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237 results for “Soil properties”
Supplementary material 1 from: Baum S, Weih M, Bolte A (2012) Stand age characteristics and soil properties affect species composition of vascular plants in short rotation coppice plantations. BioRisk 7: 51-71. https://doi.org/10.3897/biorisk.7.2699
Number of plots containing the respective species is stated.
Slope position affects growth and allometry of the endangered conifer Calocedrus macrolepis by mediating soil properties and microbial communities
<p><strong>Premise:</strong><em> </em>The allometric relationships among growth traits are highly relevant for a tree's fitness, however, the mechanism of how the slope position affects the plant growth and allometry remains poorly understood, hindering our understanding of the variation in allometry of trees along slope position in mountainous areas.</p> <p><strong>Methods:</strong> A typical slope of <em>Calocedrus macrolepis</em> plantation in southwest China was chosen to measure growth traits and their allometric relationships. In addition, spatial variations in soil properties and microbial communities were also investigated.</p> <p><strong>Results:</strong><em> </em>Slope position altered the allometric growth pattern with the larger allometric exponents of the tree height, diameter and wood volume relative to the crown size and height under the branch for the downslope. Additionally, most of soil nutrients, microbial diversity and abundances were greater at mesoslope and downslope, especially at the surface soil layer. The relative abundance both in Chloroflexi and Actinobacteria differed significantly among slope positions, while fungal dominant phyla abundances varied little across slope positions, indicating that bacterial community was more sensitive to slope position than fungal community. The growth traits and allometry were affected by the slope position, which is mainly caused by the variations of soil properties and microbial communities, and bacteria were more important than fungi in their relationships to growth traits and allometry.</p> <p><strong>Conclusions:</strong> Together, results emphasized that slope position indirectly influences the growth traits and allometry of <em>C. macrolepis</em> by regulating soil nutrients and microbial communities, which will provide important theoretical basis for the plantation management of <em>C. macrolepis</em>.</p>
C-isotopic signatures and soil properties of Amazon basin oxisols
<p>This dataset presents C isotopic data from two sites (Apuí and Manacapuru) located in the state of Amazonas, Brazil. Soils were sampled at three time periods, under weak raining (March-2016), extreme dry (August-2016), and strong wet (March-2017) conditions. The dataset first presents general information about the site (on the tab "site"), followed by more detailed information (on the tab "profile") about both sampling locations. The coordinates, altitude, mean annual temperature, mean annual precipitation, soil order in USDA taxonomy and their respective land use categories and vegetation classifications are described. </p> <p>On the 'layer' tab, information about the soil depth, percent sand, silt and clay, pH CaCl2 and H2O, Organic and Total Carbon, total nitrogen and carbon/nitrogen ratio are described. The bulk C-isotopic signature is also listed on this tab as the Bulk Layer Δ14C and its standard deviation, Bulk Layer Fraction Modern and its standard deviation. </p> <p>The "Incubation" tab describes details of the soil incubations conducted at Apuí and Manacapuru. Information about the material and length of incubation, as well as the CO2 fluxes over the duration of incubation are reported. The respired C-isotopic signature during the incubation is also given on this tab as the incubation Δ14C and its standard deviation, incubation Fraction Modern and its standard deviation. </p>
Soil properties and crop yield in fruit orchards under Mediterranean conditions in terms of intercropping, tillage and fertilizer type
