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793 results for “Startes”
A multi-year DAILY weather file for the Toolik Field Station at Toolik Lake, Alaska starting 1988 to present.
A multi-year DAILY weather file for the Arctic Tundra Long-Term Ecological Research (LTER) site at Toolik Lake, AK. Included are daily averages and/or maximums and minimums of air, wind speed, soil temperature, and sum of global radiation and precipitation. In 2008 Toolik Field Station took over maintenance of the main weather station. See http://toolik.alaska.edu/edc/index.php for current weather data. In addition to the main weather station the Arctic LTER maintains several stations that collect data on the experimental plots.
Trellis-forming stems of a tropical liana Condylocarpon guianense (Apocynaceae): a plant-made safety net constructed by simple "start-stop" development
<p>Data supporting article describing mechanical and structural organisation of a climin g plant trellis system sin the tropical rainforest of French Guiana</p> <p>Tropical vines and lianas have evolved mechanisms to avoid mechanical damage during their climbing life histories. We explore the mechanical properties and stem development of a tropical climber that develops trellises in tropical rain forest canopies. We measured the young stems of <em>Condylocarpon guianensis</em> (Apocynaceae) that construct complex trellises via self-supporting shoots, attached stems and unattached pendulous stems. The results suggest that in this species there is a size (stem diameter) and developmental threshold at which plant shoots will make the developmental transition from stiff young shoots to later flexible stem properties. Shoots that do not find a support remain stiff, becoming pendulous and retaining numerous leaves. The formation of a second TYPE II (lianoid) wood is triggered by attachment, guaranteeing increased flexibility of light-structured shoots that transition from self-supporting searchers to inter-connected net-like trellis components. The results suggest that this species shows a “hard-wired” development that limits self-supporting growth among the slender stems that make up a liana trellis. The strategy is linked to a stem-twining climbing mode and promotes a rapid transition to flexible trellis elements in cluttered densely branched tropical forest habitats. These are situations that are prone to mechanical perturbation via wind action, tree falls and branch movements. The findings suggest that some twining lianas are mechanically fine-tuned to produce trellises in specific habitats. Trellis building is carried out by young shoots that can perform very different functions via subtle development changes in order to ensure a safe space occupation of the liana canopy.</p>
Missouri reservoir profile data including depth, temperature, oxygen, photopigments, conductivity, pH, turbidity, and oxidative-reductive potential starting in 2023
This dataset of annual limnological profiles starts in 2023 and is from reservoirs in the state of Missouri (MO) in the USA collected by the University of Missouri Limnology Lab. Physical parameters derived from sensors include temperature and oxygen with depth. Sondes used were Yellow Springs Instruments (YSI) EXO3s; profiles include a range of physical, chemical, and biological parameters including depth, conductivity, pH, oxidative-reductive potential (ORP), chlorophyll a, phycocyanin (PC), and turbidity. After May 2024, the turbidity sensor was replaced with a phycoerythrin (PE) sensor. Most of the profiles were collected during the summer months (May-September) when the reservoirs were thermally stratified, but a few were taken during the rest of the year (October-April). The majority of profiles were taken at the deepest point in the reservoir directly up-reservoir of the dam. Sampling was conducted from a boat. The bulk of the data come from the Statewide Lake Assessment Project (SLAP), funded by the Missouri Department of Natural Resources. The profiles are divided into single files for each year. This data has been quality controlled for basic errors and any data outside of normal factory issued sensor ranges.
CCE LTER process cruise, in the California Current region, event log records including date, time, position and activity for use in post-cruise data integration based on co-sampling indexes. From 2006 to 2019 CCE LTER used a locally developed event logging system. During P2107, CCE LTER started to utilize the R2R Event Logger on UNOL ships, 2006 - 2024 (ongoing).
The event logger program developed and maintained by the California Cooperative Oceanic Fisheries Investigations, SIO, program is used aboard CCE LTER process cruises to create indexes with temporal, spatial and activity information for post-cruise data integration. The event log is configured aboard the ship for the recording of sampling events by both ship crew personnel on the bridge, and research personnel in the lab. The event log is processed post-cruise to correct for various errors.
