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2,078 results for “soil data”
Unpublished data: Quantifying CO2 Emissions and Carbon Sequestration from Digestate-Amended Soil Using Natural 13C Abundance as a Tracer
<p>Unprocessed data of CO2 evolution measured daily on cavity ring-down spectroscopy analyser (G2201-i CRDS isotopic CO2/CH4 analyser, Picarro, Santa Clara, CA, USA).</p>
Data from: Mechanical soil disturbance in a pine savanna has multi-year effects on plant species composition
<p>Data used in the manuscript Mechanical soil disturbance in a pine savanna has multi-year effects on plant species composition accepted for publication in Ecosphere. Data included are species lists for all plots and years, percent cover of species in each plot in 2021, and life-history characteristics (life span, dispersal mechanism, seed bank persistence) of all species. See manuscript for site description and data collection methodology. </p>
Data from: Soil incubation methods lead to large differences in inferred methane production temperature sensitivity
<p>Quantifying the temperature sensitivity of methane (CH4) production is crucial for predicting how wetland ecosystems will respond to climate warming. Typically, the temperature sensitivity (often quantified as a Q10 value) is derived from laboratory incubation studies and then used in biogeochemical models. However, studies report wide variation in incubation-inferred Q10 values, with a large portion of this variation remaining unexplained. Here we applied observations in Stordalen Mire, a thawing permafrost peatland, and a well-tested process-rich model, ecosys, to interpret incubation observations and investigate controls on inferred CH4 production temperature sensitivity. We developed a Field-Storage-Incubation (FSI) modeling approach to mimic the full incubation sequence, including field sampling at a particular time in the growing season,refrigerated storage, and the laboratory incubation process, followed by model evaluation. We found that CH4 production rates during incubation are regulated by seasonally-dependent substrate availability and active microbial biomass of key microbial functional groups. Applying a model sensitivity analysis, we found that storage duration, storage temperature, and field sampling time significantly affect CH4 production during incubation. Shorter storage duration and lower storage temperature led to larger CH4 production during incubation. Our findings revealed a wide range of inferred Q10 values (1.2 to 3.5), which we attribute to incubation temperatures, incubation duration, storage duration, and sampling time. Q10 of CH4 production is controlled by many interacting biological, biochemical, and physical processes, which cause the aggregated Q10 values to differ from those of the component processes. Terrestrial ecosystem models that use a constant Q10 value to represent temperature responses may therefore predict biased soil carbon cycling under future climate scenarios.</p> <p>This dataset includes all the data used to plot figures in the manuscript, including Fig.2-6 and Fig.S2-S11. Each sheet in the aggregated spreadsheet corresponds to one figure in the manuscript. The simulation experiment setup and analyses are thoroughly described in the manuscript. Here we provide a brief summary. The data includes field greenhouse gas observations and laboratory incubation measurements of CH4 production in Stordalen Mire. These datasets were already published and references were provided in the manuscript and spreadsheet. The data also includes simulation data, including modeled cumulative CH4 production, CH4 production rates, substrate concentrations, and active microbial biomass under different incubation temperature, sampling time and storage conditions. This data also includes inferred temperature sensitivity of CH4 production as Q10 values under different scenarios. Please refer to the manuscript for more detailed information.</p> <p>Please see "Related works" at the bottom of this page and the "References" tab in the spreadsheet for a full list of source datasets and associated publications.</p> <p> </p> <p>FUNDING:</p> <p>This research is a contribution of the EMERGE Biology Integration Institute, funded by the National Science Foundation, Biology Integration Institutes Program, Award # 2022070.</p> <p>We thank the Swedish Polar Research Secretariat and SITES for the support of the work done at the Abisko Scientific Research Station. SITES is supported by the Swedish Research Council’s grant 4.3-2021-00164. This research used resources of the National Energy Research Scientific Computing Center (NERSC) which is a U.S. Department of Energy Office of Science user facility. This research used the Lawrencium computational cluster resource provided by the IT Division at the Lawrence Berkeley National Laboratory (Supported by the Director, Office of Science, Office of Basic Energy Sciences, of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231). Incubation and field observation data were collected under the IsoGenie Project, which was funded by the Genomic Science Program of the United States Department of Energy Office of Biological and Environmental Research, grant #s DE-SC0004632, DE-SC0010580, and DE-SC0016440.</p>
