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1,693 results for “droughts”
Harmonized Palmer Drought Severity Indices throughout the Contiguous United States for HydroBASINS basins
In times of a changing hydroclimate and growing human population, there is a need to assess how various climatic and demand conditions influence water availability on the landscape. Tendency for drought conditions is a prime example of a key hydroclimatic metric that is useful for understanding water retention in the surrounding landscape. However, merging drought climatological data with co-located aquatic data is challenging. To facilitate national-scale analyses of basin-level drought conditions (i.e., Palmer Drought Severity Index; PDSI) with co-located water quality data, we present aggregated PDSI data for the contiguous United States. Data are aggregated using the HydroBASINS basin shapefiles. HYBAS_ID is retained to enable merging with HydroBASINS parent datasets.
Drought experiment on aquatic vertebrate populations in McRae Creek, HJ Andrews Experimental Forest, 2022
Three distinct reaches in McRae Creek west tributary (MCTW) within the HJ Andrews Experimental Forest in western Oregon were designated for manipulation and data collection. Manipulations included increasing the temperature (T), reducing streamflow (Q), and a reference (R reach). Population estimates of vertebrates, specifically Coastal Cutthroat Trout and Coastal Giant Salamander, were obtained using three-pass depletion methods in each reach. A Before-After-Control-Impact (BACI) design was implemented, distinguishing between the "Before" and "After" periods. "Before" surveys were conducted from July 18th to 20th, 2022, while "After" surveys occurred from September 8th to 9th, 2022. During the surveys, each species was identified, noting life stage, and relevant measurements were taken. For trout, these included the length from the snout to the tail fork (Length_Fork_Vent), the snout to the tail (Length_Tail), and weight. In the "Before" survey, all trout were tagged with elastomer tags: red for the T reach, yellow for the Q reach, and orange for the R reach. Trout larger than 80 mm also received PIT tags in their abdominal cavities. Salamanders were measured similarly, not elastomer or PIT tags were applied. During the "After" survey, no new elastomer or PIT tags were inserted; only previously tagged fish were recorded. Additionally, stream cross-sections were surveyed every 5 meters to document stream dimensions. Recorded data included the location, reach, sample date, BACI status, and distance downstream from the upstream cross-section (0 meters). Measurements at each cross-section included wetted width, bankfull width, and depths at five evenly spaced points. Furthermore, pools were identified and measured in each reach, noting the maximum pool depth, depth at the outflow, width, and length. Temperature sensors were installed in each reach, recording stream temperature every 15 minutes. Sensor locations were recorded as the distance downstream from the top of e
Ants in an Induced Drought Experiment at the Caxiuana National Forest in Brazil 2011-2012
Environmental change scenarios caused by low precipitation forecast species loss in tropical regions. We used one year of data from a rainwater exclusion experiment in primary Amazonian rainforest to test whether induced water stress, and covarying changes in humidity, soil respiration, and tree species richness, size, and total biomass and its diversity affected species richness and composition (relative abundance) of ground-dwelling ants. Induced drought reduced ant richness, whereas increased humidity and variability in biomass increased it. Species composition differed between control and rainfall-excluded plots. Occurrence of many ant species was strongly reduced, but some generalist groups of ants were favored by induced drought. The expected loss of ant species and changes in ant species composition in tropical forests likely will lead to cascading effects on ecosystem processes and services they mediate.