Canopy height profile starting 1992, 1994 and 1996 of the Luquillo Forest Dynamics Plot (LFDP), Puerto Rico
File LFDP_canopy contain the canopy heights for the Luquillo forest Dynamics plot. The first measurement started in 1992, and it was planned to measure the canopy height profile every 2 years. So far censuses starting in 1992, 1994, and 1996 have been completed. In the 1992 census the canopy height profile at points along the East and North limits of the plot were not included. In 1994 and 1996 these extra points were assessed. The National Science Foundation requires that data from projects it funds are posted on the web two years after any data set has been organized and "cleaned". The data from each census of the LFDP will be updated at intervals as each survey of the LFDP shows errors in the previous data collection. After posting on the web, researchers who are not part of the project are then welcome to use the data. Given the enormous amount of time, effort and resources required to manage the LFDP, obtain these data, and ensure data accuracy, LFDP Principal Investigators request that researchers intending to use this data comply with the requests below. Through complying with these requests we can ensure that the data are interpreted correctly, analyses are not repeated unnecessarily, beneficial collaboration between users is promoted and the Principle Investigators investment in this project is protected. Submit to the LFDP PIs a short (1 page) description of how you intend to use the data; · Invite LFDP PIs to be co-authors on any publication that uses the data in a substantial way (some PIs may decline and other LFDP scientists may need to be included); If the LFDP PIs are not co-authors, send the PIs a draft of any paper using LFDP data, so that the PIs may comment upon it; In the methods section of any publication using LFDP data, describe that data as coming from the "Luquillo Forest Dynamics Plot, part of the Luquillo Experimental Forest Long-Term Ecological Research Program"; Acknowledge in any publication using LFDP data the "The Luquillo Experim
Chlorophyll determined by extraction of samples taken approximately weekly from seawater intake starting at Palmer Station by station personnel including during winter-over period, 1991-2024.
Chlorophyll a (Chl a) is the principal photosynthetic pigment of phytoplankton, and is used as a proxy measurement for estimating phytoplankton biomass in water samples. Chl a concentrations reflect the distribution of active phytoplankton spatially and with depth in the water column and their changes over time. Chlorophyll a is determined weekly year-round at the laboratory seawater intake (SWI), from a depth of 6 meters. Concentrations are typically very low (< 1 µg Chl a per liter) in winter (April-October), and higher (1-30 µg/L) following the initiation of the annual spring-summer phytoplankton bloom in November - January.
Global Fire Weather Indices - DMC using default DC start-up
<p>This dataset was developed by Natural Resources Canada using the European Centre for Medium-range Weather Forecasts (ECMWF) ERA5-HRS Reanalysis product (C3S, 2017) as inputs to the Canadian Forest Fire Danger Rating System R Package (Wang et al. 2017). The dataset provides gridded values of the Canadian Fire Weather Index (FWI) System indices of fuel moisture and fire behaviour, including the Fine Fuel Moisture Code (FFMC), Duff Moisture Code (DMC), Drought Code (DC), Initial Spread Index (ISI), Build-Up Index (BUI), Fire Weather Index (FWI), and Daily Severity rating (DSR). Each of these indices are produced using two calculation methods applied at the beginning of fire season start-up. The first method used the default DC value (DC=15) to start-up the FWI System calculation and only accounted for the longest stretch of active fire season each year (as determined by Wotton and Flannigan, 1993). The second method used the overwintered DC value, calculated from the DC value of the last day of the previous fire season and a percentage of overwinter precipitation, and accounted for all periods of fire season throughout the year. We recommend users of this data use indices where DC has been overwintered in regions where the fire season shuts off for winter and where low overwinter precipitation occurs (eg. parts of western Canada, the western US and the Siberian Boreal forest).</p> <p>References:</p> <p>Copernicus Climate Change Service (C3S) (2017): ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate . Copernicus Climate Change Service Climate Data Store (CDS), Accessed June 20<sup>th</sup> 2019. <a href="https://cds.climate.copernicus.eu/cdsapp#!/home">https://cds.climate.copernicus.eu/cdsapp#!/home</a></p> <p>Wang, X., Wotton, B. M., Cantin, A. S., Parisien, M. A., Anderson, K., Moore, B., & Flannigan, M. D. (2017). cffdrs: an R package for the Canadian forest fire danger rating system. Ecological Processes, 6(1), 5.</p> <p>Wotton, B. M., & Flannigan, M. D. (1993). Length of the fire season in a changing climate. The Forestry Chronicle, 69(2), 187-192.</p>
Global Fire Weather Indices - FFMC using default DC start-up