Data from: Ectomycorrhizal fungi are more sensitive to high soil nitrogen levels in forests exposed to nitrogen deposition
<p>Ectomycorrhizal fungi are essential for nitrogen cycling in many temperate forests and responsive to anthropogenic nitrogen addition, which generally, decreases host carbon allocation to the fungi. In the boreal region, however, ectomycorrhizal fungal biomass has been found to correlate positively with soil nitrogen availability. Still, responses to anthropogenic input, for instance through atmospheric deposition, are commonly negative.</p> <p>To elucidate whether variation in nitrogen supply affects ectomycorrhizal fungi differently depending on geographical context, we investigated ectomycorrhizal fungal communities along two fertility gradients across nemo-boreal forests with similar ranges in soil N/C ratios and inorganic nitrogen availability but located in regions with contrasting rates of nitrogen deposition.</p> <p>Ectomycorrhizal biomass and community composition remained relatively stable across the nitrogen-gradient with low atmospheric nitrogen deposition, but biomass decreased, and the community changed more drastically, with increasing nitrogen availability in the gradient subjected to higher rates of nitrogen deposition. Moreover, potential activities of enzymes involved in ectomycorrhizal mobilisation of organic nitrogen decreased as N/C ratios increased.</p> <p>In forests with low external input, we propose that stabilising feedbacks in tree-fungal interactions maintain ectomycorrhizal fungal biomass and communities even in highly fertile soils. In contrast, anthropogenic nitrogen input seems to impair ectomycorrhizal functions.</p>
Data from: High temperatures and low soil moisture synergistically reduce switchgrass yields from marginal field sites and inhibit fermentation
<p>'Marginal lands' are low productivity sites abandoned from agriculture for reasons such as low or high soil water content, challenging topography, or nutrient deficiency. To avoid competition with crop production, cellulosic bioenergy crops have been proposed for cultivation on marginal lands, however on these sites they may be more strongly affected by environmental stresses such as low soil water content. In this study we used rainout shelters to induce low soil moisture on marginal lands and determine the effect of soil water stress on switchgrass growth and the subsequent production of bioethanol. Five marginal land sites that span a latitudinal gradient in Michigan and Wisconsin were planted to switchgrass in 2013 and during the 2018-2021 growing seasons were exposed to reduced precipitation under rainout shelters in comparison to ambient precipitation. The effect of reduced precipitation was related to the environmental conditions at each site and biofuel production metrics (switchgrass biomass yields and composition and ethanol production). During the first year (2018), the rainout shelters were designed with 60% rain exclusion, which did not affect biomass yields compared to ambient conditions at any of the field sites, but decreased switchgrass fermentability at the Wisconsin Central - Hancock site. In subsequent years, the shelters were redesigned to fully exclude rainfall, which led to reduced biomass yields and inhibited fermentation for three sites. When switchgrass was grown in soils with large reductions in moisture and increases in temperature, the potential for biofuel production was significantly reduced, exposing some of the challenges associated with producing biofuels from lignocellulosic biomass grown under drought conditions.</p>
Data from: The effect of drainage on the fine root biomass, production, and turnover in hemiboreal old-growth forests on organic soils