Leaf spectroscopy and active fluorescence datasets for early drought and nitrogen stress diagnosis in tomato
<p>The dataset contains different plant physiological parameters collected during a 14-day stress and recovery experiment on tomato (<em>Solanum lycopersicum</em> L. cv Moneymaker) plants, undergoing a nitrogen deficiency, drought or control treatment. </p> <p>A full description of the experiment, together with the scientific results, is published by Pescador-Dionisio et al. (2024), and can be found through: <a href="https://doi.org/10.1111/nph.20253">https://doi.org/10.1111/nph.20253.</a></p> <p>The goal of the dataset collection was to obtain a non-invasive proximal sensing dataset at leaf level (reflectance, transmittance, upward and downward fluorescence), in parallel to gas exchange and active fluorescence measurements. The leaf spectroscopy dataset was further processed by a pigment spectral unmixing algorithm according to Van Wittenberghe et al. (2024), to calculate fluorescence quantum efficiency (<em><strong>FQE</strong></em>) and effective absorbance (<strong><em>A_eff</em></strong>) changes associated to the activation of regulated heat dissipation (<strong><em>A_eff_535_Xan</em></strong>). The latter absorption feature is linked to the xanthophyll ('<strong>Xan</strong>') absorption in the 500-600 nm range, which is modelled by the sum of three Gaussians. For a full description of this feature, see Van Wittenberghe et al. (2021).</p> <p>Gas exchange and active fluorescence measurements were carried out with a LI-6400 portable photosysthesis system (LI-COR Biosciences, Lincoln, USA) equipped with a 6400-40 leaf chamber fluorometer. Steady-state measurements were done at 300 and 1000 μmol m−2 s−1 ('<strong><em>PAR300</em></strong>' and '<em><strong>PAR1000</strong></em>'), i.e. growing light conditions and light saturating conditions. Light response curves were taken on different days. Common fluorescence parameters (e.g., <em><strong>Fv/Fm, Fo, Fm, NPQ, YNO, YNPQ</strong></em>) are provided together with 'sustained' and reversible' NPQ parameters calculated according Porcar-Castell (2011).</p> <p>Leaf spectroscopy and active steady-state fluorescence measurements were performed on the same measuring days ('<em><strong>d0</strong></em>', '<em><strong>d2</strong></em>', '<em><strong>d4</strong></em>', '<em><strong>d7</strong></em>', '<em><strong>d14</strong></em>') and on the same leaf, both at 300 and 1000 μmol m−2 s−1 ('<em><strong>PAR300</strong></em>' and '<em><strong>PAR1000</strong></em>'), taking into account an adaptation time. We used a LED light source and several filters, placed in front of a FluoWat leaf clip, which was connected to two high-performance VIS-NIR spectroradiometers (QEPRO, Ocean Insight Inc., Orlando, Florida, USA). The spectroscopy measurements are presented in the Matlab structures for each measuring day, e.g. "<strong><em>2023_d0_Leaf_Spec_Tomato_Stress.mat</em></strong>".</p> <p>The outputs of the pigment spectral fitting code are presented by Matlab structures, e.g. "<strong><em>2023_d0_Leaf_Fitting_Tomato_Stress.mat</em></strong>", which contains the effective absorbance fitting (<strong><em>A_eff</em></strong>) of each pigment (<strong>Chl a, Chl b, Carotene-b, Anthocyanins, and Xanthophylls</strong>) for the wavelength range [500-780] nm, the absorbed photosynthetically active radiation by Chlorophyll a ('<em><strong>APAR_Chla</strong></em>') for the wavelength range [400-800] nm, and the fluorescence quantum efficiency, calculated as the ratio of the emitted fluorescence photons and the flux of photons absorbed by Chlorophyll a. </p> <p>Additional metadata from HPLC photosynthetic pigment analyses, xanthophyll-related enzyme expression, biomass and total content of elemental nitrogen are provided.</p> <p>Please follow the README files for more detailed information.</p> <p> </p>
Drought Code - ERA-Interim
