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24 results for “sampling methodology”
Summary of three different Leaf Area Index (LAI) methodologies of 19 1m x 1m point frame plots sampled near the LTER Shrub plots at Toolik Field Station in AK the summer of 2012.
Summary of three methods used to estimate the Leaf Area Index (LAI) of 19 1m x 1m plots sampled with a point frame near the LTER Shrub plots at the Toolik Field Station in AK the summer of 2012. The methods used were: (1) exponential relationship between LAI and Normalized Leaf Index (NDVI) as measured above the canopy with a Unispec spectroradiometer; (2) Delta-T SunScan canopy analyzer held at 5 cm above the ground under both direct and diffuse light conditions; (3) pin-drop point frame technique. Where values have been averaged (such as for the NDVI and SunScan measurements), the standard deviation is given. Raw data are available upon request for the Unispec data; the raw SunScan data is available under the file "PF_SunScan_LAI".
Measurements of savanna landscap fire emission factors for CO2, CO, CH4 and N2O using a UAV-based sampling methodology
<p>This dataset contains direct measurements of biomass burning emission factors for CO<sub>2</sub>, CO, CH<sub>4</sub> and N<sub>2</sub>O. It includes over 4500 EF bag measurements sampled using an unmanned aerial system (UAS), and measured fuel parameters and fire severity proxies during 129 individual fires. The measurements cover a variety of savanna ecosystems in Brazil, Australia, Botswana, Zambia, South-Africa and Mozambique under different seasonal conditions, sampled over the course of six fire seasons between 2017 and 2022. The table in the included word file explains the individual columns in the excell file. </p> <p> </p>
Fig. 5 in Comparison of sampling methodologies and estimation of population parameters for a temporary fish ectoparasite
Fig. 5. Histograms of emergence counts from the time-series emergence traps. Count bars for each day are subdivided by individual trap.
Fig. 4 in Comparison of sampling methodologies and estimation of population parameters for a temporary fish ectoparasite
Fig. 4. Scatterplot showing total body length in mm versus estimated volume of blood and plasma extracted in Ml. The box-and-whisker plots are centered on the mean body length for each of the three juvenile stages. The box edges are placed at the 2nd and 3rd quartiles for volume estimates and the whiskers show extreme minimum and maximum volumes. The mean estimate of extracted volume by juvenile stage is shown as a labeled dashed-red horizontal line. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 1 in Comparison of sampling methodologies and estimation of population parameters for a temporary fish ectoparasite
Fig. 1. Traps used in the first study. (A) Small emergence trap, (B) fish-baited emergence trap, (C) fish-baited tripod, (D) open-mesh fish-baited trap and (E) lighted plankton trap. Note that the sample container holding a small French grunt fish for the fish-baited emergence trap (B) and the fish-baited tripod trap (C) are identical units other than the sealed floats attached to the top of the sample container when used with the fish-baited emergence trap.
Fig. 2 in Comparison of sampling methodologies and estimation of population parameters for a temporary fish ectoparasite
Fig. 2. Traps used in the second study. The lighted plankton trap, in the left foreground, stands on short legs—four large emergence traps can be seen in the middleground to the right of the lighted plankton trap. A second lighted plankton trap in the background can be seen towards the center of the frame.
Fig. 3 in Comparison of sampling methodologies and estimation of population parameters for a temporary fish ectoparasite
Fig. 3. Scatterplots of total body length in mm plotted against eye length in mm along the long axis. The upper plot shows measurements for zuphea and the lower plot for praniza. The body length cutoff values separating juvenile stages are shown as a dotted-green line. Gnathiids collected from emergence traps are seen as gold-filled squares and those collected from light traps are presented as purple-filled triangles. Differences in the ontological sampling bias of these two trap designs can be seen by comparing the two scatterplots. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 6 in Comparison of sampling methodologies and estimation of population parameters for a temporary fish ectoparasite
Fig. 6. Histograms of trap counts by sample day and juvenile stage. The upper histograms show counts from emergence traps and the lower histograms show counts from light traps. Mean count for each histogram is shown as a dashed horizontal line. See text for an explanation of the number of sampling days shown in each plot.