<p>Information on the capacity of organic soils to capture and store carbon in old-growth forests in the hemiboreal forest zone is scarce and fragmented. However, fine root data can provide valuable insights into soil carbon fluxes. Thus, the aim of the current study was to provide estimates of the fine root biomass (FRB), fine root production (FRP), and fine root turnover (FRT) rate by tree species and other functional groups in old-growth (stand age 131–179 years) forests on mesotrophic organic soils dominated by Scots pine (Pinus sylvestris L.), with (drained mesotrophic organic soil) and without (undrained mesotrophic organic soil) the effects of forest drainage. The sequential soil coring method was used to estimate the FRB and FRP. The total FRB (sum of the FRB of all functional groups) was significantly higher in the undrained sites (6.8±0.3 t ha 1) than in the drained sites (3.97±0.1 t ha 1). The FRB of Scots pine in the undrained forest was significantly higher (1.7±0.1 t ha 1) than in the drained forest (0.5±0.1 t ha 1), supporting an extensive foraging strategy. The significantly higher mean FRB of Norway spruce (Picea abies [L.] Karst.) (1.4±0.1 t ha 1) in the drained sites than the undrained sites (0.7±0.2 t ha-1) can be explained by there being a higher proportion of spruce in the stand compositions, thus a higher standing volume (cubic meters per hectare) of this species and an increased FRB. The FRB of dwarf shrubs (2.43±0.2 t ha-1) formed the largest part of the total FRB in the undrained sites and the second largest (1.16±0.1 t ha-1), following Norway spruce, in the drained sites. The total FRP was similar between the undrained (2.05±0.31 t ha-1 yr-1) and drained (1.82±0.26 t ha-1 yr-1) stands. However, considerable variability in the FRP was observed between different sites of the same forest site type. The FRT rate of Scots pine was twice as high in the drained sites than the undrained sites, suggesting faster nutrient and carbon input into the drained soil compared to the undrained soil. Estimates of FRB, FRP, and FRT rate for different functional groups can be used in carbon-cycle modeling and in further calculations to estimate the carbon budget (balance) in forests on organic soils.</p>
Soil frost heave test data
<p>Soil freezing test data of silty clay, silt and sand were collected. The test data in the document included the frost heaving rate of soil under different plasticity index, dry density, temperature and water content (from left to right).</p>
Phenotypic, weather, soil, and imputed genomic data for the apple REFPOP
<p>Supporting datasets for the article "Integrative multi-environmental genomic prediction in apple" by Jung et al. (2024)<em>.</em></p> <p>Pheno_raw.xlsx – Eleven traits were assessed during up to five years from 2018 to 2022 (Year) at up to five locations* (Country). The traits evaluated were floral emergence (Flowering_begin), flowering intensity (Flowering_intensity), harvest date (Harvest_date),<strong> </strong>total fruit weight (Fruit_weight), fruit number (Fruit_number), single fruit weight (Fruit_weight_single), titratable acidity (Acidity), soluble solids content (Sugar), fruit firmness (Firmness), red over color (Color_over), and russet frequency (Russet_freq_all).</p> <p>Weather_raw.xlsx – Hourly measurements from 2018 to 2022 (Date) of temperature (Temperature), relative humidity (Humidity), and global radiation (Radiation) were obtained at five locations* (Location).</p> <p>Soil_raw.xlsx – Soil characteristics (Variable) were measured at five locations* (Group.1) and two soil depths (Group.2) in 2016.</p> <p>SNPs_final_2022.bed, SNPs_final_2022.bim, SNPs_final_2022.fam – imputed genomic dataset of 303,239 biallelic SNPs in the PLINK format.</p> <p>*The locations correspond to Belgium (BEL), Switzerland (CHE), Spain (ESP), France (FRA) and Italy (ITA).</p>
scmcclelland/joint-mediation-study: Data, Analysis, and Figure Scripts for "Soil organic carbon sequestration jointly-mediated by plants and microbes after compost application"
<p>This repository contains data, analysis, and figure scripts to create findings from the manuscript "Soil organic carbon sequestration jointly-mediated by plants and microbes after compost application" currently under minor revisions.</p> <p>This release includes updated code, primarily improvements to figures, and a new script for a supplementary map figure.</p>
Derived daily timeseries of weather, soil moisture and temperature, flow and nitrogen species (nitrate and nitrite, ammonium) concentrations data for the North Wyke Farm Platform National Biosciences Research Infrastructure, England