<p>The Drought Code (DC) is a numeric rating of the average moisture content of deep, compact organic layers. This code is a useful indicator of seasonal drought effects on forest fuels and the amount of smoldering in deep duff layers and large logs.</p> <p>This is part of a larger dataset providing gridded field calculations from the Canadian Fire Weather Index System using weather forcings from the European Centre for Medium-range Weather Forecast (ECMWF) ERA-Interim reanalysis dataset (Vitolo et al., 2019; Di Giuseppe et al., 2016). The dataset has been developed through a collaboration between the Joint Research Centre and ECMWF under the umbrella of the Global Wildfires Information System (GWIS), a joint initiative of the GEO and the Copernicus Work Programs. The whole dataset consists of seven indices, each of which describes a different aspect of the effect that fuel moisture and wind have on fire ignition probability and its behavior, if started. The indices are called: 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). For convenience, each index is archived separately. </p> <p>Data are generated using the open source software GEFF v3.0 (https://git.ecmwf.int/projects/CEMSF/repos/geff), which now uses settings and parameters provided by the JRC (more info here https://git.ecmwf.int/projects/CEMSF/repos/geff/browse/NEWS.md). </p> <p>This dataset can be manipulated using the caliver R package (Vitolo et al. 2017, 2018). </p> <p>Details: </p> <ul> <li> <p>File format: netcdf4 </p> </li> <li> <p>Coordinate system: World Geodetic System 1984 (also known as WGS 1984, EPSG:4326). </p> </li> <li> <p>Longitude range: [-180, +180] </p> </li> <li> <p>Latitude range: [-90, +90] </p> </li> <li> <p>Temporal resolution: 1 day </p> </li> </ul> <ul> <li> <p>Spatial resolution: 0.7 degrees (~80 Km) </p> </li> <li> <p>Spatial coverage: Global </p> </li> <li> <p>Time span: from 1980-01-01 to 2018-12-31 </p> </li> </ul>
Harmful algal bloom and aquatic weeds data from the Sacramento-San Joaquin Delta, collected to evaluate the impact of the 2021 Temporary Urgency Change Order and Emergency Drought Barrier
Condition 8 of the June 2021 Temporary Urgency Change Order for the Central Valley Project (CVP) and State Water Project (SWP) requires a special study of harmful algal blooms (HABs) in the Sacramento–San Joaquin Delta (Delta) and the spread of submersed aquatic vegetation (SAV), and floating aquatic vegetation (FAV), also referred to as “aquatic weeds”. A report on the study was submitted to the State Water Resources Control Board on June 1, 2022. This data package contains all publicly available data used in the report, including visual cyanobacteria reports, cyanotoxin data, water quality, nutrients, flow/hydrodynamics, chlorophyll-a concentrations, temperature, coverage of SAV and FAV, use of herbicides, and human populations. Many of these data were derived from other datasets, though some were collected specifically for this study
Data for: Climate warming and drought effects on volatile organic compound emissions from Solidago altissima
Volatile organic compounds (VOCs) were collected from Solidago altissima in drought and warming treatments in the KBS-LTER Rain Exclusion Experiment (REX). This sampling took place in July 2022 when the plants had been experiencing warming (via open-top chambers) for 20 months, and drought (via rainout shelters) for 3 weeks. The data presented here are the final data files used for analysis, and contain VOC abundance values per plant across the four climate treatments: ambient, warmed, drought, and warmed + drought. Code is available at: https://github.com/dobsonk2/REX_VOCs (https://doi.org/10.5281/zenodo.15169943)
Fungal litter mat cover in Cannopy Trimming Experiment (CTE) plots responses to canopy opening, hurricanes and drought
Fungi that bind leaf litter into mats and produce white-rot via degradation of lignin and other aromatic compounds influence forest nutrient cycling and soil fertility. Over three and a half years beginning in June 2014, 6 months before the second iteration of the Canopy Trimming Experiment (CTE), we measured quarterly the extent of white-rot litter mats formed by basidiomycete fungi in the Luquillo Mountains of Puerto Rico in response to disturbances – a simulated hurricane treatment executed by canopy trimming and debris addition in December 2014 (CTE0, a mid-year drought in 2015, and two hurricanes 10 days apart in September 2017. Percent fungal litter mat cover ranged from 0.4% after hurricanes Irma and Maria to a high of 53% in forest with undisturbed canopy prior to the 2017 hurricanes, with means mostly between 10 - 45% of fungal litter mat cover in undisturbed forest. Drought decreased litter mat cover in both treatments, except in one undisturbed plot dominated by a drought-resistant fungus, Marasmius crinis-equi. Percent fungal litter mat cover sharply declined after real hurricanes and the simulated hurricane treatment (CTE). We found that solar radiation had a significant treatment effect and was strongly