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70 results for “measuring selection”
Carbon Isotope and Ring Width Measurements from Tree Rings of Selected Canopy Species at Six Sites in the Eastern United States
Forest Water Use Efficiency (WUE) is defined as the ratio of carbon uptake per unit water vapor loss via transpiration. Micrometeorological measurements suggest that forest WUE has dramatically increased over the last two decades, in excess of what would be expected from increases in atmospheric carbon dioxide concentrations. Coinciding with observed trends in forest WUE have been marked decreases in acid deposition throughout much of North America and Europe. There is evidence that acid deposition may impact forest WUE, either by altering the availability of nutrients in forest soils or by directly affecting foliar physiology. Changes in WUE could also lead to changes in stream discharge from forested catchments. The hypothesized response of forests to changing levels of acid deposition is not currently considered in the land surface components of global climate models (GCMs). Since carbon dioxide and water vapor are the two most important greenhouse gases, it is vital to accurately model their land-atmosphere exchange. This research uses a catchment-based approach to investigate the effects of changing acid deposition on forest WUE. Tree ring carbon isotopes reconstruct historical WUE time series within six catchments that have been differentially impacted by acid deposition due to distinctions between their underlying bedrock mineralogy and geological histories. The research also capitalizes on experimental treatments that have altered soil biogeochemistry in paired catchment designs (Bear Brook, ME; Hubbard Brook, NH; and Fernow Experimental Forest, WV). Additional watersheds that vary in underlying bedrock chemistry are also used in this research to examine tree-ring WUE time series as natural experiments along a base-cation gradient. These watersheds include Sleepers River, VT; Hubbard Brook, NH; Cone Pond Watershed, NH; and Shenandoah National Park, VA.
Hubbard Brook Experimental Forest: Litter and soil radiocarbon and selective metal measurements from Bear Brook, 1998–2023
Radiocarbon time series of archived litter and soil samples from Bear Brook (west of watershed 6) at lower elevation from 1998 to 2023. Additional measurements include total carbon and nitrogen for all samples, and selective dissolution metal concentrations for the Oa/A and mineral soil layers. Selective dissolution metals include pyrophosphate-extractable aluminum (Al); iron (Fe), calcium (Ca), magnesium (Mg), and manganese (Mn); oxalate-extractable Al, Fe, Ca, Mg, and Mn; and dithionite-extractable Al, Fe, Ca, Mg, and Mn. All samples are from the Microbial Biomass and Activity Sampling Effort (Groffman and Martel, 2025, https://doi.org/10.6073/pasta/aff4a2074fd56102f62f13a19ce46f2d). These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the US Forest Service, Northern Research Station.
Selective excitation enables encoding and measurement of multiple diffusion parameters in a single experiment
<p>NMR spectra data for diffusion experiments.</p> <p>NMR pulse sequence compatible with Bruker spectrometers for the selective diffusion measurement.</p>
Particulate organic carbon and nitrogen measurements at selected depths in the water column in the CCE region since 2006 - 2024 (ongoing).
Water column bottle samples at multiple depths are taken during CCE Process cruises (since 2006, ongoing) at various CTD stations, filtered, and stored at -20°C. Measurements of particulate organic carbon (POC) and nitrogen (PON) are performed onshore in the lab where samples are acidified, dried and analyzed by high-temperature combustion. The sample and tin capsule react with oxygen and combust at 1000°C, and the sample is broken down, thus converting organic carbon to CO2 and reducing nitrogen oxides to N2 gas. Both gases are measured by thermal conductivity. Samples analyzed within the CCE constrain the mean C:N ratio of small particulates and by difference relative to measured living biomass, the biomass of suspended detritus.
Measurements, from CCE LTER process cruises in the California Current region, of dissolved inorganic concentrations of nutrient iron and of iron limitation at selected stations and depths, 2006 - 2021 (ongoing).
Measurements are made of dissolved iron, total iron and the potential for phytoplankton iron limitation on CCE LTER Process cruises (since 2006, ongoing) in coastal transition zones of the southern California Current System. This is a weak upwelling regime that is relatively low in nutrients and chlorophyll. Changes in phytoplankton (Chla response to Fe+) and nutrient parameters upon iron addition are also investigated.
Total dissolved organic carbon and nitrogen measurements at selected depths in the water column from CCE LTER process cruises in the California Current System, 2006 - 2021 (ongoing).