<p>For a selection of catchments from the North Wyke Farm Platform in southwest England, where land use conversions have been introduced, daily time series data covering weather conditions (minimum temperature, maximum temperature, total rainfall, wind speed and solar radiation), near-surface soil status (moisture content and temperature), flow and concentrations of key nitrogen species (nitrate and nitrite, ammonium) have been filtered based on attached data quality tags . The datasets run between 2013 and March 2024. For the main climate variables, data gaps were infilled with preceding- and following-on daily data, observations from a nearby weather station or existing national datasets to generate a continuous data series for modelling. For the other data series, annual and seasonal summary statistics on data coverage are provided. Information on significant field events, such as ploughing, drilling and harvest, fertiliser applications and manure spreading were also tabulated.</p>
Data for: "High-resolution Soil Moisture Evolution in Hyper-arid Regions: A Comparison of InSAR, SAR, Microwave, Optical, and Data Assimilation Systems in the southern Arabian Peninsula"
<p>Data accompanying the publication: High-resolution Soil Moisture Evolution in Hyper-arid Regions: A Comparison of InSAR, SAR, Microwave, Optical, and Data Assimilation Systems in the southern Arabian Peninsula. For filenames starting with T: Exponential fit parameters time0 and mag0 for InSAR coherence data. they are binary files, where fit = a*exp(-b*x); a = -log(mag0); b = 1/time0. timeerr contains the uncertainty of the time0 parameter, and maghigh/maglow contain the high and low uncertainty for the mag0 parameter, respectively. For for each frame or overlap region (T101, T28, T130, T28_T101, T130_T28), there is a vrt file (T..._20180524.time0.vrt), which is the metadata file applicable to all files of the same frame. Files starting with mags_times: Exponential fit parameters for ASCAT/SMAP/GLDAS data. the same parameters (time0, timeerr, mag0, maghigh, maglow) can be found in these matlab structure files. In addition, the .mat files contain the offset parameter and related uncertainty, as well as lat/lon information. </p>
Supplementary Table for Earth observation data-driven cropland soil monitoring: A review
<p>Table including 46 manuscripts written in English referring to topsoil monitoring related to Earth observation data-driven cropland soil monitoring: A review paper.</p>
The predication of soil nematode and functional groups abundance in the terrestrial on the Tibetan Plateau (Data Set)
<p>This is the dataset which is generated from the manuscript entitled 'The predication of soil nematode and functional groups abundance in the terrestrial on the Tibetan Plateau'.</p> <p>The spatial resolution of this dataset is about 1 km, of which coordinates systems is WGS84.</p> <p>There are 6 layers of nematode abundance in this GeoTiff file:</p> <p>1. abd - Total Soil Nematode Abundance</p> <p>2. bact - Abundance of bacterivores</p> <p>3. fung - Abundance of fungivores</p> <p>4. herb - Abundance of plant parasite</p> <p>5. omni - Abundance of omnivores</p> <p>6. pred - Abundance of predators</p>
Data from: Metacommunity theory review and its application in community assembly of soil animals
<p>We were interested in community assembly of soil animals and performed a literature study to find out what is known about soil metacommunities. We aimed to study keywords co-occurrence relationships of scientific journal articles in the field of "metacommunity" research from 1992-2017 as a whole. We also investigated the co-occurrence of the top 20 most frequent keywords in five 5-year time periods.</p> <p> </p> <p> </p> <p>In September 2017 we searched the Web of Science with ‘metacommunity’ as the only keyword, and found 1226 English papers published in international journals between January 1992 and September 2017. And we exported these papers from Web of Science as a plain text file (.txt) with the option ‘Full Record and Cited References’, which is archived here. The text file thus contains full records and cited references (in a concise format, so without the titles of the cited papers), and each field is prefaced by a two-character field tag. Afterwards we used the software ‘Citespace’ to create Table 1 and Figure 2 in Guo et al. (2018). We created that Figure 2 using the following settings in Citespace: we choose the “co-occurrence” function and “keyword” as node types, then created keywords co-occurrence relationships (Figure 2). Next, we created lists of the top 20 keywords in different periods, which can reveal the research hotspots (Table 1). The method for extracting the top 20 most frequent keywords was as follows: We use the Web of Science database to retrieve scientific papers from 1992 to 2017, taking into account the relationship between citation and publication time. We calculated the percentage of 200 most cited papers published in each of the 5-year periods. To do so we followed the following steps:</p> <p>Step1: we selected the 200 most cited papers from the entire datset (1226 in the 1992-2017 period).</p> <p>Step 2: we calculated the percentage of those 200 papers published each 5-year period.</p> <p>Step 3: we also calculated an correction coefficient by taking, for each 5-year period, the number of top-200 most cited papers published in that period, and dividing that number by the total number of papers (out of the 1226 selected papers) published in that period.</p> <p>Step 4 Last, we calculate the real keyword frequency by multiplying the keyword frequency in specific 5-year periods with the correction coefficient.</p>
