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169 results for “fire experiments”
Point-frame measurments from a nitrogen (N), phosphorus (P) and N+P fertilization experiment at the 2007 Anaktuvuk River, Alaska, USA fire scar during the 2016-2019 growing seasons
This file contains point-frame measurements from a nitrogen (N), phosphorus (P) and N+P fertilization experiment established in the southern section of the 2007 Anaktuvuk River fire in 2016 at a severely burned site and an unburned site. Pin-vegetation contact was recorded using a 0.75 m2 frame with 41 evenly spaced pin-drop points. Data was collected once during the height of the growing season in 2016 (when fertilization began) 2017, 2018 and 2019. This data was used to measure the impact of fertilization and fire on community composition.
Leaf area index (LAI) recorded from a nitrogen (N), phosphorus (P) and N+P fertilization experiment at the 2007 Anaktuvuk River, Alaska, USA fire scar during the 2016-2019 growing seasons
This file contains leaf area index (LAI) measurements from an nitrogen (N), phosphorus (P) and N+P fertilization experiment established in the southern section of the 2007 Anaktuvuk River fire in 2016. LAI was recorded using a handheld plant canopy analyzer (LI-COR 2200C; LI-COR, Lincoln, NE, USA) Data spans 4 years from 2016 (when fertilization began) until 2019. Data was recorded once a year at the peak of each growing season.
Alaska 2004 Burns: Counts of live and dead seedlings of lodgepole pine in a post-fire seeding experiment at 39 sites
This dataset contains counts of emerged seedlings of lodgepole pine from seeds sown in an experimental seeding study. The experiment started in 2005 at sites that burned in 2004 in interior Alaska. Records are from a set of 39 intensive study sites that were formerly dominated by black spruce along the Steese, Taylor, and Dalton highways. Seeds were sown in five 50 x 50 cm quadrats at each site in August 2005 and most emerged in early summer 2005. Seedling counts were measured for 6 years, in 2006, 2007 2008, and 2011. All pine seedlings were removed in 2011.
Fire Self-Limitation (FiSL) Experiment: Quantifying Wildfire Carbon Combustion Losses in boreal Deciduous and Mixed Forests in Interior Alaska and the Boreal Cordillera I: Site Attribute Data 2022
This dataset contains site characteristics collected in the field for plots in 8 fire scars in Interior Alaska and the Yukon. Data was collected in the summer of 2022. Fire scars sampled included Shovel Creek (2019), Aggie Creek (2015), Hess Creek (2019), Baker (2015), Munson Creek (2021), Isom Creek (2020), 2019MA014 (2019), and 2019BC005 (2019). Data includes detailed site characteristics collected at the site level. Each site included three 10 m * 2 m plots (A, B, and C) laid in a single 30 m transect (or, where constrained, in parallel).
Fire Self-Limitation (FiSL) Experiment: Quantifying Wildfire Carbon Combustion Losses in boreal Deciduous and Mixed Forests in Interior Alaska and the Boreal Cordillera II: Tree Inventory Data 2022
This dataset contains tree combustion measurements collected in the field for plots in 8 fire scars in Interior Alaska and the Yukon. Data was collected in the summer of 2022. Fire scars sampled included Shovel Creek (2019), Aggie Creek (2015), Hess Creek (2019), Baker (2015), Munson Creek (2021), Isom Creek (2020), 2019MA014 (2019), and 2019BC005 (2019). Tree species, diameters (DBH where possible, otherwise BD), condition (living/dead, standing/fallen, etc), and component combustion are recorded for every tree in each 10 m * 2 m plot.
Fire Self-Limitation (FiSL) Experiment: Quantifying Wildfire Carbon Combustion Losses in boreal Deciduous and Mixed Forests in Interior Alaska and the Boreal Cordillera III: Shrub Inventory Data
This dataset contains shrub combustion measurements collected in the field for plots in 8 fire scars in Interior Alaska and the Yukon. Data was collected in the summer of 2022. Fire scars sampled included Shovel Creek (2019), Aggie Creek (2015), Hess Creek (2019), Baker (2015), Munson Creek (2021), Isom Creek (2020), 2019MA014 (2019), and 2019BC005 (2019). Shrub species, stem diameters (BD), and component combustion were recorded for every shrub in each 10 m * 2 m plot.
