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1,826 results for “burning”
Raw microclimate data from plots at burned areas from the 2020 Holiday Farm fire in the Andrews Experimental Forest and Hagan Block, 2022-2024
This dataset includes a suite of microclimate sensor data from areas burned by the 2020 Holiday Farm fire within the McKenzie River basin. A total of 42 microclimate sensor suites were installed in July and August of 2022 distributed across RS01, RS08, RS15, WS02, WS09, WS01, HGBK. All sensor locations are within the Holiday Farm Fire footprint and within Permanent Sample Plots (PSPs). An additional sensor was placed within the Primary meteorological station (PRIMET) of the HJ Andrews Experimental Forest for comparison and calibration between open-air measurements. Sites are stratified across three treatment variables including 1) fire severity: high or low; 2) management: managed or unmanaged; 3) water balance: moister or drier topographic positions. This resulted in eight treatment blocks, each with 5 sensor suite replicates. Each microclimate site includes a suite of measurements: Hobo temperature and relative humidity sensor installed at 1.5m within a gill shield (recording at 30 minute interval), one TOMST TMS-4 temperature and soil moisture sensor was located within 1 m of plot center (recording at 15 minute interval). The TOMST sensors include air temperature sensors at 15cm, 2cm, and soil temperature at -6cm in soil near-surface. Soil moisture is measured across the ~10cm near surface zone.
Plant biomass dynamics following logging, burning, and thinning in Watersheds 6 and 7, Andrews Experimental Forest, 1979 to 2021
Watersheds 6 (WS06) and 7 (WS07) at the HJ Andrews are part of a three-watershed study initiated in the 1970’s to examine the response of hydrology and forest vegetation to logging. In 1974, Watershed 6 was clearcut logged; Watershed 7 was shelterwood cut, leaving 75-100 overstory trees per hectare (comprising about 40% of the original basal area). A nearby watershed (WS08) serves as an unlogged control. In 1975, all of Watershed 6 and the portion of WS07 below the road were broadcast-burned. In 1976, both watersheds were planted with Douglas-fir seedlings. Natural regeneration of Douglas-fir and western hemlock also established. In 1984, the remnant overstory trees in WS07 were harvested, and in 2001 the young stand in WS07 was thinned to about 550 trees per hectare. The thinning was not planned but provides an interesting twist to the study. The watersheds are located along the northern boundary of the HJA off the 327 and 328 roads, at elevations ranging from 850 to 1,160 m. Initial vegetation measurements were taken in the summer of 2002 in watersheds 6 and 7 for the purpose of characterizing plant succession after thinning in a small, high-elevation watershed. Understory vegetation plots are remeasured at approximately 6 year intervals.
Northern red oak regeneration in burned and unburned stands in the White Mountain National Forest, New Hampshire, USA, 2023-2024
This project aimed to determine whether prescribed burning of managed forest stands improves the regeneration of Quercus rubra near its northern range limit in New Hampshire. We measured oak seedling density and growth rates in three pairs of managed stands in which one had received a prescribed burn since 2017. We also measured the density of competing seedlings and shrubs, leaf area index above seedling height, soil nutrients, mycorrhizal colonization, foliar carbon/nitrogen ratio, and stable isotopes of nitrogen and carbon. We found greater oak seedling density and faster oak seedling growth rates in burned stands relative to unburned stands. A subset of these measurements were also collected in additional burned and unburned study stands in the region. A companion mesocosm experiment showed faster growth in oak seedlings grown in soil from burned vs. unburned stands. Together these studies show that the benefits of fire to oak regeneration are mediated both via greater light availability as well as effects mediated via soil.
Mycorrhizal fungal communities identified from seedlings planted in the Taylor, Dalton, and Boundary fire complexes which burned in 2004
This dataset contains the operational taxonomic unit table and taxonomic assignments for fungi that were associated with the roots of seedlings planted into the 2004 burn sites. There were 458 seedlings from 22 of the 32 established intensive sites (Johnstone and Hollingsworth 2019) consistenting of black spruce, white spruce, aspen, and lodgepole pine.
