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2,078 results for “soil data”
Data for: Experimental study on the contribution of microbial-induced carbonate precipitation to carbon sequestration in soil from the northern Qinghai-Tibet Plateau
<p>This database contains raw data on the basic soil characteristics of the Laohugou profile and raw data from laboratory simulation experiments.</p>
Data and code for "Soil as a Reservoir of Multi Annual Rainfall Determining Semiarid Vegetation Productivity"
<p><strong>Soil as a Reservoir of Multi Annual Rainfall Determining Semiarid Vegetation Productivity (Fux, Svoray & Bell, 2024)</strong></p> <p><strong>Abstract</strong><br>Climate change and natural variability alter rainfall characteristics. In dry environments, these changes <br>affect vegetation productivity, however, studies of remotely sensed data in high resolution temporal are scarce. <br>We quantified daily scale rainfall-productivity relationships by analyzing daily time series of rainfall and NDVI <br>from Landsat and Sentinel imagery from Israel, New Mexico, and SW Australia. Methodologically wise, we found that <br>the representative area size varied from 0.02--0.14 \(Km^2\), depending on the uniformity of vegetation formations. <br>More substantive, herbaceous vegetation showed maximal response to 3--4 months cumulative rainfall, while woody <br>vegetation response is dominated by rainfall accumulated over a year and even longer periods. These results emphasize <br>the water reservoirs' significance upon intermittent rainfall events and may have implications for ecohydrological <br>modeling, conservation biology, and ecosystem management.</p> <p><strong>Plain Language Summary</strong><br>Dry environments are characterized by high rainfall variability and water scarcity sets it as a limiting factor for <br>vegetation growth. Yet, vegetation response to rainstorms in semiarid regions is not fully understood. Specifically, <br>it is unclear what dominant statistical characteristic of rainstorms dictates vegetation growth. It has been long <br>debated whether daily, seasonal or annual rainfall characteristics are crucial for triggering vegetation’s response. <br>Here, we used high-resolution satellite images and daily rainfall records, from three locations worldwide, to <br>investigate the rainfall-productivity relationship. We found that for most vegetation formations, maximal correlation <br>is obtained for no lag and seasonal, or longer, rainfall accumulation periods. These results suggest that vegetation <br>does not show a significant response to rainfall pulses but rather to accumulated rainfall over longer periods (even <br>years). Thus, accumulated rainfall is likely stored in soil water reservoirs and remains accessible to ecosystems. <br>These results are more pronounced in woody vegetation and should be considered for environmental management policies.</p> <p><strong>Description</strong><br>The compressed file contains two folders, one for the characteristic unit size test and one for the rainfall-NDVI <br>cross correlations.<br>The unit size folder contains NDVI images for the dates used to calculate the characteristic unit size, the shape <br>files of the polygons used to delineate the different vegetation types areas and the R code.<br>The rainfall-NDVI cross correlations folder contain the NDVI images for each vegetation type in each region, <br>processed from the original data, and the code for creating the detrended and summed rainfall time series, the <br>detrended NDVI time series and the cross-correlation analyses.<br>The rainfall and the original satellite data are available from the resources listed in the article.</p>
Daily and sub-daily hydrometeorological and soil data (2013-2023) [COSMOS-UK]
<p>This dataset contains daily and sub-daily hydrometeorological and soil moisture observations from COSMOS-UK (cosmic-ray soil moisture) monitoring network from October 2013 to the end of 2023. These data are from 51 sites across the UK recording a range of hydrometeorological and soil variables.</p>
Data files of Carteron et al. "Soil abiotic and biotic properties constrain the establishment of a dominant temperate tree into boreal forests" in Journal of Ecology
<p>There are five data files use for the analysis present in the article of Carteron et al "Soil abiotic and biotic properties constrain the establishment of a dominant temperate tree into boreal forests" in Journal of ecology. These files are used in R script available in GituHub.</p> <p>GPS_megantic.csv: contains locations of the study plots</p> <p>colo_as.csv: Contains a summary of the root colonization by fungi</p> <p>colo.csv : Contains all the data of the root colonization by fungi</p> <p>colo.rdata: Contains all the data of the root colonization by fungi in Rdata format</p> <p>soil_thick.csv : Contains soil horizon thickness measured on the field</p> <p>traits_as.csv: Contains the traits measured on the sugar maple seedlings</p>
Data from: Sensitivity of global soil carbon stocks to combined nutrient enrichment
Soil stores approximately twice as much carbon as the atmosphere and fluctuations in the size of the soil carbon pool directly influence climate conditions. We used the Nutrient Network global change experiment to examine how anthropogenic nutrient enrichment might influence grassland soil carbon storage at a global scale. In isolation, enrichment of nitrogen and phosphorous had minimal impacts on soil carbon storage. However, when these nutrients were added in combination with potassium and micronutrients, soil carbon stocks changed considerably, with an average increase of 0.04 KgCm−2 year−1 (standard deviation 0.18 KgCm−2 year−1). These effects did not correlate with changes in primary productivity, suggesting that soil carbon decomposition may have been restricted. Although nutrient enrichment caused soil carbon gains most dry, sandy regions, considerable absolute losses of soil carbon may occur in high‐latitude regions that store the majority of the world's soil carbon. These mechanistic insights into the sensitivity of grassland carbon stocks to nutrient enrichment can facilitate biochemical modelling efforts to project carbon cycling under future climate scenarios.