Fire Self-Limitation (FiSL) Experiment: Quantifying Wildfire Carbon Combustion Losses in boreal Deciduous and Mixed Forests in Interior Alaska and the Boreal Cordillera IV: Organic Soil Carbon and Nitrogen Content from Organic Soil Samples 2022
This dataset contains lab-quantified (and some field-measured) characteristics for post-fire residual organic soil samples collected in the field for plots in 8 fire scars in Interior Alaska and the Yukon. Data was collected in the summer of 2022. Fire scars sampled included Shovel Creek (2019), Aggie Creek (2015), Hess Creek (2019), Baker (2015), Munson Creek (2021), Isom Creek (2020), 2019MA014 (2019), and 2019BC005 (2019). Lab analyses were conducted in summer and fall of 2022 at UAF and NAU.
Fire Self-Limitation (FiSL) Experiment: Quantifying Wildfire Carbon Combustion Losses in boreal Deciduous and Mixed Forests in Interior Alaska and the Boreal Cordillera V: Organic Soil Depth 2022
This dataset contains field-measured characteristics for post-fire residual organic soil samples and for additional organic soil depths collected in the field for plots in 8 fire scars in Interior Alaska and the Yukon. Data was collected in the summer of 2022. Fire scars sampled included Shovel Creek (2019), Aggie Creek (2015), Hess Creek (2019), Baker (2015), Munson Creek (2021), Isom Creek (2020), 2019MA014 (2019), and 2019BC005 (2019).
Fire Self-Limitation (FiSL) Experiment: Quantifying Wildfire Carbon Combustion Losses in boreal Deciduous and Mixed Forests in Interior Alaska and the Boreal Cordillera VI: Mineral Soil Sample and pH Data 2022
This dataset contains field- and lab-measured characteristics for post-fire mineral soil samples collected in the field for plots in 8 fire scars in Interior Alaska and the Yukon. Data was collected in the summer of 2022. Fire scars sampled included Shovel Creek (2019), Aggie Creek (2015), Hess Creek (2019), Baker (2015), Munson Creek (2021), Isom Creek (2020), 2019MA014 (2019), and 2019BC005 (2019). Lab analyses were conducted in fall of 2022 at NAU.
Fire Self-Limitation (FiSL) Experiment: Quantifying Wildfire Carbon Combustion Losses in boreal Deciduous and Mixed Forests in Interior Alaska and the Boreal Cordillera VII: Coarse and Fine Woody Debris Inventory 2022
This dataset contains characteristics of coarse woody debris and snags collected in the field for plots in 8 fire scars in Interior Alaska and the Yukon. Data was collected in the summer of 2022. Fire scars sampled included Shovel Creek (2019), Aggie Creek (2015), Hess Creek (2019), Baker (2015), Munson Creek (2021), Isom Creek (2020), 2019MA014 (2019), and 2019BC005 (2019).
Fire Self-Limitation (FiSL) Experiment: Quantifying Wildfire Carbon Combustion Losses in boreal Deciduous and Mixed Forests in Interior Alaska and the Boreal Cordillera VIII: Seedling Inventory 2022
This dataset contains characteristics of post-fire seedlings and resprouts collected in the field for plots in 8 fire scars in Interior Alaska and the Yukon. Data was collected in the summer of 2022. Fire scars sampled included Shovel Creek (2019), Aggie Creek (2015), Hess Creek (2019), Baker (2015), Munson Creek (2021), Isom Creek (2020), 2019MA014 (2019), and 2019BC005 (2019).