Herb Survey: Effect of Burning Patterns on Vegetation in the Fish Lake Burn Compartments
This study examines the effects of long-term prescribed burning treatments on vegetation structure and composition, productivity, and nutrient cycling in upland oak savanna and woodland vegetation. The basis for the study is an ongoing, experimental prescribed burning program begun in 1964 at Cedar Creek, and a similar program operating since 1962 on the adjacent Helen Allison Savanna property (owned by The Nature Conservancy). These prescribed burning programs are designed to subject upland oak communities (and some old fields) to different burn frequencies and patterns of burning, with the ultimate objectives of 1) restoring and maintaining the historically important savanna and open woodland vegetation, and 2) providing information about the effects of different burning patterns on vegetation structure and composition. This study addresses the latter of these two purposes and expands on it by also investigating possible influences of fire on resource availability (nutrients, water, and light) and net primary productivity. This study represents a continuation and expansion of experiments 015 and 094.
CSM04 Seasonal summary of numbers of small mammals on the eight LTER seasonal burn traplines in prairie habitats at Konza Prairie
Data set contains seasonal summaries (spring, summer and fall) of the number of individuals of each species of small mammal caught (relative density) on each grassland census line. Each record contains trapline, year of last fire and number of individuals per species. These live trap records are based on daily captures during three 4-day trapping periods, March, July and October, for each of 20 permanent census lines established on 10 fire-grazing treatments (2 lines per treatment). These 10 fire-grazing treatments are one unburned, one annual burn and one 4-year burn site to be grazed by native ungulates and one unburned, one annual burn, four 4-year burn and one 10-year burn site not grazed by ungulates.
Astrophysical S-factors for H-burning stars
<p> This dataset contains the latest recommendations of astrophysical S-factors for nuclear fusion reactions occurring in hydrogen-burning stars, included in the <strong><em>Solar Fusion III </em></strong>decadal review article (submitted for publication, e-print available at <a href="https://arxiv.org/abs/2405.06470" target="_blank" rel="noopener">arXiv:2405.06470</a>).</p> <p> The data includes S-factors and their derivatives at zero energy (where available). That is, <em>S(0)</em>,<em> S´(0)</em>, <em>S´´(0)</em>, in units of MeV·b, b, and b/MeV, respectively. Fractional uncertainties are also provided (marked as <em>fr_err</em>). Unavailable data are marked as <em>NA</em>.</p> <p> This data was used to compute the <a href="https://zenodo.org/records/10822316">Standard Solar Models B23 / SF-III</a>. </p> <p> For further information and references consult the <strong><em>Solar Fusion III </em></strong> article linked above.</p>
Natural Regeneration of Puerto Rican Tropical Dry Forest Sites with Limited Burn History, Guánica Forest, 2012
This dataset documents the natural regeneration of tropical dry forest sites with limited burn history in Guánica Forest, Puerto Rico, following fire disturbance. Featuring a 29-year chronosequence, the dataset encompasses both short-term (2–5 months) and long-term (2–29 years) recovery, alongside mature forest control sites (including forest sites containing native grass). Data collection was conducted between May and August 2012 and focuses on woody tree species only. The dataset includes tree census data from seven sites (chrono_census.csv), recording species identity, stem diameter, aboveground biomass destruction, and resprouting dynamics. Additional data include species mean trait values, such as relative bark thickness and specific leaf area, to examine relationships with post-fire resprouting (chrono_traits.csv), and a species abundance matrix for evaluating community composition shifts over time (chrono_ndmsmatrix.csv). Field data were collected from circular 100 m² plots randomly placed at each site, with all woody plants tagged and identified. Stem diameters (≥1 cm) were measured at breast height (DBH) or ground height (DGH) in new-burn sites. Tree mortality was assessed, and aboveground biomass loss (0–100%) was estimated in new-burn sites. Resprouting was also quantified in short-term regeneration sites in mid-August 2012. In long-term sites, tree height was measured for the five tallest individuals. The dataset is relevant for researchers investigating tropical dry forest dynamics, fire ecology, and regeneration processes in Caribbean forest ecosystems. The dataset is complete and not ongoing.
Plant succession and biomass dynamics following logging and burning in Watersheds 1 and 3, Andrews Experimental Forest, 1962 to Present
Watersheds 1 and 3 in the HJ Andrews Experimental Forest have a long history of hydrologic, geomorphic, and ecological study. Long-term successional studies in the two watersheds are unprecedented in their scope and duration (1962 to present), spanning more than 50 years of post-logging measurements. To date, studies have focused on understory responses to logging and burning, early stand developmental processes (tree growth and mortality), and understory responses to canopy closure. Understory sampling was initiated in 1962, prior to harvest, and includes approximately 190, 2 x 2 m permanent understory plots. Measurements include estimates of ground-surface conditions and abundance (cover and biomass) of herbaceous, shrub, and tree species. After broadcast burning (1963 in WS3, 1966 in WS1) plots were sampled annually through 1972/1973, but less frequently thereafter (every 2-6 years). Studies of early stand development were initiated in 1979/1980, with sample plots collocated with the understory plots. In each of approximately 190, 250 m2 tree plots, all conifer and hardwood stems greater than or equal to 1.4 m tall are tagged, measured for diameter, and assessed for status (live or dead, including the cause of mortality). Both watersheds experienced recent snow-related windthrow (2019, 2020) and parts of WS1 burned in 2020 during the Holiday Farm Fire, adding complexity to the structure and composition of the understory and overstory communities.
