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2,078 results for “soil data”
Biotic interactions promote local adaptation to soil in plants - Supplementary data
<p>Although different ecological factors shape adaptative evolution in natural habitats, we know little about how their interactions impact local adaptation. Here we used eight generations of experimental evolution with outcrossing <em>Brassica rapa</em> plants as a model system, in eight treatment groups that varied in soil type, herbivory (with/without aphids), and pollination mode (hand- or bumblebee-pollination), to study how biotic interactions affect local adaptation to soil. First, we show that several plant traits evolved in response to biotic interactions in a soil-specific way. Second, using a reciprocal transplant experiment, we demonstrate that significant local adaptation to soil-type evolved in the "number of open flowers", a trait used as a fitness proxy, but only in plants that evolved with herbivory and bee pollination. Whole genome re-sequencing of experimental lines revealed that biotic interactions caused a 10-fold increase in the number of SNPs across the genome with significant allele frequency change, and that alleles with opposite allele frequency change in different soil types (antagonistic pleiotropy) were most common in plants with an evolutionary history of herbivory and bee pollination. Our results demonstrate that the interaction with mutualists and antagonists can facilitate local adaptation to soil type through antagonistic pleiotropy. </p>
Supporting data for "Granularity of model input data impacts estimates of carbon storage in soils"
<p>The exchange of carbon between the soil and the atmosphere is an important factor in climate change. Soil organic carbon (SOC) storage is sensitive to land management, soil properties, and climatic conditions, and these data serve as key inputs to computer models projecting SOC change. Farmland has been identified as a sink for atmospheric carbon, and we have previously estimated the potential for SOC sequestration in agricultural soils in Vermont, USA using the Rothamsted Carbon Model. However, fine spatial-scale (high granularity) input data are not always available, which can limit the skill of SOC projections. For example, climate projections are often only available at scales of 10s to 100s of km2. To overcome this, we use a climate projection dataset downscaled to <1 km2 (~18,000 cells). We compare SOC from runs forced by high granularity input data to runs forced by aggregated data averaged over the 11,690 km2 study region. We spin up and run the model individually for each cell in the fine-scale runs and for the region in the aggregated runs factorially over three agricultural land uses and four Global Climate Models. </p> <p>In this repository are the downscaled climate input data that drive the RothC model, as well as the model outputs for each GCM.</p>
TUdi-Vinedivers_EJP_Vineyard_Soil_Data_Europe
<p>Dataset of soil properties (soil organic carbon contents and soil physical parameters) of vineyard topsoil samples from the TUdi/Vinedivers/EJP Soil vineyard inter-row management study in European vineyard regions.</p>
Total data for global pattern of organic carbon pools in forest soil
<p>Understanding the mechanisms of soil organic carbon (SOC) sequestration in forests is vital to ecosystem carbon budgeting, and helps gain insight in the functioning and sustainable management of world forests. An explicit knowledge of the mechanisms driving global SOC sequestration in forests is still lacking because of the complex interplays between climate, soil and forest type in influencing SOC pool size and stability. Based on a synthesis of 1179 observations from 292 studies across global forests, we quantified the relative importance of climate, soil property and forest type on total SOC content and the specific contents of physical (particulate vs. mineral-associated SOC) and chemical (labile vs. recalcitrant SOC) pools in upper 10 cm mineral soils, as well as SOC stock in the O horizons. The variability in