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677 results for “time of use”
Bioturbation increases time averaging despite promoting shell disintegration: a test using anthropogenic gradients in sediment accumulation and burrowing on the southern California shelf
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Area and Timing data and R script for: 3D scanning as a tool to measure growth rates of live coral microfragments used for coral reef restoration
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Data from: The CellPhe toolkit for cell phenotyping using time-lapse imaging and pattern recognition
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Data for: Land use change and coastal water darkening drive synchronous dynamics in phytoplankton and fish phenology on centennial time scales
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Testing alternative hypotheses for the decline of cichlid fish in Lake Victoria using fish fossils time series from sediment cores
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Data from: A user-friendly guide to using distance measures to compare time series in ecology
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Data from: Using adversarial networks to extend brain computer interface decoding accuracy over time
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Using a real-time location system to detect behavioral changes in ewes with subclinical mastitis and their lambs
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Data from: Palmer et al. 2021 “Behaviorally mediated trophic cascade attenuated by prey use of risky places at safe times” Oecologia
The mere threat of predation may incite behavioral changes in prey that lead to community-wide impacts on productivity, biodiversity, and nutrient cycling. The paucity of experimental manipulations, however, has contributed to controversy over the strength of this pathway in wide-ranging vertebrate systems. We investigated whether simulated gray wolf (Canis lupus) presence can induce behaviorally-mediated trophic cascades, specifically, whether the ‘fear’ of wolf olfactory cues alone can change deer foraging behavior in ways that affect plants and soils. Wolves were recently removed from the Cedar Creek Ecosystem Science Reserve (Minnesota, USA), such that consumptively mediated predator effects were negligible. At 32 experimental plots, we crossed two nested treatments: wolf urine application and herbivore exclosures. We deployed camera traps to quantify how white-tailed deer (Odocoileus virginianus) adjusted their spatiotemporal habitat use, foraging, and vigilance in response to wolf cues and how these behavioral changes affected plant productivity, plant communities, and soil nutrients. Weekly applications of wolf urine significantly altered deer behavior, but deer responses did not cascade to affect plant or soil properties. Deer substantially reduced crepuscular activity at wolf-simulated sites compared to control locations. As wolves in this area predominantly hunted during mornings and evenings, this response potentially allows deer to maximize landscape use by accessing dangerous areas when temporal threat is low. Our experiment suggests that prey may be sensitive to ‘dynamic’ predation risk that is structured across both space and time and, consequentially, prey use of risky areas during safe times may attenuate behaviorally-mediated trophic cascades at the predator–prey interface.
PIE LTER location and sample dates for sites used in space for time sea level rise study, Rowley, MA.
This dataset contains the GPS-ed locations of the quadrats used for the 2017-2018 Space for Time substitution experiment in tidal creek marshes off the Rowley River and Plum Island Sound in Rowley Massachusetts. The space for time study uses an intensive and comprehensive approach to compare low elevation, Spartina alterniflora marsh areas to higher elevation Spartina patens marsh areas. Other related data files include: HTL-RO-ST-MAR-Biomass, HTL-RO-ST-MAR-Birds, HTL-RO-ST-MAR-Quads, HTL-RO-ST-MAR-Sediments, HTL-RO-ST-MAR-Bites, HTL-RO-ST-MAR-Sticky, HTL-RO-ST-MAR-Decomp, HTL-RO-ST-MAR-Traps, HTL-RO-ST-MAR-Deep_pitfalls
PIE LTER bird observations associated with marsh sites used in space for time sea level rise study, Rowley, MA.