<p>This data set contains a data-mining performed to assess the impact of intercropping, tillage and fertilizer type on soil and crop yield in fruit orchards under Mediterranean conditions by a further meta-analysis of the data. </p> <p>These data correspond to the open-access article "The impact of intercropping, tillage and fertilizer type on soil and crop yield in fruit orchards under Mediterranean conditions: A meta-analysis of field studies" published in Agricultural Systems. (<a href="https://doi.org/10.1016/j.agsy.2019.102736">https://doi.org/10.1016/j.agsy.2019.102736</a>), funded by he European Commission Horizon 2020 project Diverfarming [grant agreement 728003]. Raúl Zornoza acknowledges the financial support from the Spanish Ministry of Science, Innovation and Universities through the “Ramón y Cajal” Program [RYC-2015-18758].. </p> <p> </p>
Soil Properties and Soil Macroinvertebrate Communities in Amazonian Anthropogenic Soils
<h3><strong>About</strong></h3> <p>This dataset is an update of the dataset 'A “Dirty” Footprint: Soil macrofauna biodiversity and fertility in Amazonian Dark Earths and adjacent soils' previously published in Dryad repository (https://doi.org/10.5061/dryad.3tx95x6cc). This dataset now include information on soil humification index, soil carbon related to different soil minerals and soil fatty acids characterization.</p> <h3><strong>Description</strong></h3> <p>Soils were sampled in Brazilian Amazonia in the municipalities of Iranduba-AM, Belterra-PA and Porto Velho-RO. In each region, paired sites with anthropogenic dark earths (ADE) and nearby reference (REF) non-anthropogenic soils were sampled under three different land-use systems: native secondary vegetation (<em>dense ombrophilous forest</em>) classified as old secondary forest when >20 years old, or young regeneration forest when <20 years old, and agricultural systems (maize in Iranduba, soybean in Belterra, and introduced pasture in Porto Velho).</p> <p>At each site, soil and litter macrofauna were collected using the Tropical Soil Biology and Fertility (TSBF) method (Anderson and Ingram, 1993) at five sampling points (soil monoliths 25x25 cm up to 30 cm depth) within a 1 ha plot, four at the corners and one on the center of a 60 x 60 m square, resulting in an “X” shaped sampling design. Each soil monolith was divided into surface litter and three 10 cm-thick soil layers (0-10, 10-20, 20-30 cm). Macroinvertebrates (animals with >2 mm body width) were manually hand-sorted and fixed in 92% ethanol. Earthworms, ants and termites were identified to species or genus level and other macroinvertebrates were sorted into morphospecies with higher taxonomic level assignations. Density (number of individuals) and biomass of the soil macrofauna surveyed using the TSBF method were extrapolated per square meter.</p> <p>For the earthworms, ants and termites (ecosystem engineers) additional samples were performed, especially in forest sites to better estimate species richness of these taxa. Earthworms were collected at four additional cardinal points of the grid at all sites, and hand-sorted from holes of similar dimensions as the TSBF monoliths. Termites were sampled in the forest sites only forests (except one of the REF young forests at Porto Velho), in five 20 m<sup>2</sup> (2 x 10 m) plots (close to the five main soil monoliths) by manually digging the soil and looking for termitaria in the soil, as well as in the litter and on trees using a modification of the transect method (Jones and Eggleton, 2000). Ants were sampled in 10 pitfall traps (300 ml plastic cups) set up as two 5-trap transects on the sides of each 1 ha plot, as well as in two traps to the side of each TSBF monolith (distant ~5 m) only in the forest systems of Iranduba and Belterra (not Porto Velho). Each cup was filled to a third of its volume with water, salt and detergent solution. Termites and ants were preserved in 80% ethanol and earthworms in 96% ethanol and the alcohol changed after cleaning the samples within 24 h. All the animals (earthworms, ants, termites) were identified to species level or morphospecies level (with genus assignations) by co-authors SWJ/MLCB (earthworms), AA (termites) and ACF/RMF (ants).