Data from: Monitoring microarthropods assemblages along a pH gradient in a forest soil over a 60 years' time period
<p>The goal of this study was to assess the development, over 60 years, of microarthropod communities over a pH gradient in forest soil.</p> <p>Site Description</p> <p>Hackfort is an oak coppice grove in the East-Southeast of the city of Zutphen in the province of Gelderland, the Netherlands, 52°06′09.7″ N, 6°15′56.0″ E (see Figure 1). The experimental area is about 1.5 ha and is divided in a 10 m × 10 m grid. Vegetation is dominated by common oak (<em>Quercus robur</em>), mixed with birch (<em>Betula pendula</em>), and had in 1959, an understory of wood sage plugs (<em>Teucrium scorodonia</em>), wood anemone (<em>Anemone nemorosa</em>), bracken (<em>Pteridium aquilinum</em>), and wavy-hair grass (<em>Deschampsia flexuosa</em>). In later years, the understory became more dominated by bramble species (<em>Rubus fruticosus </em>and<em> R. idaeus</em>) and common nettles (<em>Urtica dioica</em>) at the edges of the forest, due to increased N deposition from adjacent farmland. The forest is situated at the transition from western riverine deposits and eastern periglacial cover sands. The soil is a riverine deposit with a few elevation differences, making a number of gradients in clay and loam content, which results in many short-distance gradients in soil types, varying from typic haplaquolls with the largest loam contents, via psammaquentic haplorthods to humaqueptic spodic psammaquents, slightly elevated and low in loam contents.</p> <p>Microarthropod Sampling and pH Measurement</p> <p>In 1959, samples were taken at three subsequent dates: 11 September, 9 October, and 30 October. Samples in 1987 were taken on one date, 9 October, just as on 30 October 2019. Samples were taken following a standard procedure, developed at the Institute for Applied Biological Research in Nature, Wageningen, the Netherlands (later merged into the Research Institute for Nature management, Institute for Forestry and Nature Research and Alterra resp., now known as Wageningen Environmental Research); this procedure has been published by Siepel and van de Bund in 1988 (Siepel and van de Bund, 1988). Each mineral soil sample has 100 cc: a volume of 5 cm diameter and 5 cm depth plus litter on top. In 1959, two samples per date were taken on each plot, making a total of 6 samples (only pooled data are available); in 1987 and in 2019, 4 and 5 samples for each plot were taken on, respectively (data per sample available).</p> <p>Soil cores were put on a Tullgren funnel for 1 week, during which temperature was increased from 35 to 45 °C, and then, microarthropods were collected in 70% alcohol and later put into 20% lactic acid for clarification and identification (Siepel, 1990; Siepel and van de Bund, 1988). The Tullgren funnel used for extraction (Siepel, 1990) has been used ever since 1936 and efficiency has not changed as the tool and protocol was the same all over the years.</p> <p>Identification was done to the species level as much as possible using at present the keys for Oribatida(Weigmann and G., 2006), for Gamasina (Lehtinen, 1994), for Uropodina (Karg, 1989), and for Collembola (Hopkin, 2007). Material from the extractions of 1959 and 1987 was re-examined as far as possible to check the correct species identification. In the 1959 and 1987 samples, only oribatid mites were identified to the species level, whereas in 1959, all species of <em>Quadroppiidae, Oppiidae</em>, and <em>Suctobelbidae</em> were pooled. In 2019, all microarthropods were identified to the species level.