Find research datasets worth reusing

opencc-by-4.0Nov 2021View details →

Data from: A burning issue: Savanna fire management can generate enough carbon revenue to help restore Africa's rangelands and fill Protected Area funding gaps

Many savanna-dependent species in Africa including large herbivores and apex predators are at increasing risk of extinction.  Achieving effective management of protected areas (PAs) in Africa where lions live will cost an estimated USD >$1-2 B/year in new funding. We explored the potential for fire management-based carbon-financing programs to fill this funding gap and benefit degrading savanna ecosystems. We demonstrated how introducing early dry season fire management programs could produce potential carbon revenues (PCR) from either a single carbon-financing method (avoided emissions) or from multiple sequestration methods ranging from USD $59.6-$655.9 M/year (at USD $5/ton) or USD $155.0 M–$1.7 B/year (at USD $13/ton).  We highlighted variable but significant PCR for savanna PAs from USD $1.5–$44.4 M/year per PA. We suggest investing in fire management programs to jump-start the United Nations Decade of Ecological Restoration to help restore degraded African savannas and conserve imperiled keystone herbivores and apex predators.  Open Access article: <a href="https://doi.org/10.1016/j.oneear.2021.11.013">https://doi.org/10.1016/j.oneear.2021.11.013</a>

opencc-by-4.0Mar 2022View details →

Data for research article "CCS investment – fiddling while the planet burns"

This data set contains electricity systems and technology data for the UK, Poland, Texas, Wyoming, South Korea, and Indonesia. This data was used for modeling and analysis for the research article titled 'CCS investment – fiddling while the planet burns', authored by Yoga Wienda Pratama and Niall Mac Dowell from Imperial College London. In this work, we modeled and optimised the systems using Electricity Systems Optimisation framework (DOI: 10.5281/zenodo.1048943) that was developed General Algebraic Modeling System (GAMS). Data for this study is therefore provided in .gdx format that is suitable for GAMS. Procedure to reproduce this study is discussed in the article. Further questions can be addressed to Yoga Wienda Pratama (y.pratama18@imperial.ac.uk) or Niall Mac Dowell (niall@imperial.ac.uk).

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Data from: Pyrophilic plants respond to post-fire soil conditions in a frequently burned longleaf pine savanna

Fire-plant feedbacks engineer recurrent fires in pyrophilic ecosystems like savannas. The mechanisms sustaining these feedbacks may be related to plant adaptations that trigger rapid responses to fire's effects on soil. Plants adapted for high fire frequencies should quickly regrow, flower, and produce seeds that mature rapidly and disperse post-fire. We hypothesized that offspring of such plants would germinate and grow rapidly, responding to fire-generated changes in soil nutrients and biota. We conducted an experiment using longleaf pine savanna plants that were paired based on differences in reproduction and survival under annual ("more" pyrophilic) vs. less frequent ("less" pyrophilic) fire regimes. Seeds were planted in different soil inoculations from experimental fires of varying severity. The "more" pyrophilic species displayed high germination rates followed by species specific, rapid growth responses to soil location and fire severity effects on soils. In contrast, the "less" pyrophilic species had lower germination rates that were not responsive to soil treatments. This suggests that rapid germination and growth constitute adaptations to frequent fires, and that plants respond differently to fire severity effects on soil abiotic factors and microbes. Further, variable plant responses to post-fire soils may influence plant community diversity and fire-fuel feedbacks in pyrophilic ecosystems.

