| 1. |
- Schwarz, Erik, 1992-, et al.
(författare)
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Spatial Control of Microbial Pesticide Degradation in Soil : A Model-Based Scenario Analysis
- 2022
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Ingår i: Environmental Science and Technology. - : American Chemical Society (ACS). - 0013-936X .- 1520-5851. ; 56:20, s. 14427-14438
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Tidskriftsartikel (refereegranskat)abstract
- Microbial pesticide degraders are heterogeneously distributed in soil. Their spatial aggregation at the millimeter scale reduces the frequency of degrader–pesticide encounter and can introduce transport limitations to pesticide degradation. We simulated reactive pesticide transport in soil to investigate the fate of the widely used herbicide 4-chloro-2-methylphenoxyacetic acid (MCPA) in response to differently aggregated distributions of degrading microbes. Four scenarios were defined covering millimeter scale heterogeneity from homogeneous (pseudo-1D) to extremely heterogeneous degrader distributions and two precipitation scenarios with either continuous light rain or heavy rain events. Leaching from subsoils did not occur in any scenario. Within the topsoil, increasing spatial heterogeneity of microbial degraders reduced macroscopic degradation rates, increased MCPA leaching, and prolonged the persistence of residual MCPA. In heterogeneous scenarios, pesticide degradation was limited by the spatial separation of degrader and pesticide, which was quantified by the spatial covariance between MCPA and degraders. Heavy rain events temporarily lifted these transport constraints in heterogeneous scenarios and increased degradation rates. Our results indicate that the mild millimeter scale spatial heterogeneity of degraders typical for arable topsoil will have negligible consequences for the fate of MCPA, but strong clustering of degraders can delay pesticide degradation.
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| 2. |
- Chakrawal, Arjun, 1992-, et al.
(författare)
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Interacting Bioenergetic and Stoichiometric Controls on Microbial Growth
- 2022
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Ingår i: Frontiers in Microbiology. - : Frontiers Media SA. - 1664-302X. ; 13
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Tidskriftsartikel (refereegranskat)abstract
- Microorganisms function as open systems that exchange matter and energy with their surrounding environment. Even though mass (carbon and nutrients) and energy exchanges are tightly linked, there is a lack of integrated approaches that combine these fluxes and explore how they jointly impact microbial growth. Such links are essential to predicting how the growth rate of microorganisms varies, especially when the stoichiometry of carbon- (C) and nitrogen (N)-uptake is not balanced. Here, we present a theoretical framework to quantify the microbial growth rate for conditions of C-, N-, and energy-(co-) limitations. We use this framework to show how the C:N ratio and the degree of reduction of the organic matter (OM), which is also the electron donor, availability of electron acceptors (EAs), and the different sources of N together control the microbial growth rate under C, nutrient, and energy-limited conditions. We show that the growth rate peaks at intermediate values of the degree of reduction of OM under oxic and C-limited conditions, but not under N-limited conditions. Under oxic conditions and with N-poor OM, the growth rate is higher when the inorganic N (NInorg)-source is ammonium compared to nitrate due to the additional energetic cost involved in nitrate reduction. Under anoxic conditions, when nitrate is both EA and NInorg-source, the growth rates of denitrifiers and microbes performing the dissimilatory nitrate reduction to ammonia (DNRA) are determined by both OM degree of reduction and nitrate-availability. Consistent with the data, DNRA is predicted to foster growth under extreme nitrate-limitation and with a reduced OM, whereas denitrifiers are favored as nitrate becomes more available and in the presence of oxidized OM. Furthermore, the growth rate is reduced when catabolism is coupled to low energy yielding EAs (e.g., sulfate) because of the low carbon use efficiency (CUE). However, the low CUE also decreases the nutrient demand for growth, thereby reducing N-limitation. We conclude that bioenergetics provides a useful conceptual framework for explaining growth rates under different metabolisms and multiple resource-limitations.
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| 3. |
- Chakrawal, Arjun, 1992-, et al.
(författare)
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Modelling optimal ligninolytic activity during plant litter decomposition
- 2024
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Ingår i: New Phytologist. - 0028-646X .- 1469-8137.
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Tidskriftsartikel (refereegranskat)abstract
- A large fraction of plant litter comprises recalcitrant aromatic compounds (lignin and other phenolics). Quantifying the fate of aromatic compounds is difficult, because oxidative degradation of aromatic carbon (C) is a costly but necessary endeavor for microorganisms, and we do not know when gains from the decomposition of aromatic C outweigh energetic costs.To evaluate these tradeoffs, we developed a litter decomposition model in which the aromatic C decomposition rate is optimized dynamically to maximize microbial growth for the given costs of maintaining ligninolytic activity. We tested model performance against > 200 litter decomposition datasets collected from published literature and assessed the effects of climate and litter chemistry on litter decomposition.The model predicted a time-varying ligninolytic oxidation rate, which was used to calculate the lag time before the decomposition of aromatic C is initiated. Warmer conditions increased decomposition rates, shortened the lag time of aromatic C oxidation, and improved microbial C-use efficiency by decreasing the costs of oxidation. Moreover, a higher initial content of aromatic C promoted an earlier start of aromatic C decomposition under any climate.With this contribution, we highlight the application of eco-evolutionary approaches based on optimized microbial life strategies as an alternative parametrization scheme for litter decomposition models.