</p> <p>Sorting and identification of the 1959 microarthropods was carried out by an experienced acarologist (J.G. de Gunst), in 1987, this was done by a student (C. Arnold) and completed and checked by the second author. For the 2019 samples, we decided to demonstrate the potential difference in picking out the microarthropods from the extraction fluid into the slides for identification as part of the experiment: the first author made a first series of slides including all distinguished animals (dataset 2019 a), while the second author made an extra set of slides with the animals missed by the first (dataset 2019 b). The first author did know since the beginning that the second author would check all samples after her sorting session. In this way, we intended to demonstrate the potential difference in this crucial part of the procedure by a starting and an experienced professional. In the analysis, we compare dataset (2019 a) with (2019 a + b), in order to highlight the difference between a starting and an experienced acarologist. Nomenclature adopted was updated according to current standards, following, e.g., the checklists for Oribatida (Siepel et al., 2009), for Astigmatina (Siepel et al., 2016), and for Mesostigmata (Siepel, 2018). Values of pH-KCl were measured in the core material after the extraction of the microarthropods, both in 1959, 1987, and 2019.</p> <p> </p> <p>We have four data files:</p> <p>1959 hackfort microarthropods data.csv</p> <p>1989 hackfort microarthropods data.csv</p> <p>2019 hackfort microarthropods data.csv</p> <p>pH data Hackfort 1959-2019.csv.</p> <p> </p> <p>Explanation of the variables in the datasets:</p> <p>higher taxon: Oribatida, Astigmata, Mesostigmata, Prostigmata, Collembola or Protura</p> <p>Name in De Gunst 1959: taxonomic identification by De Gunst in 1959</p> <p>Valid name: Henk Siepel re-checked these species names in 2019</p> <p>Plot: plot 1, plot 2, plot 3, plot 4, plot 5</p> <p>a: identified by Yuxi Guo</p> <p>b: re-checked by Henk Siepel from remaining soil microarthropods in slide</p> <p>pH(KCL) and pH(H2O): pH values based on indicated methods</p> <p> </p>
Data to support the publication "The Impact of Soil-Improving Cropping Practices on Erosion Rates: A Stakeholder-Oriented Field Experiment Assessment" https://doi.org/10.3390/land10090964
<p>Underlying data of soil measurements and analysis by TUC team for the publication “The Impact of Soil-Improving Cropping Practices on Erosion Rates: A Stakeholder-Oriented Field Experiment Assessment” <a href="https://doi.org/10.3390/land10090964">https://doi.org/10.3390/land10090964</a> from the SoilCare project study sites in Crete. </p> <p>Abstract:</p> <p>The risk of erosion is particularly high in Mediterranean areas, especially in areas that are subject to a not so effective agricultural management–or with some omissions–, land abandonment or wildfires. Soils on Crete are under imminent threat of desertification, characterized by loss of vegetation, water erosion, and subsequently, loss of soil. Several large-scale studies have estimated average soil erosion on the island between 6 and 8 Mg/ha/year, but more localized investigations assess soil losses one order of magnitude higher. An experiment initiated in 2017, under the framework of the SoilCare H2020 EU project, aimed to evaluate the effect of different management practices on the soil erosion. The experiment was set up in control versus treatment experimental design including different sets of treatments, targeting the most important cultivations on Crete (olive orchards, vineyards, fruit orchards). The minimum-to-no tillage practice was adopted as an erosion mitigation practice for the olive orchard study site, while for the vineyard site, the cover crop practice was used. For the fruit orchard field, the crop-type change procedure (orange to avocado) was used. The experiment demonstrated that soil-improving cropping techniques have an important impact on soil erosion, and as a result, on soil water conservation that is of primary importance, especially for the Mediterranean dry regions. The demonstration of the findings is of practical use to most stakeholders, especially those that live and work with the local land.</p>
Data: Spatio-temporal prediction of soil moisture using soil maps, topographic indices and SMAP retrievals
<p><strong>Data used in:</strong></p> <p>Schönauer, M., Prinz, R., Väätäinen, K., Astrup, R., Pszenny, D., Lindeman, H., et al. (2022). Spatiotemporal prediction of soil moisture using soil maps, topographic indices and SMAP retrievals. <em>International Journal of Applied Earth Observation and Geoinformation</em>, 102730. doi: 10.1016/j.jag.2022.102730</p>
Data from: Metabarcoding of soil environmental DNA replicates plant community variation but not specificity