negatively correlated with percent litter mat cover within each of the four climatic seasons. Solar radiation was also strongly negatively correlated with relative humidity, throughfall, rain and litter wetness. However, rainfall was negatively correlated with litter mat cover, possibly due to erosion or saturation during high rainfall events. Canopy opening reduced leaf litterfall rates but did not affect litter mat cover. The main negative effect on basidiomycete fungi that bind leaf litter into mats was lower litter moisture associated with increased solar radiation from canopy opening and high leaf fall during drought. Variation in drought tolerance among basidiomycete fungal litter mat formers provided some resilience to drought. \<para\> Support f
Extreme Drought in Grassland Ecosystems (EDGE) Net Primary Production Quadrat Data at the Sevilleta National Wildlife Refuge, New Mexico
EDGE is located at six grassland sites that encompass a range of ecosystems in the Central US - from desert grasslands to short-, mixed-, and tallgrass prairie. We envision EDGE as a research platform that will not only advance our understanding of patterns and mechanisms of ecosystem sensitivity to climate change, but also will benefit the broader scientific community. Identical infrastructure for manipulating growing season precipitation will be deployed at all sites. Within the relatively large treatment plots (36 m2), we will measure with comparable methods, a broad spectrum of ecological responses particularly related to the interaction between carbon fluxes (NPP, soil respiration) and species response traits, as well as environmental parameters that are critical for the integrated experiment-modeling framework, as well as for site-based analyses. By designing EDGE as a research platform open to the broader scientific community, with subplots in all replicates (n = 180 plots) set-aside for additional studies, and by making data available to the broader ecological community EDGE will have value beyond what we envision here.
Extreme Drought in Grassland Ecosystems (EDGE) Seasonal Biomass and Seasonal and Annual NPP Data at the Sevilleta National Wildlife Refuge, New Mexico
Net primary production is a fundamental ecological variable that quantifies 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 is the change in plant biomass, including loss to death and decomposition, over a given period of time. Volumetric measurements are made using vegetation data from permanent plots collected in SEV297, "Extreme Drought in Grassland Ecosystems (EDGE) Net Primary Production Quadrat Data" and regressions correlating biomass and volume constructed using seasonal harvest weights from SEV157, "Net Primary Productivity (NPP) Weight Data."
Belowground nitrogen cycling in a montane grassland exposed to elevated CO2, warming and drought
<p>#### Data description<br> Data from a multi-factorial global change experiment (elevated CO<sub>2</sub>, warming and drought) in a montane grassland experiment in Austria (ClimGrass). Variables presented are soil nitrogen cycling rates measured using isotope pool dilutions.</p> <p>Companion paper will be linked following manuscript publication.</p> <p>#### Metadata<br> climgrass_soil_N_cycling.csv data description</p> <p>Year: 2017<br> Harvest: three harvests (May 30, July 25, October 3)<br> Season: numerical column for harvest number<br> Plot: location of plot within the ClimGrass experiment<br> Treatment: eight treatment levels<br> c0t0 (ambient CO<sub>2</sub>, ambient temperature)<br> c0t1 (ambient CO<sub>2</sub>, + 1.5°C)<br> c0t2 (ambient CO<sub>2</sub>, + 3°C)<br> c1t1 (+150 ppm, +1.5°C)<br> c2t0 (+300 ppm, ambient temperature)<br> c2t2 (+300 ppm, +3°C)<br> c0t0-d (ambient CO<sub>2</sub>, ambient temperature, extended drought)<br> c2t2-d (+300 ppm, +3°C, extended drought)<br> CO2_ppm: three values of carbon dioxide enrichment treatment (+0, +150, or +300 ppm)<br> Temp_C: three values of elevated temperature treatment (+0, +1.5, +3°C)<br> Drought: two levels (control, drought)<br> Prot_depoly: gross protein depolymerization rates (micrograms nitrogen per grams dry soil per day = µg N g-1 d-1)<br> FAA_uptake: gross free amino acid uptake rates (µg N g-1 d-1)<br> MRT_FAA_hrs: mean residence time of free amino acids (hours)<br> FAA: free amino acids (µg N g-1)<br> Mineralization: gross mineralization rates (µg N g-1 d-1)<br> Nitrification: gross nitrification rates (µg N g-1 d-1)</p> <p>#### References<br> Additional information on the experimental design can be found in the following paper:<br> Piepho, H.