scholarly journals Ecological stoichiometry as a foundation for omics-enabled biogeochemical models of soil organic matter decomposition

2021 ◽  
Author(s):  
Emily B. Graham ◽  
Kirsten S. Hofmockel
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
High Resolution ◽  
Information Exchange ◽  
Ecological Stoichiometry ◽  
Large Scale ◽  
Molecular Data ◽  
Biogeochemical Models ◽  
Decomposition Models ◽  
Som Decomposition

AbstractCoupled biogeochemical cycles drive ecosystem ecology by influencing individual-to-community scale behaviors; yet the development of process-based models that accurately capture these dynamics remains elusive. Soil organic matter (SOM) decomposition in particular is influenced by resource stoichiometry that dictates microbial nutrient acquisition (‘ecological stoichiometry’). Despite its basis in biogeochemical modeling, ecological stoichiometry is only implicitly considered in high-resolution microbial investigations and the metabolic models they inform. State-of-science SOM decomposition models in both fields have advanced largely separately, but they agree on a need to move beyond seminal pool-based models. This presents an opportunity and a challenge to maximize the strengths of various models across different scales and environmental contexts. To address this challenge, we contend that ecological stoichiometry provides a framework for merging biogeochemical and microbiological models, as both explicitly consider substrate chemistries that are the basis of ecological stoichiometry as applied to SOM decomposition. We highlight two gaps that limit our understanding of SOM decomposition: (1) understanding how individual microorganisms alter metabolic strategies in response to substrate stoichiometry and (2) translating this knowledge to the scale of biogeochemical models. We suggest iterative information exchange to refine the objectives of high-resolution investigations and to specify limited dynamics for representation in large-scale models, resulting in a new class of omics-enabled biogeochemical models. Assimilating theoretical and modelling frameworks from different scientific domains is the next frontier in SOM decomposition modelling; advancing technologies in the context of stoichiometric theory provides a consistent framework for interpreting molecular data, and further distilling this information into tractable SOM decomposition models.

scholarly journals A new frontier in molecular applications of ecological stoichiometry to understand global soil organic matter decomposition

2021 ◽  
Author(s):  
Emily B. Graham ◽  
Kirsten Hofmockel
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
High Resolution ◽  
Information Exchange ◽  
Ecological Stoichiometry ◽  
Ecosystem Functions ◽  
Biogeochemical Models ◽  
Scale Models ◽  
Metabolic Models ◽  
Som Decomposition

Coupled biogeochemical cycles drive ecosystem ecology by influencing individual-to-community scale behaviors; yet the development of integrative process-based models remains elusive. Soil organic matter (SOM) decomposition in particular is regulated by resource stoichiometry that dictates microbial nutrient acquisition (‘ecological stoichiometry’). Ecological stoichiometry has revealed promising patterns of global ecosystem functions and informed process-based biogeochemical models. Despite its basis in biogeochemical modeling, ecological stoichiometry is largely absent from implementations of high-resolution microbial measurements, and the metabolic models they inform. Such fine-scale studies are critical components of larger scale models by developing transferrable relationships. One of the challenges to integrating models across molecular resolutions is that models of each scale use different underlying frameworks with few common threads to connect them. To address this challenge, we contend that ecological stoichiometry provides a framework for merging state-of-science biogeochemical models with microbial metabolic models to predict SOM decomposition. This article discusses new approaches to genome-enabled experiments and to models leveraging stoichiometric theory. We highlight two gaps that limit our understanding of SOM decomposition: (1) understanding how individual microorganisms alter metabolic strategies in response to substrate stoichiometry and (2) translating this knowledge to the scale of biogeochemical models. We suggest iterative information exchange to refine the objectives of high-resolution investigations and to specify limited dynamics for representation in large-scale models through integrated genome-enabled reaction networks. We propose that advancing technologies in the context of stoichiometric theory provides an untapped framework for interpreting molecular data and further distilling this information into reduced complexity SOM decomposition models.

scholarly journals Colimitation of decomposition by substrate and decomposers – a comparison of model formulations