<p>This dataset was developed by Natural Resources Canada using the European Centre for Medium-range Weather Forecasts (ECMWF) ERA5-HRS Reanalysis product (C3S, 2017) as inputs to the Canadian Forest Fire Danger Rating System R Package (Wang et al. 2017). The dataset provides gridded values of the Canadian Fire Weather Index (FWI) System indices of fuel moisture and fire behaviour, including the Fine Fuel Moisture Code (FFMC), Duff Moisture Code (DMC), Drought Code (DC), Initial Spread Index (ISI), Build-Up Index (BUI), Fire Weather Index (FWI), and Daily Severity rating (DSR). Each of these indices are produced using two calculation methods applied at the beginning of fire season start-up. The first method used the default DC value (DC=15) to start-up the FWI System calculation and only accounted for the longest stretch of active fire season each year (as determined by Wotton and Flannigan, 1993). The second method used the overwintered DC value, calculated from the DC value of the last day of the previous fire season and a percentage of overwinter precipitation, and accounted for all periods of fire season throughout the year. We recommend users of this data use indices where DC has been overwintered in regions where the fire season shuts off for winter and where low overwinter precipitation occurs (eg. parts of western Canada, the western US and the Siberian Boreal forest).</p> <p>References:</p> <p>Copernicus Climate Change Service (C3S) (2017): ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate . Copernicus Climate Change Service Climate Data Store (CDS), Accessed June 20<sup>th</sup> 2019. <a href="https://cds.climate.copernicus.eu/cdsapp#!/home">https://cds.climate.copernicus.eu/cdsapp#!/home</a></p> <p>Wang, X., Wotton, B. M., Cantin, A. S., Parisien, M. A., Anderson, K., Moore, B., & Flannigan, M. D. (2017). cffdrs: an R package for the Canadian forest fire danger rating system. Ecological Processes, 6(1), 5.</p> <p>Wotton, B. M., & Flannigan, M. D. (1993). Length of the fire season in a changing climate. The Forestry Chronicle, 69(2), 187-192.</p>
Global Fire Weather Indices - ISI using default DC start-up
<p>This dataset was developed by Natural Resources Canada using the European Centre for Medium-range Weather Forecasts (ECMWF) ERA5-HRS Reanalysis product (C3S, 2017) as inputs to the Canadian Forest Fire Danger Rating System R Package (Wang et al. 2017). The dataset provides gridded values of the Canadian Fire Weather Index (FWI) System indices of fuel moisture and fire behaviour, including the Fine Fuel Moisture Code (FFMC), Duff Moisture Code (DMC), Drought Code (DC), Initial Spread Index (ISI), Build-Up Index (BUI), Fire Weather Index (FWI), and Daily Severity rating (DSR). Each of these indices are produced using two calculation methods applied at the beginning of fire season start-up. The first method used the default DC value (DC=15) to start-up the FWI System calculation and only accounted for the longest stretch of active fire season each year (as determined by Wotton and Flannigan, 1993). The second method used the overwintered DC value, calculated from the DC value of the last day of the previous fire season and a percentage of overwinter precipitation, and accounted for all periods of fire season throughout the year. We recommend users of this data use indices where DC has been overwintered in regions where the fire season shuts off for winter and where low overwinter precipitation occurs (eg. parts of western Canada, the western US and the Siberian Boreal forest).</p> <p>References:</p> <p>Copernicus Climate Change Service (C3S) (2017): ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate . Copernicus Climate Change Service Climate Data Store (CDS), Accessed June 20<sup>th</sup> 2019. <a href="https://cds.climate.copernicus.eu/cdsapp#!/home">https://cds.climate.copernicus.eu/cdsapp#!/home</a></p> <p>Wang, X., Wotton, B. M., Cantin, A. S., Parisien, M. A., Anderson, K., Moore, B., & Flannigan, M. D. (2017). cffdrs: an R package for the Canadian forest fire danger rating system. Ecological Processes, 6(1), 5.</p> <p>Wotton, B. M., & Flannigan, M. D. (1993). Length of the fire season in a changing climate. The Forestry Chronicle, 69(2), 187-192.</p>
Global Fire Weather Indices - DC using default DC start-up
<p>This dataset was developed by Natural Resources Canada using the European Centre for Medium-range Weather Forecasts (ECMWF) ERA5-HRS Reanalysis product (C3S, 2017) as inputs to the Canadian Forest Fire Danger Rating System R Package (Wang et al. 2017). The dataset provides gridded values of the Canadian Fire Weather Index (FWI) System indices of fuel moisture and fire behaviour, including the Fine Fuel Moisture Code (FFMC), Duff Moisture Code (DMC), Drought Code (DC), Initial Spread Index (ISI), Build-Up Index (BUI), Fire Weather Index (FWI), and Daily Severity rating (DSR). Each of these indices are produced using two calculation methods applied at the beginning of fire season start-up. The first method used the default DC value (DC=15) to start-up the FWI System calculation and only accounted for the longest stretch of active fire season each year (as determined by Wotton and Flannigan, 1993). The second method used the overwintered DC value, calculated from the DC value of the last day of the previous fire season and a percentage of overwinter precipitation, and accounted for all periods of fire season throughout the year. We recommend users of this data use indices where DC has been overwintered in regions where the fire season shuts off for winter and where low overwinter precipitation occurs (eg. parts of western Canada, the western US and the Siberian Boreal forest).</p> <p>References:</p> <p>Copernicus Climate Change Service (C3S) (2017): ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate . Copernicus Climate Change Service Climate Data Store (CDS), Accessed June 20<sup>th</sup> 2019. <a href="https://cds.climate.copernicus.eu/cdsapp#!/home">https://cds.climate.copernicus.eu/cdsapp#!/home</a></p> <p>Wang, X., Wotton, B. M., Cantin, A. S., Parisien, M. A., Anderson, K., Moore, B., & Flannigan, M. D. (2017). cffdrs: an R package for the Canadian forest fire danger rating system. Ecological Processes, 6(1), 5.</p> <p>Wotton, B. M., & Flannigan, M. D. (1993). Length of the fire season in a changing climate. The Forestry Chronicle, 69(2), 187-192.</p>
