Romul_Hum model of soil organic matter formation coupled with soil biota activity. I. Problem formulation, model description, and testing

Komarov, Alexander; Chertov, Oleg; Быховец, С. С.; Shaw, Cindy; Nadporozhskaya, Marina; Frolov, P.A.; Shashkov, Maxim; Shanin, Vladimir; Grabarnik, Pavel; Priputina, Irina; Zubkova, Elena

doi:10.1016/j.ecolmodel.2016.08.007

Cited by 40 publications

(33 citation statements)

References 66 publications

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“…This is at least partly explained by the failure of the exponential models to take into account the slow decomposition rate at the early stages of decomposition (Figures a and b). In addition, organic matter stabilization by fungi or other soil biota during the decomposition process (Chertov et al, ; Komarov et al, ) may explain slow decomposition rate of the remaining fraction in the late decay phases.…”

Section: Discussionmentioning

confidence: 99%

Carbon flux from decomposing wood and its dependency on temperature, wood N₂ fixation rate, moisture and fungal composition in a Norway spruce forest

Rinne‐Garmston

Peltoniemi

Chen

et al. 2019

Global Change Biology

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Globally 40–70 Pg of carbon (C) are stored in coarse woody debris on the forest floor. Climate change may reduce the function of this stock as a C sink in the future due to increasing temperature. However, current knowledge on the drivers of wood decomposition is inadequate for detailed predictions. To define the factors that control wood respiration rate of Norway spruce and to produce a model that adequately describes the decomposition process of this species as a function of time, we used an unprecedentedly diverse analytical approach, which included measurements of respiration, fungal community sequencing, N2 fixation rate, nifH copy number, 14C‐dating as well as N%, δ13C and C% values of wood. Our results suggest that climate change will accelerate C flux from deadwood in boreal conditions, due to the observed strong temperature dependency of deadwood respiration. At the research site, the annual C flux from deadwood would increase by 27% from the current 117 g C/kg wood with the projected climate warming (RCP4.5). The second most important control on respiration rate was the stage of wood decomposition; at early stages of decomposition low nitrogen content and low wood moisture limited fungal activity while reduced wood resource quality decreased the respiration rate at the final stages of decomposition. Wood decomposition process was best described by a Sigmoidal model, where after 116 years of wood decomposition mass loss of 95% was reached. Our results on deadwood decomposition are important for C budget calculations in ecosystem and climate change models. We observed for the first time that the temperature dependency of N2 fixation, which has a major role at providing N for wood‐inhabiting fungi, was not constant but varied between wood density classes due to source supply and wood quality. This has significant consequences on projecting N2 fixation rates for deadwood in changing climate.

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Section: Discussionmentioning

confidence: 99%

Carbon flux from decomposing wood and its dependency on temperature, wood N₂ fixation rate, moisture and fungal composition in a Norway spruce forest

Rinne‐Garmston

Peltoniemi

Chen

et al. 2019

Global Change Biology

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“…$ Coefficients of Michaelis-Menten kinetics were set based on ranges given in (Wang et al, 2013;Sinsabaugh et al, 2014). + Predation parameters are poorly constrained, values were set based on reported ranges (Coleman et al, 2017, p. 218;Komarov et al, 2017), initial values were set to lower limits of experimental estimates of soil faunal C budgets (Pausch et al, 2018). § Values of sorption parameters were based on sorption characteristics of small polymers and monomers (Kaiser and Zech, 1997;Vandenbruwane et al, 2007;Fischer et al, 2010;Oren and Chefetz, 2012;Pagel et al, 2014Pagel et al, , 2016.…”

Section: Functional Microbial Groupsmentioning

confidence: 99%

Spatial Control of Carbon Dynamics in Soil by Microbial Decomposer Communities

Pagel

Kriesche

Uksa

et al. 2020

Front. Environ. Sci.