This dataset contains observations of birds foraging at high and low tide at space for time substition plots in tidal creek marshes off the Rowley River and Plum Island Sound in Rowley Massachusetts. The space for time study uses an intensive and comprehensive approach to compare low elevation, Spartina alterniflora marsh areas to higher elevation Spartina patens marsh areas. Birds were observed using timed interval observations, with one sampling bout per tide per site. Other related data files include: HTL-RO-ST-MAR-Sites, HTL-RO-ST-MAR-Biomass, HTL-RO-ST-MAR-Quads, HTL-RO-ST-MAR-Sediments, HTL-RO-ST-MAR-Bites, HTL-RO-ST-MAR-Sticky, HTL-RO-ST-MAR-Decomp, HTL-RO-ST-MAR-Traps, HTL-RO-ST-MAR-Deep_pitfalls
PIE LTER predation and herbivory rates associated with marsh sites used in space for time sea level rise study, Rowley, MA.
This dataset contains aggregated observations of predation and herbivory rates on tethered bait in each quadrat of the space for time substitution observations in salt marsh sites in Rowley and Newbury, MA.
Supplementary material to the masters thesis: NUTS-3 Regionalization of Industrial Load Shifting Potential in Germany using a Time-Resolved Model
<p>This is the supplementary material to the masters thesis:</p> <p>"NUTS-3 Regionalization of Industrial Load Shifting Potential in Germany using a Time-Resolved Model"</p> <p><strong>LICENSE</strong></p> <p>All output data provided is under Creative Commons Attribution 4.0 International Public License. All Python scripts provided are under Apache License, Version 2.0. Refer to the ‘Input data documentation’ file for source and data license information for the input data. For license information, refer to the LICENSE files.</p> <p><strong>DATASET DESCRIPTION</strong></p> <p>The supplementary material is organized into four different subdirectories:</p> <ul> <li>The subdirectory ‘Industrial processes’ contains the input data, Python scripts, and output data for the estimation of NUTS-3 load shifting potential of suitable electrically powered industrial processes (cement milling, mechanical pulping, paper production, air separation).</li> <li>The subdirectory ‘Process heat’ contains the input data, Python scripts, and output data for the estimation of NUTS-3 load shifting potential of industrial process heat applications that are powered by electricity.</li> <li>The subdirectory ‘Future projections’ contains the input data, Python scripts, and output data for the estimation of NUTS-0 annual average industrial processes load shifting potential in the future up until 2050.</li> <li>The subdirectory ‘Other tables for reference’ contains data tables that are not used as input data to the Python scripts, but which may serve as useful further reference for the reader. These tables are the original or intermediate tables from which the input data tables were created.</li> </ul> <p>For more information refer to the README file.</p> <p>For a detailed description of the approach developed by the author, the input data used and the generated results, refer to the masters thesis "NUTS-3 Regionalization of Industrial Load Shifting Potential in Germany using a Time-Resolved Model", available here: <a href="https://elib.dlr.de/134116/">https://elib.dlr.de/134116/</a></p> <p>In case of questions please contact: bruno.schyska@dlr.de or wilko.heitkoetter@dlr.de</p> <p> </p>
plan4res - public dataset for case study 1 part MIM-1: time series used for multi-modal investment pathway modelling
<p>Public data set which is used within the plan4res project for performing case study 1 "Multi-modal European energy concept for achiving COP21" - Multi-modal Investment modelling (MIM) Part 1: Time series for the reference year 2015</p> <p>The related documentation is included in plan4res' deliverable D4.5 chapter 3.2 (see 10.5281/zenodo.3785010) </p> <p>The data set includes the following data:</p> <p>a) characteristic annual load profiles for large industrial heat demand for chemical, iron & steel, food & beverage and pulp & paper industries for the reference year 2015</p> <p>HOTMAPS__TD_OUT_D_CHEM__20200608T160653__20200422T120000Z__v01.csv <br> HOTMAPS__TD_OUT_D_FOOD__20200608T160724__20200422T120000Z__v01.csv <br> HOTMAPS__TD_OUT_D_IRON__20200608T160705__20200422T120000Z__v01.csv HOTMAPS__TD_OUT_D_PAPER__20200608T160715__20200422T120000Z__v01.csv </p> <p>b) characteristic demand profiles for road-side car passenger transport and availability of cars for charging while (home) parking for the reference year 2015 </p> <p>SIEMENS__TD_OUT_D_RoadCar__20200608T160627__20200401T120000Z__v01.csv SIEMENS__TD_CAP_CarPark__20200608T160637__20200401T120000Z__v01.csv </p> <p>c) load profiles for exogeneous demand of electricity for the reference year 2015. The exogenous demand includes all electricity consumptions not explicitly modeled within MIM modeling.