DOI: 10.5061/dryad.ht76hdrvz
title: First atlas of soil microbial biodiversity in Mexico: a biogeographical approach

description: Mexico is recognized for its great biological diversity, supported by a
 wide variety of ecosystems. Nonetheless, to date, there is no
 comprehensive study about the magnitude of microbial diversity and its
 biogeographical patterns across Mexican ecosystems. Here, we present a
 meta-analysis describing the diversity and biogeographical patterns of
 soil microbial communities across Mexico. We gathered 16S rRNA sequencing
 data from &gt; 700 soil samples collected across Mexico. We analyzed
 whether soil microbial communities differ between ecoregions and
 vegetation types. In addition, we evaluated the influence of edaphic and
 climatic factors on the diversity patterns of soil microbial communities.
 Our results showed that soil bacterial communities across Mexico exhibit
 biogeographical patterns across ecoregions and vegetation types.
 Specifically, diversity patterns in arid regions significantly differ from
 those in temperate and tropical ecoregions. Through redundancy and
 correlation analysis, we found that pH, carbon and nitrogen levels,
 temperature, and precipitation are the main drivers of the bacterial
 diversity patterns across ecoregions and vegetation types. This work
 contributes to a better understanding of the biogeographical patterns of
 soil microorganisms across Mexico, highlighting the influence of
 environmental variation in driving such diversity patterns.
description: # First atlas of soil microbial biodiversity in Mexico: a biogeographical
 approach Dataset DOI: [10.5061/dryad.ht76hdrvz] ## Description of the data
 and file structure These data and scripts were used to retrieve and
 analyze information from 718 soil samples obtained from peer-reviewed
 studies and novel sequencing efforts investigating the bacterial diversity
 of Mexican soils. ### Files and variables #### File:
 Metadata_final_atlas.csv.csv **Description:**  ##### Variables * sampleID:
 Name of the sample Data from SoilGrids * bdod = Bulk density of the fine
 earth fraction (cg/cm³) * cfvo = Volumetric fraction of coarse fragments
 (&gt; 2 mm) (cm3/dm3 (vol‰)) * nitrogen = Total nitrogen (N) (cg/kg) *
 phh2o = Soil pH (pHx10) * sand = Proportion of sand particles (&gt;
 0.05/0.063 mm) in the fine earth fraction (g/kg) * silt = Proportion of
 silt particles (≥ 0.002 mm and ≤ 0.05/0.063 mm) in the fine earth fraction
 (g/kg) * soc = Soil organic carbon content in the fine earth fraction
 (dg/kg) * ocd = Organic carbon density (hg/m³) Data from Global-AI_PET *
 AI = Aridity Index (mean annual precipitation / mean annual evaporation
 demand) Data from WorldClim * BIO1 = Annual Mean Temperature (°C) * BIO2 =
 Mean Diurnal Range (Mean of monthly (max temp - min temp)) (°C) * BIO3 =
 Isothermality (BIO2/BIO7) (×100) (%) * BIO4 = Temperature Seasonality
 (standard deviation ×100) * BIO5 = Max Temperature of Warmest Month (°C) *
 BIO6 = Min Temperature of Coldest Month (°C) * BIO7 = Temperature Annual
 Range (BIO5-BIO6) (°C) * BIO8 = Mean Temperature of Wettest Quarter (°C) *
 BIO9 = Mean Temperature of Driest Quarter (°C) * BIO10 = Mean Temperature
 of Warmest Quarter (°C) * BIO11 = Mean Temperature of Coldest Quarter (°C)
 * BIO12 = Annual Precipitation (mm) * BIO13 = Precipitation of Wettest
 Month (mm) * BIO14 = Precipitation of Driest Month (mm) * BIO15 =
 Precipitation Seasonality (Coefficient of Variation) (%) * BIO16 =
 Precipitation of Wettest Quarter (mm) * BIO17 = Precipitation of Driest
 Quarter (mm) * BIO18 = Precipitation of Warmest Quarter (mm) * BIO19 =
 Precipitation of Coldest Quarter (mm) * ELEV = Elevation (masl) #### File:
 Soil_atlas_R_code.Rmd **Description:** R code use to analyze 16S amplicon
 data generated in Qiime2 #### Supplementary_Table_1.csv **Description:**
 Table containing the SRR_ID for each sample used in this study. These IDs
 are used by Dumping_SRA.sh to download data from the SRA database ####
 faith_pd_vector.qza **Description:** QZA generated by Qiime containing
 Faith's Phylogenetic diversity metrics for each sample at a read
 depth of 40,000 sequences per sample #### observed_features_vector.qza
 **Description:** QZA generated by Qiime containing Observed features
 (Richness) metrics for each sample at a read depth of 40,000 sequences per
 sample #### shannon_vector.qza **Description:** QZA generated by Qiime
 containing Shannon index metrics for each sample at a read depth of 40,000
 sequences per sample #### weighted_unifrac_distance_matrix.qza
 **Description:** QZA generated by Qiime containing a weighted unifrac
 distance matrix for the 718 samples at a read depth of 40,000 sequences
 per sample #### estadosmx.shp **Description:** Mexico shape file used as
 input for the microgeo package in R #### insertion-tree.qza
 **Description:** QZA generated by Qiime containing a phylogenetic tree
 inferred using the fragment-insertion sepp plugin #### Final_table.qza
 **Description:** QZA generated by Qiime, containing an ASV table inferred
 by DADA2 #### Final_seqs.qza **Description:** QZA generated by Qiime,
 containing a representative sequence table inferred by DADA2 ####
 Final_taxonomy.qza **Description:** QZA generated by Qiime, containing the
 taxonomic assignments for each ASV using a naive-bayes classifier trained
 using the V3-V4 region of the 16S rRNA recovered from Silva DB 138.1 ####
 File: Dumping_SRA.sh **Description:** Script to download data from the SRA
 db using the SRR_ID provided for each sample in Supplementary Table 1 ####
 File: Qiime_commands **Description:** Comands used to procces 16S rRNA
 data  #### File: Extract_data_from_kms_or_kml_files
 **Description:** Commands to obtain geographical data from KML files ####
 File: Manifest_creator.sh **Description:** Script to create manifest files
 used to import fastq file into Qiime2 ## Code/software To view the files
 in this repository, you will need access to a terminal, a text editor, or
 an R console. ## Access information Other publicly accessible locations of
 the code: *
 [https://github.com/mexico-soil-biodiversity/Code-for-mexico-soil-bacterial-atlas-/tree/main/Code](https://github.com/mexico-soil-biodiversity/Code-for-mexico-soil-bacterial-atlas-/tree/main/Code) Data was derived from the following sources: * [https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1230145](https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1230145) (data set of 16S rRNA sequenced generated by our group) * [https://www.ncbi.nlm.nih.gov/sra/](https://www.ncbi.nlm.nih.gov/sra/) (The files from peer-reviewed publications were retrieved from SRA DB; accession numbers are provided in Supplementary Table 1) ### Note The dataset of this study contains both data generated by our research group and publicly available data from the NCBI SRA database. All newly generated data are original contributions and can be released under CC0. The data recovered from the SRA DB are openly accessible and publicly accessible without restriction once released according to NCBI policy, with no restrictions incompatible with CC0.