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The effects of afforestation on soil bacterial communities in temperate grassland are modulated by soil chemical properties.

ABSTRACT: Grassland afforestation dramatically affects the abiotic, biotic, and ecological function properties of the original ecosystems. Interference from afforestation might disrupt the stasis of soil physicochemical properties and the dynamic balance of microbiota. Some studies have suggested low sensitivity of soil properties and bacterial community to afforestation, but the apparent lack of a significant relationship is probably due to the confounding effects of the generalist habitat and rare bacterial communities. In this study, soil chemical and prokaryotic properties in a 30-year-old Mongolia pine (Pinus sylvestris var. mongolica Litv.) afforested region and adjacent grassland in Inner Mongolia were classified and quantified. Our results indicate that the high richness of rare microbes accounts for the alpha-diversity of the soil microbiome. Few OTUs of generalist (core bacteria) and habitat-specialist bacteria are present. However, the high abundance of this small number of OTUs governs the beta-diversity of the grassland and afforested land bacterial communities. Afforestation has changed the soil chemical properties, thus indirectly affecting the soil bacterial composition rather than richness. The contents of soil P, Ca2+, and Fe3+ account for differentially abundant OTUs such as Planctomycetes and subsequent changes in the ecologically functional potential of soil bacterial communities due to grassland afforestation. We conclude that grassland afforestation has changed the chemical properties and composition of the soil and ecological functions of the soil bacterial community and that these effects of afforestation on the microbiome have been modulated by changes in soil chemical properties.

SUBMITTER: Wu SH

PROVIDER: S-EPMC6330960 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Project description:The use of plant traits to predict ecosystem functions has been gaining growing attention. Above-ground plant traits, such as leaf nitrogen (N) content and specific leaf area (SLA), have been shown to strongly relate to ecosystem productivity, respiration and nutrient cycling. Furthermore, increasing plant functional trait diversity has been suggested as a possible mechanism to increase ecosystem carbon (C) storage. However, it is uncertain whether below-ground plant traits can be predicted by above-ground traits, and if both above- and below-ground traits can be used to predict soil properties and ecosystem-level functions.Here, we used two adjacent field experiments in temperate grassland to investigate if above- and below-ground plant traits are related, and whether relationships between plant traits, soil properties and ecosystem C fluxes (i.e. ecosystem respiration and net ecosystem exchange) measured in potted monocultures could be detected in mixed field communities.We found that certain shoot traits (e.g. shoot N and C, and leaf dry matter content) were related to root traits (e.g. root N, root C:N and root dry matter content) in monocultures, but such relationships were either weak or not detected in mixed communities. Some relationships between plant traits (i.e. shoot N, root N and/or shoot C:N) and soil properties (i.e. inorganic N availability and microbial community structure) were similar in monocultures and mixed communities, but they were more strongly linked to shoot traits in monocultures and root traits in mixed communities. Structural equation modelling showed that above- and below-ground traits and soil properties improved predictions of ecosystem C fluxes in monocultures, but not in mixed communities on the basis of community-weighted mean traits. Synthesis. Our results from a single grassland habitat detected relationships in monocultures between above- and below-ground plant traits, and between plant traits, soil properties and ecosystem C fluxes. However, these relationships were generally weaker or different in mixed communities. Our results demonstrate that while plant traits can be used to predict certain soil properties and ecosystem functions in monocultures, they are less effective for predicting how changes in plant species composition influence ecosystem functions in mixed communities.

Project description:BackgroundSoil ecosystems consist of complex interactions between biological communities and physico-chemical variables, all of which contribute to the overall quality of soils. Despite this, changes in bacterial communities are ignored by most soil monitoring programs, which are crucial to ensure the sustainability of land management practices. We applied 16S rRNA gene sequencing to determine the bacterial community composition of over 3000 soil samples from 606 sites in New Zealand. Sites were classified as indigenous forests, exotic forest plantations, horticulture, or pastoral grasslands; soil physico-chemical variables related to soil quality were also collected. The composition of soil bacterial communities was then used to predict the land use and soil physico-chemical variables of each site.ResultsSoil bacterial community composition was strongly linked to land use, to the extent where it could correctly determine the type of land use with 85% accuracy. Despite the inherent variation introduced by sampling across ~?1300?km distance gradient, the bacterial communities could also be used to differentiate sites grouped by key physico-chemical properties with up to 83% accuracy. Further, individual soil variables such as soil pH, nutrient concentrations and bulk density could be predicted; the correlations between predicted and true values ranged from weak (R2 value = 0.35) to strong (R2 value = 0.79). These predictions were accurate enough to allow bacterial communities to assign the correct soil quality scores with 50-95% accuracy.ConclusionsThe inclusion of biological information when monitoring soil quality is crucial if we wish to gain a better, more accurate understanding of how land management impacts the soil ecosystem. We have shown that soil bacterial communities can provide biologically relevant insights on the impacts of land use on soil ecosystems. Furthermore, their ability to indicate changes in individual soil parameters shows that analysing bacterial DNA data can be used to screen soil quality. Video Abstract.

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The effects of afforestation on soil bacterial communities in temperate grassland are modulated by soil chemical properties.

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