</p> <p>HRE4__TD_OUT_ElectricityExo__20200608T160732__20200401T120000Z__v01.csv </p> <p>c) regionally resolved demand profiles for (individual) space heating and space cooling for the reference year 2015</p> <p>HRE4__TRD_CAP_Cool_2015__20200608T160051__20200401T120000Z__v01.csv <br> HRE4__TRD_CAP_HeatInd_2015__20200608T155849__20200401T120000Z__v01.csv</p> <p>d) regionally resolved generation profiles of electricity from photovoltaic, wind onshore, wind offshore, hydro run-of-river, and for heat generation from solar thermal for the reference year 2015</p> <p>NINJA__TRD_CAP_PV_2015__20200608T160440__20191104T120000Z__v01.csv <br> NINJA__TRD_CAP_WindOFF_2015__20200608T155422__20191104T120000Z__v01.csv <br> NINJA__TRD_CAP_WindON_2015__20200608T155251__20191104T120000Z__v01.csv HRE4__TRD_CAP_HydroRoR_2015__20200608T155550__20200401T120000Z__v01.csv <br> HRE4__TRD_CAP_SolarThermal_2015__20200608T155718__20200401T120000Z__v01.csv </p> <p>e) regionally resolved generation profile of electricity from wind offshore transformed in a way to represent potential capacity factors in future as stated by doi:10.2760/041705. Data based on reference year 2015</p> <p>SIEMENS__TRD_CAP_WindOFF_2040__20200608T155127__20200401T120000Z__v01.csv </p> <p>x) A list of geographical description of the zone hierarchy data used in MIM for the EU33 region set.:</p> <p>SIEMENS__ZoneHierarchy_MIM_EU33__20181231T120000Z___20200131T1200000Z__v001.csv </p> <p>Further info:</p> <p>Time series are based on historical data for the reference year 2015. </p> <p>Values are normalized over one reference year in a way that either the maximum = 1 (CAP) or the integral = 1 (OUT).</p> <p>All values are listed in arbitrary units. </p> <p>All country names are according to ISO 3166-1 alpha-2.</p>
R code for Snyder, Ellner, and Hooker, "Time and chance: using age partitioning to understand how luck drives variation in reproductive success"
<p>Over the course of individual lifetimes, luck usually explains a large fraction of the between- individual variation in lifespan or lifetime reproductive output (LRO) within a population, while variation in individual traits or "quality" explains much less. To understand how, where in the life cycle, and through which demographic processes luck trumps trait variation, we show how to partition by age the contributions of luck and trait variation to LRO variance, and how to quantify three distinct components of luck. We apply these tools to several empirical case studies.</p> <p>We find that luck swamps effects of trait variation at all ages, primarily due to randomness in individual state dynamics ("state trajectory luck"). Luck early in life is most important. Very early state trajectory luck generally determines whether or not an individual ever breeds, likely by ensuring that they are not dead or doomed quickly. Less early luck drives variation in success among those breeding at least once. Consequently, the importance of luck often has a sharp peak early in life, or two peaks. We suggest that ages/stages where the importance luck peaks are potential targets for interventions to benefit a population of concern, different from those identified by eigenvalue elasticity analysis.</p>
Data presented in: Walking Drosophila navigate complex plumes using stochastic decisions biased by the timing of odor encounters
<p>How insects navigate complex odor plumes, where the location and timing of odor packets are uncertain, remains unclear. Here, we imaged complex odor plumes simultaneously with freely-walking flies, quantifying how behavior is shaped by encounters with individual odor packets. We found that navigation was stochastic, and did not rely on the continuous modulation of speed or orientation. Instead, flies turned stochastically with stereotyped saccades, whose direction was biased upwind by the timing of prior odor encounters, while the magnitude and rate of saccades remained constant. Further, flies used the timing of odor encounters to modulate the transition rates between walks and stops. In more regular environments, flies continuously modulate speed and orientation, even though encounters can still occur randomly due to animal motion. We find that in less predictable environments, where encounters are random in both space and time, walking flies instead navigate with random walks biased by encounter timing.</p>