opencc-zeroJun 2022View details →

opencc-by-4.0Aug 2022View details →

Crop Residue Burning Emission Coefficients

This dataset provides a comprehensive collection of crop-specific coefficients related to the burning of agricultural waste or “residue”: Emission Factors, Combustion Efficiencies, and Crop-to-Residue Ratios. The crop-type emission factor tables contain the corresponding reference number, author citations, location, field/lab/expert flag, with average minus one standard deviation (“Minus SD”), average (or stated value), and average plus one standard deviation (“Plus SD”) emission factor values for CO2, CO, CH4, NOx, SO2, NH3, PM2.5, and PM10.0, and a notes column. There is a corresponding emission factor table reference list. There are emission factor tables for wheat, rice, sugarcane, maize, generic, and miscellaneous crops (beans, alfalfa, millet, cotton, rapeseed, sorghum, and barley). The combustion efficiency table contains the corresponding reference number, author citations, field/lab/expert flag, with average minus one standard deviation (“Minus SD”), average (or stated value), and average plus one standard deviation (“Plus SD”) values for wheat, maize, sugarcane, rice, and generic crops. There is a corresponding combustion efficiency table reference list.  The crop-to-residue table contains values for wheat, maize, rice, cotton, soybean, sugarcane, alfalfa, barley, beans, and sorghum. The references are also provided.

opencc-by-4.0May 2024View details →

Role of bark beetle disturbance and fuel types on fire radiative power and burn severity in the Bohemian-Saxon Switzerland - Data and Material.

This data repository includes different datasets for fuel types, burn severity, fire radiative power and burned area, which were analysed and used in our paper on the Role of bark beetle disturbance and fuel types on fire radiative power and burn severity in the Bohemian-Saxon Switzerland. Study area: National Park Bohemian and Saxon Switzerland and conservation areas, Germany and Czech Republic. Burn severity: dnbr_fire22.nc – Burn severity data covering the burned area, which has been calculated with the Difference Normalized Burn Index (dNBR) using Sentinel-2 and Landsat 8, 9 images. Remote sensing images were reprojected and resampled to 10 m to ensure harmonization before index calculation. cbi.csv – Burn severity surveyed in the field in autumn 2022 as validation data for the dNBR. Contains: ID, coordinates, CBI, CBI values separated for different strata (A to E) and individual strata variables, forest type and species for intermediate trees (strata D) and tall trees (strata E), and the dNBR value that covered the plot extent. Burned area: burned_area.shp – Burned area was mapped by rangers in the Saxon Switzerland National Park and was taken from the dataset provided by the Copernicus Emergency Management Service (EMS) for the Bohemian Switzerland National Park. FRP: frp.nc - Fire Radiative Power gridded to 300 m and clipped to the burned area. FRP during the main fire spread 24/07/22 - 29/07/22.  Fuel: fueltype_bohemiansaxonswitzerland.nc/fueltype_bohemiansaxonswitzerland_postfire.nc – Raster datasets (10m spatial resolution, EPSG:32633) of fuels present in the area before and after the fire. The fuel classification system can be found in the fuel_classification.xlsx. fuel_classification.xlsx – The fuel type classification system for the study area. Fuel type ID's as seen in fueltype_bohemiansaxonswitzerland.nc (pre- and postfire).

Figure 6 in Oral glutamine dipeptide or oral glutamine free amino acid reduces burned injury progression in rats

Figure 6. Graphical representation of Glutathione (ΜM) in the seven days after injury in G1-Control, G2-Dip, and G3-Free AA. G2-Dip presented a larger amount concerning the G1-Control *(P<0.05).

Figure 4 in Oral glutamine dipeptide or oral glutamine free amino acid reduces burned injury progression in rats

Figure 4. Graphical representation of interspace (stasis) regions length (mm) in the seven days after injury in G1-Control,G2-Dip, and G3-FreeAA.G1-Control presented smaller interspaces in 666 relation to the treated groups G2-Dip (P<0.01) and G3-FreeAA *(P<0.01).

Figure 5 in Oral glutamine dipeptide or oral glutamine free amino acid reduces burned injury progression in rats

Figure 5. Graphical representation of fibroblast counts in three fields of the interspace dermis among in the seven days after injury in G1-Control, G2-Dip, and G3-FreeAA. G1-Control presented less amount of fibroblast concerning the treated groups G2-Dip (P<0.01) and G3-Free AA *(P<0.01).