2008 ◽  
Vol 5 (1) ◽  
pp. 163-190 ◽  
Author(s):  
T. Wutzler ◽  
M. Reichstein
Keyword(s):  
Organic Matter ◽  
Steady State ◽  
Soil Organic Matter ◽  
Priming Effect ◽  
Deep Soil ◽  
Fresh Organic Matter ◽  
Decomposition Models ◽  
Decomposer Community ◽  
Som Decomposition

Abstract. Decomposition of soil organic matter (SOM) is limited by both the available substrate and the active decomposer community. The understanding of this colimitation strongly affects the understanding of feedbacks of soil carbon to global warming and its consequences. This study compares different formulations of soil organic matter (SOM) decomposition. We compiled formulations from literature into groups according to the representation of decomposer biomass on the SOM decomposition rate a) non-explicit (substrate only), b) linear, and c) non-linear. By varying the SOM decomposition equation in a basic simplified decomposition model, we analyzed the following questions. Is the priming effect represented? Under which conditions is SOM accumulation limited? And, how does steady state SOM stocks scale with amount of fresh organic matter (FOM) litter inputs? While formulations (a) did not represent the priming effect, with formulations (b) steady state SOM stocks were independent of amount of litter input. Further, with several formulations (c) there was an offset of SOM that was not decomposed when no fresh OM was supplied. The finding that a part of the SOM is not decomposed on exhaust of FOM supply supports the hypothesis of carbon stabilization in deep soil by the absence of energy-rich fresh organic matter. Different representations of colimitation of decomposition by substrate and decomposers in SOM decomposition models resulted in qualitatively different long-term behaviour. A collaborative effort by modellers and experimentalists is required to identify appropriate and inappropriate formulations.

scholarly journals Colimitation of decomposition by substrate and decomposers – a comparison of model formulations

2008 ◽  
Vol 5 (3) ◽  
pp. 749-759 ◽  
Author(s):  
T. Wutzler ◽  
M. Reichstein
Keyword(s):  
Organic Matter ◽  
Steady State ◽  
Soil Organic Matter ◽  
Priming Effect ◽  
Deep Soil ◽  
Fresh Organic Matter ◽  
Decomposition Models ◽  
Decomposer Community ◽  
Som Decomposition

Abstract. Decomposition of soil organic matter (SOM) is limited by both the available substrate and the active decomposer community. The understanding of this colimitation strongly affects the understanding of feedbacks of soil carbon to global warming and its consequences. This study compares different formulations of soil organic matter (SOM) decomposition. We compiled formulations from literature into groups according to the representation of decomposer biomass on the SOM decomposition rate a) non-explicit (substrate only), b) linear, and c) non-linear. By varying the SOM decomposition equation in a basic simplified decomposition model, we analyzed the following questions. Is the priming effect represented? Under which conditions is SOM accumulation limited? And, how does steady state SOM stocks scale with amount of fresh organic matter (FOM) litter inputs? While formulations (a) did not represent the priming effect, with formulations (b) steady state SOM stocks were independent of amount of litter input. Further, with several formulations (c) there was an offset of SOM that was not decomposed when no fresh OM was supplied. The finding that a part of the SOM is not decomposed on exhaust of FOM supply supports the hypothesis of carbon stabilization in deep soil by the absence of energy-rich fresh organic matter. Different representations of colimitation of decomposition by substrate and decomposers in SOM decomposition models resulted in qualitatively different long-term behaviour. A collaborative effort by modellers and experimentalists is required to identify formulations that are more or less suitable to represent the most important drivers of long term carbon storage.

scholarly journals Measuring and modelling continuous quality distributions of soil organic matter

2009 ◽  
Vol 6 (5) ◽  
pp. 9045-9082 ◽  
Author(s):  
S. Bruun ◽  
G. I. Ågren ◽  
B. T. Christensen ◽  
L. S. Jensen
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Management Practices ◽  
Model Development ◽  
Turnover Rates ◽  
Continuous Distributions ◽  
Continuous Quality ◽  
Direct Interpretation ◽  
Decomposition Models ◽  
Som Decomposition