-P., Herndl, M., Pötsch, E.M., Bahn, M., 2017. Designing an experiment with quantitative treatment factors to study the effects of climate change. Journal of Agronomy and Crop Science 203, 584–592. doi:https://doi.org/10.1111/jac.12225</p> <p>More information on the isotope pool dilution method used can be found in the following paper:<br> Wanek, W., Mooshammer, M., Blöchl, A., Hanreich, A., Richter, A., 2010. Determination of gross rates of amino acid production and immobilization in decomposing leaf litter by a novel 15 N isotope pool dilution technique. Soil Biology and Biochemistry 42, 1293–1302. doi:10.1016/j.soilbio.2010.04.001</p>
Remote Sensing Drought Monitoring Dataset based Temperature Vegetation Precipitation Dryness Index (TVPDI) from 2001 to 2020 in China
<p>In this dataset, the MODIS vegetation index and land surface temperature products are processed into NDVI and LST monthly time series with a spatial resolution of 1 km, and the final precipitation data of GPM IMERG are downscaled, unified at a spatial resolution of 1 km. And after a standardization process, using the spatial distance model, a remote sensing drought monitoring dataset in China from 2001 to 2020 was produced based on the Temperature Vegetation Precipitation Dryness Index. For the specific construction process of this data, please refer to https://linkinghub.elsevier.com/retrieve/pii/S0034425720303278</p>
Data from: Effects of plastic fragments on plant performance are mediated by soil properties and drought
<p>In recent years, the effects of plastic contamination on soil and plants have received growing attention. Plastic can affect soil water content and thus may interact with the effects of drought on soil and plants. However, the effects of plastic on soil are highly context-dependent, and interactions with drought have been hardly tested. We conducted two greenhouse experiments to test the combined effects of plastic fragments (of varying size and concentration), water availability and soil texture, on soil water content and performance of the plant <em>Arabidopsis thaliana</em>. Plastic fragments had stronger negative effects on soil water content in low water availability, and the shape of this response (linear <em>vs.</em> unimodal) was mediated by soil texture. Conversely, increasing concentration of plastic had positive effects on plant growth. We suggest that plastic fragments introduce fracture points within soil aggregates. This increases number and size of soil pores favoring water loss but also facilitating root growth. Our results suggest complex interactive effects of plastic and drought, that may lead to a decoupling of plant and soil response. These processes should be taken into account in ecological studies and agricultural practices.</p>
Meteorological drought lacunarity around the world and its classification
<p>Drought duration strongly depends on the definition thereof. In meteorology, dryness is habitually measured by means of fixed thresholds (e.g. 0.1 or 1 mm usually define dry spells) or climatic mean values (as is the case of the Standardised Precipitation Index), but this also depends on the aggregation time interval considered. However, robust measurements of drought duration are required for analysing the statistical significance of possible changes. Herein we have climatically classified the drought duration around the world according to their similarity to the voids of the Cantor set. Dryness time structure can be concisely measured by the n-index (from the regular/irregular alternation of dry/wet spells), which is closely related to the Gini index and to a Cantor-based exponent. This enables the world’s climates to be classified into six large types based upon a new measure of drought duration. We performed the dry-spell analysis using the full global gridded daily Multi-Source Weighted-Ensemble Precipitation (MSWEP) dataset. The MSWEP combines gauge-, satellite-, and reanalysis-based data to provide reliable precipitation estimates. The study period comprises the years 1979-2016 (total of 45165 days), and a spatial resolution of 0.5º, with a total of 259,197 grid points.</p> <p>FILES </p> <p>1. "drought_class" (geotiff)</p> <p>2. "legend_drought_class" (csv): legend values for drought classification. </p> <p>3. "rasterbrick_index_HurstCantorGini" (geotiff): raster with three layers (Hurst, Cantor and Gini Index applied to dry spells). </p> <p>4. "rasterbrick_nindex_spells" (geotiff): raster with four layers (Dry Spell Spells n-index, maximum expected dry spell<em>Y</em><sub>1 </sub>, mean dry spell and mean wet spell).</p> <p> </p> <p>Projection: "+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs" (EPSG.4326)</p>
