Dataset for effects of the transition from dry forest to pasture on diversity and structure of bacterial communities in Northeastern Brazil

Diogo Paes da Costa; Ademir Sérgio Ferreira Araujo; Arthur Prudêncio de Araujo Pereira; Lucas William Mendes; Rafaela Felix da França; Thallyta das Graças Espíndola da Silva; Julyana Braga de Oliveira; Jenifer Sthephanie Araujo; Gustavo Pereira Duda; Rômulo Simões Cezar Menezes; Erika Valente de Medeiros

doi:10.1016/j.dib.2022.107842

Dataset for effects of the transition from dry forest to pasture on diversity and structure of bacterial communities in Northeastern Brazil

Data Brief. 2022 Jan 19:41:107842. doi: 10.1016/j.dib.2022.107842. eCollection 2022 Apr.

Affiliations

¹ Microbiology and Enzimology Lab., Federal University of Agreste Pernambuco, 55292-270 Garanhuns, PE, Brazil.
² Soil Quality Lab., Agricultural Science Center, Federal University of Piauí, 64049-550 Teresina, PI, Brazil.
³ Microbial Ecology and Biotechnology Lab., Federal University of Ceará, 60020-181 Fortaleza, CE, Brazil.
⁴ Center for Nuclear Energy in Agriculture, University of Sao Paulo, 13400-970 Piracicaba, SP, Brazil.
⁵ Department of Soils, Federal Rural University of Rio de Janeiro, 23890-000 Seropédica, RJ, Brazil.
⁶ Department of Nuclear Energy, Federal University of Pernambuco, 50740-540 Recife, PE, Brazil.

Abstract

The data included in this article supplement the research article titled "Forest-to-pasture conversion modifies the soil bacterial community in Brazilian dry forest Caatinga (manuscript ID: STOTEN-D-21-19067R1)". This data article included the analysis of 18 chemical variables in 36 composite samples (included 4 replicates) of soils from the Microregion of Garanhuns (Northeast Brazil) and also partial 16S rRNA gene sequences from genomic DNA extracted from 27 of these samples (included 3 best quality replicates) for paired-end sequencing (up to 2 × 300 bp) in Illumina MiSeq platform (NCBI - BioProject accession: PRJNA753707). Soils were collected in August 2018 in a tropical subhumid region from the Brazilian Caatinga, along with 27 composite samples from the aboveground part of pastures to determine nutritional quality based on leaf N content. The analysis of variance (ANOVA) and post-hoc tests of environmental data and the main alpha-diversity indices based on linear mixed models (LMM) were represented in the tables. In this case, the collection region (C1 - Brejão, C2 - Garanhuns, and C3 - São João) was the random-effect variable and adjacent habitats formed by a forest (FO) and two pastures (PA and PB succeeded by this forest) composed the fixed-effect variable (land cover), both nested within C. In addition, a table with similarity percentages breakdown (SIMPER) was also shown, a procedure to assess the average percent contribution of individual phyla and bacterial classes. The figures showed the details of the study location, sampling procedure, vegetation status through the Normalized Difference Vegetation Index (NDVI), in addition to the general abundance and composition of the main bacterial phyla.

Keywords: 16S rRNA; Caatinga biome; Microbial ecology; NDVI; Tropical soil.