the total SOC content of the mineral soils was better explained by climate (47~60%) and soil factors (26%~50%) than by NPP (10~20%). The total SOC content and contents of particulate (POC) and recalcitrant SOC (ROC) of the mineral soils all decreased with increasing mean annual temperature because SOC decomposition overrides the C replenishment under warmer climate. The content of mineral-associated organic carbon (MAOC) was influenced by temperature, which directly affected microbial activity. Additionally, the presence of clay and iron oxides physically protected SOC by forming MAOC. The SOC stock in the O horizons was larger in the temperate zone and Mediterranean regions than in the boreal and sub/tropical zones. Mixed forests had 64% larger SOC pools than either broadleaf or coniferous forests, because of i) higher productivity, and ii) litter input from different tree species resulting in diversification of molecular composition of SOC and microbial community. While climate, soil and forest type jointly determine the formation and stability of SOC, climate predominantly controls the global patterns of SOC pools in forest ecosystems.</p>
Soilcare data agricultural soil quality improvement
<p>Dataset that contains survey data on Spanish and UK respondents on agricultural soil quality protection and improvement</p>
Рис. 3. Teratocephalon hexahamus gen. n., sp. n.: A — трофико-сенсорный отΑеΛ теΛа; B — трофико-генитаΛьный отΑеΛ теΛа; C, D — переΑний конец теΛа. a — анус, am — амфиΑы, v — вуΛьва, cc — гоΛовная капсуΛа, ve — «жеΛуΑочек», pu — заΑняя матка, nr — нервное коΛьцо, rc — прямая кишка, au — переΑняя матка, r — ренетта, ep — экскреторная пора, o — яичник, e — яйцо Fig. 3. Teratocephalon hexahamus gen. n., sp. n.: A — trophic-sensory part of the body; B — trophic-reproductive part of the body; C, D — anterior end of the body. a — anus; am — amphids; v — vulva; cc — cephalic capsule; ve — "ventricle"; pu — posterior uterus; nr — nerve ring; pu — anterior uterus; r — renetta; rc — rectum; ep — excretory pore; o — ovary; e — egg in Recent data on soil nematodes of the families Teratocephalidae and Metateratocephalidae from Primorsky Region, Russia
Рис. 3. Teratocephalon hexahamus gen. n., sp. n.: A — трофико-сенсорный отΑеΛ теΛа; B — трофико-генитаΛьный отΑеΛ теΛа; C, D — переΑний конец теΛа. a — анус, am — амфиΑы, v — вуΛьва, cc — гоΛовная капсуΛа, ve — «жеΛуΑочек», pu — заΑняя матка, nr — нервное коΛьцо, rc — прямая кишка, au — переΑняя матка, r — ренетта, ep — экскреторная пора, o — яичник, e — яйцо Fig. 3. Teratocephalon hexahamus gen. n., sp. n.: A — trophic-sensory part of the body; B — trophic-reproductive part of the body; C, D — anterior end of the body. a — anus; am — amphids; v — vulva; cc — cephalic capsule; ve — "ventricle"; pu — posterior uterus; nr — nerve ring; pu — anterior uterus; r — renetta; rc — rectum; ep — excretory pore; o — ovary; e — egg
Рис. 1. Teratocephalus lirellus Andrassy, 1969: A — трофико-сенсорный отΑеΛ теΛа; B — поΛовая система; C — фрагмент теΛа с боковым поΛем; D — хвост; E — фрагмент поΛовой системы и среΑней кишки; F, G — переΑний конец теΛа. am — амфиΑы, lf — боковое поΛе, v — вуΛьва, cc — гоΛовная капсуΛа, pu — заΑняя матка, au — переΑняя матка, r — ренетта, ep — экскреторная пора, o — яичник Fig. 1. Teratocephalus lirellus Andrassy, 1969: A — trophic-sensory part of the body; B — reproductive system; C — fragment of the body with a lateral field; D — tail; E — fragment reproductive system and intestine; F, H — anterior end of the body. am — amphid; lf — lateral field; v — vulva; cc — cephalic capsule; pu — posterior uterus; au — anterior uterus; r — renetta; ep — excretory pore; o — ovary in Recent data on soil nematodes of the families Teratocephalidae and Metateratocephalidae from Primorsky Region, Russia
