Disturbance triggers non-linear microbe–environment feedbacks

Jason Toyoda,Robert E. Danczak,Aditi Sengupta,James C. Stegen,Sarah J. Fansler,Vanessa A. Garayburu-Caruso,Rosalie K. Chu,Jacqueline Wells,Hyun-Seob Song,Lupita Renteria

doi:10.5194/bg-18-4773-2021

Abstract

Abstract. Conceptual frameworks linking microbial community membership, properties, and processes with the environment and emergent function have been proposed but remain untested. Here we refine and test a recent conceptual framework using hyporheic zone sediments exposed to wetting–drying transitions. Our refined framework includes relationships between cumulative properties of a microbial community (e.g., microbial membership, community assembly properties, and biogeochemical rates), environmental features (e.g., organic matter thermodynamics), and emergent ecosystem function. Our primary aim was to evaluate the hypothesized relationships that comprise the conceptual framework and contrast outcomes from the whole and putatively active bacterial and archaeal communities. Throughout the system we found threshold-like responses to the duration of desiccation. Membership of the putatively active community – but not the whole bacterial and archaeal community – responded due to enhanced deterministic selection (an emergent community property). Concurrently, the thermodynamic properties of organic matter (OM) became less favorable for oxidation (an environmental component), and respiration decreased (a microbial process). While these responses were step functions of desiccation, we found that in deterministically assembled active communities, respiration was lower and thermodynamic properties of OM were less favorable. Placing the results in context of our conceptual framework points to previously unrecognized internal feedbacks that are initiated by disturbance and mediated by thermodynamics and that cause the impacts of disturbance to be dependent on the history of disturbance.

Highlights

1.1 Conceptual foundationsGiven the influence of microbes over ecosystem function, deeper knowledge of microbe–environment relationships is needed to improve ecosystem models (Bier et al, 2015)
We evaluated relationships between cumulative properties of the microbial community, environmental features, and emergent ecosystem function by hypothesizing that (i) stronger influences of determinism result in well-adapted microbes that will generate higher respiration rates; (ii) longer duration in an inundated state will result in greater influences of stochastic assembly – due to weaker ecological selection – and lower respiration rates following re-inundation due to relatively consistent abiotic conditions (Birch, 1964); (iii) microbial processes are facilitated by organic matter (OM) that is thermodynamically more favorable for oxidation, leading to an association between respiration rates and OM thermodynamics; and (iv) more wet–dry transitions will increase among-replicate heterogeneity, thereby increasing control point influence (CPI) by increasing withintreatment variability in respiration rates
The sediments were subjected to increasing temporal environmental variance and evaluated for associations between microbial membership, microbial properties, microbial community assembly, OM chemistry, absolute respiration rate, and cumulative respiration rates represented as CPI

Summary

Introduction

1.1 Conceptual foundationsGiven the influence of microbes over ecosystem function, deeper knowledge of microbe–environment relationships is needed to improve ecosystem models (Bier et al, 2015). There is strong interest in quantifying and predicting microbe–environment relationships such as defining microbial life history strategies as traits in ecosystem models (Malik et al, 2020), assessing microbial biomass stoichiometry distributions in response to changing resource environments (Manzella et al, 2019), and evaluating the extent of microbial adaptation to changing environments and their role in biogeochemical processes (Wallenstein and Hall, 2012). To enhance and synthesize understanding of microbe– environment interactions, it is useful to develop conceptual frameworks based on linkages among microbial characteristics and ecosystem processes. Previous work has used such frameworks to improve mechanistic representation and predictive capacity of microbe–environment interactions in ecosystem models (Wieder et al, 2015).

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