Microbial dynamics in a High Arctic glacier forefield: a combined field,
laboratory, and modelling approach

Abstract. Modelling the development of soils in glacier forefields is necessary in order to assess how microbial and geochemical processes interact and shape soil development in response to glacier retreat. Furthermore, such models can help us predict microbial growth and the fate of Arctic soils in an increasingly ice-free future. Here, for the first time, we combined field sampling with laboratory analyses and numerical modelling to investigate microbial community dynamics in oligotrophic proglacial soils in Svalbard. We measured low bacterial growth rates and growth efficiencies (relative to estimates from Alpine glacier forefields) and high sensitivity of bacterial growth rates to soil temperature (relative to temperate soils). We used these laboratory measurements to inform parameter values in a new numerical model and significantly refined predictions of microbial and biogeochemical dynamics of soil development over a period of roughly 120 years. The model predicted the observed accumulation of autotrophic and heterotrophic biomass. Genomic data indicated that initial microbial communities were dominated by bacteria derived from the glacial environment, whereas older soils hosted a mixed community of autotrophic and heterotrophic bacteria. This finding was simulated by the numerical model, which showed that active microbial communities play key roles in fixing and recycling carbon and nutrients. We also demonstrated the role of allochthonous carbon and microbial necromass in sustaining a pool of organic material, despite high heterotrophic activity in older soils. This combined field, laboratory, and modelling approach demonstrates the value of integrated model–data studies to understand and quantify the functioning of the microbial community in an emerging High Arctic soil ecosystem.

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Microbial dynamics in a High-Arctic glacier forefield: a combined field, laboratory, and modelling approach

10.5194/bg-2016-52 ◽

2016 ◽

Author(s):

James A. Bradley ◽

Sandra Arndt ◽

Marie Šabacká ◽

Liane G. Benning ◽

Gary L. Barker ◽

...

Keyword(s):

Microbial Community ◽

Numerical Model ◽

Microbial Communities ◽

Community Dynamics ◽

Heterotrophic Bacteria ◽

High Arctic ◽

Soil Development ◽

Arctic Soils ◽

Field Laboratory ◽

Modelling Approach

Abstract. Modelling the development of soils in glacier forefields is necessary in order to assess how microbial and geochemical processes interact and shape soil development in response to glacier retreat. Furthermore, such models can help us predict microbial growth and the fate of Arctic soils in an increasingly ice-free future. Here, for the first time, we combined field sampling with laboratory analyses and numerical modelling to investigate microbial community dynamics in oligotrophic proglacial soils in Svalbard. We measured low bacterial growth rates and growth efficiencies (relative to estimates from Alpine glacier forefields), and high sensitivity to soil temperature (relative to temperate soils). We used these laboratory measurements to inform parameter values in a new numerical model and significantly refined predictions of microbial and biogeochemical dynamics of soil development over a period of roughly 120 years. The model predicted the observed accumulation of autotrophic and heterotrophic biomass. Genomic data indicated that initial microbial communities were dominated by bacteria derived from the subglacial environment, whereas older soils hosted a mixed community of autotrophic and heterotrophic bacteria. This finding was validated by the numerical model, which showed that active microbial communities play key roles in fixing and recycling carbon and nutrients. We also demonstrated the role of allochthonous carbon and microbial necromass in sustaining a pool of organic material, despite high heterotrophic activity in older soils. This combined field, laboratory and modelling approach demonstrates the value of integrated model-data studies to understand and quantify the functioning of the microbial community in an emerging High-Arctic soil ecosystem.

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Towards a function-first framework to make soil microbial ecology predictive

10.5194/egusphere-egu21-14139 ◽

2021 ◽

Author(s):

Johannes Rousk ◽

Lettice Hicks

Keyword(s):