Рис. 1. Teratocephalus lirellus Andrassy, 1969: A — трофико-сенсорный отΑеΛ теΛа; B — поΛовая система; C — фрагмент теΛа с боковым поΛем; D — хвост; E — фрагмент поΛовой системы и среΑней кишки; F, G — переΑний конец теΛа. am — амфиΑы, lf — боковое поΛе, v — вуΛьва, cc — гоΛовная капсуΛа, pu — заΑняя матка, au — переΑняя матка, r — ренетта, ep — экскреторная пора, o — яичник Fig. 1. Teratocephalus lirellus Andrassy, 1969: A — trophic-sensory part of the body; B — reproductive system; C — fragment of the body with a lateral field; D — tail; E — fragment reproductive system and intestine; F, H — anterior end of the body. am — amphid; lf — lateral field; v — vulva; cc — cephalic capsule; pu — posterior uterus; au — anterior uterus; r — renetta; ep — excretory pore; o — ovary
Рис. 2. Euteratocephalus montanus sp. n.: A — трофико-сенсорый и трофико-генитаΛьный отΑеΛы теΛа; B — хвост; C — трофико-генитаΛьный отΑеΛ теΛа; D — фрагмент теΛа с боковым поΛем; E, F — переΑний конец теΛа. am — амфиΑы, lf — боковое поΛе, v — вуΛьва, va — вагина, g — гемизониΑ, cc — гоΛовная капсуΛа, ve — «жеΛуΑочек», pr — преректум,r — ренетта, f — фазмиΑа,ep — экскреторная пора, o — яичник, e — яйцо Fig. 2. Euteratocephalus montanus sp. n.: A — trophic-sensory and trophic-reproductive parts of the body; B — tail; C — trophic-reproductive part of the body; D — fragment of the body with a side field; E, F — anterior end of the body. am — amphid, lf — lateral field; v — vulva; va — vagina; g — gemizonid; cc — cephalic capsule; ve — "ventricle"; pr — prerectum; r — renetta; f — phasmids, ep — excretory pore; o — ovary; e — egg in Recent data on soil nematodes of the families Teratocephalidae and Metateratocephalidae from Primorsky Region, Russia
Рис. 2. Euteratocephalus montanus sp. n.: A — трофико-сенсорый и трофико-генитаΛьный отΑеΛы теΛа; B — хвост; C — трофико-генитаΛьный отΑеΛ теΛа; D — фрагмент теΛа с боковым поΛем; E, F — переΑний конец теΛа. am — амфиΑы, lf — боковое поΛе, v — вуΛьва, va — вагина, g — гемизониΑ, cc — гоΛовная капсуΛа, ve — «жеΛуΑочек», pr — преректум,r — ренетта, f — фазмиΑа,ep — экскреторная пора, o — яичник, e — яйцо Fig. 2. Euteratocephalus montanus sp. n.: A — trophic-sensory and trophic-reproductive parts of the body; B — tail; C — trophic-reproductive part of the body; D — fragment of the body with a side field; E, F — anterior end of the body. am — amphid, lf — lateral field; v — vulva; va — vagina; g — gemizonid; cc — cephalic capsule; ve — "ventricle"; pr — prerectum; r — renetta; f — phasmids, ep — excretory pore; o — ovary; e — egg
Model configuration files and forcing data for Implementing deep soil and dynamic root uptake in Noah-MP (v4.5): impact on Amazon dry-season transpiration
<p>This repository includes the model configuration files, input data, and forcing data used for simulations in Bieri et al. (2025) - <em>Implementing deep soil and dynamic root uptake in Noah-MP (v4.5): impact on Amazon dry-season transpiration.</em></p> <ul> <li>forcing.tar.gz - Compressed folder containing HRLDAS Noah-MP model forcing NetCDF files <ul> <li>These forcing files were derived from the NASA Global Land Data Assimilation System (GLDAS; Beaudoing et al. 2020)</li> <li>The compressed file contains 3-hourly forcing files for the entire simulation period (01 Jun 2000 to 31 Dec 2019)</li> </ul> </li> <li>wrfinput_d01 - NetCDF file used as HRLDAS input file in HRLDAS Noah-MP simulations <ul> <li>Generated from WRF WPS (https://github.com/wrf-model/WPS)</li> </ul> </li> <li>Namelist files <ul> <li>namelist.hrldas.ROOT - Model namelist settings used for ROOT experiment</li> <li>namelist.hrldas.SOIL - Model namelist settings used for SOIL experiment</li> <li>namelist.hrldas.GW - Model namelist settings used for GW experiment</li> <li>namelist.hrldas.CONTROL - Model namelist settings used for FD (CONTROL) experiment</li> </ul> </li> </ul>
Characterization and Simulation Data of Cylindrical, Elliptical, Parabolic, Conical and Root-like Tips with Diameters in Sandy Loam Soil