Global Fire Weather Indices - BUI using overwintered DC start-up
<p>This dataset was developed by Natural Resources Canada using the European Centre for Medium-range Weather Forecasts (ECMWF) ERA5-HRS Reanalysis product (C3S, 2017) as inputs to the Canadian Forest Fire Danger Rating System R Package (Wang et al. 2017). The dataset provides gridded values of the Canadian Fire Weather Index (FWI) System indices of fuel moisture and fire behaviour, including the Fine Fuel Moisture Code (FFMC), Duff Moisture Code (DMC), Drought Code (DC), Initial Spread Index (ISI), Build-Up Index (BUI), Fire Weather Index (FWI), and Daily Severity rating (DSR). Each of these indices are produced using two calculation methods applied at the beginning of fire season start-up. The first method used the default DC value (DC=15) to start-up the FWI System calculation and only accounted for the longest stretch of active fire season each year (as determined by Wotton and Flannigan, 1993). The second method used the overwintered DC value, calculated from the DC value of the last day of the previous fire season and a percentage of overwinter precipitation, and accounted for all periods of fire season throughout the year. We recommend users of this data use indices where DC has been overwintered in regions where the fire season shuts off for winter and where low overwinter precipitation occurs (eg. parts of western Canada, the western US and the Siberian Boreal forest).</p> <p>References:</p> <p>Copernicus Climate Change Service (C3S) (2017): ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate . Copernicus Climate Change Service Climate Data Store (CDS), Accessed June 20<sup>th</sup> 2019. <a href="https://cds.climate.copernicus.eu/cdsapp#!/home">https://cds.climate.copernicus.eu/cdsapp#!/home</a></p> <p>Wang, X., Wotton, B. M., Cantin, A. S., Parisien, M. A., Anderson, K., Moore, B., & Flannigan, M. D. (2017). cffdrs: an R package for the Canadian forest fire danger rating system. Ecological Processes, 6(1), 5.</p> <p>Wotton, B. M., & Flannigan, M. D. (1993). Length of the fire season in a changing climate. The Forestry Chronicle, 69(2), 187-192.</p>
Global Fire Weather Indices - FWI using overwintered DC start-up
<p>This dataset was developed by Natural Resources Canada using the European Centre for Medium-range Weather Forecasts (ECMWF) ERA5-HRS Reanalysis product (C3S, 2017) as inputs to the Canadian Forest Fire Danger Rating System R Package (Wang et al. 2017). The dataset provides gridded values of the Canadian Fire Weather Index (FWI) System indices of fuel moisture and fire behaviour, including the Fine Fuel Moisture Code (FFMC), Duff Moisture Code (DMC), Drought Code (DC), Initial Spread Index (ISI), Build-Up Index (BUI), Fire Weather Index (FWI), and Daily Severity rating (DSR). Each of these indices are produced using two calculation methods applied at the beginning of fire season start-up. The first method used the default DC value (DC=15) to start-up the FWI System calculation and only accounted for the longest stretch of active fire season each year (as determined by Wotton and Flannigan, 1993). The second method used the overwintered DC value, calculated from the DC value of the last day of the previous fire season and a percentage of overwinter precipitation, and accounted for all periods of fire season throughout the year. We recommend users of this data use indices where DC has been overwintered in regions where the fire season shuts off for winter and where low overwinter precipitation occurs (eg. parts of western Canada, the western US and the Siberian Boreal forest).</p> <p>References:</p> <p>Copernicus Climate Change Service (C3S) (2017): ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate . Copernicus Climate Change Service Climate Data Store (CDS), Accessed June 20<sup>th</sup> 2019. <a href="https://cds.climate.copernicus.eu/cdsapp#!/home">https://cds.climate.copernicus.eu/cdsapp#!/home</a></p> <p>Wang, X., Wotton, B. M., Cantin, A. S., Parisien, M. A., Anderson, K., Moore, B., & Flannigan, M. D. (2017). cffdrs: an R package for the Canadian forest fire danger rating system. Ecological Processes, 6(1), 5.</p> <p>Wotton, B. M., & Flannigan, M. D. (1993). Length of the fire season in a changing climate. The Forestry Chronicle, 69(2), 187-192.</p>
Global Fire Weather Indices - DMC using overwintered DC start-up
