Romul_Hum model of soil organic matter formation coupled with soil biota activity. III. Parameterisation of earthworm activity

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

doi:10.1016/j.ecolmodel.2016.06.013

Cited by 28 publications

(14 citation statements)

References 68 publications

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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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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 importance of soil structural modifications on SOM stabilization mediated by soil biota has stimulated the development of models including the explicit representation of structural effects on SOM, which improve predictive capacity without explicit representation of soil fauna ( Kuka, Franko & Rühlmann, 2007 ). Komarov et al (2017) and Chertov et al (2017a , 2017b) recently proposed a new mechanistic soil model which incorporates many of these ideas (ROMUL), which however, is quite complex and requires very detailed parameters and measurements.…”

Section: Introductionmentioning

confidence: 99%

“…In our view, in many cases it can be enough to distinguish between fungi and bacteria assuming the former are more oligotrophic and the latter copiotrophic. This approach is practical because of their differential contribution to SOM decay, and also because F:B ratio can be easily related to soil C:N ratio and/or to pH similar to the approach in Romul_Hum ( Chertov et al, 2017a , 2017b ; Fierer et al, 2009 ).…”

Section: Introductionmentioning

confidence: 99%

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KEYLINK: towards a more integrative soil representation for inclusion in ecosystem scale models. I. review and model concept

Deckmyn

Flores

Mayer

et al. 2020

PeerJ

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The relatively poor simulation of the below-ground processes is a severe drawback for many ecosystem models, especially when predicting responses to climate change and management. For a meaningful estimation of ecosystem production and the cycling of water, energy, nutrients and carbon, the integration of soil processes and the exchanges at the surface is crucial. It is increasingly recognized that soil biota play an important role in soil organic carbon and nutrient cycling, shaping soil structure and hydrological properties through their activity, and in water and nutrient uptake by plants through mycorrhizal processes. In this article, we review the main soil biological actors (microbiota, fauna and roots) and their effects on soil functioning. We review to what extent they have been included in soil models and propose which of them could be included in ecosystem models. We show that the model representation of the soil food web, the impact of soil ecosystem engineers on soil structure and the related effects on hydrology and soil organic matter (SOM) stabilization are key issues in improving ecosystem-scale soil representation in models. Finally, we describe a new core model concept (KEYLINK) that integrates insights from SOM models, structural models and food web models to simulate the living soil at an ecosystem scale.

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“…The eco-physiological parameters of food consumption, excretion efficiency, assimilation efficiency, lifespan, and mortality for anecic earthworms were developed using an approach similar to that for food web meso-fauna in the Romul Hum model. The addition of the earthworm module to the Romul Hum model allows for assessment of the combined effects of earthworm cast production and microand meso-faunal food web activity within the casts, on the formation of stable SOM (Chertov et al 2017b). Some of the SOM transformation models described above are summarized in Table 1.…”

Section: Stability Of Organic Matter In Soilsmentioning

confidence: 99%

Qualitative and quantitative soil organic matter estimation for sustainable soil management

Kwiatkowska-Malina

2017

J Soils Sediments

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Purpose The aims of this paper were to review tools and methods for qualitative and quantitative evaluation of soil organic matter (SOM) coming from diverse egzogenic sources for effective soil management, and to introduce a new approach to predict dynamics of SOM transformations, especially humification, as a key process in the formation of humic substances (HSs). Materials and methods A review of existing literature is presented on tools and methods for qualitative and quantitative assessment of organic matter in soil originating from various sources for reasonable soil management, attempting to provide a better understanding of the advances in organic matter transformations and new research directions for modeling. Diverse tools and methods for qualitative and quantitative evaluation of organic matter in soil coming from diverse sources have been adopted so far to express transformation processes. Results and discussion For the qualitative analysis of SOM and humic acids (HAs), the analytical techniques are applied, e.g., HPSEC, NMR, and ESI-FTICRMS. The quantitative analysis is done through the following parameters: humification index (HI), humification degree (HD), and humification rate (HR). These analyses indicated that because of lack of reliable data from sufficiently long-term experiments, mathematical modeling may be applied as a numerical tool for quantitative estimation and prediction of humification of SOM. The effective soil management should include soil properties as well as different functions: food production, nutrient and water cycling, storage, filtrating, buffering, biological habitat, gene pool, source of raw materials, climate regulations, heritage, platform for man-made structure. The soil utility value should be evaluated through the SOM qualitative and quantitative analysis of organic carbon and total nitrogen. Knowledge about dynamics of SOM transformations is essential, particularly in the context of stability and efficiency of different sources of organic matter applied into soil. A qualitative understanding of SOM dynamics transformations along with modeling for quantitative assessment of HS formation should be used to develop sustainable soil management. The modeling may be considered as a tool for predicting SOM humification dynamics and consequently the formation of HSs from the diverse sources. The existing archival data from a long-term experiment may be used to build and calibrate the reliable mathematical model of SOM humification. Conclusions Managing of SOM remains a sound basis for maintaining soil in a good condition for optimizing productivity. The development of land management strategies to optimize both the increase of soil organic carbon levels and the recycling of nutrients from SOM needs to be a priority. This should include policy makers and other users as well.

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Romul_Hum model of soil organic matter formation coupled with soil biota activity. III. Parameterisation of earthworm activity

Cited by 28 publications

References 68 publications

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

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

KEYLINK: towards a more integrative soil representation for inclusion in ecosystem scale models. I. review and model concept

Qualitative and quantitative soil organic matter estimation for sustainable soil management

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