Water column bottle samples at multiple depths are taken during CCE Process cruises (since 2006, ongoing) at various CTD stations, and measurements of total organic carbon (TOC) and total nitrogen (TN) are performed onshore in the lab. TOC includes both dissolved and particulate organic carbon (DOC and POC, respectively). TN includes particulate and dissolved organic nitrogen as well as dissolved inorganic nitrogen species. In open ocean waters, POC is subtracted from TOC, and likely provides an accurate estimate of DOC because particles are typically small and homogeneously distributed in the sample. In coastal waters, and at stations where relatively high chlorophyll concentrations are present, the TOC measurement is not easily converted to DOC by subtracting POC values. Experience has shown that particles in these regions are large and inhomogeneously distributed. Therefore, samples collected in the CCE are reported as TOC and TN, expressed as micromoles of carbon (nitrogen) per liter of sea water.
Particulate organic carbon and nitrogen measurements at selected depths in the water column from CalCOFI-CCE Augmented cruises in the California Current System, 2004 - November 2022
Water column bottle samples at multiple depths are taken during CalCOFI cruises (since 2004, ongoing) at various CTD stations, filtered, and stored at -20°C. Measurements of particulate organic carbon (POC) and nitrogen (PON) are performed onshore in the lab where samples are acidified, dried and analyzed by high-temperature combustion. The sample and tin capsule react with oxygen and combust at 1000°C, and the sample is broken down, thus converting organic carbon to CO2 and reducing nitrogen oxides to N2 gas. Both gases are measured by thermal conductivity. Samples analyzed within the CCE constrain the mean C:N ratio of small particulates and by difference relative to measured living biomass, the biomass of suspended detritus.
Aeolian saltation fieldwork: values for size-selective transport measurements
<p>This excel spreadsheet (‘SizeSelectiveTransport.xlsx’) contains the following information on surface and airborne particle size distributions (PSDs) for size-selective saltation transport analyses at our six field sites (Jericoacoara, Rancho Guadalupe, Oceano N1, Oceano S1, Oceano N2, Oceano S2):</p> <ul> <li><strong>“d_lower_mm”</strong> – Lower limit diameter for each particle size bin [mm].</li> <li><strong>“d_mid_mm”</strong> – Midpoint diameter for each particle size bin [mm].</li> <li><strong>“d_upper_mm”</strong> – Upper limit diameter for each particle size bin [mm].</li> <li><strong>“dVdlnd_bed”</strong> – Site-averaged non-dimensionalized volume fraction in each size bin for surface samples, <span class="math-tex">\(\frac{dV_{bed}}{d\ln(d)}\)</span>.</li> </ul> <p>The field measurements from which these values were calculated are described in Martin and Kok (2017).</p> <ul> <li><strong>“dVdlnd_air”</strong> – Site-averaged non-dimensionalized volume fraction in each size bin for airborne samples, <span class="math-tex">\(\frac{dV_{air}}{d\ln(d)}\)</span>.</li> <li>Site-averaged non-dimensionalized volume fraction in each size bin for airborne samples, conditioned on each non-dimensionalized shear stress range, <span class="math-tex">\(\frac{dV_{air}}{d\ln(d)}|_{\tau/\tau_{it}}\)</span>. Cases in which a PSD is lacking for a shear stress range are marked as “NaN”: <ul> <li><strong>“dVdlnd_air_taunorm_below_10”</strong> – for <span class="math-tex">\(\tau/\tau_{it} \leq 1.0\)</span></li> <li><strong>“dVdlnd_air_taunorm_10_15”</strong> – for <span class="math-tex">\(1.0 < \tau/\tau_{it} \leq 1.5\)</span></li> <li><strong>“dVdlnd_air_taunorm_15_22</strong>” – for <span class="math-tex">\(1.5 < \tau/\tau_{it} \leq 2.2\)</span></li> <li><strong>“dVdlnd_air_taunorm_22_30”</strong> – for <span class="math-tex">\(2.2 < \tau/\tau_{it} \leq 3.0\)</span></li> <li><strong>“dVdlnd_air_taunorm_30_40”</strong> – for <span class="math-tex">\(3.0 < \tau/\tau_{it} \leq 4.0\)</span></li> </ul> </li> <li><strong>“f_bed”</strong> – Fraction of bed surface particles in size bin <em>i</em>, <span class="math-tex">\(f_{bed,i}\)</span>. Fraction is computed only for bins with particle diameter <em>d</em> > 1.3 mm. Bins below this value are marked as “NaN”.