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CMY01 Mycorrhizal colonization and plant community responses to long-term suppression of Mycorrhizal Fungi
Twenty replicate permanent 2x2 m plots were established in early 1991 along a randomly located transect, with a 2m space between each plot, on the following watersheds: 1B, 1D, annually burned HQB, 10B, 20D and infrequently burned HQB. Ten of the plots were randomly assigned as long-term mycorrhizal suppression plots. In each of these plots, AM fungi were suppressed by the application of the fungicide benomyl as a soil drench (7.5 liters per plot) at the rate of 1.25 g/m2 (active ingredient). The mycorrhizal suppression plots were treated biweekly throughout each growing season (April through October) beginning in 1991. The control plots each received no fungicide, but an equivalent volume of water (7.5 liters) was applied biweekly. To evaluate the effectiveness of the fungicide, three soil cores (2.5 cm diameter x 14 cm deep) were removed from both fungicide-treated and control plots each October throughout the study. Roots were extracted from the soil, washed free of soil, stained in trypan blue (Phillips and Hayman, 1970), and examined microscopically to assess percentage root colonization by mycorrhizal fungi using a Petri dish scored in 1-cm squares (Daniels et al.1981).
El Verde long-term invertebrate data - Luquillo Forest Dynamics Plot (LFDP)
The data set consists of 44 files: (1) abundance data for the walking stick, Lamponius portoricensis, (2) estimates of abundance (Minimum Number Known Alive) for 17 species of terrestrial snails, and (3) 42 files containing data on size and mark-recapture estimates of population size for the snails Caracolus caracolla and Nenia tridens from the Wet Season of 1995 to the Wet Season of 2019 (no dry season data for 1995 or after 2012). Note: MNKA estimates are not always identical to the number of individuals indicated in the Mark-Recapture data, because some individuals (e.g., those that were lost before being marked) had to be excluded from calculations for Mark-Recapture estimates of abundance. Note, no data were collected in 2020 or 2021 due to the COVID-19 pandemic. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
Long-Term Elevation Plots (LTEP) (Altitudinal transects vegetation data along three rivers in the Luquillo Experimental Forest)
The composition of plant communities changes with elevation in the Luquillo Experimental Forest (LEF). The goal of this project is to document the patterns of these changes, and in particular, to determine whether the distributions of individual species are independent of one another, or whether they are related, in either a congruent or a hierarchical manner. Thirty-two permanent vegetation plots, each 50m by 20m are being established in the LEF, with 5 plots along the Icacos river, 11 along the Mamayes river and 16 along the Sonadora stream. The plots were established at every 100m in elevation, starting at 200m above sea level. All woody, free-standing stems greater than 1cm dbh were marked, identified and mapped into 5x5 subquadrats. We anticipated that gradient analysis will show whether the distributions of species are coincident or independent, enabling us to evaluate whether separate, genuine plant communities exist in the LEF. Because the plots are permanent, we also expected that they allow us to better evaluate how different vegetation types, at different elevations, respond to large scale disturbances, especially hurricanes. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
USGS Long-term daily streamflow data at several LEF locations
Vist the USGS water data center (https://waterdata.usgs.gov) for more information on these discharge and other data collected in Northeastern Puerto Rico. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
Canopy invertebrate near El Verde and the Long Term Elevation Plots
We study long-term responses of insects and other arthropods to various disturbances and environmental changes, as well as important roles in ecosystem processes. Five tree species in 1991, six during 1992-1995, and seven since 1997 were selected to represent early and late successional forests at El Verde. These trees were sampled in both gap and non-gap plots resulting from Hurricane Hugo. During the past 27 years, these plots have been subjected to multiple disturbances, including Hurricane Georges in 1998 and major droughts in 1994, 1997 and 2002, in addition to several minor hurricanes and droughts. Each of these disturbances has influenced the arthropod community. This project is ongoing. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
MCR LTER: Coral Reef: Long-Term Coral Population and Community Dynamics: Annual Island Wide Coral Demography Survey 2011 ongoing
Demographic performance (recruitment, growth, and survival) are quantified annually for multiple individual colonies of the three most common genera (Acropora, Pocillopora, Porites) at both backreef and forereef sites. Each coral was tagged in 2011 and subsequently sampled again in 2012 to track colony growth and mortality dynamics. However, since 2013, investigators have transitioned to identifying coral through detailed mapping methodology and will continue to identify corals using this method in the subsequent years. The mapping system developed in 2013 provides data appropriate for detailed demographic study of coral on varying spatial scales around the island. This material is based upon work supported by the U.S. National Science Foundation under Grant No. OCE 16-37396 (and earlier awards) as well as a generous gift from the Gordon and Betty Moore Foundation. Research was completed under permits issued by the French Polynesian Government (Délégation à la Recherche) and the Haut-commissariat de la République en Polynésie Francaise (DTRT) (Protocole d'Accueil 2005-2022). This work represents a contribution of the Moorea Coral Reef (MCR) LTER Site.
