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Data from: Can measurements of foraging behaviour predict variation in weight gains of free-ranging cattle?

Technologies are now available to continuously monitor livestock foraging behaviours, but it remains unclear whether such measurements can meaningfully inform livestock grazing management decisions. Empirical studies in extensive rangelands are needed to quantify relationships between short-term foraging behaviours (e.g. minutes to days) and longer-term measures of animal performance. The objective of this study was to examine whether four different ways of measuring daily foraging behaviour (grazing-bout duration, grazing time per day, velocity while grazing, and turn angle while grazing) were related to weight gain by free-ranging yearling steers grazing semiarid rangeland. These data include measurements interpreted from yearling steer outfitted with neck collars supporting a solar-powered device that measured GPS locations at 5 minute intervals and used an accelerometer to predict grazing activity at 4 second intervals. Average daily weight gains of steers are included as well as an estimate of standing forage biomass derived from the Harmonized Landsat-Sentinel remote-sensing product. These data support research to advance knowledge regarding the use of on-animal sensors that monitor foraging behaviour, which have the potential to transmit indicators to livestock managers in real time (e.g. daily). This approach can help inform decisions such as when to move animals among paddocks, or when to sell or transition animals from rangeland to confined feeding operations.

0
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Tags:
NP215accelerometeraverage daily gaincattle weight gainforage limitationgrazing bout durationgrazing velocitysemiarid rangelandshortgrass steppe
Formats:
CSV
United States Department of Agriculture10 months ago
EGS Collab Experiment 1: Continuous Active-Source Seismic Monitoring (CASSM) DataSource

The U.S. Department of Energy's Enhanced Geothermal System (EGS) Collab project aims to improve our understanding of hydraulic stimulations in crystalline rock for enhanced geothermal energy production through execution of intensely monitored meso-scale experiments. The first experiment was performed at the 4850 ft level of the Sanford Underground Research Facility (SURF), approximately 1.5 km below the surface at Lead, South Dakota. The data reported here were collected by the continuous active-source seismic monitoring (CASSM) system (Ajo-Franklin et al., 2011). This system was permanently installed in the testbed and consisted of 17 piezoelectric sources that were recorded by 2-12 channel hydrophone arrays, 18 3-C accelerometers, and 4 3-C geophones at a Nyquist frequency of 24kHz. The source array was activated in a repeated sequence of shots (each source fired 16 times and stacked into resultant waveforms) for the duration of the experiment (April 25, 2018 - March 7, 2019) with few exceptions. Please see the attached documents describing the source / receiver geometry. The data are available in both seg2 (.dat extension) and segy (.sgy extension) format. Each segy file contains multiple seg2 files.

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Tags:
Active SourceCASSMEGSEGS CollabExperiment 1ImagingMonitoringSURFSanford Underground Research FacilitySeismicaccelerometercontinuousenergyexperimentfracturinggeophonegeophysicsgeothermalhydraulichydrophonemeso scalestimulationwell instrumentation
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National Renewable Energy Laboratory (NREL)about 1 year ago
Sample Data from a Distributed Acoustic Sensing Experiment at Garner Valley, CaliforniaSource

In September 2013, an experiment using Distributed Acoustic Sensing (DAS) was conducted at Garner Valley, a test site of the University of California Santa Barbara (Lancelle et al., 2014). This submission includes one 45 kN shear shaker (called "large shaker" on the basemap) test for three different measurement systems. The shaker swept from a rest, up to 10 Hz, and back down to a rest over 60 seconds. Lancelle, C., N. Lord, H. Wang, D. Fratta, R. Nigbor, A. Chalari, R. Karaulanov, J. Baldwin, and E. Castongia (2014), Directivity and Sensitivity of Fiber-Optic Cable Measuring Ground Motion using a Distributed Acoustic Sensing Array (abstract # NS31C-3935), AGU Fall Meeting.

0
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Tags:
DASMapPoroTomoaccelerometercaliforniadistributed acoustic sensingfiber opticsfiber-opticgarner valleygeophonegeothermalposterproject summaryvibroseis
Formats:
PDFCSVsgydatHTMLhtml
National Renewable Energy Laboratory (NREL)about 1 year ago
University of Massachusetts Marine Renewable Energy Center Waverider Buoy DataSource

The compressed (.zip) file contains Datawell MK-III Directional Waverider binary and unpacked data files as well as a description of the data and manuals for the instrumentation. The data files are contained in the two directories within the zip file, "Apr_July_2012" and "Jun_Sept_2013". Time series and summary data were recorded in the buoy to binary files with extensions '.RDT' and '.SDT', respectively. These are located in the subdirectories 'Data_Raw' in each of the top-level deployment directories. '.RDT' files contain 3 days of time series (at 1.28 Hz) in 30 minute "bursts". Each '.SDT' file contains summary statistics for the month indicated computed at half-hour intervals for each burst. Each deployment directory also contains a description (in 'File.list') of the Datawell binary data files, and a figure ('Hs_vs_yearday') showing the significant wave height associated with each .RDT file (decoded from the filename). The corresponding unpacked Matlab .mat files are contained in the subdirectories 'Data_Mat'. These files have the extension '.mat' but use the root filename of the source .RDT and .SDT files.

0
No licence known
Tags:
HydrokineticMHKMarineMarine Renewable Energy CenterMarthaMarthasMatlabNantucketNantucket ShoalsRDTRhode IslandSDTVineyardWaveriderWoods Hole Oceanographic Institutionaccelerometeraccelerometer databinarybinary databouy databuoy orientationburstcharacterizationdatadataloggerdatawelldirectional spreadenergyfrequencygeospatial datainstrumentationmagnetic field inclinationmean directionnormalized height power spectrumoceanoceanographicrawraw dataresourcesignificant wave heightspectral bandwidthtime seriesunpackedunpacked datawave datawave height spectrum
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National Renewable Energy Laboratory (NREL)about 1 year ago