Abstract. An understanding of the dynamics of soil organic matter (SOM) is important for our ability to develop management practices that preserve soil quality and sequester carbon. Most SOM decomposition models represent the heterogeneity of organic matter by a few discrete compartments with different turnover rates, while other models employ a continuous quality distribution. To make the multi-compartment models more mechanistic in nature, it has been argued that the compartments should be related to soil fractions actually occurring and having a functional role in the soil. In this paper, we make the case that fractionation methods that can measure continuous quality distributions should be developed, and that the temporal development of these distributions should be incorporated into SOM models. The measured continuous SOM quality distributions should hold valuable information not only for model development, but also for direct interpretation. Measuring continuous distributions requires that the measurements along the quality variable are so frequent that the distribution is approaching the underlying continuum. Continuous distributions leads to possible simplifications of the model formulations, which considerably reduce the number of parameters needed to describe SOM turnover. A general framework for SOM models representing SOM across measurable quality distributions is presented and simplifications for specific situations are discussed. Finally, methods that have been used or have the potential to be used to measure continuous quality SOM distributions are reviewed. Generally, existing fractionation methods have to be modified to allow measurement of distributions or new fractionation techniques will have to be developed. Developing the distributional models in concert with the fractionation methods to measure the distributions will be a major task. We hope the current paper will help spawning the interest needed to accommodate this.

scholarly journals Measuring and modeling continuous quality distributions of soil organic matter

2010 ◽  
Vol 7 (1) ◽  
pp. 27-41 ◽  
Author(s):  
S. Bruun ◽  
G. I. Ågren ◽  
B. T. Christensen ◽  
L. S. Jensen
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Management Practices ◽  
Model Development ◽  
Turnover Rates ◽  
Continuous Distributions ◽  
Continuous Quality ◽  
Direct Interpretation ◽  
Decomposition Models ◽  
Som Decomposition

Abstract. An understanding of the dynamics of soil organic matter (SOM) is important for our ability to develop management practices that preserve soil quality and sequester carbon. Most SOM decomposition models represent the heterogeneity of organic matter by a few discrete compartments with different turnover rates, while other models employ a continuous quality distribution. To make the multi-compartment models more mechanistic in nature, it has been argued that the compartments should be related to soil fractions actually occurring and having a functional role in the soil. In this paper, we make the case that fractionation methods that can measure continuous quality distributions should be developed, and that the temporal development of these distributions should be incorporated into SOM models. The measured continuous SOM quality distributions should hold valuable information not only for model development, but also for direct interpretation. Measuring continuous distributions requires that the measurements along the quality variable are so frequent that the distribution approaches the underlying continuum. Continuous distributions lead to possible simplifications of the model formulations, which considerably reduce the number of parameters needed to describe SOM turnover. A general framework for SOM models representing SOM across measurable quality distributions is presented and simplifications for specific situations are discussed. Finally, methods that have been used or have the potential to be used to measure continuous quality SOM distributions are reviewed. Generally, existing fractionation methods will have to be modified to allow measurement of distributions or new fractionation techniques will have to be developed. Developing the distributional models in concert with the fractionation methods to measure the distributions will be a major task. We hope the current paper will help generate the interest needed to accommodate this.

Accumulation patterns of soil organic matter in forests as a legacy of historical charcoal burning

2021 ◽  
Author(s):  
Anna Schneider ◽  
Alexander Bonhage ◽  
Florian Hirsch ◽  
Alexandra Raab ◽  
Thomas Raab
Keyword(s):  
Land Use ◽  
Organic Matter ◽  
Soil Organic Matter ◽  
Large Scale ◽  
Soil Surface ◽  
Landscape Scale ◽  
Legacy Effects ◽  
Charcoal Production ◽  
Study Region ◽  
Land Use Legacies