Data from: The vertical distribution and control of microbial necromass carbon in forest soils
<p><span><b>Aim:</b> Forest soils contain large amounts of terrestrial organic carbon (C), but the formation pathway of soil organic C (SOC) remains unclear. Recent evidence suggests that microbial necromass is a significant source of SOC, yet a global quantitative assessment across the whole-soil profile is lacking. We aimed to assess the vertical distribution and control of microbial-derived SOC in forest soils.</span></p> <p><span><b>Location:</b> Global forests.</span></p> <p><span><b>Time period:</b> 1996-2019.</span></p> <p><span><b>Major taxa studied:</b> Soil microbial necromass carbon.</span></p> <p><span><b>Methods:</b> We evaluated the proportions of fungal and bacterial necromass C in total SOC in the litter layer, O horizon soil, and various depths of mineral soil in forests using microbial biomarker (glucosamine and muramic acid) data.</span></p> <p><span><b>Results:</b> The total microbial necromass C increased significantly with soil depth, ranging from 30% of SOC in O horizon soil to 62% of SOC in mineral soils below 50 cm. However, only bacterial necromass C followed this increasing trend with soil depth; fungal necromass C showed little variation across the whole-soil profile. Higher fungal and bacterial necromass C was observed in soils with lower C/N ratios and smaller aggregate sizes. Soil C/N ratio and microbial biomass C dominantly determined microbial necromass C in surface soil (above 20 cm), but soil clay content was the primary factor in subsoil (below 20 cm).</span></p> <p><span><b>Main conclusions: </b>Microbial necromass C accounted for high percentages of the total SOC in forest soils (particularly at depths >20 cm), but its long-term stabilization may be governed by different mechanisms at different soil horizons. Substrate quality regulates microbial activity and then controls biomass turnover in surface soil, while aggregate occlusion could facilitate mineral protection of microbial necromass C in subsoil. These differential controls of microbial-derived organic C could be applied in Earth system studies for predicting soil organic C dynamics in forests.</span></p>
Dataset for effects of shear zone thickness in root-reinforced soils: Willow F X-ray CT scans and digital volume correlation data
<p>Dataset for effects of shear zone thickness in root-reinforced soils: Willow F X-ray CT scans and digital volume correlation data</p>
Raw data of "Overrepresentation of Alopecurus myosuroides with high levels of resistance towards herbicides applied in spring on heavy clay soils"
<p>The file contains the raw data of the manuscript "Overrepresentation of <em>Alopecurus myosuroides </em>with<em> </em>high levels of resistance towards herbicides applied in spring on heavy clay soils"</p>
Data for comprehensive effect of soil particle size composition and wind speed on dust emission efficiency
<p>The original data obtained by the wind tunnel experiments aims to investigate the comprehensive effect of soil particle size composition and wind speed on dust emission efficiency</p>
Evaluation and optimisation of the soil carbon turnover routine in the MONICA model (version 3.3.1) - MONICA model source code and data
<p>Zip file consisting of the data used in the manuscript "Evaluation and optimisation of the soil carbon turnover routine in the MONICA model".<br> The data consists of 11 German long term experimenting field sites, formatted in MONICA readable input files. Each consisting of one dataset for weather information (.met), and three .json files describing the management, site and soil properties of each treatment. The validation datasets consist of soil temperature and soil moisture measurement and are distinguishable by the .vals file type/format.</p> <p>For further information please refer to the manuscript.</p>
Soil Physicochemical Properties Data in Bornean Tropical Heath Kerangas Forests Invaded by Acacia mangium
<p>This dataset contains collected data from a research project on the impact of the invasive alien tree species<em> Acacia mangium</em> Willd. on nutrient-poor sandy soils in tropical heath Kerangas forests, an increasingly threatened lowland forest in Brunei Darussalam, Borneo. Soil samples were collected in 2015 from three selected habitats: intact Kerangas forest, <em>Acacia</em>-invaded Kerangas forest, and <em>Acacia mangium</em> plantation. In each plot, eight soil cores were collected in the topsoil (0 - 15 cm) and subsoil (30 - 50 cm) layers, and soil parameters such as gravimetric water, organic matter content, texture, nutrient concentrations of nitrogen (N), phosphorus (P), potassium (K), magnesium (Mg) and calcium (Ca), exchangeable Mg, Ca, K, available P, and pH were documented. Sampling and analysis were performed according to standard protocols.</p>
Data set. Quantitative soil characterization using frequency domain electromagnetic induction method in heterogeneous fields
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Data from: Sensitivity of global soil carbon stocks to combined nutrient enrichment
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Data from: Modeling spatial patterns of soil respiration in maize fields from vegetation and soil property factors with the use of remote sensing and geographical information system
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Data from: Effects of forestry-driven changes to groundcover and soil moisture on amphibian desiccation, dispersal, and survival
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Data from: Contrasting effects of ammonium and nitrate additions on the biomass of soil microbial communities and enzyme activities in subtropical China
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Data from: Determination of factors associated with natural soil suppressivity to potato common scab
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Data from: Relative importance of competition and plant-soil feedback, their synergy, context dependency and implications for coexistence
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Data from: Effect of chemical additives on electrokinetic remediation of Cr-contaminated soil coupled with a permeable reactive barrier
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Data from: Effect of coupled reduced irrigation and nitrogen fertilizer on soil mite community composition in a wheat field
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International Brain Laboratory public data
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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.