Soil pH Determines Microbial Diversity and Composition in the Park Grass Experiment

Abstract

The Park Grass experiment (PGE) in the UK has been ongoing since 1856. Its purpose is to study the response of biological communities to the long-term treatments and associated changes in soil parameters, particularly soil pH. In this study, soil samples were collected across pH gradient (pH 3.6-7) and a range of fertilizers (nitrogen as ammonium sulfate, nitrogen as sodium nitrate, phosphorous) to evaluate the effects nutrients have on soil parameters and microbial community structure. Illumina 16S ribosomal RNA (rRNA) amplicon sequencing was used to determine the relative abundances and diversity of bacterial and archaeal taxa. Relationships between treatments, measured soil parameters, and microbial communities were evaluated. Clostridium, Bacteroides, Bradyrhizobium, Mycobacterium, Ruminococcus, Paenibacillus, and Rhodoplanes were the most abundant genera found at the PGE. The main soil parameter that determined microbial composition, diversity, and biomass in the PGE soil was pH. The most probable mechanism of the pH impact on microbial community may include mediation of nutrient availability in the soil. Addition of nitrogen to the PGE plots as ammonium sulfate decreases soil pH through increased nitrification, which causes buildup of soil carbon, and hence increases C/N ratio. Plant species richness and plant productivity did not reveal significant relationships with microbial diversity; however, plant species richness was positively correlated with soil microbial biomass. Plants responded to the nitrogen treatments with an increase in productivity and a decrease in the species richness.

Contribution of soil respiration to the global carbon equation

“…The importance of soil enzymes to ecosystem functions, including soil respiration, has been reviewed by Makoi and Ndakidemi (2008). Soil microbial communities and activities are regulated by climate, oxygen supply, nutrient levels, pH, and substrate availability (Zogg et al, 1997;Yao et al, 2000;Barnard et al, 2014;Zhalnina et al, 2015). Given the fast propagation of microbes, microbial regulation of Rs is mainly conducted through the constraints of the above biotic and abiotic factors on microbial communities.…”

Soil resilience and recovery: rapid community responses to management changes

“…In addition to these overarching effects, there are temporal fluctuations in soil microbial community structure within replicate plots, albeit less marked than between treatments (Lauber et al 2013). Although comparison of long-term treatments provides evidence that soil management influences soil biota (Hirsch et al 2009;Zhalnina et al 2013Zhalnina et al , 2015, there is scant information on the responses during the early years following change.…”

“…Many studies show differences in communities from soils with contrasting treatments Garbeva et al 2008;Geisseler and Scow 2014;de Quadros et al 2012;Zhalnina et al 2013). In non-agricultural systems there is evidence for the development of distinct bacterial communities selected over centuries (Cutler et al 2014;Jangid et al 2011) and fungal communities over decades (Hogberg et al 2014) with soil pH a major factor in microbial community structure at continental, landscape and field scale (Fierer and Jackson 2006;Griffiths et al 2011;Zhalnina et al 2015). Soil factors including pH and C: N ratio had a greater influence than land use on bacterial communities in Netherlands soil (Kuramae et al 2011), although these factors will also be influenced by agricultural land use.…”

Changes of anaerobic to aerobic conditions but not of crop type induced bulk soil microbial community variation in the initial conversion of paddy soils to drained soils

“…On the one hand, pH directly influences bacterial and fungal physiology status (Beales, 2004;Royer-Tardif et al, 2010). On the other hand, pH influences nutrient availability and ion toxicity in soils (Zhalnina et al, 2015). In the current study, soil pH was significantly correlated with other soil parameters, such as IN (R 2 = 0.682, P = 0.006, Supplementary material, Table S1).…”