</li> <li><strong>“f_air_bar”</strong> – Mean fraction of airborne particles in size bin <em>i</em>, <span class="math-tex">\(\langle f_{air,i} \rangle\)</span>. Fraction is computed only for bins with particle diameter <em>d </em>> 1.3 mm. Bins below this value are marked as “NaN”.</li> <li><strong>“f_air_sigma”</strong> – Uncertainty on mean fraction of airborne particles in size bin <em>i</em>, <span class="math-tex">\(\sigma_{\langle f_{air,i} \rangle}\)</span>. “NaN” values correspond to undefined values for f_air_bar.</li> </ul> <p>The Matlab file (‘GrainSizeData.mat’) includes further raw data, including number-based size distributions for individual samples.</p>
Photoplethysmography in dogs and cats: selection of measurement sites for pet monitor
<p>The PPG measurements of the study Cugmas et al, 2018.</p> <p>Notes.txt include all information about the dataset.</p>
Auditory stream segregation and selective attention for cochlear implant listeners: Evidence from behavioral measures and event-related potentials
<p>Data set generated for the study "Auditory stream segregation and selective attention for cochlear implant listeners: Evidence from behavioral measures and event-related potentials" </p> <ol> <li><strong>behavioral.txt</strong>: d' scores obtained by the listeners on the deviant detection task. <ul> <li>subject: listener ID</li> <li>distractor: Electrode separation condition</li> <li>deviant: Deviant triplet</li> <li>d: d' scores</li> <li>exp: experimental session (BEH / ERP)</li> </ul> </li> <li><strong>ERP_by_condition.txt</strong>: <ul> <li>Subject: listener ID</li> <li>Type: Sound type (Target / Distractor)</li> <li>Dev: Deviant condition. Early = deviant triplets 1 or 2. Late = deviant triplet 3 or <em>none.</em></li> <li>rep: Triplet number</li> <li>sound: sound number within the triplet</li> <li>amplitude: amplitude difference between the active and the passive listening conditions.</li> </ul> </li> </ol> <p> </p>
SNAPPING PSI surface motion measurements over selected sites presented in MDPI Remote Sensing paper "SNAPPING Services on the Geohazards Exploitation Platform for Copernicus Sentinel-1 Surface Motion Mapping"
<p>SNAPPING PSI surface motion measurements over selected sites as presented in the paper with the title "SNAPPING Services on the Geohazards Exploitation Platform for Copernicus Sentinel-1 Surface Motion Mapping" by Michael Foumelis, Jose Manuel Delgado Blasco, Fabrice Brito, Fabrizio Pacini, Elena Papageorgiou, Panteha Pishehvar and Philippe Bally on Remote Sensing Open Access Journal.</p> <p>Whenever using this dataset, please cite its original paper (<a href="https://doi.org/10.3390/rs14236075">https://doi.org/10.3390/rs14236075</a>) and include the reference to this dataset (<a href="https://doi.org/10.5281/zenodo.7369653">https://doi.org/10.5281/zenodo.7369653</a>).</p> <p>This dataset includes average Line-of-Sight velocities for the following sites and dates:</p> <table> <tbody> <tr> <td><strong>Site name</strong></td> <td><strong>Country</strong></td> <td><strong>Period</strong></td> <td><strong>Relative orbit</strong></td> <td><strong>Orbit direction</strong></td> </tr> <tr> <td>Cap-Haïtien</td> <td>Haiti</td> <td>Jan-2017 / Dec-2019</td> <td>106</td> <td>ascending</td> </tr> <tr> <td>Gran Renaissance Ethiopian Dam</td> <td>Ethiopia</td> <td>Jan-2019 / Jun-2021</td> <td>50</td> <td>descending</td> </tr> <tr> <td>La Palma Volcano</td> <td>Spain</td> <td>Jun-2019 / Dec-2021</td> <td>169</td> <td>descending</td> </tr> <tr> <td>Santorini Volcano</td> <td>Greece</td> <td>Apr-2015 / May-2021</td> <td>29</td> <td>ascending</td> </tr> <tr> <td>San Francisco</td> <td>USA</td> <td>Jan-2016 / Dec-2020</td> <td>115</td> <td>descending</td> </tr> <tr> <td>Thessaloniki International Airport (SKG)</td> <td>Greece</td> <td>Apr-2015 / Dec-2020</td> <td>102</td> <td>ascending</td> </tr> </tbody> </table>
Leaf area for select species was measured in arctic tundra experimental sites from late June into early August,Toolik Field Sattion, Alaska, Arctic LTER 2000.