Data and code for: Time of night and moonlight structure vertical space use by insectivorous bats in a Neotropical rainforest: an acoustic monitoring study
<p>Abstract</p> <p>Previous research has shown diverse vertical space use by various taxa, highlighting the importance of forest canopy. Yet, we often fail to explore how this three-dimensional space use changes over time. Here we use canopy tower systems in French Guiana to monitor neotropical bat activity above and below the forest canopy throughout nine nights in the wet season. We show that different bats use both canopy and understory space differently, and that this can change throughout the night. We find that bats are overall more active in the canopy, but multiple species/acoustic complexes are more active in the understory. We also find that species that do not seem to prefer understory or canopy, when data are aggregated by night, do show temporally changing preferences in hourly activity. This work highlights the need to consider temporal axes in studies of space use, both throughout daily cycles and across seasons.</p>
Insights from empirical analyses and simulations on using multiple fossil calibrations with relaxed clocks to estimate divergence times
<p>Relaxed clock methods account for among-branch-rate-variation when estimating divergence times by inferring different rates for individual branches. In order to infer different rates for individual branches, important assumptions are required. This is because molecular sequence data does not provide direct information about rates, but instead provides direct information about the total number of substitutions along any branch, which is a product of the rate and time for that branch. Often, the assumptions required for estimating rates for individual branches depend heavily on the implementation of multiple fossil calibrations in a single phylogeny. Here, we show that the basis of these assumptions is often critically undermined. First, we highlight that the temporal distribution of the fossil record often violates key assumptions of methods that use multiple fossil calibrations with relaxed clocks. With respect to "node calibration" methods, this conclusion is based on our inference that different fossil calibrations are unlikely to reflect the relative ages of different clades. With respect to the fossilised-birth-death-process, this conclusion is based on our inference that the fossil recovery rate is often highly heterogeneous. We then demonstrate that methods of divergence time estimation that use multiple fossil calibrations are highly sensitive to assumptions about the fossil record and among-branch-rate-variation. Given the problems associated with these assumptions, our results highlight that using multiple fossil calibrations with relaxed clocks often does little to improve the accuracy of divergence time estimates.</p> <p> </p>
Multiple Sclerosis: Cerebral Circulation Time is prolonged and not correlated with expanded disability status scale (EDSS). A study using digital subtracted angiography
<p>Dataset used to study the relationship between cerebral circulation time (CCT) and some clinical evidences, e.g. expand disability status scale (EDSS), disease duration, age at onset,... CCT was measured through the digital subtraction angiography (DSA) technique. </p> <p>Statistical Parametric Mapping software (SPM, Wellcome Department of Cognitive Neurology, Institute of Neurology, University College London; http://www.fil.ion.ucl.ac.uk/spm/) and ad-hoc scripts developed in the MATLAB scientific computing environment (http://www.mathworks.com, MathWorks, MA, USA) were applied to valuate the lesion volume and brain volume in MS patients.</p>
Dataset for Anomaly Detection Using Inter-Arrival Curves for Real-time Systems
<p>The dataset shows the input files and detailed results for the experiments discussed in the paper. A README file provide more details on the data.</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.