<p>Plants use many strategies to move efficiently in soil, such as growth from the tip, tropic movements, and morphological changes. In this paper, we propose a method to translate morphological features of <em>Zea mays</em> roots into a new design of soft robots that will be able to move in soil. The method relies on image processing and curve fitting techniques to extract the profile of <em>Z</em>. <em>mays</em> primary root. We implemented an analytic translation of the root profile in a 3D model (CAD) to fabricate root-like probes by means of 3D printing technology. Then, we carried out a comparative analysis among the artificial root-like probe and probes with different tip shapes (cylindrical, conical, elliptical, and parabolic) and diameters (11, 9, 7, 5, and 3 mm). The results showed that the energy consumption and the penetration force of the bioinspired probe are better with respect to the other shapes for all the diameters of the developed probes. For 100 mm of penetration depth and 7 mm of probe diameter, the energy consumption of the bioinspired probe is 89% lesser with respect to the cylindrical probe and 26% lesser with respect to the conical probe. The penetration performance of the considered tip shapes was evaluated also by means of numerical simulations, obtaining a good agreement with the experimental results. Additional investigations on plant root morphology, movement strategies, and material properties can allow the development of innovative bioinspired solutions exploitable in challenging environments. This research can bring to breakthrough scenarios in different fields, such as exploration tasks, environmental monitoring, geotechnical studies, and medical applications</p>
Data from: Rhizosphere bacterial community composition depends on plant species identity and soil legacy effects
<p>This record contains supplementary information for the article "Rhizosphere bacterial community composition depends on plant diversity legacy in soil and plant species identity".</p> <p><strong>Supplemental Table S1.</strong> The table contains the annotation for all the samples sequenced and analyzed.</p> <p><strong>Supplemental Table S2. </strong>The table contains all primer sequences used in the study.</p> <p><strong>Supplemental Table S3.</strong> The zip-file contains a table with the taxonomic annotation of the operational taxonomic units (OTUs) identified in the study.</p> <p><strong>Supplemental Table S4. </strong> The zip-file contains a table with sequence counts of the operational taxonomic units (OTUs) identified in the study.</p> <p><strong>Supplemental Table S5. </strong>The workbook contains a sheet with the number of operational taxonomic units (OTUs) exhibiting differential abundance in any of the contrasts tested in this study. Note that “down/up” indicates whether the OTU was less (“down”) or more (“up”) abundant in the first group of the contrast. For example, given the contrast “PH_mix_vs_mon_”, “down” corresponds to higher abundance in the pots from the monoculture plant history. Conversely, “up” refers to higher abundance in the pots from the mixed culture plant history. In addition, the workbook contains one sheet per contrast with the logBaseMean (log2 of the average normalized abundance across all samples), the logFC (log2 of the fold-change), the <em>P</em>-value, and the adjusted <em>P</em>-value (FDR). Only OTUs with a <em>P</em>-value <= 0.05 or an adjusted <em>P</em>-value (FDR) <= 0.1 are given.</p> <p><strong>Supplemental Table S6. </strong>The table contains the number of bacterial OTUs annotated with a given bacterial phylum.</p> <p><strong>Supplemental Table S7. </strong>The table contains all phyla tested for enrichment/depletion in the set of OTUs with an increased abundance in monoculture and mixed culture soils respectively. “Total counts (all OTUs)” corresponds to the total number of all OTUs annotated with a given phyla (reference set). “Observed” corresponds to the number of OTUs annotated with a given phyla in the set OTUs with increased abundance in monoculture/mixed culture soils (test set). "Expected" gives the number of OTUs which would be expected to be annotated with a given phyla if the test set were randomly sampled from the reference set.</p> <p><strong>Supplemental File S1.</strong> The zip-file contains a fasta file with the 10'205 OTU sequences identified in the study.</p> <p> </p> <p> </p>
Prince Edward Island (Canada) Predictive Soil Mapping data set (30 m)