Leaf area for select species was measured in arctic tundra experimental sites from late June into early August. Measurements were made in acidic and non acidic tussock tundra and in shrub tundra in control and fertilized plots.
iCollections butterfly images selected for automated measurement
<p>Images of butterflies from the Natural History Museum (NHMUK) iCollections project, used for automated wing length measurement with <a href="https://github.com/machine-shop/butterfly-wings">https://github.com/machine-shop/butterfly-wings</a></p> <p>Original iCollections dataset: https://doi.org/10.5519/0038559</p> <p> </p>
Wear topography measurements: selected polymers after friction tests with steel – lubrication with ionic liquids containing CNTs
<p>Measurement files of the topography of worn surfaces of polymers cooperating with steel and lubricated with hybrids of ionic liquids and carbon nanotubes. The files correspond to the tests presented in:</p> <p><span>Tribological tests - block-on-ring - polymers vs. AISI 4130 - IL+CNTs, IL+Cu_CNTs https://doi.org/10.5281/zenodo.10817199. </span></p>
A dataset of proton kinetic-scale current sheets selected at 1 AU using Wind spacecraft measurements
<p>This is a dataset of proton kinetic-scale current sheets selected at 1 AU using 11 Samples/s magnetic field measurements aboard Wind spacecraft. The current sheets were selected using Partial Variance Increments method. The detailed analysis of this dataset can be found at https://arxiv.org/abs/2112.15256v1</p> <p>The first column gives a CS index number, the second panel gives a date in the year/month/day format, the last two columns give <br> temporal positions of the left and right boundaries of a CS. These moments of times are in seconds from the beginning of the day indicated in the second column. </p>
Selected quantitative measurements of Ceratitis capitata embryonic development
<p>Selected quantitative measurements of <em>Ceratitis capitata</em> embryonic development (processed image data, Mathematica notebooks, as well as intermediate measurement and visualization files)</p>
Accompanying data set for the manuscript "REverSe TRanscrIptase Chain Termination (RESTRICT) for Selective Measurement of Nucleotide Analogs Used in HIV Care and Prevention"
<p>This data set contains all experimental and theoretical data included in the manuscript " REverSe TRanscrIptase Chain Termination (RESTRICT) for Selective Measurement of Nucleotide Analogs Used in HIV Care and Prevention", namely:</p> <p>RESTRICT_model: MATLAB script for completing calculations in the RESTRICT theoretical model.</p> <p>Figure 2:</p> <ul> <li>Raw data from theoretical model showing contributions of individual model components, Kaff = 0.3</li> <li>Normalized data from theoretical model showing contributions of individual model components, Kaff = 0.3</li> <li>Experimental NRTI Drug Screen 180 nt TTCA 500 nM dNTP</li> </ul> <p>Figure 3:</p> <ul> <li>Experiment-dNTP-Concentration-Screen</li> <li>Theory-dNTP-Concentration-Screen</li> <li>Experiment-Template-Length-Screen</li> <li>Theory-Template-Length-Screen</li> <li>Experiment-Sequence-Screen</li> <li>Theory-Sequence-Screen</li> </ul> <p>Figure 4:</p> <ul> <li>Experimental-NRTI-Drug-Screen-90nt-TCAA-only</li> <li>Theory-TCAA90-Kaff=0point2</li> <li>Experimental-NRTI-Drug-Screen-GGCA-only</li> <li>Theory-GGCA180-Kaff=0point2</li> </ul> <p>Figure 5:</p> <ul> <li>GGCA-vs-TTCA-Specificity-Analysis</li> </ul>
Measurements of natural radioactivity levels and associated radiation hazard indices in Moringa plant leaf samples from selected areas in southern Ethiopia.