A Methodology for the Fast Identification and Monitoring of Microplastics in Environmental Samples using Random Decision Forest Classifiers
<p>This short video shows the results of the application of a classifier for microplastics as described by Hufnagl et al. (2019).</p> <p> </p> <p>If you reuse this video please cite</p> <p> </p> <p>Hufnagl, B., Steiner, D., Renner, Löder, M. G. J., Laforsch, C. and Lohninger, H. <em>A Methodology for the Fast Identification and Monitoring of Microplastics in</em><em> Environmental Samples using Random Decision Forest Classifiers,</em> Analytical Methods, 2019, DOI:10.1039/C9AY00252A</p>
A global LC-MS2-based methodology to identify and quantify anionic phospholipids in plant samples
<p>This table contains peaks aera values from LC-MS used to develop a method for identification and quantification of anionic lipid in plant sample: Genva et al. 2023: “A global LC-MS2-based methodology to identify and quantify anionic phospholipids in plant samples”</p>
Data for: Validation of a nutria (Myocastor coypus) environmental DNA assay highlights considerations for sampling methodology
<p>Nutria (<em>Myocastor coypus</em>) is a semi-aquatic rodent species that is invasive across multiple regions within the United States. Here we evaluated a qPCR assay previously described for use in Japan for application across invasive populations in the United States. We also compared two environmental DNA sampling methodologies for this assay: field filtration of large volumes of water passed through filters versus direct sampling of small volumes of water. We validated assay specificity, generality, and sensitivity, compared assay performance between two independent laboratories, and successfully tested the assay<em> in situ </em>on a known wild population. The filtration method required fewer samples for environmental DNA detection than direct sampling, but the choice of methods should be assessed based on specific field conditions and time and budget considerations. Our extensive assay validation and comparison across laboratories suggests that the assay is ready to be applied in environmental DNA monitoring of nutria throughout the United States.</p>
Data from: Sampling methodology influences habitat suitability modeling for Chiropteran species
<p>Technological advances increase opportunities for novel wildlife survey methods. With increased detection methods, many organizations and agencies are creating habitat suitability models (HSMs) to identify critical habitats and prioritize conservation measures. However, multiple occurrence data types are utilized independently to create these HSMs with little understanding of how biases inherent to those data might impact HSM efficacy.</p> <p>We sought to understand how different data types can influence HSMs using three bat species (<em>L. borealis</em>, <em>L. cinereus</em>, and <em>P. subflavus</em>). We compared the overlap of models created from passive-only (acoustics), active-only (mist-netting and wind turbine mortalities), and combined occurrences to identify the effect of multiple data types and detection bias.</p> <p>For each species, the active-only models had the highest discriminatory ability to tell occurrence from background points and for two of the three species, active-only models performed best at maximizing the discrimination between presence and absence values. By comparing the niche overlaps of HSMs between data types, we found a high amount of variation with no species having over 45% overlap between the models. Passive models showed more suitable habitat in agricultural lands, while active models showed higher suitability in forested land, reflecting sampling bias.</p> <p>Overall, our results emphasize the need to carefully consider the influences of detection and survey biases on modeling, especially when combining multiple data types or using single data types to inform management interventions. Biases from sampling, behavior at the time of detection, false positive rates, and species life history intertwine to create striking differences among models. The final model output should consider biases of each detection type, particularly when the goal is to inform management decisions, as one data type may support very different management strategies than another. </p>
Data from: Measuring behavior patterns and evaluating time sampling methodology to characterize brush use in weaned beef cattle
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Data from: Sampling methodology influences habitat suitability modeling for Chiropteran species
Open the record for dataset details and reuse information.
Data for: Validation of a nutria (Myocastor coypus) environmental DNA assay highlights considerations for sampling methodology
Open the record for dataset details and reuse information.