<p>Prince Edward Island (Canada) Predictive Soil Mapping data set. Training points include:</p> <ul> <li>soil organic matter (624 points): unit: percent, g/100g ) samples from the topsoil (0-23 cm depth),</li> <li>soil types (672 points),</li> </ul> <p>Covariate layers include:</p> <ul> <li>DEM derivatives (Channel_Network_Base_Level.tif, MRRTF.tif, Relative_Slope_Position.tif, Slope.tif, TWI.tif, Valley_Depth.tif, Vertical_Distance_To_Channel_Network.tif),</li> <li>landcover_2016_reclassify.tif (categorical values),</li> <li>DSS_soil_polygons.tif (soil polygons),</li> </ul> <p>Some covariates are type numeric, some type factor. To use the pre-processed data download only the RDS file. E.g. "PEI100m.soil.rds" contains all covariates layers resampled to 100 m resolution and all training points.</p>
Data for paper 'Segmentation of Roots in Soil with U-Net'
<p>Data for the paper 'Segmentation of Roots in Soil with U-Net'</p> <p>Paper available at: https://arxiv.org/abs/1902.11050</p> <p>Code available at: https://github.com/Abe404/segmentation_of_roots_in_soil_with_unet</p> <p>Model available at: https://doi.org/10.5281/zenodo.3484015</p>
Soil biota (earthworm, nematode and soil surface fauna) data of organic, permaculture and conventional horticultural farms of Central Hungary
<p>This dataset has been produced from the PhD research of Alfréd Szilágyi supervised by Csaba Centeri and Eszter Kovács Tormáné. The study compared permaculture, organic and conventional farming systems regarding their ecosystem-service provision potential and sustainability. Multiple ecological indicators were measured in the field during the field study in 2020, and the basic datasets (soil test results; photo gallery of the studied farms with soil core sample; soil resistance and moisture; decomposition; earthworms; nematodes; soil surface fauna; pollinators; agrobiodiversity and habitat types) are uploaded in Zenodo separately to provide scientific data on permaculture systems. In this way, we hope to contribute to international efforts to evaluate the performance of agroecological agriculture alternatives. These publications also serve as supplements to the PhD thesis. For the sake of further usability of the datasets short description of the used methods is described. For further information please contact the authors.</p>
Data from: Species-soil relationships across Amazonia: niche specificity and consistency in understory ferns
<p>One of the two data files contains occurrence and abundance information for Adiantum and Lindsaea fern species in 1215 sampling units distributed across Amazonia. The other data file contains metadata and soil base cation concentration values. Explanations of the data columns are in the README.txt file.</p>
Data for "Site-Specific Management Zones Delineation Based on Apparent Soil Electrical Conductivity in Two Contrasting Fields of Southern Brazil"
<p>This dataset contains soybean yield, soil property values, and apparent electrical conductivity (ECa) from two farms located in the South of Brazil. The data description and methods can be found in the paper:</p> <p><strong>Bottega, E. L., Safanelli, J. L., Zeraatpisheh, M., Amado, T. J. C., Queiroz, D. M. de, & Oliveira, Z. B. de. (2022). Site-Specific Management Zones Delineation Based on Apparent Soil Electrical Conductivity in Two Contrasting Fields of Southern Brazil. In Agronomy (Vol. 12, Issue 6, p. 1390). MDPI AG. https://doi.org/10.3390/agronomy12061390</strong></p> <p>Abstract:</p> <p>Management practices that aim to increase the profitability of agricultural production with minimal environmental impact must consider within-field soil variability, and this site-specific management can be addressed by precision agriculture (PA). Thus, this work aimed to investigate which key soil attributes are distinguishable management zones (MZ) delineated based on the soil apparent electrical conductivity (ECa), using fuzzy k-means, in two fields with contrasting soil textures in southern Brazil. For this, a grid scheme (50 × 50 m) was applied to measure ECa, conduct soil