</p> <p>Soil samples for chemical and particle size analysis were collected from each TSBF monolith after the soil fauna hand-sorting. Around 2 to 3 kg soil from each depth (0-10, 10-20, 20-30 cm) and the following soil properties were evaluated according to standard methodologies (Teixeira et al., 2017): pH (CaCl<sub>2</sub>); Ca<sup>2+</sup>, Mg<sup>2+</sup>, Al<sup>3+</sup> (KCl 1 mol L<sup>-1</sup>); K<sup>+</sup>, P, Fe, Zn, Mn, Cu and Ni (Mehlich-1); Pseudo-total contents of trace elements (Ba, Cd, Co, Cu, Ni, Pb, Se and ZN) were determined by acid digestion (HNO<sub>3</sub> + HCl); Fe (sulfuric extract); total nitrogen (TN) and carbon (TC) using an element analyzer (CNHS). Base saturation and cation exchange capacity (CEC) were calculated using standard formulae (Teixeira et al., 2017) and particle size fractions (% sand, silt, clay) were obtained following standard methodologies (Teixeira et al., 2017). Soil magnetic susceptibility (MS) and apparent electrical conductivity (EC<sub>a</sub>) (Siemens per meter – S m<sup>-1</sup>) were obtained using a KT-10 S/C magnetic susceptibility/conductivity meter (Terraplus) with 10 Hz of operating frequency.</p> <p>Soil macromorphology samples were taken close to the TSBF monolith (~2 m) using a 10 x 10 x 10 cm metal frame. The collected material was separated into different fractions including: living invertebrates, litter, roots, pebbles, pottery sherds, charcoal (biochar), non-aggregated/loose soil (NA), physical aggregates (PA), root-associated aggregates (RA), and fauna-produced aggregates (FA) using the methodology proposed by Velasquez et al. (2007).</p> <p>Laser-induced fluorescence spectroscopy analysis (LIFS) was performed on soil macroaggregate fraction (FA, PA, RA and NAS) from both YF and the pasture from Porto Velho to obtain the humification index of soil organic matter according to Milori et al. (2006).</p> <p>Were analysed fatty acids in soil macroaggregates (PA, RA and FA) from one site in Teotônio. The process involved extracting 2 g of each sample with a chloroform: methanol solution and a surrogate compound, 5α-cholestane. The extract was centrifuged, combined, and the solvent removed using a rotary evaporator and nitrogen. Extracts were stored at -20°C until analyzed by GC-MS. Samples were silylated, with excess silylating agent removed, followed by the addition of hexane and vortexing for GC-Q-MS analysis. The equipment used included an Agilent Technologies GC (7890B) and MS (5977A), with an autosampler and HP-5ms column. MassHunter and MSD ChemStation software facilitated analysis and quantification, respectively. Deconvolution and retention index calculations were performed using AMDIS software. Compounds were identified using NIST MS software, requiring at least three specific mass fragments per compound and a retention index deviation of less than 1.5%. Analyte intensities were normalized by dried soil sample weights and the internal standard.</p> <p>Soil samples from TSBF monoliths were fractionated by dry sieving into small (<500 µm) and large (>500 µm) aggregate size classes. These were further fractionated into sand-particulate organic matter (sand-MOP) (>53 µm), silt-organic matter associated with minerals (MOM) (53-2 µm), and clay-MOM (<2 µm). Total organic carbon and nitrogen in these fractions were measured using a Vario EL III elemental analyzer. Clay-MOM samples underwent a four-step sequential extraction with hydroxylamine, sodium dithionite, sodium pyrophosphate, and sodium hydroxide to determine carbon, silicon, iron, and aluminum contents associated with different soil components. For further details see Ramalho (2020).</p> <p>Soil bulk density and total porosity were determined using undisturbed core samples (0.05 m diameter, 0.05 m depth) collected at ~2 m from the TSBF samples following the method proposed by Teixeira et al. (2017).</p> <p>All data is provided in excel format, and includes 14 tabs in the data file: Metadata and legend, Site description, Soil chem, BD+POR, Macromorph, Seq_ext, Biomark, HLIF, Macro_den, Macro_bio, Morpho_TSBF, Add_worm, Add_ants, Add_termites. The Metadata and legend tab provides a detailed explanation for each variable included in each table, including the units used for each. The Site description tab include a brief description of the sites sampled. Soil chem, BD+POR, Macromorph, Seq_ext, Biomark and HLIF tables contain the data on soil chemical, physical, macromorphological, organic matter related to soil minerals, fatty acids and humidification index variables, respectively. The Macro_den and Macro_bio contain the data about density and biomass on all the soil invertebrate taxa found, respectively. The Morphosp_TSBF, Add_worm, Add_ants and Add_termites tables contain the invertebrate species/morphospecies occurrence in TBSF and extra samples for earthworms, ants and termites, respectively.