<blockquote> <p>While metabarcoding of plant DNA from their environment is an exciting method that can supplement inventorying of live plant species, the accuracy and specificity has yet to be fully assessed over complex continuous landscapes. In this work, we evaluate plant community profiles produced via metabarcoding of soil by comparing them to a morphological survey. We assessed plant communities by metabarcoding of soil DNA in 130 sites along ecological gradients (nutrients, succession, moisture) in Denmark using chloroplast <i>trn</i>L region (10-143 bp) primer set and compared the resulting communities to communities produced with a longer nuclear ITS2 region (~216 bp) and a morphological survey. We found that the community variation observed within the morphological survey was well represented by molecular surveys, with significant correlation with both community composition and richness using both primer sets. While the majority of the ITS2 sequences could be assigned to species (over 80%), we had less success with the <i>trn</i>L sequences (70%), which was only possible after restricting the reference database to local species. We conclude that the community profiles produced by metabarcoding can be highly effective in performing large-scale macroecological studies. However, the discovery rates and taxonomic assignments produced via metabarcoding remained inferior to morphological surveys, but manual curation of databases improves the <i>specificity</i> of assignments made by the <i>trn</i>L primers, and improves the <i>accuracy</i> of the assignments made with the ITS2 primers. Finally, we suggest that a greater percentage of named diversity would be recovered by increasing soil sampling with the use of additional universal primer sets.</p> </blockquote>
Soil Moisture and Sea Surface Temperature Data for Wikle et al. (2022)
<p>Raw data (.nc) in NetCDF4 format, and formatted and rearranged data (.csv) in CSV format. With R Markdown document detailing the steps taken. All data obtained originally from NOAA's NCEP and NCDC data store systems. </p> <p>Data used in developing and demonstrating explainable AI models for <em>An Overview of Model Agnostic Explainability Methods for Machine Learning Applied to Environmental Data</em>, Wikle et al. (2022), for the <em>Special Issue on Environmental Data Science</em> for <em>Environmetrics. </em>See https://zenodo.org/record/6353636 for the corresponding model codebase. </p>
Data from: Long-term cattle grazing shifts the ecological state of forest soils
<p><span>Cattle grazing profoundly affects abiotic and biotic characteristics of ecosystems. While most research has been performed on grasslands, the effect of large managed ungulates on forest ecosystems has largely been neglected.</span></p> <p><span>Compared to a baseline semi-natural state, we investigated how long-term cattle grazing of birch forest patches affected the abiotic state and the ecological community (microbes and invertebrates) of the soil subsystem.</span></p> <p><span>Grazing strongly modified the soil abiotic environment by increasing phosphorus content, pH and bulk density, while reducing the C:N ratio. The reduced C:N-ratio was strongly associated with a lower microbial biomass, mainly caused by a reduction of fungal biomass. This was linked to a decrease in fungivorous nematode abundance and the nematode channel index, indicating </span><span>a relative </span><span>uplift in the importance of the bacterial energy-channel in the nematode assemblages. </span></p> <p><span>Cattle grazing highly modified invertebrate community composition producing distinct assemblages from the semi-natural situation. Richness and abundance of microarthropods was consistently reduced by grazing (excepting collembolan richness) and grazing-associated changes in soil pH, Olsen P and reduced soil pore volume (bulk density) limiting niche space and refuge from physical disturbance. Anecic earthworm species predominated in grazed patches, but were absent from ungrazed forest, and may benefit from manure inputs, while their deep vertical burrowing behaviour protects them from physical disturbance.</span></p> <p><span>Perturbation of birch forest habitat by long-term ungulate grazing profoundly modified soil biodiversity, either </span><span>directly through increased physical disturbance and manure input or indirectly by modifying soil abiotic conditions.</span><span> Comparative analyses revealed the ecosystem engineering potential of large ungulate grazers in forest systems through major shifts in the composition and structure of microbial and invertebrate assemblages, including the potential for reduced energy flow through the fungal decomposition pathway. The precise consequences for species trophic interactions and biodiversity-ecosystem function relationships remains to be established, however. </span></p>
ScienceDex guides
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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.