<p>This dataset was developed by Natural Resources Canada using the European Centre for Medium-range Weather Forecasts (ECMWF) ERA5-HRS Reanalysis product (C3S, 2017) as inputs to the Canadian Forest Fire Danger Rating System R Package (Wang et al. 2017). The dataset provides gridded values of the Canadian Fire Weather Index (FWI) System indices of fuel moisture and fire behaviour, including the Fine Fuel Moisture Code (FFMC), Duff Moisture Code (DMC), Drought Code (DC), Initial Spread Index (ISI), Build-Up Index (BUI), Fire Weather Index (FWI), and Daily Severity rating (DSR). Each of these indices are produced using two calculation methods applied at the beginning of fire season start-up. The first method used the default DC value (DC=15) to start-up the FWI System calculation and only accounted for the longest stretch of active fire season each year (as determined by Wotton and Flannigan, 1993). The second method used the overwintered DC value, calculated from the DC value of the last day of the previous fire season and a percentage of overwinter precipitation, and accounted for all periods of fire season throughout the year. We recommend users of this data use indices where DC has been overwintered in regions where the fire season shuts off for winter and where low overwinter precipitation occurs (eg. parts of western Canada, the western US and the Siberian Boreal forest).</p> <p>References:</p> <p>Copernicus Climate Change Service (C3S) (2017): ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate . Copernicus Climate Change Service Climate Data Store (CDS), Accessed June 20<sup>th</sup> 2019. <a href="https://cds.climate.copernicus.eu/cdsapp#!/home">https://cds.climate.copernicus.eu/cdsapp#!/home</a></p> <p>Wang, X., Wotton, B. M., Cantin, A. S., Parisien, M. A., Anderson, K., Moore, B., & Flannigan, M. D. (2017). cffdrs: an R package for the Canadian forest fire danger rating system. Ecological Processes, 6(1), 5.</p> <p>Wotton, B. M., & Flannigan, M. D. (1993). Length of the fire season in a changing climate. The Forestry Chronicle, 69(2), 187-192.</p>
Global Fire Weather Indices - DC using overwintered DC start-up
<p>This dataset was developed by Natural Resources Canada using the European Centre for Medium-range Weather Forecasts (ECMWF) ERA5-HRS Reanalysis product (C3S, 2017) as inputs to the Canadian Forest Fire Danger Rating System R Package (Wang et al. 2017). The dataset provides gridded values of the Canadian Fire Weather Index (FWI) System indices of fuel moisture and fire behaviour, including the Fine Fuel Moisture Code (FFMC), Duff Moisture Code (DMC), Drought Code (DC), Initial Spread Index (ISI), Build-Up Index (BUI), Fire Weather Index (FWI), and Daily Severity rating (DSR). Each of these indices are produced using two calculation methods applied at the beginning of fire season start-up. The first method used the default DC value (DC=15) to start-up the FWI System calculation and only accounted for the longest stretch of active fire season each year (as determined by Wotton and Flannigan, 1993). The second method used the overwintered DC value, calculated from the DC value of the last day of the previous fire season and a percentage of overwinter precipitation, and accounted for all periods of fire season throughout the year. We recommend users of this data use indices where DC has been overwintered in regions where the fire season shuts off for winter and where low overwinter precipitation occurs (eg. parts of western Canada, the western US and the Siberian Boreal forest).</p> <p>References:</p> <p>Copernicus Climate Change Service (C3S) (2017): ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate . Copernicus Climate Change Service Climate Data Store (CDS), Accessed June 20<sup>th</sup> 2019. <a href="https://cds.climate.copernicus.eu/cdsapp#!/home">https://cds.climate.copernicus.eu/cdsapp#!/home</a></p> <p>Wang, X., Wotton, B. M., Cantin, A. S., Parisien, M. A., Anderson, K., Moore, B., & Flannigan, M. D. (2017). cffdrs: an R package for the Canadian forest fire danger rating system. Ecological Processes, 6(1), 5.</p> <p>Wotton, B. M., & Flannigan, M. D. (1993). Length of the fire season in a changing climate. The Forestry Chronicle, 69(2), 187-192.</p>
Global Fire Weather Indices - DSR using overwintered DC start-up
<p>This dataset was developed by Natural Resources Canada using the European Centre for Medium-range Weather Forecasts (ECMWF) ERA5-HRS Reanalysis product (C3S, 2017) as inputs to the Canadian Forest Fire Danger Rating System R Package (Wang et al. 2017). The dataset provides gridded values of the Canadian Fire Weather Index (FWI) System indices of fuel moisture and fire behaviour, including the Fine Fuel Moisture Code (FFMC), Duff Moisture Code (DMC), Drought Code (DC), Initial Spread Index (ISI), Build-Up Index (BUI), Fire Weather Index (FWI), and Daily Severity rating (DSR). Each of these indices are produced using two calculation methods applied at the beginning of fire season start-up. The first method used the default DC value (DC=15) to start-up the FWI System calculation and only accounted for the longest stretch of active fire season each year (as determined by Wotton and Flannigan, 1993). The second method used the overwintered DC value, calculated from the DC value of the last day of the previous fire season and a percentage of overwinter precipitation, and accounted for all periods of fire season throughout the year. We recommend users of this data use indices where DC has been overwintered in regions where the fire season shuts off for winter and where low overwinter precipitation occurs (eg. parts of western Canada, the western US and the Siberian Boreal forest).</p> <p>References:</p> <p>Copernicus Climate Change Service (C3S) (2017): ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate . Copernicus Climate Change Service Climate Data Store (CDS), Accessed June 20<sup>th</sup> 2019. <a href="https://cds.climate.copernicus.eu/cdsapp#!/home">https://cds.climate.copernicus.eu/cdsapp#!/home</a></p> <p>Wang, X., Wotton, B. M., Cantin, A. S., Parisien, M. A., Anderson, K., Moore, B., & Flannigan, M. D. (2017). cffdrs: an R package for the Canadian forest fire danger rating system. Ecological Processes, 6(1), 5.</p> <p>Wotton, B. M., & Flannigan, M. D. (1993). Length of the fire season in a changing climate. The Forestry Chronicle, 69(2), 187-192.</p>