<p>Human land use and occupation often lead to a high heterogeneity of soil stratigraphy and properties in landscapes within small, clearly delimited areas. Legacy effects of past land use also are also abundant in recent forest areas. Although such land use legacies can occur on considerable fractions of the soil surface, they are hardly considered in soil mapping and inventories. The heterogenous spatial distribution of land use legacy soils challenges the quantification of their impacts on the landscape scale. Relict charcoal hearths (RCH) are a widespread example for the long-lasting effect of historical land use on soil landscapes in forests of many European countries and also northeastern USA. Soils on RCH clearly differ from surrounding forest soils in their stratigraphy and properties, and are most prominently characterized by a technogenic substrate layer with high contents of charcoal. The properties of RCH soils have recently been studied for several regions, but their relevance on the landscape scale has hardly been quantified.</p><p>We analyse and discuss the distribution and ecological relevance of land use legacy soils across scales for RCH in the state of Brandenburg, Germany, with a focus on soil organic matter (SOM) stocks. Our analysis is based on a large-scale mapping of RCH from digital elevation models (DEM), combined with modelled SOM stocks in RCH soils. The distribution of RCH soils in the study region shows heterogeneity at different scales. The large-scale variation is related to the concentration of charcoal production to specific forest areas and the small-scale accumulation pattern is related to the irregular distribution of single RCH within the charcoal production fields. Considerable fractions of the surface area are covered by RCH soils in the major charcoal production areas within the study region. The results also show that RCH can significantly contribute to the soil organic matter stocks of forests, even for areas where they cover only a small fraction of the soil surface. The study highlights that considering land use legacy effects can be relevant for the results of soil mapping and inventories; and that prospecting and mapping land use legacies from DEM can contribute to improving such approaches.</p>

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.

scholarly journals Large-scale genome sequencing of mycorrhizal fungi provides insights into the early evolution of symbiotic traits

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Shingo Miyauchi ◽  
Enikő Kiss ◽  
Alan Kuo ◽  
Elodie Drula ◽  
Annegret Kohler ◽  
...  
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Transposable Elements ◽  
Genome Sequencing ◽  
Mycorrhizal Fungi ◽  
Large Scale ◽  
Terrestrial Ecosystems ◽  
Pathogenic Species ◽  
Fungal Genomes ◽  
Induced Genes

Abstract Mycorrhizal fungi are mutualists that play crucial roles in nutrient acquisition in terrestrial ecosystems. Mycorrhizal symbioses arose repeatedly across multiple lineages of Mucoromycotina, Ascomycota, and Basidiomycota. Considerable variation exists in the capacity of mycorrhizal fungi to acquire carbon from soil organic matter. Here, we present a combined analysis of 135 fungal genomes from 73 saprotrophic, endophytic and pathogenic species, and 62 mycorrhizal species, including 29 new mycorrhizal genomes. This study samples ecologically dominant fungal guilds for which there were previously no symbiotic genomes available, including ectomycorrhizal Russulales, Thelephorales and Cantharellales. Our analyses show that transitions from saprotrophy to symbiosis involve (1) widespread losses of degrading enzymes acting on lignin and cellulose, (2) co-option of genes present in saprotrophic ancestors to fulfill new symbiotic functions, (3) diversification of novel, lineage-specific symbiosis-induced genes, (4) proliferation of transposable elements and (5) divergent genetic innovations underlying the convergent origins of the ectomycorrhizal guild.

Quantitative Characterization of Soil Organic Matter and Its Fractionation Products by Solid State High Resolution C-13 (CPMAS) Spectroscopy

1991 ◽  
Vol 46 (11-12) ◽  
pp. 982-988 ◽  
Author(s):  
R. Fründ ◽  
H.-D. Lüdemann
Keyword(s):  
Organic Matter ◽  
Humic Acid ◽  
Solid State ◽  
Soil Organic Matter ◽  
High Resolution ◽  
Extraction Procedure ◽  
Chemical Information ◽  
Organic Carbon Content ◽  
Quantitative Characterization

Abstract In a systematic study the organic carbon content of typical Germ an soils was studied by solid state C-13 CPM AS spectroscopy.In order to check the quantitative validity of the standard sodium hydroxide extraction procedure, which fractionates soil organic matter into hum in, humic acid, and fulvic acid also the high resolution solid state spectra of these fractions were determined.The chemical information obtained from these spectra is discussed.

Sign in / Sign up

Export Citation Format

Share Document