</p> <h3><strong>References used in methods section</strong></h3> <p>Anderson, J.M., Ingram, J.S.I., 1993. Tropical Soil Biology and Fertility: A handbook of methods, 2 edition. ed. Oxford University Press, Oxford. https://doi.org/10.2307/2261129</p> <p>Jones, D.T., Eggleton, P., 2000. Sampling termite assemblages in tropical forests: testing a rapid biodiversity assessment protocol. Journal of Animal Ecology 37, 191–203. https://doi.org/10.1046/j.1365-2664.2000.00464.x</p> <p>Milori, D.M.B.P., Galeti, H.V.A., Martin-Neto, L., Dieckow, J., González-Pérez, M., Bayer, C., Salton, J., 2006. Organic Matter Study of Whole Soil Samples Using Laser-Induced Fluorescence Spectroscopy. Soil Science Society of America Journal. 70, 57. https://doi.org/10.2136/sssaj2004.0270</p> <p>Teixeira, P.C., Donagemma, G.K., Fontana, A., Teixeira, W.G., 2017. Manual de métodos de análise de solo, 3<sup>o</sup>. ed. Embrapa, Brasília.</p> <p>Ramalho. B., 2020. Caracterização das interações organo-mineral em Terra Preta de Índio. Thesis. Universidade Federal do Paraná. 113p.</p> <p>Velasquez, E., Pelosi, C., Brunet, D., Grimaldi, M., Martins, M., Rendeiro, A.C., Barrios, E., Lavelle, P., 2007. This ped is my ped: Visual separation and near infrared spectra allow determination of the origins of soil macroaggregates. Pedobiologia 51, 75–87. https://doi.org/10.1016/j.pedobi.2007.01.002</p> <h3><strong>Funding</strong></h3> <p>The study was supported by the Newton Fund and Fundação Araucária (grant Nos. 45166.460.32093.02022015, NE/N000323/1), Natural Environment Research Council (NERC) UK (grant No. NE/M017656/1), a European Union Horizon 2020 Marie-Curie fellowship to LC (MSCA-IF-2014-GF-660378) and another to DWGS (No. 796877), by CAPES scholarships to WCD, ACC, TF, RFS, AF, LM, HSN, TS, AM and RSM (PVE A115/2013), Araucaria Foundation scholarships to LB, AS, ACC and ES, Post-doctoral fellowships to DWGS (NERC grant NE/M017656/1) and ES (CNPq No. 150748/2014-0), PEER (Partnerships for Enhanced Engagement in Research Science Program) NAS/USAID award number AID-OAA-A-11-0001 - project 3-188 to RMF, and by CNPq grants, scholarships and fellowships to ACF, GGB, RF, SWJ, EGN and PL (Nos. <a>140260/2016-1</a>, 307486/2013-3, 302462/2016-3, <a>401824/2013-6</a>, 307179/2013-3, 400533/2014-6). We thank INPA, UFOPA, Embrapa Rondônia, Embrapa Amazônia Ocidental and Embrapa Amazônia Oriental and their staff for logistical support, and the farmers for access to and permission to sample on their properties. Sampling permit for Tapajós National Forest was granted by ICMBio.</p>
Measured properties in soil samples and marine sediment collected in Galion Bay (Martinique, France) in order to trace erosion sources in insular tropical catchments
<p>This dataset was compiled in order to select the optimal suite of tracers and identify and quantify the main sources of sediment deposited in Galion Bay and associated chlordecone transfers since the 1960s. It includes measured properties for potential sources collected across the Galion catchment (Martinique, France) and along a sediment core sampled in Galion Bay (GAL17-04, N°IGSN TOAE0000000573). Associated with this dataset, metadata are integrated for sources and targets registered using International Geological Sample Numbers (IGSN).</p>
Soil properties and Q10 values along a latitudinal transect and for a 4-year laboratory incubation
<p>Soil physicochemical protection, substrates and microorganisms data were included for soils collected from seven sites along a 5,000-km-long latitudinal transect and from a 4-year laboratory incubation experiment. Q10 values data for microorganism reciprocal transplant experiments and aggregate disruption experiments were also included.</p>
Tree communities and soil properties influence fungal community assembly in neotropical forests