VERTIGO - STARTS Residencies - Public dataset
<p>1 - Summary</p> <p>This archive contains a set of texts produced in the framework of the VERTIGO European project in charge of the STARTS Residencies program. More details about VERTIGO and STARTS Residencies are given in the following section. </p> <p>The STARTS Residencies program of art-science residencies was organised at an unprecedented scale and generated new knowledge which may be useful for further studies. This knowledge concerns the methodology it developed for art-science team building (the process of the call), for ensuring their proper execution through a formalised monitoring approach, and detailed information about each of the residencies and of the concerned stakeholders (Artists, Tech Projects, Producers).</p> <p>These texts are all extracted from the project’s website vertigo.starts.eu and the purpose of this archive is twofold :<br> • to give long-term access to a set of data which is expected to last beyond the life cycle of the vertigo.starts.eu website<br> • to provide additional rights of use beyond the website’s copyright terms which limit the use to access. The terms of the license are specified in an attached document.</p> <p><br> 2 - Introduction to VERTIGO – STARTS Residencies </p> <p>VERTIGO is a Coordination and Support Action (CSA) N°732112 under the European H2020 ICT S+T+ARTS initiative, innovation at the nexus of Science Technology, and the ARTS, supported by the European Commission - DG-CONNECT. STARTS promotes the arts as catalysts for efficient conversion of science and technology knowledge into products, services, and processes. </p> <p>The period of execution of VERTIGO was from December 2016 to May 2020 (42 months). It was managed by a European consortium including the following partners :<br> • IRCAM-Centre Pompidou (Institut de Recherche et Coordination Acoustique/Musique, France) – Project Coordinator : Hugues Vinet (IRCAM)<br> • Fhg-IUK (ICT Group of the Fraunhofer Institute, Germany)<br> • EPFL (Ecole Polytechnique Fédérale de Lausanne, Switzerland)<br> • Inova+ (SME, Portugal)<br> • Artshare (SME, Portugal)<br> • Libelium (SME, Spain)<br> • Association Culture Tech (France)</p> <p>VERTIGO was selected in the framework of the first H2020 ICT Call (ICT36-2016) supporting the STARTS initiative. To achieve its objectives, the STARTS Residencies program managed by VERTIGO has organised and funded artist residencies within Tech Projects - companies, research labs, universities and consortia located in Europe and managing research, development and innovation project, either internal or collaborative. </p> <p>The STARTS Residencies program was organised in 3 yearly open calls for proposals which were selected by an international jury. A total budget of 900.000 € has been allocated for funding the participation of artists in 45 residencies. The selected artists were expected to contribute to the innovative aspects of Tech Projects’ research by bringing original perspectives through artistic practices. Those practices would lead to the production of original artwork based on the project technology and featuring novel use-cases with a high potential for innovation. STARTS Residencies also acted as a platform to showcase produced works to the public and actors of innovation in the framework of various public events and communication actions and through the development of the STARTS starts.eu web site.</p> <p>The three yearly calls for the selection of the residencies stakeholders took place from 2017 to 2019, each of which included two steps: first a call for Tech Projects interested in hosting an artist which resulted in the selection and publication of a list of available Tech Projects, and then a call for artistic residencies based on one Tech project from the list and aiming at producing an artwork based on the Tech Project technology. Artists could apply alone or together with a Producer, an organisation willing to bring additional support (funding, production means) to the residency and the artwork production and dissemination. STARTS Residencies also therefore organised a call for Producers available for considering joint applications with artists. After review of the residencies application by the concerned Tech Projects representatives, an international jury then selected the best STARTS residencies matching the various defined criteria including the congruence with the Tech Project’s expectations, the artistic quality, the technical approach, the potential innovation impact and the relevance of the implementation plan. <br> Once residencies were selected, a process of collaboration was started and coordinated by one representative of VERTIGO-STARTS Residencies, following a monitoring methodology defined for all the residencies. This process, which started with the signature of a co-production agreement between all stakeholders (Tech project, artist(s), VERTIGO representative, optional Producer) included 3 formal meetings (inception, mid-term, completion) with defined deliveries for each of them. </p> <p>VERTIGO also developed the starts.eu web platform as the main matchmaking hub of the STARTS community. All information about VERTIGO and its STARTS Residencies program is presented in the subdomain vertigo.starts.eu. It contains all public information about the selected residencies, the selected Tech Projects and Producers, the presentation of events in which the residencies were presented, as well as all written public documentation (deliverables, brochure, event programs, etc.).