Above ground plant and below ground stem biomass of samples from the severely burned site of the Anaktuvuk River fire, Alaska
Above ground plant and below ground stem biomass were measured in 2011 from three sites at and around the Anaktuvuk River Burn: severely burned, moderately burned and unburned. These samples were analyzed for carbon and nitrogen concentrations.
Summer soil temperature and moisture at the Anaktuvuk River Severely burned site from 2010 to 2013
Soil moisture and temperature were recorded at the Anaktuvuk River burn area during the summers from 2010 to 2013. Six sensors were deployed and measured temperature on half-hourly intervals over the summer and into the fall depending on battery function. Sensors were place in a hexagonal shape around a central data logger. Note that over time sensor depths changed due to frost heave and other environmental factors. All data contained should be treated as suspect where sensors may have been at surface. These sensors were removed August 20, 2013, no replacement sensors were installed.
Summer soil temperature and moisture at the Anaktuvuk River Moderately burned site from 2010 to 2013
Soil moisture and temperature were recorded at the Anaktuvuk River burn area during the summers from 2010 to 2013. Six sensors were deployed and measured temperature on half-hourly intervals over the summer and into the fall depending on battery function. Sensors were place in a hexagonal shape around a central datalogger. Note that over time sensor depths changed due to frost heave and other environmental factors. All data contained should be treated as suspect where sensors may have been at surface. These sensors were removed August 20, 2013, no replacement sensors were installed.
Effects of 2015 experimental burn on Eriophorum vaginatum at Toolik Lake Field Station, Alaska 2016
This was an experimental burn conducted in the summer of 2015 to provide sites for an experiment to see whether seeds of Eriophorum vaginatum from different ecotypes could establish in recently burned areas. It consisted of ten 2 meter X 2 meter plots along with a similar number of control plots. There was little seedling establishment but other data have been collected on the plots.
Alaska 2004 Burns: Growth and survival of tree seedlings in post-fire experimental transplant study across 39 sites
This dataset contains measurements of tree seedlings growth for an experimental transplant study 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. Seedlings were monitored for 10 years, with detailed measurements in 2006, 2008, 2011, 2013, and 2015. Aboveground biomass was harvested in 2011.
Overwintering Fires from 2009-2010 Burns near Fairbanks, Alaska: Post-fire Seedling Recruitment Collected 2023
This dataset contains data from adjacent overwintering and single-season burn sites. For the overwintering fires, we targeted locations that had burned in the summers of 2009, smouldered through the winter months, and reignited in 2010. Adjacent to these overwintering sites, we identified single-season burn sites from within portions of the 2009 fires that were unaffected by overwintering. A total of seven overwintering fire sites and four single-season fire sites were sampled. Within each site, three plots were established. Data inlcudes within plot measurments of post-fire seedling composition and density, residual SOL, burn depth estimated by black spruce adventitious roots, thaw depth, and pre-fire tree species composition and estimates of combustion. This is one of three packages from this project; this one contains the seedling recruitment data.
Overwintering Fires from 2009-2010 Burns near Fairbanks, Alaska: Residual Soil Organic Layer Depth, Burn Depth and Thaw Depth Collected 2023
This dataset contains data from adjacent overwintering and single-season burn sites. For the overwintering fires, we targeted locations that had burned in the summers of 2009, smouldered through the winter months, and reignited in 2010. Adjacent to these overwintering sites, we identified single-season burn sites from within portions of the 2009 fires that were unaffected by overwintering. A total of seven overwintering fire sites and four single-season fire sites were sampled. Within each site, three plots were established. Data inlcudes within plot measurments of post-fire seedling composition and density, residual SOL, burn depth estimated by black spruce adventitious roots, thaw depth, and pre-fire tree species composition and estimates of combustion. This is one of three packages from this project; this one contains the soils data.