<p>The influence exerted by tree communities, topography and soil chemistry on the assembly of macrofungal communities remains poorly understood, especially in highly diverse tropical forests. Here, we used a large dataset that combines inventories of macrofungal Basidiomycetes fruiting bodies, tree species composition and measurements for 16 soil physico-chemical parameters, collected in 34 plots located in four sites of lowland rainforests in French Guiana. Plots were established on three different topographical conditions: hilltop, slope and seasonally flooded soils. We found hyperdiverse Basidiomycetes communities, mainly comprising members of Agaricales and Polyporales. Phosphorus, clay contents and base saturation in soils strongly varied across plots and shaped the richness and composition of tree communities. The latter composition explained 23% of the variation in the composition of macrofungal communities, probably through high heterogeneity of the litter chemistry and selective effects of biotic interactions. The high local heterogeneity of habitats influenced the distribution of both macrofungi and trees, as a result of diversed local soil hydromorphic conditions associated to contrasting soil chemistry. This first regional study across habitats of French Guiana forests revealed new niches for macrofungi, such as ectomycorrhizal ones, and illustrate how macrofungi inventories are still paramount to can be to understand the processes at work in the tropics.</p>
Large-scale drivers of relationships between soil microbial properties and organic carbon across Europe
<p>The aim of this study was to quantify direct and indirect relationships between soil microbial community properties (potential basal respiration, microbial biomass) and abiotic factors (soil, climate) in three major land-cover types.</p> <p>Location: Europe</p> <p>Time period: 2018</p> <p>Major taxa studied: Microbial community (fungi and bacteria)</p> <p>We collected 881 soil samples from across Europe in the framework of the Land Use/Land Cover Area Frame Survey (LUCAS). We measured potential soil basal respiration at 20ºC and microbial biomass (substrate-induced respiration) using an O2-microcompensation apparatus. Climate and soil data were obtained from previous LUCAS surveys and online databases. Structural equation modeling (SEM) was used to quantify relationships between variables, and equations extracted from SEMs were used to create predictive maps. Fatty acid methyl esters were measured in a subset of samples to distinguish fungal from bacterial biomass. Soil microbial properties in croplands were more heavily affected by climate variables than those in forests. Potential soil basal respiration and microbial biomass were correlated in forests but decoupled in grasslands and croplands, where microbial biomass depended on soil carbon. Forests had a higher ratio of fungi to bacteria than grasslands or croplands. Soil microbial communities in grasslands and croplands are likely carbon-limited in comparison with those in forests, and forests have a higher dominance of fungi indicating differences in microbial community composition. Notably, the often already-degraded soils of croplands could be more vulnerable to climate change than more natural soils. The provided maps show potentially vulnerable areas that should be explicitly accounted for in coming management plans to protect soil carbon and slow the increasing vulnerability of European soils to climate change.</p>
Dataset associated with "Assessment of the effects of the 2021 Caldor megafire on soil physical properties, eastern Sierra Nevadas, USA"
<p>This dataset includes both raw and processed data associated with the publication entitled "Assessment of the effects of the 2021 Caldor megafire on soil physical properties, eastern Sierra Nevadas, USA", published in MDPI Fire (doi: <a href="https://doi.org/10.3390/fire6020066">10.3390/fire6020066</a>). Raw files include exported .xlsx files from Meter Group HYPROP analyses, .csv files from 10 replicate measurements of saturated hydraulic conductivity for each analyzed sample using the Meter Group KSAT device, and raw .dat files from measurement of bulk thermal properties. A single additional file also documents the laboratory results from particle size and loss on ignition analyses. Processed data includes curve fitting parameters associated with fitting the soil water retention curves (SWRC) and thermal conductivity functions (TCFs) for each sample, as described in Sion et al. (2023). Additional requests associated with data from Sion et al. (2023) should be directed to the lead author.</p>