Data, Analytical Code, and Model Outputs From: Restoration Treatments Enhance Tree Growth and Alter Climatic Constraints During Extreme Drought
<p>This archive includes data (forest inventories, tree ring measurements, climate variables), statistical code, model outputs, and a preprint copy of Rodman et al. (2024). For more information on specific information, processing methods, and data formats, see "README.md" or "README.html" files associated with this archive</p>
Data for manuscript titled 'Impact of urbanization and drought on river water quality, case study of nutrient levels in Cuenca and Giron (Azuay, Ecuador)'
<p>The uploaded zip-file entails the data obtained through four field campaigns performed in the province of Azuay (Ecuador) in the period July 2023 - May 2024, which is used as a basis for the manuscript titled 'Impact of urbanization and drought on river water quality, case study of nutrient levels in Cuenca and Giron (Azuay, Ecuador)' that was submitted to a Special Issue in the journal Water in 2024. The study aimed at illustrating the impact of urbanisation and drought on the abiotic water conditions of the rivers passing through the studied urban areas.</p> <p>The data includes a subfolder with data obtained from an external website (https://generacioncsr.celec.gob.ec/graficasproduccion/) and aligns with the folder structure of the GitHub-repository that contains the analysis scripts (to be added when the manuscript is accepted). The data file only contains the baseline data, while results can be obtained through running the R-scripts in the GitHub-repository. Additional comments on the analyses are also provided in the analysis scripts.</p> <p><strong>DATA COLLECTION</strong></p> <p>Information on the locations was collected prior to the first field campaign (July 2023) and confirmed in the field (and corrected when necessary). The following variables were registered: Date & Time, Coordinates (latitude and longitude, in WGS84 format), Altitude (in meters above mean sea level), Distance (to a fixed location downstream; being the province border), and Category (River or Stream).</p> <p>Information on the physicochemical conditions was collected directly in the field with a <strong>Horiba U-52</strong> multiprobe. The following variables were registered: Temperature, pH, Electrical conductivity (reference at 25 °C), Oxygen level (as concentration), and Turbidity (in NTU).</p> <p>At each site, a bucket was rinsed thrice with prevailing surface water and subsequently filled with a water sample of the top of the water column. The multiprobe was rinsed with this sample water and then submerged in the bucket, followed by continuous stirring (to avoid a decrease of the oxygen levels) until the readings stabilised. After stabilisation, readings were recorded on a separate data sheet prior to being digitalised.</p> <p>Information on the nutrient levels was obtained through the collection of water samples in the field and the subsequent analysis in the laboratory. The following nutrients were selected: ammonium, nitrate, nitrite, and orthophosphate. For the analyses, <strong>Merck test kits</strong> (equivalent to USEPA analyses) were used in combination with a Genesys UV-VIS spectrophotometer (Thermofisher).</p> <p><strong>In the field</strong>, a bucket was rinsed thrice with prevailing surface water and subsequently filled with a water sample of the top of the water column. A polyethylene syringe was rinsed thrice with sample water and subsequently filled prior to being fitted with a 0.45 µm PES filter. About 100 mL of sampled water was filtered and collected in a 250 mL polyethylene bottle that was rinsed with the first 5 mL of filtered water. The bottle was stored in a cooling box and transported to the laboratory.