Bacterial and archaeal spatial distribution and its environmental drivers in an extremely haloalkaline soil at the landscape scale

PeerJ. 2019 Jun 18:7:e6127. doi: 10.7717/peerj.6127. eCollection 2019.

Abstract

Background: A great number of studies have shown that the distribution of microorganisms in the soil is not random, but that their abundance changes along environmental gradients (spatial patterns). The present study examined the spatial variability of the physicochemical characteristics of an extreme alkaline saline soil and how they controlled the archaeal and bacterial communities so as to determine the main spatial community drivers.

Methods: The archaeal and bacterial community structure, and soil characteristics were determined at 13 points along a 211 m transect in the former lake Texcoco. Geostatistical techniques were used to describe spatial patterns of the microbial community and soil characteristics and determine soil properties that defined the prokaryotic community structure.

Results: A high variability in electrolytic conductivity (EC) and water content (WC) was found. Euryarchaeota dominated Archaea, except when the EC was low. Proteobacteria, Bacteroidetes and Actinobacteria were the dominant bacterial phyla independent of large variations in certain soil characteristics. Multivariate analysis showed that soil WC affected the archaeal community structure and a geostatistical analysis found that variation in the relative abundance of Euryarchaeota was controlled by EC. The bacterial alpha diversity was less controlled by soil characteristics at the scale of this study than the archaeal alpha diversity.

Discussion: Results indicated that WC and EC played a major role in driving the microbial communities distribution and scale and sampling strategies were important to define spatial patterns.

Keywords: Biogeography; Cross validation; Geostatistics; Ordinary kriging; Prediction; Soil maps; Soil properties; Spatial patterns.

Associated data

  • figshare/10.6084/m9.figshare.6357344.v1

Grants and funding

This research was funded by ‘Centro de Investigación y de Estudios Avanzados’ (Cinvestav, Mexico), and ‘Apoyo Especial para Fortalecimiento de Doctorado PNPC 2013, 2014’ and project ‘Infraestructura 205945’ from ‘Consejo Nacional de Ciencia y Tecnología’ (CONACyT, Mexico). Martha Adriana Martínez-Olivas (230274) and Carmine Fusaro received a doctoral grant from CONACyT. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.