Fire Self-Limitation (FiSL) Experiment: Quantifying Wildfire Carbon Combustion Losses in boreal Deciduous and Mixed Forests in Interior Alaska and the Boreal Cordillera IX: metrics derived from All Raw Data Collected Plus Data from Previous Studies on the 2004 Alaska Wildfires Included in Analysis 2022
This data set includes metrics derived from field and lab data collected for deciduous and mixed deciduous-confier plots collected in the summer of 2022 (Shovel Creek (2019), Aggie Creek (2015), Hess Creek (2019), Baker (2015), Munson Creek (2021), Isom Creek (2020), 2019MA014 (2019), and 2019BC005 (2019)), as well as additional data for conifer plots from previous studies of the Taylor Highway Complex (2004), Dall Creek/Yukon Crossing (2004), and Boundary (2004) fires. Those additional data were acquired from: https://www.lter.uaf.edu/d1/d1-detail/id/773 and https://daac.ornl.gov/ABOVE/guides/ABoVE_Plot_Data_Burned_Sites.html. From this complete data set of 333 plots, 311 plots were used in analyses in Black at al. (NCC) paper: "Increased deciduous tree dominance reduces wildfire carbon losses in boreal forests". Plots excluded (from 2022 FiSL data) were poplar-dominated, mixed poplar/conifer dominated, missing soil C data, or conifer-dominated (adventituous root heights were not recorded consistently at sites in 2022 making it impossible to estimate pre-fire conifer stand organic soil C pools for 2022-collected conifer plots). Only 2005-collected conifer plots were used in NCC paper analyses. For all plots, in addition to field/lab derived site characteristics and combustion metrics, post hoc remotely sensed metrics were derived: pre-fire NDVI/EVI-2 trends, 1980-2010 climate normals, and DOB weather metrics.
KKE01 The Konza-Kruger Experiment: A cross-continental fire and grazing experiment at Konza Prairie
For more than a decade, we have compared responses of mesic (subhumid) savanna grasslands (>500 mm MAP in the tropics and >600 mm MAP outside the tropics) in North America and South Africa to alterations in both fire and grazing regimes. The long-term, comparative experiment that forms the centerpiece of this cross-continental research program is located in tallgrass prairie at the Konza Prairie Biological Station (Kansas, USA) and in knob-thorn marula savanna at the Kruger National Park (Limpopo and Mpumalanga provinces, South Africa). We refer to this study as the Konza-Kruger (K-K) Experiment. At both sites, we have been manipulating grazing by removing all large herbivores (>5 kg) from research plots with permanent exclosures (each with a paired plot that grazers can freely access). These exclosures were established in replicated fire frequency experiments ongoing at each site (treatments range from >25-50 yrs of annual burning, burning every 3-4 yrs, or complete fire exclusion).
NBC01 Konza Prairie Belowground Plot Experiment: Soil chemistry responses to experimental manipulations of fire, nutrients and mowing
To address the potential interactive effects of fire, aboveground biomass removal, and nutrient amendments on above- and belowground responses, a long-term field experiment was initiated in 1986 as part of the Konza Prairie Long-Term Ecological Research (LTER) program. The general goals of this experiment are: 1) to document both short- and long-term responses of plants and soils to fire, aboveground biomass removal (a surrogate for grazing in these small plots), and nutrient amendments (additions of N and/or P); and 2) to provide a better understanding of the mechanisms underlying tallgrass prairie responses to fire, aboveground biomass removal and nutrient enrichment. Effects of burning, mowing, and N + P additions on soil chemistry are measured on the 64 belowground plots at irregular intervals. Variables measured include P, NO3, NH4, Mn, Cu, K, Zn, Ca, Fe, Mg, Na, ph, Organic matter and Organic-N.
PAB05 Aboveground net primary productivity of tallgrass prairie based on accumulated plant biomass on the LTER fire reversal experiment watersheds
Data set contains estimates of end-of-season standing crop biomass (grams per square meter) of live graminoids, forbs, woody plants, and previous year's dead vegetation for 2 soil types (shallow and deep) on the four Fire Reversal Experiment watersheds. This experiment is based on reversing fire treatments on four watersheds, two of which had a history of annual spring burning and two of which had a history of long-term fire suppression. The dataset includes both pre- and post-fire treatments.