Overwintering Fires from 2009-2010 Burns near Fairbanks, Alaska: Pre-fire Tree Species Density and Combustion Collected 2023
This dataset contains data from adjacent overwintering and single-season burn sites. For the overwintering fires, we targeted locations that had burned in the summers of 2009, smouldered through the winter months, and reignited in 2010. Adjacent to these overwintering sites, we identified single-season burn sites from within portions of the 2009 fires that were unaffected by overwintering. A total of seven overwintering fire sites and four single-season fire sites were sampled. Data inlcudes within plot measurments of post-fire seedling composition and density, residual SOL, burn depth estimated by black spruce adventitious roots, thaw depth, and pre-fire tree species composition and estimates of combustion. This is one of three packages from this project; this one contains the pre-fire tree species density and combustion data.
Burn Study Sites Quadrat Data for the Net Primary Production Study at the Sevilleta National Wildlife Refuge, New Mexico
In 2003, the U.S. Fish and Wildlife Service conducted a prescribed burn over a large part of the northeastern corner of the Sevilleta National Wildlife Refuge. Following this burn, a study was designed to look at the effect of fire on above-ground net primary productivity (ANPP) (i.e., the change in plant biomass, represented by stems, flowers, fruit and foliage, over time) within three different vegetation types: mixed grass (MG), mixed shrub (MS) and black grama (G). Forty permanent 1m x 1m plots were installed in both burned and unburned (i.e., control) sections of each habitat type. The core black grama site included in SEV129 is used as a G control site for analyses and does not appear in this dataset. The MG control site caught fire unexpectedly in the fall of 2009 and some plots were subsequently moved to the south. For details of how the fire affected plot placement, see Methods below. In spring 2010, sampling of plots 16-25 was discontinued at the MG (burned and control) and G (burned treatment only) sites, reducing the number of sampled plots to 30 at each.To measure ANPP (i.e., the change in plant biomass, represented by stems, flowers, fruit and foliage, over time), the vegetation variables in this dataset, including species composition and the cover and height of individuals, are sampled twice yearly (spring and fall) at each plot. The data from these plots is used to build regressions correlating biomass and volume via weights of select harvested species obtained in SEV157, "Net Primary Productivity (NPP) Weight Data." This biomass data is included in SEV185, "Burn Study Sites Seasonal Biomass and Seasonal and Annual NPP Data."
Burn Study Sites Seasonal Biomass and Seasonal and Annual NPP Data for the Net Primary Production Study at the Sevilleta National Wildlife Refuge, New Mexico
In 2003, the U.S. Fish and Wildlife Service conducted a prescribed burn over a large part of the northeastern corner of the Sevilleta NWR. This study was designed to look at the effect of fire on above-ground net primary productivity (ANPP) within different vegetation types. Net primary production (NPP) is a fundamental ecological variable that measures rates of carbon consumption and fixation. Estimates of NPP are important in understanding energy flow at a community level as well as spatial and temporal responses to a range of ecological processes. While measures of both below- and above-ground biomass are important in estimating total NPP, this study focuses on above-ground net primary production (ANPP). Above-ground net primary production (ANPP) is equal to the change in plant mass, including loss to death and decomposition, over a given period of time. To measure this change, ANPP is sampled twice a year (spring and fall) for all species in each of three vegetation types. In addition, volumetric measurements are obtained from adjacent areas to build regressions correlating biomass and volume. Three vegetation types were chosen for this study: mixed grass (MG), mixed shrub (MS) and black grama (G). Forty permanent 1m x 1m plots were installed in both burned and unburned sections of each habitat type. The core black grama site included in SEV129 was incorporated into this dataset as an unburned control, so an additional unburned G site was not created. The data for this site is noted as site=G and treatment=C (i.e., control). The original mixed-grass unburned plot caught fire unexpectedly in the fall of 2009 and was subsequently moved to the south. Volumetric measurements are made using vegetation data from permanent plots collected in SEV156, "Burn Study Sites Quadrat Data for the Net Primary Production Study" and regressions correlating biomass and volume constructed using seasonal harvest weights from SEV157, "Net Primary Productivity (NPP) Weight Data."
