Data/hora: 02/06/2024 09:04:05

Biblioteca(s): | Embrapa Florestas.
Data corrente: | 19/11/2018
Data da última atualização: | 22/02/2019
Autoria: | LAMMEL, D. R.; BARTH, G.; OVASKAINEN, O.; CRUZ, L. M.; ZANATTA, J. A.; RYO, M.; SOUZA, E. M. de; PEDROSA, F. O.
Afiliação: | Daniel R. Lammel, UFPR; Gabriel Barth, ABC Research Foundation; Otso Ovaskainen, University of Helsinki; Leonardo M. Cruz, UFPR; JOSILEIA ACORDI ZANATTA, CNPF; Masahiro Ryo, 3Freie Universität Berlin and Berlin-Brandenburg Institute of Advanced Biodiversity Research (BBIB); Emanuel M. de Souza, UFPR; Fábio O. Pedrosa, UFPR.
Título: | Direct and indirect effects of a pH gradient bring insights into the mechanisms driving prokaryotic community structures.
Ano de publicação: | 2018
Fonte/Imprenta: | Microbiome, v. 6, article 106, June 2018. 13 p.
DOI: | 10.1186/s40168-018-0482-8
Idioma: | Inglês
Conteúdo: | Background: pH is frequently reported as the main driver for prokaryotic community structure in soils. However, pH changes are also linked to ?spillover effects? on other chemical parameters (e.g., availability of Al, Fe, Mn, Zn, and Cu) and plant growth, but these indirect effects on the microbial communities are rarely investigated. Usually, pH also co-varies with some confounding factors, such as land use, soil management (e.g., tillage and chemical inputs), plant cover, and/or edapho-climatic conditions. So, a more comprehensive analysis of the direct and indirect effects of pH brings a better understanding of the mechanisms driving prokaryotic (archaeal and bacterial) community structures. Results: We evaluated an agricultural soil pH gradient (from 4 to 6, the typical range for tropical farms), in a liming gradient with confounding factors minimized, investigating relationships between prokaryotic communities (16S rRNA) and physical?chemical parameters (indirect effects). Correlations, hierarchical modeling of species communities (HMSC), and random forest (RF) modeling indicated that both direct and indirect effects of the pH gradient affected the prokaryotic communities. Some OTUs were more affected by the pH changes (e.g., some Actinobacteria), while others were more affected by the indirect pH effects (e.g., some Proteobacteria). HMSC detected a phylogenetic signal related to the effects. Both HMSC and RF indicated that the main indirect effect was the pH changes on the availability of some elements (e.g., Al, Fe, and Cu), and secondarily, effects on plant growth and nutrient cycling also affected the OTUs. Additionally, we found that some of the OTUs that responded to pH also correlated with CO2, CH4, and N2O greenhouse gas fluxes. Conclusions: Our results indicate that there are two distinct pH-related mechanisms driving prokaryotic community structures, the direct effect and ?spillover effects? of pH (indirect effects). Moreover, the indirect effects are highly relevant for some OTUs and consequently for the community structure; therefore, it is a mechanism that should be further investigated in microbial ecology.
Palavras-Chave: | 16S rRNA; Ecologia microbiana; Illumina sequencing; Solo sub tropical; Sub-tropical soil.
Thesagro: | Bactéria; Ph; Química do Solo.
Thesaurus Nal: | Archaea; Microbial ecology; Soil chemistry.
Categoria do assunto: | P Recursos Naturais, Ciências Ambientais e da Terra
URL: | http://ainfo.cnptia.embrapa.br/digital/bitstream/item/186279/1/2018-Josi-Microbiome-Direct.pdf
Registro original: | Embrapa Florestas (CNPF)
Exemplares: | CNPF - (56560-1) - UPC - AP - DD -  -  -  - DIS