Fuel loads monitoring dataset of Campos Amazônicos Fire Experiment (Amazonas, Brazil)
<p>This dataset presents fuel loads monitoring data related to the Campos Amazônicos Fire Experiment (CAFE) (Amazonas, Brazil) project. Located within a protected area within the largest enclave of tropical savanna in the Southern Amazon, CAFE comprises a careful and systematic experimental design that was conceived from the start to evaluate satellite observations and their potential and limitations in studying spatial and temporal fire dynamics in tropical savannas.</p> <p>More information about the experimental design can be found in the following publication:</p> <p>Alves, D. B.; Fidelis, A.; Pérez-Cabello, F.; Alvarado, S. T.; Conciani, D. E.; Cambraia, B. C.; Silveira, A. L. P.; Silva, T. S. F. Impact of Image Acquisition Lag-Time on Monitoring Short-Term Postfire Spectral Dynamics in Tropical Savannas: the Campos Amazônicos Fire Experiment. Journal of Applied Remote Sensing v. 16, n. 3 (2022) - <a href="https://doi.org/10.1117/1.JRS.16.034507">https://doi.org/10.1117/1.JRS.16.034507</a></p> <p>_____________________________________________________________________________</p> <p>August 08, 2022 - Version 1.0 includes data from 30 monitored experimental plots of 1 hectare each (100×100 m). Three experimental treatments were then established: 12 plots were burned in May (Early-Dry Season – EDS), further 12 plots were burned in August (Mid-Dry Season – MDS), and 6 plots were kept as control by ensuring fire exclusion throughout the duration of the experiment. Controlled burning occurred during two separate field campaigns in 2019, the first between May 19th and 25th, and the second between August 22nd and 26th.</p> <p>Measurements of fuel load were obtained from eight subplots of 0.5 × 0.5 m randomly distributed within each plot. Samples included graminoids, leaves and branches near the ground. Biomass was dried at 70°C for 48 hours, and weighed to determine total fuel load (kg. m<sup>-2</sup>) for each sample. Samples were taken before fire for all control, EDS and MDS burn plots during both field campaigns, and repeated sampling was carried out after fire for the burned plots. In 2020, all 30 monitored plots were sampled again in May and August.</p> <p>The files available include: i) a table (Fuel_load_measures.csv) that contains the measures of fuel loads for each plot; ii) a text file (List_of_variables.rtf), which details each variable available in the table.</p> <p>_____________________________________________________________________________</p> <p>We thank the management team of the Campos Amazônicos National Park, and in particular to its Fire Brigade (squad leaders José Furtado Neto, Genaldo Júnior, Ademilton Carvalho, Simei Limoeiro, José Alexandre Medeiros, Antonio Machado and Leandro Lacerda, and on behalf of them to all other members of the brigade), who ensure safe burning of all fire experiments (SISBIO license number 67210-5). This work was supported by the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP, grant numbers 2019/07357-8; 2015/06743-0); the Conselho Nacional de Pesquisa e Desenvolvimento (CNPq, grant numbers 154660/2018-3; 441968/2018-0; 303988/2018-5).</p>
Fire behavior dataset of Campos Amazônicos Fire Experiment (Amazonas, Brazil)
<p>This dataset presents fire behavior data related to the Campos Amazônicos Fire Experiment (CAFE) (Amazonas, Brazil) project. Located within a protected area within the largest enclave of tropical savanna in the Southern Amazon, CAFE comprises a careful and systematic experimental design that was conceived from the start to evaluate satellite observations and their potential and limitations in studying spatial and temporal fire dynamics in tropical savannas.