Microbial Community ◽

Environmental Factors ◽

Microbial Communities ◽

Functional Response ◽

Community Composition ◽

Ecosystem Function ◽

Bacterial Growth ◽

Response Curve ◽

Ecosystem Functions ◽

Soil Microbial

Soil microbial communities perform vital ecosystem functions, such as the decomposition of organic matter to provide plant nutrition. However, despite the functional importance of soil microorganisms, attribution of ecosystem function to particular constituents of the microbial community has been impeded by a lack of information linking microbial function to community composition and structure. Here, we propose a function-first framework to predict how microbial communities influence ecosystem functions.We first view the microbial community associated with a specific function as a whole, and describe the dependence of microbial functions on environmental factors (e.g. the intrinsic temperature dependence of bacterial growth rates). This step defines the aggregate functional response curve of the community. Second, the contribution of the whole community to ecosystem function can be predicted, by combining the functional response curve with current environmental conditions. Functional response curves can then be linked with taxonomic data in order to identify sets of &#8220;biomarker&#8221; taxa that signal how microbial communities regulate ecosystem functions. Ultimately, such indicator taxa may be used as a diagnostic tool, enabling predictions of ecosystem function from community composition.In this presentation, we provide three examples to illustrate the proposed framework, whereby the dependence of bacterial growth on environmental factors, including temperature, pH and salinity, is defined as the functional response curve used to interlink soil bacterial community structure and function. Applying this framework will make it possible to predict ecosystem functions directly from microbial community composition.

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Role of bacterial growth rates in the epidemiology and pathogenesis of urinary infections in women.

Journal of Clinical Microbiology ◽

10.1128/jcm.10.6.766-771.1979 ◽

1979 ◽

Vol 10 (6) ◽

pp. 766-771 ◽

Cited By ~ 14

Author(s):

J D Anderson ◽

F Eftekhar ◽

M Y Aird ◽

J Hammond

Keyword(s):

Bacterial Growth ◽

Growth Rates ◽

Urinary Infections ◽

Bacterial Growth Rates

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Estimations of Bacterial Growth Rates in Natural Waters1

Journal of Bacteriology ◽

10.1128/jb.99.1.156-160.1969 ◽

1969 ◽

Vol 99 (1) ◽

pp. 156-160 ◽

Cited By ~ 74

Author(s):

Holger W. Jannasch

Keyword(s):

Bacterial Growth ◽

Growth Rates ◽

Bacterial Growth Rates

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Linking Microbial Community Structure to Trait Distributions and Functions Using Salinity as an Environmental Filter

mBio ◽

10.1128/mbio.01607-19 ◽

2019 ◽

Vol 10 (4) ◽

Cited By ~ 7

Author(s):

Kristin M. Rath ◽

Arpita Maheshwari ◽

Johannes Rousk

Keyword(s):

Community Structure ◽

Microbial Community ◽

Salt Tolerance ◽

Microbial Communities ◽

Bacterial Growth ◽

Soil Microbes ◽

Fungal Growth ◽

Environmental Filter ◽

Trait Distribution ◽

Nonsaline Soil

ABSTRACT The structure and function of microbial communities vary along environmental gradients; however, interlinking the two has been challenging. In this study, salinity was used as an environmental filter to study how it could shape trait distributions, community structures, and the resulting functions of soil microbes. The environmental filter was applied by salinizing nonsaline soil (0 to 22 mg NaCl g−1). Our targeted community trait distribution (salt tolerance) was determined with dose-response relationships between bacterial growth and salinity. The bacterial community structure responses were resolved with Illumina 16S rRNA gene amplicon sequencing, and the microbial functions determined were respiration and bacterial and fungal growth. Salt exposure quickly resulted in filtered trait distributions, and stronger filters resulted in larger shifts. The filtered trait distributions correlated well with community composition differences, suggesting that trait distribution shifts were driven at least partly by species turnover. While salt exposure decreased respiration, microbial growth responses appeared to be characterized by competitive interactions. Fungal growth was highest when bacterial growth was inhibited by the highest salinity, and it was lowest when the bacterial growth rate peaked at intermediate salt levels. These findings corroborated a higher potential for fungal salt tolerance than bacterial salt tolerance for communities derived from a nonsaline soil. In conclusion, by using salt as an environmental filter, we could interlink the targeted trait distribution with both the community structure and resulting functions of soil microbes. IMPORTANCE Understanding the role of ecological communities in maintaining multiple ecosystem processes is a central challenge in ecology. Soil microbial communities perform vital ecosystem functions, such as the decomposition of organic matter to provide plant nutrition. However, despite the functional importance of soil microorganisms, attribution of ecosystem function to particular constituents of the microbial community has been impeded by a lack of information linking microbial processes to community composition and structure. Here, we apply a conceptual framework to determine how microbial communities influence ecosystem processes, by applying a “top-down” trait-based approach. By determining the dependence of microbial processes on environmental factors (e.g., the tolerance to salinity), we can define the aggregate response trait distribution of the community, which then can be linked to the community structure and the resulting function performed by the microbial community.

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