</p> <p><strong>In the laboratory</strong>, the 250 mL bottle was stored at 4 °C until analysis. Within 36 hours, concentrations of ammonium, nitrate, nitrite, and orthophosphate were determined <strong>in triplicate</strong>. More specifically, the following test kits were used to determine said nitrogen and phosphorus concentrations (with quantification range between brackets):</p> <ul> <li>Ammonium: 1.14752.0001 (0.05-3.00 mgN/L)</li> <li>Nitrate: 1.14773.0001 (2-20 mgN/L)</li> <li>Nitrite: 1.14776.0001 (0.02-1.00 mgN/L)</li> <li>Orthophosphate: 1.14848.0001 (0.05-5.00 mgP/L)</li> </ul> <p>Regarding the <strong>spectrophotometric determination</strong>, all analyses were complemented with a blank and a standard with a known concentration of each individual nutrient component. For each nutrient, a specific wavelength was used and the resulting absorbance was converted to the associated nutrient concentration through known factors (similar to the use of calibration curves), after setting the absorbance of the blank as reference absorbance (i.e. a concentration of 0 mg/L). All of the analyses were performed with plastic 1-cm cuvettes during the first campaign, while 5-cm cuvettes were used in the remaining three campaigns due to low nutrient levels (except for nitrate, for which an analysis through 5-cm cuvettes is not supported by the used test kits).</p>
The Potential of Fragipans in Sustaining Pearl Millet during Drought Periods in North-Central Namiba (dataset)
<p><strong>Abstract</strong></p> <p>Sandy soils with fragipans are usually considered poorly suited for agriculture. However, these soils are cultivated in north-central Namibia as they can secure a minimum harvest during droughts. To understand the hydrological influence of fragipans in these soils, Ehenge, and what makes them valuable, their soil moisture content was measured over a time span of four months. These data were then compared to a deep soil without fragipan, Omutunda, which is more productive during normal years, but less productive during droughts. The results illustrate that the combination of sandy topsoil and shallow fragipan has beneficial effects on plant available water during dry periods, because of three reasons: (i) The high infiltration rate in the sandy topsoil, (ii) the prevention of deep drainage of water by the fragipan, and (iii) the limited evaporation losses through the capillary rise in the sand. The results also confirm the disadvantages of Ehenge during wet periods.</p> <p><strong>Description of Dataset</strong></p> <p>The dataset comprises a .pdf-file with a detailed data description, seven .csv-files (relevant datasets), and two txt-files with the R-code to produce the relevant Figures 4 and 5 from the paper “The Potential of Fragipans in Sustaining Pearl Millet during Drought Periods in North-Central Namibia” by Prudat et al. 2021.</p> <p><strong>File description<br> Rainfall.csv</strong>: daily rainfall in mm at two locations (<em>Omutunda</em> & <em>Ehenge</em>)<br> <strong>NDOB13_ehenge.csv/ NDOB13_omutunda.csv</strong>: soil temperature and soil moisture per minute<br> <strong>NDOB13_ehenge_daily.csv/ NDOB13_omutunda_daily.csv</strong>: soil temperature and volumetric soil moisture content (θ<sub>TDR</sub>) aggregated per day using the arithmetic mean<br> <strong>NDOB13_ehenge_RASW_daily.csv/ NDOB13_omutunda_RASW_daily.csv</strong>: The relative available soil water (RASW) was calculated based on the measured plant available water,</p> <p><strong>Scripts</strong><br> (1) <strong>RASW_rainfall_daily</strong>: Script to calculate and plot the relative available soil water (RASW) at the two stations and the rainfall<br> (2) <strong>Max_soil_surface_temperature</strong>: Script to calculate and plot the maximum soil surface temperature at the two stations</p> <p> </p><p><strong>References</strong></p> <p></p> <p>Cobos, D., Campbell, C., 2007. Correcting temperature sensitivity of ECH2O soil moisture sensors. Decagon Devices Pullman WA.</p> <p>Hillel, D., 1998. Environmental soil physics: Fundamentals, applications, and environmental considerations. Academic press.</p>
Spring arctic oscillation as a trigger of summer drought in Siberian subarctic over the past 1494 years
<p>Annually resolved July precipitation and Arctic Oscillation in May reconstructions derived from the d<sup>13</sup>C and d<sup>18</sup>O in larch tree-ring cellulose over the period 516-2009 CE for eastern Taimyr (Siberia). July precipitation reconstruction was obtained under the Russian Science Foundation (RSF) Grant number 21-17-00006 (<a href="https://rscf.ru/en/project/21-17-00006/">https://rscf.ru/en/project/21-17-00006/</a>) granted to Project Investigator Olga V. Churakova.</p>
Below-ground hydraulic constraints during drought-induced decline in Scots pine