</p> <p><br> 3 - Contents of the dataset</p> <p>The dataset contents can be summarised as follows :</p> <p>• a presentation of each of the 45 residencies with one directory per artist, made of the following elements :<br> o The residency portfolio: produced by the VERTIGO partners at the completion of the residency, it provides all factual information (involved stakeholders, the period of execution), abstracts, and a synthesis on the residency: its elements of specificity, its impact in terms of innovation and public information available (events, publications, etc.); <br> o 3 questions to the artist: asked the artist at the beginning of the residency<br> o The residency final public report produced by the artist at the end of the residency</p> <p>• a presentation of the selected Tech Projects, not only the ones involved in the implemented residencies, but also the ones that published their offer to host a residency without an actual implementation as part of STARTS Residencies. These texts were produced following the same template by all the Tech Projects to be included in the list of available Tech Projects for the artistic calls. They include an abstract, a summary of their main challenges, what they expect from the artists and which resources they foresee to bring them. It should be noted that their situation may have evolved from these initial statements and the moment when they hosted a residency. </p> <p>• a presentations of the available Producers: similarly to Tech Projects, texts of presentation of organisations that advertised their availability for co-applying with an artist for an artistic residency.<br> </p>
Time series data of COVID-19 cases (rT-PCR-confirmed), hospitalisations (laboratory-confirmed), and hospital-associated deaths (laboratory confirmed) in South Africa, by imputed dates of symptom onset, from the start of the pandemic in March 2020 through April 2022.
<p>Time series data of COVID-19 cases (rT-PCR-confirmed), hospitalisations (laboratory-confirmed), and hospital-associated deaths (laboratory confirmed) in South Africa, by imputed dates of symptom onset, from the start of the pandemic in March 2020 through April 2022. These data were used to estimate the time-varying reproduction number (R) in South Africa, as described in https://www.medrxiv.org/content/10.1101/2022.07.22.22277932v1.full.</p>
Observation of a regular structure formation on the surface of vibrated ball beds started from random lose packing
<p>Near 4,000 2-mm diameter plastic balls were poured 88 times into plexiglass cylinder of internal diameter 26 mm. Then, such initially random loose-packing systems/beds were vibrated vertically with 100 Hz frequency using the vibration table Vibrax (Renfert GmbH, Germany) working in sinusoidal mode until a regular structure was observed on the cylinder surface. The power levels of the vibrations in the recorded ordering of balls were selected to represent all four levels (1, 2, 3 or 4) of vibrations available in the table, where number 1 means the weakest vibration and 4 means the strongest one.</p> <p>Locations of the balls on all sides of a vibrated cylindrical bed were simultaneously recorded on one video frame thanks to the use of two perpendicular mirrors, which enables observation of four images: one of the real cylinder and three of its mirror reflections. View of the table with the attached cylinder containing balls and two mirrors is presented in Fig. 1, while an explanation of the scene, as seen by the recording camera, is given in the scheme in Fig. 2. Video names were given in a standard form explained in the README.txt file.</p>
An Empirical Study of Container Image Configurations and Their Impact on Start Times (Container Image Data)
<p>Dataset with the container image metadata used for our IEEE/ACM CCGRID 2023 paper "An Empirical Study of Container Image Configurations and Their Impact on Start Times".</p> <p>Abstract of the paper: A core selling point of application containers is their fast start times compared to other virtualization approaches like virtual machines. Predictable and fast container start times are crucial for improving and guaranteeing the performance of containerized cloud, serverless, and edge applications. While previous work has investigated container starts, there remains a lack of understanding of how start times may vary across container configurations. We address this shortcoming by presenting and analyzing a dataset of approximately 200,000 open-source Docker Hub images featuring different image configurations (e.g., image size and exposed ports). Leveraging this dataset, we investigate the start times of containers in two environments and identify the most influential features. Our experiments show that container start times can vary between hundreds of milliseconds and tens of seconds in the same environment. Moreover, we conclude that no single dominant configuration feature determines a container's start time and that hardware and software parameters must be considered together for an accurate assessment.