State of Wildfires 2024-25: Regional Summaries of Burned Area, Fire Emissions, and Individual Fire Characteristics for National, Administrative and Biogeographical Regions
<p>This dataset supports the State of Wildfires 2024-25 report under review at <em>Earth System Science Data</em> (Kelley et al., <em>under review)</em>. It is an update of the State of Wildfires 2023-24 report (Jones et al. 2024). The dataset provides annual data and final-year anomalies in burned area (BA), fire carbon (C) emissions, and fire properties (e.g. distributional statistics for fire count, size, rate of growth). Annual data relate to the global fire season defined as March-February (e.g., March 2024-February 2025), aligning with an annuall lull in the global fire calendar (see Jones et al., 2024). The complete methodology is described by Kelley et al. (<em>under review</em>).</p> <h3>Citation</h3> <p>Work utilising our regional summaries should <strong>cite both Kelley et al. (under review) AND the primary reference for the variable(s) of interest</strong> as follows:</p> <ul> <li>Giglio et al. (2018) for MODIS MCD64A1 BA.</li> <li>van der Werf et al. (2017) for GFED4.1s fire C emissions.</li> <li>Kaiser er al. (2012) for GFAS fire C emissions.</li> <li>van der Werf et al. (2017) AND Kaiser er al. (2012) for the average of GFED4.1s and GFAS fire C emissions.</li> <li>Andela et al. (2019) for the Global Fire Atlas.</li> <li>Giglio et al. (2016) for the Fire Radiative Power (FRP) observations.</li> <li>Chuvieco et al. (2024) for FireCCIS311 BA.</li> <li>Giglio et al. (2024) for VIIRS VNP64A1 BA.</li> </ul> <h3>Input Data</h3> <p><strong>Burned Area (BA)</strong></p> <ul> <li>BA data from NASA’s MODIS BA product (MCD64A1) are extended from Giglio et al. (2018) and are available from <a href="https://lpdaac.usgs.gov/products/mcd64a1v061/">Giglio et al. (2021)</a>. <ul> <li>Period: 2002-February 2025</li> <li>Resolution: 500m, daily</li> </ul> </li> <li>BA data from ESA's Climate Change Initiative BA product (FireCCIS311) are extended from Lizundia-Loiola et al. (2022) and are available from <a href="Chuvieco,%20E.;%20Pettinari,%20M.L.;%20Lizundia-Loiola,%20J.;%20Khairoun,%20A.;%20Danne,%20O.;%20Boettcher,%20M.;%20Storm,%20T.%20(2024):%20ESA%20Fire%20Climate%20Change%20Initiative%20(Fire_cci):%20Sentinel-3%20SYN%20Burned%20Area%20Grid%20product,%20version%201.1.%20NERC%20EDS%20Centre%20for%20Environmental%20Data%20Analysis,%2029%20February%202024.%20https://catalogue.ceda.ac.uk/uuid/da8e669a74334c82a56e0b470bc4ef04">Chuvieco et al. (2024)</a>. <ul> <li>Period: 2019-February 2025</li> <li>Resolution: 300m, daily</li> </ul> </li> <li>BA data from NASA’s VIIRS BA product (VNP64A1) are available from <a href="https://lpdaac.usgs.gov/products/vnp64a1v002/">Giglio et al. (2024)</a>. <ul> <li>Period: 2012-February 2025 (only the data after 2019 are used for consistency in the comparisons between MCD64A1, FireCCIS311, and VNP64A1).</li> <li>Resolution: 500m, daily</li> </ul> </li> </ul> <p><strong>Fire Carbon (C) Emissions</strong></p> <ul> <li>GFED4.1s fire C emissions data are extended from van der Werf and are available at <a href="https://globalfiredata.org/">https://globalfiredata.org/</a>. <ul> <li>Period: 2003-February 2025</li> <li>Resolution: 0.25 degree, daily</li> </ul> </li> </ul> <ul> <li>GFAS fire C emissions data are extended from Kaiser et al. (2012) and are available from the <a href="https://confluence.ecmwf.int/display/CKB/CAMS+global+biomass+burning+emissions+based+on+fire+radiative+power+%28GFAS%29%3A+data+documentation">ECMWF Confluence Server</a>. <ul> <li>Period: 2003-February 2025</li> <li>Resolution: 0.1 degree, daily</li> </ul> </li> </ul> <p><strong>Global Fire Atlas (Individual Fire Properties)</strong></p> <ul> <li>Global Fire Atlas data are extended from Andela et al. (2019) and are available from the repository maintained by <a href="https://doi.org/10.5281/zenodo.11400062">Andela and Jones (2025)</a>. <br> <ul> <li>Period: 2002-February 2025</li> <li>Driven by 500m MODIS BA data (collection 6.1)</li> </ul> </li> </ul> <p><strong>Fire Intensities</strong></p> <ul> <li>FRP data are extended from MOD14A1 and MYD14A1 (Giglio et al., 2016) and are available at <a href="https://lpdaac.usgs.gov/products/mod14a1v061/">Giglio and Justice (2021)</a>.