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pmoA_mapping_Scotland_Appendix S1_NSIS_2_dataset

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NIAID Data Ecosystem2026-03-10 收录
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https://figshare.com/articles/dataset/pmoA_mapping_Scotland_Appendix_S1_NSIS_2_dataset/7039790
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The present dataset is part of the supplementary section of a manuscript (Nazaries et al. 2018 – Environmental drivers of the geographical distribution of methanotrophs: insights from a national survey – manuscript accepted; in production by Soil Biology and Biochemistry) with the aim of mapping the geographical distribution of important methanotrophs (i.e. methane-oxidising bacteria) and their community structure. The first tab (called "Information") of the spreadsheet provided here gives the details (metadata) of the variables available, namely: abbreviation, description (or full name), unit and eventual comments. The second tab (called "NSIS_2 dataset") contains the actual raw data values of this NSIS_2 dataset. It is the collection of 62 climo-edaphic properties and terrain attributes, with a total number of 697 soil samples. It was created for a national-wide soil survey in Scotland named the National Soils Inventory of Scotland re-sampling (NSIS_2). For more details, see link below for Lilly et al. 2010 (see link below). Soil sampling was executed by the James Hutton Institute (Aberdeen) between 2006 and 2009 following a 20-km2 grid (for details, see Yao et al. 2013 – doi: 10.1111/1462-2920.12141). pmoA genes of methanotrophs were isolated by PCR and enzyme restriction was performed using the T-RFLP method (Terminal-Restriction Length Polymorphism – see Singh et al. 2006 – doi:10.1128/AEM.00510-06). The pmoA terminal-restriction fragments (or T-RF) were retained to analyse the methanotroph community structure (122 T-RFs/OTU in total) and bio-geography (see Nazaries et al. 2018 – Environmental drivers of the geographical distribution of methanotrophs: insights from a national survey – manuscript accepted; in production by Soil Biology and Biochemistry). The present dataset corresponds to the Appendix S1 of the manuscript. . From this dataset, the three most abundant T-RFs (pmoA fragments 33 base-pair (bp) long, pmoA-81 and pmoA-130) were modeled to predict their geographical distribution across Scotland in relation to the common ecosystem habitats found across Scotland and their most important physico-chemical soil properties. In order to achieve this, a novel hybrid geo-statistical modelling approach was adopted as summarised in Figure 1 of Nazaries et al. 2018 (Environmental drivers of the geographical distribution of methanotrophs: insights from a national survey – manuscript accepted; in production by Soil Biology and Biochemistry).
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2018-09-20
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