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| 4. |
- Chakrawal, Arjun, 1992-
(författare)
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Novel approaches in modeling of soil carbon : Upscaling theories and energetics
- 2021
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Soils contain more carbon (C) than terrestrial (above ground) and atmospheric carbon combined. Mismanagement of soil C could lead to increased greenhouse gas emissions, whereas practices leading to increased C storage would help mitigate climate change while improving soil fertility and ecological functions. At the center of these complex feedbacks, soil microorganisms play a pivotal role in the cycling of C and nutrients, and thus in soil-climate interactions. However, this role is not fully understood; therefore, developing new methods for studying their dynamics is essential for an understanding of bio-physicochemical processes leading to mineralization or stabilization of soil organic matter (SOM).Current soil C cycling models lack a robust upscaling approach that links SOM decomposition from process (μm) to observation scale (cm to km). Moreover, these models often neglect energy fluxes from microbial metabolism, which may provide additional constraints in model parameterization and alternative observable quantities such as heat dissipation rate to study decomposition processes. In this doctoral work, I investigated two aspects of microbial processes and their consequences for SOM dynamics: 1) use of energetics to constrain SOM dynamics by explicitly accounting for thermodynamics of microbial growth, and 2) spatial constraints at microscale resulting from the non-uniform distribution of microorganisms and substrates.In the first part of the thesis, I developed a general mass and energy balance framework for the uptake of added substrates and native SOM. This framework provided the theoretical underpinnings for understanding variations in the calorespirometric ratios—the ratio of rates of heat dissipation to CO2 production—a useful metric used as a proxy for microbial carbon-use efficiency (CUE). Moreover, in a follow-up work, I extended this mass-energy framework to describe dynamic (time-varying) conditions, which was used to interpret rates of heat and CO2 evolution from different soils amended with glucose. The dynamic mass-energy framework was also used as a tool for data-model integration and estimation of microbial functional traits, such as their CUE and maximum substrate uptake rates. In the second part of the thesis, I linked the micro and macroscale dynamics of decomposition using scale transition theory. The findings of this study were further validated from laboratory experiments, in which spatial heterogeneity in the added substrate was manipulated.Results from the first part show that the calorespirometric ratios can be used to identify active metabolic pathways and to estimate CUE. Further, the heat dissipation rate can be used as a reliable complement or alternative to mass fluxes such as respiration rates for estimating microbial traits and constraining model parameters. In the second part, I show that the co-location of microorganisms and substrates increased, and separation decreased the microbial activity measured as heat dissipation from the incubation experiment. These results were in line with the expectation from the scale transition theory. In summary, this work provides novel approaches for studying soil C cycling and explicitly highlights a way forward to address two fundamental issues in microbial decomposition—the role of spatial heterogeneities and of energetic constraints on microbial metabolisms.
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| 5. |
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| 6. |
- Manzoni, Stefano, et al.
(författare)
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Decomposition rate as an emergent property of optimal microbial foraging
- 2023
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Ingår i: Frontiers in Ecology and Evolution. - : Frontiers Media SA. - 2296-701X. ; 11
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Tidskriftsartikel (refereegranskat)abstract
- Decomposition kinetics are fundamental for quantifying carbon and nutrient cycling in terrestrial and aquatic ecosystems. Several theories have been proposed to construct process-based kinetics laws, but most of these theories do not consider that microbial decomposers can adapt to environmental conditions, thereby modulating decomposition. Starting from the assumption that a homogeneous microbial community maximizes its growth rate over the period of decomposition, we formalize decomposition as an optimal control problem where the decomposition rate is a control variable. When maintenance respiration is negligible, we find that the optimal decomposition kinetics scale as the square root of the substrate concentration, resulting in growth kinetics following a Hill function with exponent 1/2 (rather than the Monod growth function). When maintenance respiration is important, optimal decomposition is a more complex function of substrate concentration, which does not decrease to zero as the substrate is depleted. With this optimality-based formulation, a trade-off emerges between microbial carbon-use efficiency (ratio of growth rate over substrate uptake rate) and decomposition rate at the beginning of decomposition. In environments where carbon substrates are easily lost due to abiotic or biotic factors, microbes with higher uptake capacity and lower efficiency are selected, compared to environments where substrates remain available. The proposed optimization framework provides an alternative to purely empirical or process-based formulations for decomposition, allowing exploration of the effects of microbial adaptation on element cycling.
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