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5 décembre 2023
- doi: 10.57745/VLWJ51
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Agricultural Sciences Earth and Environmental Sciences biomass molecular biology microbial ecology DNA land use soil soil propertySujets proches
Soil Mould, Vegetable Vegetable mold Earth (Soils) Mold, VegetableCiter ce document
Samuel Dequiedt et al., « RMQS1 molecular microbial biomass », Recherche Data Gouv, ID : 10.57745/VLWJ51
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RMQS: The French Soil Quality Monitoring Network (RMQS) is a national program for the assessment and long-term monitoring of the quality of French soils. This network is based on the monitoring of 2,240 sites representative of French soils and their land use. These sites are spread over the whole French territory (metropolitan and overseas) along a systematic square grid of 16 km x 16 km cells. The network covers a broad spectrum of climatic, soil and land-use conditions (croplands, permanent grasslands, woodlands, orchards and vineyards, natural or scarcely anthropogenic land and urban parkland). The first sampling campaign in metropolitan France took place from 2000 to 2009. Dataset: Soil DNA was extracted and quantified from soils sampled from the center of RMQS grid cells (between 0 and 20cm). A specific and standardized DNA extraction procedure was used so that all samples could be compiled and interpreted in terms of molecular microbial biomass (MMB). See Horrigue et.al. 2016 for details. Values were re-extracted from GenoSol platform database, each value corresponding to the last MMB measure performed between 2012 and 2018. File structure: Two columns tabulated file with a MMB value per sample. id_site: sample/site unique identifier across RMQS. Stripped down from a longer identifier containing campaign number and site type. biomass: molecular microbial biomass measured in microgram of DNA per gram of soil. Details: Some sites sample could not be collected, they do not appear in dataset. Sites with ID longer than 4 number are supplementary sites that are not in the center of the cells (e.g. 10797 and 20797 that came from cell 797). Some of them can replace missing official site (e.g. 12258 is in the dataset, but not 2258. See dataset doi:10.15454/QSXKGA for filtering sites using its site_officiel column.