Spatial soil properties maps for Switzerland at 30 m resolution
<p>The Swiss Soil Property Map (SSPM) was developed using the quantile random forest machine learning algorithm and remotely sensed surrogate information such as terrain, climate, vegetation, and soil covariates. The SSPM dataset provides maps at 30 m resolution for different soil depths (0, 30, 60, and 100 cm) in GeoTIFF format. The mean and respective uncertainty information is provided for each map. Please note that the phosphorus spatial map is only available for the topsoil (0-20 cm) due to the unavailability of the dataset at deeper depths.</p> <table> <caption>Description of soil properties (SP) and their units</caption> <tbody> <tr> <td>SP</td> <td>Description</td> <td>units</td> </tr> <tr> <td>Sand </td> <td>Sand content</td> <td>%</td> </tr> <tr> <td>Clay</td> <td>Clay content</td> <td>%</td> </tr> <tr> <td>OC</td> <td>Organic carbon content </td> <td>%</td> </tr> <tr> <td>N</td> <td>Nitrogen content</td> <td>% </td> </tr> <tr> <td>P</td> <td>Phosphorus content</td> <td>mg/kg</td> </tr> </tbody> </table> <p>For more details / to cite this dataset please use:</p> <ul> <li><strong>Gupta, S. </strong>, Hasler, K. J., Alewell, C.: Mapping soil properties of Switzerland using remote sensing datasets and machine learning approach. Manuscript <strong>submitted</strong>, <strong>Geoderma Regional</strong>, 2023</li> </ul> <p> </p>
Effects of plant traits and ecosystem properties on wave attenuation and soil carbon content
<p><span>Understanding</span><span> the</span><span> relationships among the environment, species traits and ecosystem properties is important </span><span>for developing</span><span> management measures </span><span>that optimize</span><span> the delivery of ecosystem services (</span><span>ESs</span><span>). Here, we identify the most important relationships responsible for the delivery of two key </span><span>ESs</span><span> provided by tidal marshes: (1) nature-based shoreline protection through wave attenuation and (2) mitigation of climate change through soil carbon storage. In two tidal zones below and above the mean high water (MHW, Elbe Estuary, Germany) level, we measured environmental parameters, such as soil salinity and inundation, as well as plant traits representing adaptations to hydrodynamic stress and strongly influencing decomposition rates.</span></p> <p><span>Multiple linear regression</span> <span>results showed that wave attenuation rates were positively related to aboveground community biomass and stem bending resistance, and soil organic carbon was positively related to stem-specific density (below the MHW level). In the tidal zone above the MHW level, soil carbon density was governed by inundation duration and decomposition rates.</span></p> <p><span>Our study highlights that (1) ES</span> <span>delivery is not equally spread across tidal marshes and (2) ecosystem management should stimulate the development and persistence of habitat diversity (here</span><span>,</span><span> low and high marsh zones)</span> <span>to maximize ES delivery potential. Securing the delivery of the two studied ESs under climate change will depend on providing suitable (</span><span>landward</span><span>) space to sustain the functioning of the two marsh zones. In the studied marshes, these services are highly dependent on a few species (i.e., wave attenuation on <em>Schoenoplectus tabernaemontani</em> and <em>Bolboschoenus maritimus</em> and carbon storage on <em>Phragmites australis</em>)</span><span>,</span><span> and as such</span><span>,</span><span> current and future ESs strongly depend on specific species' responses to changing environmental conditions.</span></p>
Data from: Can the soil seed bank of Rumex obtusifolius in productive grasslands be explained by management and soil properties?