</p> <p>More information about the experimental design can be found in the following publication:</p> <p>Alves, D. B.; Fidelis, A.; Pérez-Cabello, F.; Alvarado, S. T.; Conciani, D. E.; Cambraia, B. C.; Silveira, A. L. P.; Silva, T. S. F. Impact of Image Acquisition Lag-Time on Monitoring Short-Term Postfire Spectral Dynamics in Tropical Savannas: the Campos Amazônicos Fire Experiment. Journal of Applied Remote Sensing v. 16, n. 3 (2022) - <a href="https://doi.org/10.1117/1.JRS.16.034507">https://doi.org/10.1117/1.JRS.16.034507</a></p> <p>_________________________________________________________________________________________________________</p> <p>August 08, 2022 - Version 1.0 includes data from 24 experimental fires carried out in 2019 (12 in Early-Dry Season - EDS; 12 in Middle-Dry Season - MDS), each corresponding to a plot of 1 hectare (100x100 meters). Controlled burning occurred during two separate field campaigns in 2019, the first between May 19th and 25th, and the second between August 22nd and 26th. The files available include: i) a table (Fire_behavior_dataset.csv) that contains the fire parameters calculated for each experimental fire performed; ii) a text file (List_of_variables.rtf), which details each variable available in the table.</p> <p>_________________________________________________________________________________________________________</p> <p>We thank the management team of the Campos Amazônicos National Park, and in particular to its Fire Brigade (squad leaders José Furtado Neto, Genaldo Júnior, Ademilton Carvalho, Simei Limoeiro, José Alexandre Medeiros, Antonio Machado and Leandro Lacerda, and on behalf of them to all other members of the brigade), who ensure safe burning of all fire experiments (SISBIO license number 67210-5). This work was supported by the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP, grant numbers 2019/07357-8; 2015/06743-0); the Conselho Nacional de Pesquisa e Desenvolvimento (CNPq, grant numbers 154660/2018-3; 441968/2018-0; 303988/2018-5)</p>
Fight or flight? Behaviour and experiences of laypersons in the face of an incipient fire
<p>This dataset contains raw data collected in an experimental study by the University of Muenster, Germany, in cooperation with the German Fire Protection Association and the State Fire Service Institute NRW, Germany. The study is part of a larger research project and examined the behavior of laypersons when confronted with an incipient fire.</p> <p>Within minutes, an incipient fire can develop into a life-threatening full fire. Consequently, it should be fought as early as possible. But are laypersons capable of doing this? In such a situation, how do they behave and feel? These questions are addressed in the current study. Persons without any professional firefighting training (N=64) were confronted in two experimental runs with a real incipient fire in the form of a burning pillow.</p> <p>The study was approved by the ethics committee of the Department 7 of the University of Münster (ID 2018-16-MT) and pre-registered with AsPredicted.org under the number 20436 (https://aspredicted.org/8py33.pdf). The study was supported by the German Federal Ministry of Education and Research (funding code FKZ 13N14208).</p> <p>In addition to the raw data, the codebook as well as the R- analysis script is included here for better comprehensibility. The raw data contains only the information of persons who were included in the analysis and have agreed to it. Some demographic information was deleted to ensure anonymity.</p>
FlowBlaze on Fed4FIRE+ FB-FIRE Final Results of the Experiment
<p>This repository contains the results of the FB-FIRE experiment. The aim of FB-FIRE is to test, validate and assess in the Fed4FIRE+ Virtual Wall testbed the performance of FlowBlaze, a novel stateful programmable dataplane engine that can simplify network functions (NF) design and implementation, while providing high performance packet forwarding, and support for future hardware offloading to SmartNICs. FlowBlaze is an abstraction that can be implemented in an efficient DPDK-accelerated software engine, conceived to rapidly design and deploy complex network functions hiding the complexity of software optimizations associated to the development of network functions.</p>
Internet on FIRE, a Fed4FIRE+ Experiment
<p>Log files related to three different experiments done on the Fed4FIRE TestBeds within the Internet on Fire project.</p> <p>Experiment 1: BGP Tests related to Fabrikant topology.</p> <p>Experiment2: BGP Tests related to Elmokashfi topologies, 1000 Nodes.</p> <p>Experiment3: BGP Tests related to Elmokashfi topologies, 2000 Nodes.</p> <p>Experiment4: BGP Tests related to Elmokashfi topologies, 4000 Nodes.</p> <p>Experiment5: BGP Tests related to Elmokashfi topologies, 12000 Nodes.</p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.