Zooplankton and micronekton abundance using an Isaacs-Kidd Midwater trawl on Northeast U.S. Shelf Long Term Ecological Research (NES-LTER) Transect cruises, ongoing since 2023
During Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) Transect cruises, acoustic backscattering layers were identified using multifrequency echosounders and were targeted for collection of zooplankton and micronekton using an Isaacs-Kidd Midwater Trawl. On each cruise, trawling was conducted at at least three stations, including the one at the shelfbreak front, one inshore of the front, and one offshore of the front. The catches from the trawls were preserved on ship and later identified to the lowest possible taxonomic level using a dissecting microscope. Each identified taxon was counted to provide net total abundance by taxon. Trawling was initiated in spring 2023 and is ongoing.
Lake Mendota long term water quality model
The data are associated with the following manuscript: Hanson, P. C., Ladwig, R., Buelo, C., Albright, E. A., Delany, A. D., & Carey, C. (2023). Legacy phosphorus and ecosystem memory control future water quality in a eutrophic lake. Lake water and ice observational data and lake bathymetry are from the North Temperate Lakes Long Term Ecological Research program. Brief abstract of the work: To investigate how water quality in Lake Mendota might respond to nutrient pollution reduction, we used computer models to simulate the elimination of phosphorus inputs from the catchment and track water quality change. The data herein are used to drive and calibrate the model. In addition, model code and simulation output are included as "other entities."
PIE LTER locations of vegetation transects in Rowley salt marsh sites used for measuring long term changes.
A description of transects used for long term studies of marsh vegetation in Rowley, MA. Four sites ((12 transects) were originally set up to study the impact of salt marsh haying. Two of these sites (labeled McH and EPH) were regularly hayed until 2002. The other two (PUH and CC) were reference sites. Two additional sites labeled RM (8 transects) were originally set up to track invasion by Phragmites australis.
Nassarius obsoletus (Ilyanassa obsoleta) density measurements for Rowley River tidal creeks associated with long term fertilization experiments, Rowley and Ipswich, MA.
Nassarius obsoletus (Ilyanassa obsoletus) length and biomass measurements for Rowley River tidal creeks associated with long term fertilization experiments, Rowley and Ipswich, MA. The TIDE project aims to simulate eutrophication on a large scale by the addition of NO3- aiming to reach 70μM concentrations from May to September every year during the growing season. This fertilization of the marsh has been going on at Sweeney Creek since the 2004 growing season through 2016 and at Clubhead Creek in 2005 and from 2009 till 2016.
Nassarius obsoletus (Ilyanassa obsoleta) length and biomass measurements for Rowley River tidal creeks associated with long term fertilization experiments, Rowley and Ipswich, MA.
Nassarius obsoletus (Ilyanassa obsoleta) length and biomass measurements for Rowley River tidal creeks associated with long term fertilization experiments, Rowley and Ipswich, MA. The TIDE project aims to simulate eutrophication on a large scale by the addition of NO3- aiming to reach 70μM concentrations from May to September every year during the growing season. This fertilization of the marsh has been going on at Sweeney Creek since the 2004 growing season through 2014 and at Clubhead Creek in 2005 and from 2009 till 2014.
Mummichog (Fundulus heteroclitus) counts and gut content analysis from lift trap transect collections along Rowley River tidal creeks associated with long term fertilization experiments, Rowley, MA.
The lift traps were used to capture mummichogs accessing the high marsh platform. Mummichogs were collected to study the effect of marsh-edge geomorphology on mummichog distribution and foraging. The TIDE project aims to simulate eutrophication on a large scale by the addition of NO3- aiming to reach 70μM concentrations from May to September every year during the growing season. This fertilization of the marsh has been going on at Sweeney Creek since the 2004 growing season through 2016 and at Clubhead Creek in 2005 and from 2009 till 2016. Years 2017-2020 are enrichment recovery years.