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Trait-based models have improved the understanding and prediction of soil organic matter dynamics in terrestrial ecosystems. Microscopic observations and pore scale models are now increasingly used to quantify and elucidate the effects of soil heterogeneity on microbial processes. Combining both approaches provides a promising way to accurately capture spatial microbial-physicochemical interactions and to predict overall system behavior. The present study aims to quantify controls on carbon (C) turnover in soil due to the mm-scale spatial distribution of microbial decomposer communities in soil. A new spatially explicit trait-based model (SpatC) has been developed that captures the combined dynamics of microbes and soil organic matter (SOM) by taking into account microbial life-history traits and SOM accessibility. Samples of spatial distributions of microbes at µm-scale resolution were generated using a spatial statistical model based on Log Gaussian Cox Processes which was originally used to analyze distributions of bacterial cells in soil thin sections. These µm-scale distribution patterns were then aggregated to derive distributions of microorganisms at mm-scale. We performed Monte-Carlo simulations with microbial distributions that differ in mm-scale spatial heterogeneity and functional community composition (oligotrophs, copiotrophs, and copiotrophic cheaters). Our modeling approach revealed that the spatial distribution of soil microorganisms triggers spatiotemporal patterns of C utilization and microbial succession. Only strong spatial clustering of decomposer communities induces a diffusion limitation of the substrate supply on the microhabitat scale, which significantly reduces the total decomposition of C compounds and the overall microbial growth. However, decomposer communities act as functionally redundant microbial guilds with only slight changes in C utilization. The combined statistical and process-based modeling approach derives distribution patterns of microorganisms at the mm-scale from microbial biogeography at microhabitat scale (µm) and quantifies the emergent macroscopic (cm) microbial and C dynamics. Thus, it effectively links observable process dynamics to the spatial control by microbial communities. Our study highlights a powerful approach that can provide further insights into the biological control of soil organic matter turnover.

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“…В дальнейшем, разработанная модель будет интегрирована с уже существующими моделями корневой [127] и кроновой [25] конкуренции, моделью динамики органического вещества почвы Romul_Hum [153][154][155] и рядом других компонентов, которые будут объединены в рамках новой версии модели EFIMOD. Как и предыдущие версии, она будет ориентирована на моделирование динамики биогенного круговорота органического вещества и азота в разных типах лесных экосистем с учетом разнообразных сценариев лесопользования и их экологических последствий, а также внешних воздействий.…”

Section: заключениеunclassified

Parameterization of Productivity Model for the Most Common Trees Species in European Part of Russia for Simulation of Forest Ecosystem Dynamics

Shanin¹,

Grabarnik²,

Быховец³

et al. 2019

Math.Biol.Bioinf.

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The proposed model is the version of well-known biomass production model 3-PG (Physiological Principles Predicting Growth), which allows for calculation of biomass production in dependence of consumed soil nitrogen and available solar radiation. The model utilizes the concept of modifiers, i.e. functions describing the effect of tree age and environmental factors (air temperature and humidity, soil moisture, carbon dioxide concentration) on productivity. To make the model applicable to mixed forests of European Russia, the substantial modifications were implemented. In particular, more detailed response functions to air temperature, soil moisture and absorbed nitrogen were introduced. We also implemented new procedure of calculation of light use efficiency taking into account the difference between shade-tolerant and shade-intolerant tree species. The rank distribution equation was used for the description of an increment allocation to different tree biomass compartments. Model parameters were estimated for the 12 most common tree species of European Russia. The model was implemented as sub-routine for calculation of biomass production in forest ecosystem model EFIMOD 2. The model performance was tested against the wide range of environmental conditions.

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Romul_Hum model of soil organic matter formation coupled with soil biota activity. I. Problem formulation, model description, and testing

Cited by 40 publications

References 66 publications

Carbon flux from decomposing wood and its dependency on temperature, wood N₂ fixation rate, moisture and fungal composition in a Norway spruce forest

Carbon flux from decomposing wood and its dependency on temperature, wood N₂ fixation rate, moisture and fungal composition in a Norway spruce forest

Spatial Control of Carbon Dynamics in Soil by Microbial Decomposer Communities

Parameterization of Productivity Model for the Most Common Trees Species in European Part of Russia for Simulation of Forest Ecosystem Dynamics

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Romul_Hum model of soil organic matter formation coupled with soil biota activity. I. Problem formulation, model description, and testing

Cited by 40 publications

References 66 publications

Carbon flux from decomposing wood and its dependency on temperature, wood N2 fixation rate, moisture and fungal composition in a Norway spruce forest

Carbon flux from decomposing wood and its dependency on temperature, wood N2 fixation rate, moisture and fungal composition in a Norway spruce forest

Spatial Control of Carbon Dynamics in Soil by Microbial Decomposer Communities

Parameterization of Productivity Model for the Most Common Trees Species in European Part of Russia for Simulation of Forest Ecosystem Dynamics

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Carbon flux from decomposing wood and its dependency on temperature, wood N₂ fixation rate, moisture and fungal composition in a Norway spruce forest

Carbon flux from decomposing wood and its dependency on temperature, wood N₂ fixation rate, moisture and fungal composition in a Norway spruce forest