<p>Dataset from the paper 'Below-ground hydraulic constraints during drought-induced decline in Scots pine'.</p> <p><strong>Files:</strong></p> <p>DOY refers to day of year 2012, idtree is tree identity and Class is defoliation class. Tree characteristics can be found in the supplementary materials of the paper. Variables are expressed in the same units as in the paper.</p> <p><em>WaterPotentials.csv</em> - water potential data (predawn, PD, midday MD, difference)</p> <p><em>SapFlowDeltaPResistbc.csv</em> - daily sap flow per unit leaf area (Jl_daily), delta pressure (deltaP), VPD,SWC, belowcrown resistance (r_bc).</p> <p><em>Resistbc_percent.csv</em> - below-crown resistance as a percentage of total tree resistance</p> <p> </p>
Remote Sensing Drought Monitoring Dataset based Temperature Vegetation Precipitation Dryness Index (TVPDI) from 2001 to 2021 in China (v2.0)
<p>The Enhanced Vegetation Index (EVI), Land Surface Temperature (LST) and Precipitation (P) were used as new data sources based on the spatial distance model to construct an optimized multi-source remote sensing dryness index named Temperature-Vegetation-Precipitation Dryness Index based on the shortcomings of the TVPDIorigin (i.e., TVPDI<sub>o</sub>) data source. The TVPDI<sub>n</sub> of the long time series was also compared and analyzed with the classical drought index - Standardized Precipitation Evapotranspiration Index (SPEI-3) on a 3-month scale, different drought response level products of Solar-Induced Chlorophyll Fluorescence (SIF), soil moisture (SM) from ESA CCI (European Space Agency's Climate Change Initiative), and total crop yield, then the sensitivity and validity of the TVPDI<sub>n</sub> for wetness and dryness monitoring were synthesized and validated. On this basis, here are the results of the verification:</p> <p>(1) Compared with the original data source TVPDI<sub>o</sub> using the new multi-source remote sensing data source of precipitation and vegetation index to construct TVPDI<sub>n</sub>, the overall correlation between the two and SPEI-3 was good, with a maximum of 0.57 and 0.56, respectively (p< 0.1), but the overall TVPDI<sub>n</sub> constructed in this study had a better fit compared to the original data source TVPDI<sub>o</sub> and was more sensitive to the monitoring of dry and wet conditions.</p> <p>(2) According to the comparison of TVPDI<sub>n</sub> with ESA CCI sm, TVPDI<sub>n</sub> showed a high correlation of more than 0.9 with soil water content, which proved that TVPDI<sub>n</sub> was highly consistent with soil moisture; compared with SIF, 54.5% of the regional correlation coefficients were greater than 0.8 (p< 0.01), and spatially, the correlation results were better in the northwest than in the east, indicating that the response of TVPDI<sub>n</sub> to vegetation productivity is more agile in regions with continental climate such as the northwest. The results of correlation with grain yield comparison showed that good positive correlations were presented with TVPDI<sub>n</sub> in Liaodong Peninsula, northern North China Plain, and most of Qilian Mountains, southern edge of Qinling Mountains, middle and lower reaches of Yangtze River, and South China, indicating that TVPDI<sub>n</sub> has a high consistency in the changes of agricultural grain production in the above mentioned regions, and also proving the index in monitoring agricultural aridity and guiding agricultural production The good performance of the index in monitoring agricultural aridity and guiding agricultural production.</p> <p> This dataset is version 2.0, and covers all of China's territory, but the temperature-vegetation- precipitation dryness index of the open water surface are often set to a null value. Note:The data format is "TIF", the spatial resolution is "1 km", the time resolution is "1 month" and dimensionless. The pixel value is the NTVPDI value, and the closer the pixel value is to 0, the drier it is, and the larger the data, the wetter the land surface. The practical utility of this dataset is to compare the degree of dryness and wetness of China's land, to monitor short-term and medium-term droughts, and to substitute model parameters related to soil moisture. This is of great value to the impartial formulation of China's environmental and economic policies, regular monitoring and evaluation of drought and flood conditions. This product will be freely available to all users worldwide and will be continuously improved to suit new goals and needs.</p>
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.