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4 results for “PLFA”
Peat characteristics, microbial PLFA, and fungal and actinobacterial sequences from Lakkasuo peatland drainage experiment, year 2004
<p>We analysed the response of microbial communities, characterized by phospholipid fatty acids (PLFAs), and fungal and actinobacterial communities, characterized by PCR-DGGE fingerprinting and direct sequencing, to changing hydrological conditions at three different sites in the boreal peatland complex Lakkasuo in southern Finland. Additionally, several peat characteristics were measured. The experimental design involved undrained controls as well as short-term (3 years) and long-term (43 years) water-level drawdown. The sites were, in their undrained state, a herb-rich sedge fen, a sedge fen, and a bog with hummock-lawn-hollow microtopography.</p> <p>Codes are explained in the Notes sheets of the Excel files. The contents of the csv files are identical to the corresponding Excel file data sheets.</p> <p>Please check the decimal separator! Comma is used in Finland, and that may have been carried over. All commas in data columns are decimal separators.</p>
Enzymes, PLFA, NLFA and soil properties measured in Juniperus thurifera forest expansion gradient
<table> <tbody> <tr> <td>Columns<span> </span></td> <td>Description</td> <td>Unit</td> <td>Comments</td> </tr> <tr> <td>Site</td> <td>Huertahernando, Ribarredonda, Maranchón</td> <td> </td> <td>3 levels</td> </tr> <tr> <td>Stage</td> <td>Stage of forest expansion gradient (Mature forest, transition zone and expanding front)</td> <td> </td> <td>3 levels</td> </tr> <tr> <td>Microhabitat</td> <td>Under canopy/Open areas</td> <td> </td> <td>2 levels</td> </tr> <tr> <td>Sample code</td> <td>Sample code corresponding to sampling point</td> <td> </td> <td> </td> </tr> <tr> <td>Plot</td> <td>18 plots</td> <td> </td> <td> </td> </tr> <tr> <td>From F to AG<span> </span></td> <td>PLFAs peaks</td> <td>nmol g-1 soil</td> <td> </td> </tr> <tr> <td>Column AF</td> <td>NLFA peak</td> <td>nmol g-1 soil</td> <td> </td> </tr> <tr> <td>OM<span> </span></td> <td>organic matter</td> <td>%</td> <td> </td> </tr> <tr> <td>pH</td> <td>pH</td> <td> </td> <td> </td> </tr> <tr> <td>From AK to AQ</td> <td>Enzimes</td> <td>pmol mg-1 min-1</td> <td> </td> </tr> </tbody> </table>
Dataset for the article "Beyond PLFA: Concurrent extraction of neutral and glycolipid fatty acids provides new insights into soil microbial communities"
<p>The following are data and code used for statistical analysis and figure plotting in the manuscript</p> <p>Gorka et al. (2023) "Beyond PLFA: Concurrent extraction of neutral and glycolipid fatty acids provides new insights into soil microbial communities", Soil Biology and Biochemistry</p> <p>It contains the following files:</p> <p>1. Pure lipid standard data</p> <ul> <li>Total ion chromatogram (TIC) area data (<strong>area.csv</strong>)</li> <li>Assignment of lipids that the measured fatty acids originate from (<strong>LipidClass.csv</strong>)</li> <li>An R script reproducing the calculations and plotting for Fig. 2 and Fig. S1 (<strong>pure_lipids.R</strong>)</li> </ul> <p>2. Microbial pure culture fatty acid data data</p> <ul> <li>TIC area data of the PLFA, NLFA, and GLFA data from pure culture extracts (<strong>area.csv</strong>)</li> <li>Files needed for calculating the data and assigning taxonomic groups in the R code (<strong>weights.csv</strong>, <strong>C_atoms.csv</strong>, <strong>species_list.csv</strong>)</li> <li>An R script reproducing the calculations and plotting for Fig. 3, Fig. 4, Fig. S2, and Fig. S3 (<strong>pure_cultures.R</strong>)</li> </ul> <p>3. Soil fatty acid data</p> <ul> <li>Absolute abundance data in nmol C g<sup>-1</sup> dry weight of the PLFA, NLFA, and GLFA data from soil extracts (<strong>nmolC.csv</strong>)</li> <li>Taxonomic group assignments of fatty acids needed to run the R code (<strong>phylum.csv</strong>)</li> <li>An R script reproducing the calculations and plotting for Fig. 5, and Fig. S4 (<strong>soil.R</strong>)</li> </ul>
Site data and PLFA obtained along a rainfall and soil type gradient in the Sahel region of West Africa 2019-2020 (PRJNA930013)
<p>The Sahel of West Africa is a vulnerable biome that is experiencing rapid population growth, agricultural intensification, and soil degradation that threatens food security. A potential solution is intercropping with the indigenous shrub, <em>Guiera senegalensis</em>, that coexists with crops to varying degrees in farmers’ fields throughout the Sahel. Previous research of the Optimized Shrub-intercropping System (OSS) with <em>G. senegalensis</em> (high density of ~1200 1500 shrubs ha<sup>-1</sup> ) with annual incorporation of coppiced residue) has been shown to dramatically improve pearl millet (<em>Pennisetum glaucum</em>) yield; attributed in part to improved soil quality, nutrient availability, water use efficiency and harboring a distinct and active microbial community that may confer benefits to surrounding crops. Whether this microbial response is consistent over a climate and soil type gradient in farmers’ fields has not been investigated. Therefore, the objective was to determine the microbiomes and metabolic pathways of millet root zone soil in the presence or absence of <em>G. senegalenis</em>, sampled along a north-south soil and rainfall gradient in farmers’ fields. The experimental design was a completely randomized 3 X 2 factorial (2 landscape replications) with the following treatments: three rainfall (450 to 750 mm per annum)/soil type gradient sites north to south in the Senegal Peanut Basin and two sampling location treatments (millet root zone soil within and outside the influence of the <em>G.</em> <em>senegalensis</em>). <em>G. senegalensis</em> shifted certain predicted bacterial metabolic pathways and enriched certain bacterial and fungal genera, some of which are known to have plant growth promoting properties. These positive shrub effects were most evident at the northern site that has low rainfall and low organic matter soils. Here we share soil chemical, plant and PLFA datasets obtained in the 2019- 2020 sampling seasons and related to metagenomic data publicly available via NCBI PRJNA930013.</p>
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