<p>Moringa stenopetala (MS) is a multipurpose tree whose leaf is consumed by people of all ages in southern Ethiopia. In this study, natural radioactivity levels of <sup>226</sup>Ra, <sup>232</sup>Th, and <sup>40</sup>K, as well as the related dangerous radiological characteristics, were measured on different sites of moringa samples using high-purity germanium (HPGe) gamma-ray spectrometry. Average activity concentrations of <sup>226</sup>Ra, <sup>232</sup>Th, and <sup>40</sup>K in moringa leaves are found to be 0.49 ± 0.12, 3.84 ± 1.12, and 573.29 ± 26.79 Bq.kg<sup>-1</sup>, respectively. Moreover, the average values of the corresponding radiological parameters, Ra<sub>eq</sub>, H<sub>int</sub>, and annual effective dose (E<sub>ave</sub>) (sum), were also found to be 50.13 ± 3.79 Bq.kg<sup>-1</sup>, 0.136 ± 0.010, and 0.238 ± 0.089 mSvy<sup>-1</sup>, respectively. When the obtained results for all of the samples were compared to globally accepted criteria, they were discovered to be lower than the allowable world average levels. Furthermore, the lifetime cancer risk was revealed to be far lower than the allowable limit. According to the study, the risk of absorbing natural radionuclides from moringa leaf ingestion is insignificant. The findings can be utilized to create radiation safety norms and regulations for the use of moringa leaves as food and medication.</p>
Data from: The measurement of selection when detection is imperfect: how good are naïve methods?
The life spans of animals can be measured in natural populations by uniquely marking individuals and then releasing them into the field. Selection on survival (a component of fitness) can subsequently be quantified by regressing the life spans of these marked individuals on their trait values. However, marked individuals are not always seen on every subsequent catching occasion, and for this reason, imperfect detection is considered a problem when estimating survival selection in natural populations. Capture–mark–recapture methods have been advocated as a powerful means to correct for imperfect detection. Here, we use simulated and field data sets to evaluate the effect of assuming perfect detection ('naïve methods'), when detection is really imperfect. We compared the performance of the naïve methods with methods correcting for imperfect detection (mark–recapture methods, or MR). Although the effects of trait-dependent recapture probability are mitigated when recapture probability is high, mark–recapture methods still provide the safest choice when recapture probability might be trait-dependent. In our simulations, mark–recapture methods had a power advantage over naïve methods, but all methods lost statistical power at low recapture probabilities. The main advantage of mark–recapture methods over naïve methods is the ability to control for hidden trait-dependent recapture probability, as it is often hard to tell a priori if trait dependence is an issue in a particular study. However, when trait-dependent recapture probability is weak, naïve methods and mark–recapture methods perform similarly as long as recapture rates do not become too low, and the main problem of survival selection studies is still low statistical power. We provide a R package (EasyMARK) alongside with this paper to facilitate future integration between MR methods and classical selection studies. EasyMARK provides the opportunity to convert the regression coefficients from MR-approaches in to classical standardized selection gradients.
Data from: Composite measures of selection can improve the signal-to-noise ratio in genome scans
The growing wealth of genomic data is yielding new insights into the genetic basis of adaptation, but it also presents the challenge of extracting the relevant signal from multi-dimensional datasets. Different statistical approaches vary in their power to detect selection depending on the demographic history, type of selection, genetic architecture and experimental design. Here, we develop and evaluate new approaches for combining results from multiple tests, including multivariate distance measures and methods for combining P-values. We evaluate these methods on (i) simulated landscape genetic data analysed for differentiation outliers and genetic-environment associations and (ii) empirical genomic data analysed for selective sweeps within dog breeds for loci known to be selected for during domestication. We also introduce and evaluate how robust statistical algorithms can be used for parameter estimation in statistical genomics. On the simulated data, many of the composite measures performed well and had decreased variation in outcomes across many sampling designs. On the empirical dataset, methods based on combining P-values generally performed better with clearer signals of selection, higher significance of the signal, and in closer proximity to the known selected locus. Although robust algorithms could identify neutral loci in our simulations, they did not universally improve power to detect selection. Overall, a composite statistic that measured a robust multivariate distance from rank-based P-values performed the best. We found that composite measures of selection could improve the signal of selection in many cases, but they were not a panacea and their power is limited by the power of the univariate statistics they summarize. Since genome scans are widely used, improving inference for prioritizing candidate genes may be beneficial to medicine, agriculture, and breeding. Our results also have application to outlier detection in high-dimensional datasets and to combining results in meta-analyses in many disciplines. The compound measures we evaluate are implemented in the r package minotaur.
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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)
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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
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