<p><em>Rumex obtusifolius</em> is a problematic weed in temperate grasslands worldwide as it decreases yield and nutritional value of forage. Because the species can recruit from the seed bank, we determined the effect of management and soil properties on the soil seed bank of <em>R. obtusifolius</em> in intensively managed, permanent grasslands in Switzerland (CH), Slovenia (SI), and United Kingdom (UK). Following a paired case-control design, soil cores were taken from the topsoil of grassland with a high density of <em>R. obtusifolius</em> plants (cases) and from nearby parcels with very low R. obtusifolius density (controls). Data on grassland management, soil nutrients, pH, soil texture, and density of R. obtusifolius plants were also collected. Seeds in the soil were germinated under optimal conditions in a glasshouse. The number of germinated seeds of R. obtusifolius in case parcels was 866 ±152 m<sup>-2</sup> (CH, mean ±SE), 628 ±183 m<sup>-2</sup> (SI), and 752 ±183 m<sup>-2</sup> (UK), with no significant difference among countries. Densities in individual case parcels ranged from 0 up to approximately 3000 seeds m<sup>-2</sup> (each country). Control parcels had significantly fewer seeds, with a mean of 51 ±18, 75 ±52, and 98 ±52 seeds m<sup>-2</sup> in CH, SI, and UK, respectively, and a range between 0 and up to 1000 seeds m-2. Across countries, variables explaining variation in the soil seed bank of <em>R. obtusifolius</em> in case parcels were soil pH (negative relation), silt content (negative), land-use intensity (negative), and aboveground <em>R. obtusifolius</em> plant density (positive). Because a large soil seed bank can sustain grassland infestation with <em>R. obtusifolius</em>, management strategies to control the species should target the reduction in the density of mature plants, prevention of the species' seed production and dispersal, as well as the regulation of the soil pH to a range optimal for forage production.</p>
Soil water retention curves and soil physicochemical properties
<p class="MsoPlainText"><span>To identify the contribution of soil organic and inorganic fractions to soil water retention, we compiled the data of soil water retention curves and soil physicochemical properties. Data includes site information (Table 1), soil pH, soil C, cation exchange capacity (CEC), exchangeable basic cations, particle size distribution, soil texture class, contents of short-range-order minerals (Table 2), and soil water retention at different pressures, saturated hydraulic conductivity, and termite nest percent in soil profile (Table 3).</span></p>
Influence of small-scale spatial variability of soil properties on yield formation of winter wheat
<p>This is a data set of soil properties and plant properties of winter wheat.</p> <p>The data derived from a long-term field trial for the year 2016 at the Asendorf field station 70 km north of Hanover, Germany (49 m above sea level, 52°45′48.4′′N 9°01′24.3′′E) and a field site in Triesdorf, located in Northern Bavaria (450 m a.s.l., 49°12'36.5"N 10°38'33.9"E).</p> <p>Data includes soil (OC, bulk density, texture, pH-value) and plant data (grain yield, thousand grain weight, tillers per m², spikes per m²). All methods and data will be described in an upcoming journal article in the Journal Plant and Soil (DOI:10.1007/s111104-023-06212-2).</p>
Data from: Photodegradation modifies microplastic effects on soil properties and plant performance
<p>Microplastics in soil affect plant-soil systems depending on their shape and polymer type. However, previous research has not yet considered the effects of degraded plastics, which are the plastic materials actually present in the environment. We selected 8 microplastics representing different shapes (fibers, films and foams) and polymer types, and exposed them to UV-C degradation. Each microplastic was mixed with soil at a concentration of 0.4% (w/w). The phytometer Daucus carota grew in each pot. At harvest, soil properties and plant biomass were measured.</p> <p>Photodegradation altered microplastics physical and chemical properties, impacting plant-soil systems. Microplastics degradation effects on plant and soil were observed with fibers and foams, but there were negligible effects with films. The latter could be explained by the polymer structure of films and manufacturer's additives, potentially delaying their degradation.</p> <p>Degraded fibers increased soil respiration more than their non-degraded counterparts, as photodegradation increased the positive effects of fibers on soil water retention. The emergence of oxygenated groups during degradation may have increased the hydrophilicity of fibers, enhancing their ability to retain water. Degraded foams increased soil respiration, which could be related to the possible leaching of organic substances with lower partition coefficients, which may promote soil microbial activity.</p> <p>By contrast, degraded foams decreased soil aggregation, likely as degradation produced larger holes increasing their permeability. Also, the increase of hydrophilic molecules could have decreased soil particle cohesiveness. Degraded fibers and foams increased shoot and root mass as a result of microplastic effects on soil properties. Photodegraded microplastics affected root traits, which could be linked to microplastic effects on soil water status and plant coping strategies.</p>
Data from: Relationships between rhizosphere microbial communities, soil abiotic properties and root trait variation within a pine species
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Leaf enzyme plays a more important role in leaf nitrogen resorption efficiency than soil properties along an elevation gradient
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Changes in community-weighted trait mean, functional diversity, soil chemical properties and temperature along an elevational gradient in Tenerife, Canary Islands
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Soil water retention curves and soil physicochemical properties
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