Soil Bacterial Community Structure Responses to Precipitation Reduction and Forest Management in Forest Ecosystems across Germany

Soil microbial communities play an important role in forest ecosystem functioning, but how climate change will affect the community composition and consequently bacterial functions is poorly understood. We assessed the effects of reduced precipitation with the aim of simulating realistic future drought conditions for one growing season on the bacterial community and its relation to soil properties and forest management. We manipulated precipitation in beech and conifer forest plots managed at different levels of intensity in three different regions across Germany. The precipitation reduction decreased soil water content across the growing season by between 2 to 8% depending on plot and region. T-RFLP analysis and pyrosequencing of the 16S rRNA gene were used to study the total soil bacterial community and its active members after six months of precipitation reduction. The effect of reduced precipitation on the total bacterial community structure was negligible while significant effects could be observed for the active bacteria. However, the effect was secondary to the stronger influence of specific soil characteristics across the three regions and management selection of overstorey tree species and their respective understorey vegetation. The impact of reduced precipitation differed between the studied plots; however, we could not determine the particular parameters being able to modify the response of the active bacterial community among plots. We conclude that the moderate drought induced by the precipitation manipulation treatment started to affect the active but not the total bacterial community, which points to an adequate resistance of the soil microbial system over one growing season

Differences in the number of phylotypes at the genus level.

<p>The bacterial community was compared between the reduced precipitation (R) and the control (C) subplots of conifer intensive (left) and beech unmanaged (right) plots. (a—Schorfheide, b—Hainich, c—Schwäbische Alb). For plot ID see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0122539#pone.0122539.t001" target="_blank">Table 1</a>.</p

General plot information and characteristics of the understorey plant community.

<p>Plot and understorey properties were obtained from the control and precipitation manipulated subplots for the different exploratories and management types.</p><p>Species richness = total number of species found on the quadratic area of 2.45 m², LAI_sp = leaf area index and H’ = Shannon’s diversity index; mean values and standard deviation of means are provided (n = 4). Plot Sbu had no understorey vegetation.</p><p>^a S = Schorfheide-Chorin; H = Hainich-Dün; A = Schwäbische Alb; bu = beech, unmanaged; bm = beech, managed; cm = conifer, intensively managed;</p><p>^b According to WRB [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0122539#pone.0122539.ref049" target="_blank">49</a>].</p><p>General plot information and characteristics of the understorey plant community.</p

NMS ordination plots of the bacterial community structure obtained from reduced precipitation (R) and control (C) subplots.

<p>Soil samples were taken from nine plots of the three exploratories in September 2012. The community structure of the metabolically active (b, c) and the total (a) bacteria were analysed by T-RFLP (a, b) and tag-pyrosequencing (c). Statistically significant correlations (p < 0.05) of soil characteristics (C_org: soil organic carbon; N_t: total nitrogen) and understorey parameters (richness: species richness and H’: Shannon’s diversity index of the understorey plant community) were indicated by arrows. For plot ID see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0122539#pone.0122539.t001" target="_blank">Table 1</a>.</p

Significance test (MRPP) of the effect of reduced precipitation on the bacterial community structure.

<p>^a Pairwise comparison of the control and precipitation manipulated subplots. For plot ID see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0122539#pone.0122539.t001" target="_blank">Table 1</a>;</p><p>* p < 0.05,</p><p>** p < 0.01</p><p>Significance test (MRPP) of the effect of reduced precipitation on the bacterial community structure.</p

Ratio of the absolute soil water content between reduced precipitation and control subplots.

<p>The absolute water content in the upper 20 cm of the soil was estimated using the forest-hydrological model LWF- Brook90 for all three exploratories (S = Schorfheide; H = Hainich; A = Schwäbische Alb).</p

Phylotypes with abundance shifts between the reduced precipitation and the control subplots.

<p>Shown groups had a relative abundance of more than 1% of the bacterial community and increased or decreased by more than 50% due to reduced precipitation. For plot ID see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0122539#pone.0122539.t001" target="_blank">Table 1</a>.</p

Europa Biodiversity Observation Network: integrating data streams to support policy

Observations are key to understand the drivers of biodiversity loss, and the impacts on ecosystem services and ultimately on people. Many EU policies and initiatives demand unbiased, integrated and regularly updated biodiversity and ecosystem service data. However, efforts to monitor biodiversity are spatially and temporally fragmented, taxonomically biased, and lack integration in Europe. EuropaBON aims to bridge this gap by designing an EU-wide framework for monitoring biodiversity and ecosystem services. EuropaBON harnesses the power of modelling essential variables to integrate different reporting streams, data sources, and monitoring schemes. These essential variables provide consistent knowledge about multiple dimensions of biodiversity change across space and time. They can then be analyzed and synthesized to support decision-making at different spatial scales, from the sub-national to the European scale, through the production of indicators and scenarios. To develop essential biodiversity and ecosystem variables workflows that are policy relevant, EuropaBON is built around stakeholder engagement and knowledge exchange (WP2). EuropaBON will work with stakeholders to identify user and policy needs for biodiversity monitoring and investigate the feasibility of setting up a center to coordinate monitoring activities across Europe (WP2). Together with stakeholders, EuropaBON will assess current monitoring efforts to identify gaps, data and workflow bottlenecks, and analyse cost-effectiveness of different schemes (WP3). This will be used to co-design improved monitoring schemes using novel technologies to become more representative temporally, spatially and taxonomically, delivering multiple benefits to users and society (WP4). Finally, EuropaBON will demonstrate in a set of showcases how workflows tailored to the Birds Directive, Habitats Directive, Water Framework Directive, Climate and Restoration Policy, and the Bioeconomy Strategy, can be implemented (WP5)