Mummichog (Fundulus heteroclitus) gut content analysis from Breder trap transect collections in tidal creeks associated with long term fertilization experiments, Rowley, MA.
At PIE, mummichog (Fundulus heteroclitus) use the spring-cycle high tides to access the flooded high marsh platform and eat invertebrate prey, coupling the high marsh and aquatic creek food webs by gathering energy produced on the high marsh and making it available to the aquatic food web. Changes in the geomorphology of saltmarsh creek edges greatly influence the survival, biomass, and resource use of mummichog populations. Here we use gut content analysis assess the diet of mummichog on the high marsh platform during a flooding spring-cycle tide in July 2018 across 3 PIE creeks known to present different geomorphologic patterns in their low marsh zones. These data allow us to quantify the amount of terrestrial invertebrate prey mummichog consume on a single flooding tide and determine the impact altered low marsh geomorphology has on the trophic relationships in PIE food webs. These mummichog were captured in Breder traps; information about the consumer communities captured in these traps was recorded separately (LTE-TIDE-BrederTrap-Demographics). These data were included in part of the study “Habitat decoupling via saltmarsh creek geomorphology alters connection between spatially-coupled food webs” (Lesser et al. 2020) and were a portion of an MBL REU project.
Demographics of high marsh consumers from Breder trap transect collections in tidal creeks associated with long term fertilization experiments, Rowley, MA
At PIE, mummichog (Fundulus heteroclitus) use the spring-cycle high tides to access the flooded high marsh platform and eat invertebrate prey, coupling the high marsh and aquatic creek food webs by gathering energy produced on the high marsh and making it available to the aquatic food web. Changes in the geomorphology of saltmarsh creek edges greatly influence the survival, biomass, and resource use of mummichog populations. Here, we capture animals using Breder traps to quantify the communities accessing the high marsh at night during one of these high tides in July 2018 across 3 PIE creeks known to present different geomorphologic patterns in their low marsh zones. These data can be used for the assessment of the impact of low marsh geomorphology on consumer communities in PIE marshes. Mummichog captured in these Breder traps were further analyzed for gut content (LTE-TIDE-BrederTrap-GutContents). These data were included in part of the study “Habitat decoupling via saltmarsh creek geomorphology alters connection between spatially-coupled food webs” (Lesser et al. 2020) and were a portion of an MBL REU project.
Mummichog (Fundulus heteroclitus) caloric value analysis from various collections along Rowley River tidal creeks associated with long term fertilization experiments, Rowley, MA.
At PIE, mummichog (Fundulus heteroclitus) use the spring-cycle high tides to access the flooded high marsh platform and eat invertebrate prey, coupling the high marsh and aquatic creek food webs by gathering energy produced on the high marsh and making it available to the aquatic food web. Changes in the geomorphology of saltmarsh creek edges greatly influence the survival, biomass, and resource use of mummichog populations. Here, we use bomb calorimetry to assess individual mummichog caloric content per gram of biomass at 4 PIE creeks known to present different geomorphologic patterns in their low marsh zones. These data can be used for the assessment of the impact of low marsh geomorphology on mummichog caloric content and energy production in PIE food webs. These data were included as part of two studies “Habitat decoupling via saltmarsh creek geomorphology alters connection between spatially-coupled food webs” (Lesser et al. 2020) and “Cross-habitat access modifies the ‘trophic relay’ in New England saltmarsh ecosystems” (Lesser et al. 2021).
Invert species counts and density along transects on the high marsh along Rowley River tidal creeks associated with long term fertilization experiments, Rowley, MA.
At PIE, mummichog (Fundulus heteroclitus) use the spring-cycle high tides to access the flooded high marsh platform and consume invertebrate prey. Invertebrate surveys were conducted before and after spring tides that flooded the high marsh area to determine the effect of mummichog predation that occurs on the high marsh during the flood events and to assess the impact of low marsh geomorphology on top-down control by mummichog. These data were included in part of the study "Cross-habitat access modifies the ‘trophic relay’ in New England saltmarsh ecosystems” (Lesser et al. 2021) as well as a part of a NEU Three Seas Master's thesis.
Stable isotope values for organisms collected in the Rowley River tidal creeks associated with long term fertilization experiments, Rowley, MA.