Figure 3 in Oral glutamine dipeptide or oral glutamine free amino acid reduces burned injury progression in rats

Figure 3. Histopathology study of the necrotic areas: (A) Photomicrograph of G2-Dip animal, with necrosis presence in the dermis (superior arrows) just below the epidermis (E) and in the hypodermis (arrows below in the right). Hair follicle (HF). Masson's trichrome; 100x; (B) Photomicrograph of G1-Control animal, hemorrhagic foci are observed in both dermis and hypodermis (arrows). Central blood vessel (BV). Masson's trichrome; 400x; (C) Photomicrograph of G3-FreeAA animal, with a large area of edema in both dermis and hypodermis (arrows). Hair follicle (HF). Masson's trichrome; 100x; (D) Photomicrograph of G1-Control animal: hemorrhagic focus can be observed in the hypodermis and many neutrophils (minor arrows) in a blood vessel (BV) lumen, some in diapedesis through its wall (larger arrow). The thinner arrows show a small intercellular inflammatory infiltrate. Giemsa; 400x.

Figure 2 in Oral glutamine dipeptide or oral glutamine free amino acid reduces burned injury progression in rats

Figure 2. Graphical representation of necrosis percentage evolution obtained by photographic analysis in the burn interspace, two and seven days after injury in G1-Control, G2-Dip and G3-FreeAA. In the G3-FreeAA there was a significant reduction of necrosis between two and seven days *(P<0.05).

Figure 1 in Oral glutamine dipeptide or oral glutamine free amino acid reduces burned injury progression in rats

Figure 1. Rat comb burn model: (A) Comb metal plate; (B) Comb burn injury, with four rectangular full-thickness burn areas separated by three unburned interspaces (stasis zone); (C) rectangular burned full thickness areas just after the injury; (D) animal from treated group 7 days after injury showing interspaces (stasis zone) without necrosis.

FLAME: a novel approach for modelling burned area in the Brazilian biomes using the Maximum Entropy concept - Input Data

This repository contains driving data used by training and evaluation of FLAME in the "FLAME: a novel approach for modelling burned area in the Brazilian biomes using the Maximum Entropy concept" paper. All NetCDF files are on regular, 0.5-degree grids on a monthly timestep over Brazil.  <div>Not all variables were used in the final analysis <table> <tbody> <tr> <td>               NetCDF File</td> <td>     Variable </td> <td> Used/not Used </td> <td> Source/Reference </td> </tr> <tr> <td> burned_area.nc </td> <td> Burned area </td> <td> As training data </td> <td>MCD64A1/ Giglio et al. (2018)</td> </tr> <tr> <td> burned_area_nat_veg.nc </td> <td> Burned area in natural vegetation </td> <td> As training data </td> <td>MCD64A1/ Giglio et al. (2018) and Mapbiomas, 2022</td> </tr> <tr> <td> burned_area_non_nat_veg.nc </td> <td> Burned area in non natural vegetation </td> <td> As training data </td> <td>MCD64A1/ Giglio et al. (2018) and Mapbiomas, 2022</td> </tr> <tr> <td>  tas_max.nc </td> <td>  Maximum Temperature </td> <td> Used </td> <td> ISIMIP3a FRIELER et al. (2023) </td> </tr> <tr> <td> precip.nc </td> <td> Precipitation </td> <td> Used </td> </tr> <tr> <td> vpd.nc </td> <td> Vapor pressure deficit </td> <td> Not Used </td> </tr> <tr> <td> rhumid.nc </td> <td>  Relative Humidity  </td> <td> Not Used </td> </tr> <tr> <td> consec_dry_days.nc</td> <td> Consecutive number of dry days  </td> <td>Not Used</td> </tr> <tr> <td> soilM.nc </td> <td> Soil  Moisture </td> <td> Not Used </td> <td> JULES-ES </td> </tr> <tr> <td> lightn.nc    </td> <td>  Lightning </td> <td> Not Used </td> <td>  ISIMIP3a FRIELER et al. (2023) </td> </tr> <tr> <td> popDen.nc </td> <td>  Population density </td> <td> Not Used </td> </tr> <tr> <td> road_density.nc </td> <td> Road density </td> <td>Used</td> <td>  GRIP global (MEIJER et al., 2018) </td> </tr> <tr> <td> cveg.nc </td> <td> Vegetation carbon </td> <td> Not Used </td> <td> JULES-ES </td> </tr> <tr> <td> csoil.nc </td> <td> Carbon in dead vegetation </td> <td>Used</td> <td> JULES-ES </td> </tr> <tr> <td> forest.nc </td> <td>   Forest </td> <td> Used </td> <td>  MAPBIOMAS, 2022 </td> </tr> <tr> <td> grassland.nc </td> <td>   Grassland </td> <td> Not Used </td> </tr> <tr> <td> savanna.nc </td> <td>   Savanna </td> <td> Not Used </td> </tr> <tr> <td> cropland.nc </td> <td>   Cropland </td> <td> Not Used </td> </tr> <tr> <td> pasture.nc </td> <td>   Pasture </td> <td> Used </td> </tr> <tr> <td> np.nc </td> <td> Number of patches  </td> <td> Not Used </td> <td> Calculated from MAPBIOMAS, 2022 </td> </tr> <tr> <td> ed.nc  </td> <td>Edge density</td> <td>Used</td> </tr> </tbody> </table> </div>