</p> <p>Dataset description: Our images dataset contains 200,986 entries with 21 features associated to each container image. In the following, we describe the meaning of each feature. Further information is available in <a href="https://github.com/opencontainers/image-spec">OCI Image Specification</a> and the <a href="https://docs.docker.com/engine/reference/run/">Docker Run Documentation</a>. Besides the 20 features grouped in the five categories below, each dataset entry has a image_id, which is used to uniquely identify the dataset entry.</p> <p>Features</p> <p>Metadata features (prefix: meta)</p> <ul> <li><strong>meta_repo_digest</strong> : The repo digest is a SHA-256 hash which is used to uniquely identify and pull the image from Docker Hub</li> <li><strong>meta_architecture</strong> : The CPU architecture which the binaries in the image are built to run on</li> <li><strong>meta_os</strong> : The name of the operating system which the image is built to run on</li> <li><strong>meta_docker_version</strong> : The Docker version used to built this image</li> </ul> <p>I/O stream features (prefix: io)</p> <ul> <li><strong>io_attach_stdin</strong> : boolean setting to determine whether the console should be attached to the process stdin stream</li> <li><strong>io_attach_stdout</strong> : boolean setting to determine whether the console should be attached to the process stdout stream</li> <li><strong>io_attach_stderr</strong> : boolean setting to determine whether the console should be attached to the process stderr stream</li> <li><strong>io_tty</strong> : boolean setting to determine whether the console should pretend to be a TTY when attached</li> <li><strong>io_open_std_in</strong> : boolean setting to determine whether the process stdin stream should be kept open even if console not attached</li> <li><strong>io_std_in_once</strong> : boolean setting to determine whether the process retrieved input from the stdin stream at least once</li> </ul> <p>Start command features (prefix: cmd)</p> <ul> <li><strong>cmd_args</strong> : Length of list of arguments to use as the command to execute when the container starts</li> <li><strong>cmd_envvars</strong> : Environment variables set per default when the container starts</li> <li><strong>cmd_additional_args</strong> : Length of list for additional arguments to the containers entrypoint</li> </ul> <p>File system features (prefix: fs)</p> <ul> <li><strong>fs_volumes</strong> : Number of volumes to create/use by default</li> <li><strong>fs_size</strong> : Size of this image in bytes</li> <li><strong>fs_virtual_size</strong> : Virtual size of this image in bytes (equals size)</li> <li><strong>fs_graph_driver_name</strong> : Name of the image's graph driver</li> <li><strong>fs_root_fs_type</strong> : Name of the file system type used in the image</li> <li><strong>fs_layers</strong> : Number of root file system layers</li> </ul> <p>Networking features (prefix: net)</p> <ul> <li><strong>net_ports</strong> : Number of ports to expose per default</li> </ul> <p> </p> <p>Dataset acquisition: The dataset has been acquired from Docker Hub using a web crawler. We used substring matches with the <a href="https://hub.docker.com/explore">Docker Hub Explore function</a>. As search strings, we used all letter combination with sizes 1 to 3, meaning that our first search string was 'a' and our last was 'zzz'. We included both results from the 'recently updated' and the 'most popular' selection. We came up with an initial list of 286,294 image names. We then tested we could pull and start these images once. These tests have been conducted from April to June 2022. We sorted out all images that were either not pullable or startable and retrieved all total of 200,986 valid images. In the following, we describe the error types that we encountered and that let to the removal of the causing image from the dataset:</p> <ul> <li>The image manifest was unknown when we tried to download it meaning that is has been renamed or deleted from the time when our web crawler was running</li> <li>The entrypoint command required a dependency that was missing in the image and therefore the container could not be started</li> <li>The image did not specify an entrypoint command and could therefore not be started</li> <li>The image declared an invalid root file system type</li> <li>The image had a malformed root file system</li> <li>The image configuration was incomplete and therefore not all required data could be obtained</li> </ul> <p>See also our CodeOcean capsule with the processing scripts for our paper: https://doi.org/10.24433/CO.4595026.v2</p>
Vertical profiles of in-situ biogenic silica (bSi) from discrete rosette bottle samples from CCE-LTER starting with cruise P1706.
Samples are taken at discrete depths from rosette bottles in the California Current Ecosystem and measured for biogenic silica (bSi) concentration to create bSi depth profiles. Diatom community and physiology affect biogenic silica concentration. These data are being used to investigate the effects of Fe limitation on carbon and silica cycling in the CCE.
ScienceDex guides
Understand access before you commit
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.