To assess differences in trophic relationships and enerygy transfer related to long term fertilization of tidal creeks (TIDE Project: https://thetideproject.org/), organisms including primary producers, invertebrates, and fish were sampled and analyzed for stable isotopes of nitrogen (δ14N) , carbon (δ13C), and sulfur (δ34S). Collections were made during summers from 2000-2018 from reference and nutrient-enriched branches of 4 tidal creeks.
Long-term dynamics of soil organic matter and aboveground net primary production in a Chihuahuan Desert Grassland at the Sevilleta National Wildlife Refuge, New Mexico (1989-2014)
Drylands contain a third of the organic carbon stored in global soils; however, the long-term dynamics of soil organic carbon and soil organic matter (SOM) in drylands remain poorly understood relative to dynamics of the vegetation carbon pool. We examined long-term patterns in SOM against both climate and prescribed fire in a Chihuahuan Desert grassland in central New Mexico, USA. SOM was measured each spring and fall for 25 years (1989–2014) in unburned desert grassland and from 2003 to 2014 following a prescribed fire. SOM concentration from 0-20 cm depth did not show a clear long-term trend but fluctuated seasonally at both burned and unburned sites, ranging from a minimum of 0.9% to a maximum of 3.3%. SOM concentration declined nonlinearly in wet seasons and peaked in dry seasons. These results not only contrast with the positive relationships between aboveground net primary production and precipitation for this region, but also with previous reports of greater SOM in wetter sites across drylands globally, suggesting that space is not a good substitute for time in predicting the dynamics of dryland SOM. We suggest that declines in SOM in wet periods are caused by increased soil respiration, runoff, leaching, and soil erosion. In addition to tracking natural variability in climate, SOM concentration also decreased by 14% following prescribed fire, a response that magnified over time and has persisted for nearly a decade due to the slow recovery of primary production. Our results document the surprisingly dynamic nature of soil organic matter and its high sensitivity to climate and fire in this dryland ecosystem.
Long-Term Tracing of Indoor Solar Harvesting
<p><strong>Dataset Information</strong></p> <p>This dataset presents long-term term indoor solar harvesting traces and jointly monitored with the ambient conditions. The data is recorded at 6 indoor positions with diverse characteristics at our institute at ETH Zurich in Zurich, Switzerland.</p> <p>The data is collected with a measurement platform [3] consisting of a solar panel (AM-5412) connected to a bq25505 energy harvesting chip that stores the harvested energy in a virtual battery circuit. Two TSL45315 light sensors placed on opposite sides of the solar panel monitor the illuminance level and a BME280 sensor logs ambient conditions like temperature, humidity and air pressure.</p> <p>The dataset contains the measurement of the energy flow at the input and the output of the bq25505 harvesting circuit, as well as the illuminance, temperature, humidity and air pressure measurements of the ambient sensors. The following timestamped data columns are available in the raw measurement format, as well as preprocessed and filtered HDF5 datasets:</p> <ul> <li><code>V_in</code> - Converter input/solar panel output voltage, in volt</li> <li><code>I_in</code> - Converter input/solar panel output current, in ampere</li> <li><code>V_bat</code> - Battery voltage (emulated through circuit), in volt</li> <li><code>I_bat</code> - Net Battery current, in/out flowing current, in ampere</li> <li><code>Ev_left</code> - Illuminance left of solar panel, in lux</li> <li><code>Ev_right</code> - Illuminance left of solar panel, in lux</li> <li><code>P_amb</code> - Ambient air pressure, in pascal</li> <li><code>RH_amb</code> - Ambient relative humidity, unit-less between 0 and 1</li> <li><code>T_amb</code> - Ambient temperature, in centigrade Celsius</li> </ul> <p>The following publication presents and overview of the dataset and more details on the deployment used for data collection. A copy of the abstract is included in this dataset, see the file <code>abstract.pdf</code>.</p> <blockquote> <p>L. Sigrist, A. Gomez, and L. Thiele. "Dataset: Tracing Indoor Solar Harvesting." In Proceedings of the 2nd Workshop on Data Acquisition To Analysis (DATA '19), 2019.