Water level data from the Tarland Burn, Aberdeenshire, Scotland, 1st January - 31st December 2023

Water level was recorded, in hourly intervals, at four locations on the Tarland Burn,  Aberdeenshire, Scotland from 1st January to 31st december 2023.  Measurements were made using pressure transducers and logging equipment supplied by Campbell Scientific. Station latitude and longitude are provided. Blank cells in the data sheets are due to instrument failure or temporary loss of power. This data can be used to extend the series of previously published data from 2013- 2022 (https://doi.org/10.5281/zenodo.7777653) which also included rating curves derived using a Valeport electromagnetic flow meter (801 model), or ADCP "boat" at higher water level. This work has been funded by the Scottish Government as part of the strategic research programme and provides empirical data which underpins research on natural flood management, water quality, and biodiversity.

opencc-zeroJun 2024View details →

Dataset: Burning Rock Biotech Limited (BNR) Stock Performance

This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.

Fig. 3 in Evaluation Of Teratogenic Activity Of The Smoke Of Burning Combustible Plastic Influencing The Drosophila Melanogaster

Fig. 3. Amount of abdominal tergite anomalies in wild type Drosophila melanogaster depending on the dose of burning plastic (polysterene) smoke and larvae age (hours after eggs are laid)

Fig. 4 in Evaluation Of Teratogenic Activity Of The Smoke Of Burning Combustible Plastic Influencing The Drosophila Melanogaster

Fig. 4. Amount of abdominal tergite anomalies in wild type Drosophila melanogaster depending on the dose of burning plastic (polysterene) smoke and pupae age (hours after eggs are laid)

Fig. 9 in Evaluation Of Teratogenic Activity Of The Smoke Of Burning Combustible Plastic Influencing The Drosophila Melanogaster

Fig. 9. Abdominal tergite anomalies in wild type Drosophila melanogaster in the result of treating pupae with the smoke of burning polysterene; 1 – females, 2 – males

Fig. 2 in Evaluation Of Teratogenic Activity Of The Smoke Of Burning Combustible Plastic Influencing The Drosophila Melanogaster

Fig. 2. Amount of abdominal tergite anomalies in wild type Drosophila melanogaster depending on the dose of burning plastic (polyethyleneterephtalane) smoke and pupae age (hours after eggs are laid)

Fig. 1 in Evaluation Of Teratogenic Activity Of The Smoke Of Burning Combustible Plastic Influencing The Drosophila Melanogaster

Fig. 1. Amount of abdominal tergite anomalies in wild type Drosophila melanogaster depending on the dose of burning plastic (polyethyleneterephtalane) smoke and larvae age (hours after eggs are laid)