn (Taltech) and Leuven (KUL), titled "Open Data in German Forest Governance: Towards an EU Forest Resilience Monitor". </p> <p>It contains a classification of inicators sourced from:</p> <ul> <li> <p><span>Nikinmaa, L., Lindner, M., Cantarello, E., Jump, A. S., Seidl, R., Winkel, G., & Muys, B. (2020). Reviewing the use of resilience concepts in forest sciences. <em>Current Forestry Reports, 6</em>, 61-80.</span></p> </li> <li> <p><span>European Commission. (2023a). Proposal for a REGULATION OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL on a monitoring framework for resilient European forests. <em>Directorate-General for Environment</em>. Lastly retrieved on December 17, 2023 from </span><span><a href="https://ec.europa.eu/transparency/documents-register/detail?ref=COM(2023)728&amp;lang=en&lang=en"><span>https://ec.europa.eu/transparency/documents-register/detail?ref=COM(2023)728&amp;lang=en&lang=en</span></a></span><span>. </span></p> </li> <li> <p><span>European Parliament. (2024, February 27). European Parliament legislative resolution of 27 February 2024 on the proposal for a regulation of the European Parliament and of the Council on nature restoration (COM(2022)0304 – C9-0208/2022 – 2022/0195(COD)). Lastly retrieved on April 26, 2024 from </span><span><a href="https://www.europarl.europa.eu/doceo/document/TA-9-2024-0089_EN.html"><span>https://www.europarl.europa.eu/doceo/document/TA-9-2024-0089_EN.html</span></a></span><span>. </span></p> </li> </ul>
Data from: Primer sets evaluation and sampling method assessment for the monitoring of fish communities in the North-western part of the Mediterranean Sea through eDNA metabarcoding
<p>Environmental DNA (eDNA) metabarcoding appears to be a promising tool for surveying fish communities. However, the effectiveness of this method relies on primer set performance and on a robust sampling strategy. While some studies have evaluated the efficiency of several primers for fish detection, it has not yet been assessed <em>in situ </em>for the Mediterranean Sea. In addition, mainly surface waters were sampled and no filter porosity testing was performed. In this pilot study, our aim was to evaluate the ability of six primer sets, targeting 12S rRNA (AcMDB07; MiFish; Tele04) or 16S rRNA (Fish16S; Fish16SFD; Vert16S) loci, to detect fish species in the Mediterranean Sea using a metabarcoding approach. We also assessed the influence of sampling depth and filter pore size (0.45 µm <em>versus</em> 5 µm filters). To achieve this, we developed a novel sampling strategy allowing simultaneous surface and bottom filtration of large water volumes along on-site the same transect. We found that 16S rRNA primer sets enabled more fish taxa to be detected across each taxonomic level. The best combination was Fish16S/Vert16S/AcMDB07, which recovered 95% of the 97 fish species detected in our study. There were highly significant differences in species composition between surface and bottom samples. Filters of 0.45 µm led to the detection of significantly more fish species. Therefore, to maximize fish detection in the studied area, we recommend to filter both surface and bottom waters through 0.45 µm filters and to use a combination of these three primer sets.</p>
Fig. 2 in Data On Protected And Insufficiently Known Insect Species Obtained From The Invertebrate Monitoring In Latvia (2015 - 2016)
Fig. 2. The spatial arrangement scheme of the monitoring activities in one of the squares.
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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)
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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.