</p> </blockquote> <p><strong>Folder Structure and Files</strong></p> <ul> <li><code>processed/</code> - This folder holds the imported, merged and filtered datasets of the power and sensor measurements. The datasets are stored in HDF5 format and split by measurement position <code>posXX</code> and and power and ambient sensor measurements. The files belonging to this folder are contained in archives named <code>yyyy_mm_processed.tar</code>, where <code>yyyy</code> and <code>mm</code> represent the year and month the data was published. A separate file lists the exact content of each archive (see below).</li> <li><code>raw/</code> - This folder holds the raw measurement files recorded with the RocketLogger [1, 2] and using the measurement platform available at [3]. The files belonging to this folder are contained in archives named <code>yyyy_mm_raw.tar</code>, where <code>yyyy</code> and <code>mm</code>represent the year and month the data was published. A separate file lists the exact content of each archive (see below).</li> <li><code>LICENSE</code> - License information for the dataset.</li> <li><code>README.md</code> - The README file containing this information.</li> <li><code>abstract.pdf</code> - A copy of the above mentioned abstract submitted to the DATA '19 Workshop, introducing this dataset and the deployment used to collect it.</li> <li><code>raw_import.ipynb</code> [<a href="https://nbviewer.jupyter.org/urls/zenodo.org/record/3715472/files/raw_import.ipynb">open in nbviewer</a>] - Jupyter Python notebook to import, merge, and filter the raw dataset from the <code>raw/</code> folder. This is the exact code used to generate the processed dataset and store it in the HDF5 format in the <code>processed/</code>folder.</li> <li><code>raw_preview.ipynb</code> [<a href="https://nbviewer.jupyter.org/urls/zenodo.org/record/3715472/files/raw_preview.ipynb">open in nbviewer</a>] - This Jupyter Python notebook imports the raw dataset directly and plots a preview of the full power trace for all measurement positions.</li> <li><code>processing_python.ipynb</code> [<a href="https://nbviewer.jupyter.org/urls/zenodo.org/record/3715472/files/processing_python.ipynb">open in nbviewer</a>] - Jupyter Python notebook demonstrating the import and use of the processed dataset in Python. Calculates column-wise statistics, includes more detailed power plots and the simple energy predictor performance comparison included in the abstract.</li> <li><code>processing_r.ipynb</code> [<a href="https://nbviewer.jupyter.org/urls/zenodo.org/record/3715472/files/processing_r.ipynb">open in nbviewer</a>] - Jupyter R notebook demonstrating the import and use of the processed dataset in R. Calculates column-wise statistics and extracts and plots the energy harvesting conversion efficiency included in the abstract. Furthermore, the harvested power is analyzed as a function of the ambient light level.</li> </ul> <p><strong>Dataset File Lists</strong></p> <p><em>Processed Dataset Files</em></p> <p>The list of the processed datasets included in the <code>yyyy_mm_processed.tar</code> archive is provided in <code>yyyy_mm_processed.files.md</code>. The markdown formatted table lists the name of all files, their size in bytes, as well as the SHA-256 sums.</p> <p><em>Raw Dataset Files</em></p> <p>A list of the raw measurement files included in the <code>yyyy_mm_raw.tar</code> archive(s) is provided in <code>yyyy_mm_raw.files.md</code>. The markdown formatted table lists the name of all files, their size in bytes, as well as the SHA-256 sums.</p> <p><strong>Dataset Revisions</strong></p> <p><em>v1.0 (2019-08-03)</em></p> <p>Initial release.<br> Includes the data collected from 2017-07-27 to 2019-08-01. The dataset archive files related to this revision are <code>2019_08_raw.tar</code> and <code>2019_08_processed.tar</code>.<br> For position <em>pos06</em>, the measurements from 2018-01-06 00:00:00 to 2018-01-10 00:00:00 are filtered (data inconsistency in file <code>indoor1_p27.rld</code>).</p> <p><em>v1.1 (2019-09-09)</em></p> <p>Revision of the processed dataset v1.0 and addition of the final dataset abstract.<br> Updated processing scripts reduce the timestamp drift in the processed dataset, the archive <code>2019_08_processed.tar</code> has been replaced.<br> For position <em>pos06</em>, the measurements from 2018-01-06 16:00:00 to 2018-01-10 00:00:00 are filtered (<code>indoor1_p27.rld</code> data inconsistency).</p> <p><em>v2.0 (2020-03-20)</em></p> <p>Addition of new data.<br> Includes the raw data collected from 2019-08-01 to 2019-03-16. The processed data is updated with full coverage from 2017-07-27 to 2019-03-16. The dataset archive files related to this revision are <code>2020_03_raw.tar</code> and <code>2020_03_processed.tar</code>.