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

2017 ◽  
Vol 345 ◽  
pp. 113-124 ◽  
Author(s):  
Alexander Komarov ◽  
Oleg Chertov ◽  
Sergey Bykhovets ◽  
Cindy Shaw ◽  
Marina Nadporozhskaya ◽  
...  
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Problem Formulation ◽  
Soil Biota ◽  
Model Description ◽  
Soil Organic Matter Formation

Romul_Hum—A model of soil organic matter formation coupling with soil biota activity. II. Parameterisation of the soil food web biota activity

2017 ◽  
Vol 345 ◽  
pp. 125-139 ◽  
Author(s):  
Oleg Chertov ◽  
Alexander Komarov ◽  
Cindy Shaw ◽  
Sergey Bykhovets ◽  
Pavel Frolov ◽  
...  
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Food Web ◽  
Soil Biota ◽  
Soil Food Web ◽  
Soil Organic Matter Formation

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

2017 ◽  
Vol 345 ◽  
pp. 140-149 ◽  
Author(s):  
Oleg Chertov ◽  
Cindy Shaw ◽  
Maxim Shashkov ◽  
Alexander Komarov ◽  
Sergey Bykhovets ◽  
...  
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Soil Biota ◽  
Soil Organic Matter Formation ◽  
Earthworm Activity

Soil texture affects the coupling of litter decomposition and soil organic matter formation

2021 ◽  
pp. 108302
Author(s):  
Gerrit Angst ◽  
Jan Pokorný ◽  
Carsten W. Mueller ◽  
Isabel Prater ◽  
Sebastian Preusser ◽  
...  
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Litter Decomposition ◽  
Soil Texture ◽  
Soil Organic Matter Formation

Soil organic matter formation is controlled by the chemistry and bioavailability of organic carbon inputs across different land uses

2021 ◽  
Vol 770 ◽  
pp. 145307
Author(s):  
Mohammad Bahadori ◽  
Chengrong Chen ◽  
Stephen Lewis ◽  
Sue Boyd ◽  
Mehran Rezaei Rashti ◽  
...  
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Organic Carbon ◽  
Land Uses ◽  
Soil Organic Matter Formation

FOREST LITTER CONSTRAINTS ON THE PATHWAYS CONTROLLING SOIL ORGANIC MATTER FORMATION

2021 ◽  
pp. 108447
Author(s):  
Luís F.J. Almeida ◽  
Ivan F. Souza ◽  
Luís C.C. Hurtarte ◽  
Pedro Paulo Teixeira ◽  
Thiago M. Inagaki ◽  
...  
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Forest Litter ◽  
Soil Organic Matter Formation

scholarly journals Unifying soil organic matter formation and persistence frameworks: the MEMS model

2019 ◽  
Vol 16 (6) ◽  
pp. 1225-1248 ◽  
Author(s):  
Andy D. Robertson ◽  
Keith Paustian ◽  
Stephen Ogle ◽  
Matthew D. Wallenstein ◽  
Emanuele Lugato ◽  
...  
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Model Performance ◽  
Soil C ◽  
Biogeochemical Models ◽  
Novel Approach ◽  
C Stocks ◽  
Microbial Efficiency ◽  
Organic Matter Fractions ◽  
Soil Organic Matter Formation

Abstract. Soil organic matter (SOM) dynamics in ecosystem-scale biogeochemical models have traditionally been simulated as immeasurable fluxes between conceptually defined pools. This greatly limits how empirical data can be used to improve model performance and reduce the uncertainty associated with their predictions of carbon (C) cycling. Recent advances in our understanding of the biogeochemical processes that govern SOM formation and persistence demand a new mathematical model with a structure built around key mechanisms and biogeochemically relevant pools. Here, we present one approach that aims to address this need. Our new model (MEMS v1.0) is developed from the Microbial Efficiency-Matrix Stabilization framework, which emphasizes the importance of linking the chemistry of organic matter inputs with efficiency of microbial processing and ultimately with the soil mineral matrix, when studying SOM formation and stabilization. Building on this framework, MEMS v1.0 is also capable of simulating the concept of C saturation and represents decomposition processes and mechanisms of physico-chemical stabilization to define SOM formation into four primary fractions. After describing the model in detail, we optimize four key parameters identified through a variance-based sensitivity analysis. Optimization employed soil fractionation data from 154 sites with diverse environmental conditions, directly equating mineral-associated organic matter and particulate organic matter fractions with corresponding model pools. Finally, model performance was evaluated using total topsoil (0–20 cm) C data from 8192 forest and grassland sites across Europe. Despite the relative simplicity of the model, it was able to accurately capture general trends in soil C stocks across extensive gradients of temperature, precipitation, annual C inputs and soil texture. The novel approach that MEMS v1.0 takes to simulate SOM dynamics has the potential to improve our forecasts of how soils respond to management and environmental perturbation. Ensuring these forecasts are accurate is key to effectively informing policy that can address the sustainability of ecosystem services and help mitigate climate change.

Strategies used by soil biota to overcome soil organic matter stability — why is dead organic matter left over in the soil?

Geoderma ◽  
2005 ◽  
Vol 128 (1-2) ◽  
pp. 167-176 ◽  
Author(s):  
Klemens Ekschmitt ◽  
Manqiang Liu ◽  
Silke Vetter ◽  
Oliver Fox ◽  
Volkmar Wolters
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Soil Biota ◽  
Dead Organic Matter

Soil organic matter formation along a chronosequence in the Morteratsch proglacial area (Upper Engadine, Switzerland)

CATENA ◽  
2010 ◽  
Vol 82 (2) ◽  
pp. 61-69 ◽  
Author(s):  
Markus Egli ◽  
Christian Mavris ◽  
Aldo Mirabella ◽  
Daniele Giaccai
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Soil Organic Matter Formation
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