<br> <ul> <li>Period: 2002-February 2025</li> <li>Resolution: 1km, daily</li> </ul> </li> </ul> <h3>Regional Analysis</h3> <p>We performed "cookie-cutting" (spatial and temporal masking) of the above input data sets to features in each of the following regional layers (e.g. per country in the "Countries" layer). </p> <p>The statistics derived from cookie-cutting are listed below. Full details in Kelley et al. (2025).</p> <div> <table> <tbody> <tr> <td> <p>Layer</p> </td> <td> <p>Short Form </p> </td> <td> <p>Source</p> </td> </tr> <tr> <td> <p>Biomes</p> </td> <td> <p>NA</p> </td> <td> <p>Olson et al. (2001)</p> </td> </tr> <tr> <td> <p>Ecoregions</p> </td> <td> <p>NA</p> </td> <td> <p>Olson et al. (2001)</p> </td> </tr> <tr> <td> <p>Continents</p> </td> <td> <p>NA</p> </td> <td> <p>ArcGIS Hub (2024)</p> </td> </tr> <tr> <td> <p>Continental Biomes</p> </td> <td> <p>NA</p> </td> <td> <p>See above</p> </td> </tr> <tr> <td> <p>Countries</p> </td> <td> <p>NA</p> </td> <td> <p>EU Eurostat (2020)</p> </td> </tr> <tr> <td> <p>UC Davis Global Administrative Areas (GADM) Level 1</p> </td> <td> <p>GADM-L1</p> </td> <td> <p>UC Davis (2022)</p> <br><br></td> </tr> <tr> <td> <p>Intergovernmental Panel on Climate Change Sixth Assessment Report (AR6) Working Group I (WGI) Reference Regions </p> </td> <td> <p>IPCC AR6 WGI Regions</p> </td> <td> <p>Iturbide et al. (2020)</p> </td> </tr> <tr> <td> <p>Global C Project Regional C Cycle Assessment and Processes (RECCAP2) Reference Regions</p> </td> <td> <p>RECCAP2 Regions</p> </td> <td> <p>Ciais et al. (2022)</p> </td> </tr> <tr> <td> <p>Global Fire Emissions Database (GFED) Basis Regions</p> </td> <td> <p>GFED4.1s Regions</p> </td> <td> <p>van der Werf et al. (2006)</p> </td> </tr> </tbody> </table> </div> <h3> </h3> <h3>Regional Statistics and Anomalies</h3> <ul> <li><strong>Burned Area (BA)</strong> <ul> <li>Calculated regional totals for each fire season.</li> <li>Relative and standardized anomalies from historical data (since 2002).</li> <li>Ranking amongst all recorded fire seasons.</li> <li>Onset, peak, and cessation based on monthly deviations from climatological means.</li> </ul> </li> </ul> <ul> <li><strong>Carbon Emissions</strong> <ul> <li>Calculated regional totals for each fire season.</li> <li>Relative and standardized anomalies from historical data (since 2003).</li> <li>Ranking amongst all recorded fire seasons.</li> <li>Onset, peak, and cessation based on monthly deviations from climatological means.</li> <li>Statistics available for GFAS, GFED, and their mean.</li> </ul> </li> </ul> <ul> <li><strong>Individual Fire Properties</strong> <ul> <li>Based on values of individual fire size and rate of growth ignition from the ignition point vectors of the Global Fire Atlas.</li> <li>Calculated regional count.</li> <li>Calculated regional maxima and 95th percentiles of fire size and rate of growth for each fire season.</li> <li>Relative and standardized anomalies from historical data (since 2002).</li> <li>Ranked anomalies among all recorded fire seasons.</li> </ul> </li> </ul> <ul> <li><strong>Fire Intensity</strong> <ul> <li>Based on active fire observations of FRP, which are pooled within each fire of the Global Fire Atlas.</li> <li>For each fire, the 95th percentile value of all FRP observations is the assigned intensity value (i.e. a "peak fire intensity" omitting any spurious high-end values).</li> <li>Regionally, the peak fire intensity values are averaged across individual fires.</li> <li>Relative and standardized anomalies from historical data (since 2002).</li> <li>Ranked anomalies among all recorded fire seasons.</li> </ul> </li> </ul>
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.