</p> <p><strong>Dataset Authors, Copyright and License</strong></p> <ul> <li>Authors: Lukas Sigrist, Andres Gomez, and Lothar Thiele</li> <li>Contact: Lukas Sigrist (<a href="mailto:lukas.sigrist@tik.ee.ethz.ch">lukas.sigrist@tik.ee.ethz.ch</a>)</li> <li>Copyright: (c) 2017-2019, ETH Zurich, Computer Engineering Group</li> <li>License: Creative Commons Attribution 4.0 International License (<a href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</a>)</li> </ul> <p><strong>References</strong></p> <p>[1] L. Sigrist, A. Gomez, R. Lim, S. Lippuner, M. Leubin, and L. Thiele. <em>Measurement and validation of energy harvesting IoT devices.</em> In Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017.</p> <p>[2] ETH Zurich, Computer Engineering Group. RocketLogger Project Website, <a href="https://rocketlogger.ethz.ch/">https://rocketlogger.ethz.ch/</a>.</p> <p>[3] L. Sigrist. <em>Solar Harvesting and Ambient Tracing Platform</em>, 2019. <a href="https://gitlab.ethz.ch/tec/public/employees/sigristl/harvesting_tracing">https://gitlab.ethz.ch/tec/public/employees/sigristl/harvesting_tracing</a></p>
Standing Balance Experiment with Long Duration Random Pulses Perturbation
<p>Standing balance experiment and the measured data-set are fundamental for identifying postural feedback controllers. As the generalized feedback controllers can only be identified from long duration balance data (under random external perturbations), a standing balance experiment is conducted and the long duration motion data was recorded. The data-set includes the perturbation reaction data from eight subjects. Each subject performed four experiment trials, including two quiet standing and two perturbed trials. Each trial lasted five minutes. A total of 80 minutes quiet standing and 80 minutes perturbed standing data are included in this data-set. Recorded information including three dimensional trajectories of thirty-two markers (27 on subjects' trunk and legs and 5 on the treadmill frame), six dimensional ground reaction forces, and nine Electromyography signals (EMGs, on subjects' right leg). In addition, joint angles and torques were calculated using a human body model and inverse dynamics. Basic statistical analysis of the data is also included.</p> <p>Measured raw data for each subject in each experimental trial includes three files:</p> <ol> <li>Mocapxxxx.txt: contains motion capture marker data, ground reaction force, and 76 analog channels. Data was recorded at 100 Hz sampling rate.</li> <li>Mocapxxxx_Motion Analysis_analog.txt: contains 76 high sampling rate (1000Hz) analog channels' data. Analog data is consisted of the analog singal from the froce sensor on the treadmill, EMG signals in the Delsys EMG sensors, and 3 axises acceeleration signals of the Delsys EMG sensors.</li> <li>Recordxxxx.txt: contains the sway motion data of treadmill and the three-axis acceleration data of two Xsens MTi-10 series sensors.</li> </ol> <p>Measured raw data also includes two files of the unloaded trial, which is used for the inertia compensation.</p> <ol> <li>Mocap0000.txt: contains motion capture marker data (5 markers on the treadmill frame) and ground reaction forces.</li> <li>Record0000.txt: contains the treadmill sway motion data and the acceleration data (three-axis) of two Xsens MTi-10 series sensors.</li> </ol> <p>Processed data of each subject in each experimental trial contains four files:</p> <ol> <li>Mocapxxxx.txt: contains the gap filled motion capture marker data and the inertia compensated ground reaction force data.</li> <li>Motionxxxx.txt: contains the calculated the trajectories of three joints' (hip, knee, and ankle) angles, angular velocities, moments, and joint contact forces.</li> <li>Data_infoxxxx.txt: contains the quality of recorded raw marker data (percentage and biggest duration of missing marker data), and the percentage of removed inertia artifacts in ground reaction forces</li> <li>MotionAnalysis.fig: shows the mean and standard deviation of three joints' trajectories in four experimental trials.</li> </ol> <p>There are two more plots in the processed data folder which shows the joint motion/moment and the raw/compensated ground reaction forces of one example experimental trial (subject 07 trial 03).</p> <p>The processed data was generated using the code in the 'Processing_Code' folder. The code was wrote using Matlab and the main function is "Data_Processing_Main.m"</p> <p>More details of the standing balance experiment can be found in the document 'Standing_Balance_Experiment_with_Long_Duration_Random_Pulses_Perturbation.pdf'</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.