Systematic review for optimizing sample size in dairy cow methane emission studies: a comprehensive methodological approach
<p>Collection of research data focusing on methane (CH4) emissions from dairy cows across various breeds and conditions. The dataset encompasses a range of studies published from 2012 to 2023, each documented with specific parameters including the study title, authors, country of research, cow breed, lactation status, methods used for CH4 measurement, experimental designs, CH4 yield and its variability, dry matter intake, and diet composition.</p>
FIGURE 3. Sampling methodologies used for specimen collection. A in Updated checklist of semi-terrestrial and estuarine crabs (Crustacea: Decapoda: Brachyura) of Barbados, West Indies
FIGURE 3. Sampling methodologies used for specimen collection. A, Baited onion bag trap (0.95 m x 0.55 m; mesh size: 0.5 mm); B, Large crab trap (B:1.0 x 0.40 m; mesh size: 50 x 40 mm); C, Small cage crab trap (C: 0.5 x 0.2 m, mesh size: 30 x 15 mm); D, Hand nets (diameter: 60 mm; mesh size: 0.1 mm); E, Fruit bait outside of crab burrow.
Dataset for Label-free Surface Enhanced Raman Scattering (SERS) on Centrifugal Silver Plasmonic Paper (CSPP): a novel methodology for unprocessed biofluids sampling and analysis.
<p>This dataset contains all the spectra used in "Label-free Surface Enhanced Raman Scattering (SERS) on Centrifugal Silver Plasmonic Paper (CSPP): a novel methodology for unprocessed biofluids sampling and analysis". Data are available in 2 different formats:</p> <p>- a compressed archive ("Spectra.zip") with 5 folders ("Figure 1-5”) containing all the *.txt files used to generate the 5 figures in the original paper (1 file = 1 spectrum).</p> <p>- 5 single CSV files (“Figure-X_all-spectra-and-metadata.csv”) with all the spectra and metadata relative to a specific figure. The data are structured as follow, with each row being 1 spectrum, followed by metadata.</p>
Sampling in Cloud Benchmarking: A Critical Review and Methodological Guidelines
<p>This replication package contains the data and code to replicate our critical review on sampling in cloud benchmarking.</p> <p> </p> <p><strong>Paper</strong></p> <p>Akbari, Saman, and Manfred Hauswirth. "Sampling in Cloud Benchmarking: A Critical Review and Methodological Guidelines." <em>2024 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)</em>. IEEE, 2024. DOI: <a href="https://doi.org/10.1109/CloudCom62794.2024.00034" target="_blank" rel="noopener">10.1109/CloudCom62794.2024.00034</a>.</p> <pre>@inproceedings{akbari2024sampling, title={Sampling in Cloud Benchmarking: A Critical Review and Methodological Guidelines}, author={Akbari, Saman and Hauswirth, Manfred}, booktitle={2024 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)}, pages={160--167}, year={2024}, organization={IEEE} }</pre> <p> </p> <p><strong>Abstract</strong></p> <blockquote> <p>Cloud benchmarks suffer from performance fluctuations caused by resource contention, network latency, hardware heterogeneity, and other factors along with decisions taken in the benchmark design. In particular, the sampling strategy of benchmark designers can significantly influence benchmark results. Despite this well-known fact, no systematic approach has been devised so far to make sampling results comparable and guide benchmark designers in choosing their sampling strategy for use within benchmarks. To identify systematic problems, we critically review sampling in recent cloud computing research. Our analysis identifies concerning trends: (i) a high prevalence of non-probability sampling, (ii) over-reliance on a single benchmark, and (iii) restricted access to samples. To address these issues and increase transparency in sampling, we propose methodological guidelines for researchers and reviewers. We hope that our work contributes to improving the generalizability, reproducibility, and reliability of research results.</p> </blockquote>
An in vitro methodology demonstrates the five steps of trained immunity in mice: implications on biomarker discovery, adaptive immune responses, mouse strains, sample cryopreservation and genetic abla
GEO Series GSE290033. Mus musculus. 11 samples. Type: Expression profiling by high throughput sequencing.
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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.