sampling for analysis, and determine soybean yield. The MZ were delineated based on the ECa spatial distribution, and statistical non-parametric tests (p < 0.05) were employed to compare the soil chemical and physical attributes among MZ. The management zones were able to distinguish the average values of Clay, Silt, pH, Ca<sup>2+</sup>, Mg<sup>2+</sup>, SB, Al<sup>3+</sup>, H<sup>+</sup> + Al<sup>3+</sup>, AS%, and BS%. In the field classified as sandy clay loam texture, management zones were able to differentiate the average values of soybean yield, Clay, Ca<sup>2+</sup>, Mg<sup>2+</sup>, SB, and CEC. Thus, this study supports the ECa as an efficient tool for delineating MZ of contrasting cropland soils in southern Brazil to understand the within-field soil variability and adjust the inputs accordingly.</p>
data source for paper "Unity of granular configuration of soil"
<ol> <li>'Table S1' presents soil data sources from China, around the world, and from lunar samples, including their abbreviations, soil textures, locations, and specimen numbers.</li> <li>'GSD data S2' contains grain size distribution data for soils belonging to four models: unimodal, bimodal, trimodal and multimodal.</li> <li>'Matlab code for simulating soil grain size data S3' is designed to simulate soil particles from the source area.</li> </ol>
Data of soil infiltration tests and soil samples, Los Arenales MAR Systems, Santiuste and La Laguna del Señor infiltration basins
<p><span>Infiltration test and soil sample data utilised in the article "a nature-based solution to enhance aquifer recharge: combining trees and infiltration basins"</span></p>
Long-term biochar and soil organic carbon stability– Evidence from field experiments in Germany-ROW DATA
<p> Row data for researcher paper Long-term biochar and soil organic carbon stability– Evidence from field experiments in Germany</p>
Data from: Recovery of silver fir (Abies alba Mill.) seedlings from ungulate browsing mirrors soil nitrogen availability
<p><em>Abies alba</em> (Mill.) has a high potential for mitigating climate change in European mountain forests, yet, its natural regeneration is severely limited by ungulate browsing. Here, we simulated browsing in a common garden experiment to study growth and physiological traits, measured from bulk needles, using a randomized block design with two levels of browsing severity and seedlings originating from 19 populations across Switzerland. Genetic factors explained most variation in growth (on average, 51.5%) and physiological traits (10.2%) under control conditions, while heavy browsing considerably reduced the genetic effects on growth (to 30%), but doubled those on physiological traits related to C storage. While browsing reduced seedling height, it also lowered seedling water use efficiency (decreased δ<sup>13</sup>C) and increased their δ<sup>15</sup>N. Different populations reacted differently to browsing stress, and for seedling height, starch concentration and δ<sup>15</sup>N population differences appeared to be the result of natural selection. First, we found that populations originating from the warmest regions recovered the fastest from browsing stress, and they did so by mobilizing starch from their needles, which suggests a genetic underpinning for a growth-storage trade-off across populations. Second, we found that seedlings originating from mountain populations growing on steep slopes had a higher δ<sup>15</sup>N in the common garden than those originating from flat areas, indicating that they have been selected to grow on N poor, potentially drained, soils. This finding was corroborated by the fact that N concentration in adult needles was lower on steep slopes than on flat ground, strongly indicating that steep slopes are the most N poor environments. These results suggest that populations adapted to these N poor environments have a genetically based high N use efficiency, which could be necessary for their recover from ungulate browsing.</p>
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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.