scholarly journals A meta-analysis on pyrogenic organic matter induced priming effect

GCB Bioenergy ◽  
2014 ◽  
Vol 7 (4) ◽  
pp. 577-590 ◽  
Author(s):  
Bernardo Maestrini ◽  
Paolo Nannipieri ◽  
Samuel Abiven
Keyword(s):  
Organic Matter ◽  
Priming Effect ◽  
Meta Analysis ◽  
Pyrogenic Organic Matter

Transformation and stabilization of pyrogenic organic matter in a temperate forest field experiment

2014 ◽  
Vol 20 (5) ◽  
pp. 1629-1642 ◽  
Author(s):  
Nimisha Singh ◽  
Samuel Abiven ◽  
Bernardo Maestrini ◽  
Jeffrey A. Bird ◽  
Margaret S. Torn ◽  
...  
Keyword(s):  
Organic Matter ◽  
Field Experiment ◽  
Temperate Forest ◽  
Pyrogenic Organic Matter

Algal blooms modulate organic matter remineralization in freshwater sediments: A new insight on priming effect

2021 ◽  
pp. 147087
Author(s):  
Yarui Wang ◽  
Muhua Feng ◽  
Jianjun Wang ◽  
Xinfang Chen ◽  
Xiangchao Chen ◽  
...  
Keyword(s):  
Organic Matter ◽  
Algal Blooms ◽  
Priming Effect ◽  
Freshwater Sediments

scholarly journals Rhizosphere priming effect: A meta-analysis

2017 ◽  
Vol 111 ◽  
pp. 78-84 ◽  
Author(s):  
Changfu Huo ◽  
Yiqi Luo ◽  
Weixin Cheng
Keyword(s):  
Priming Effect ◽  
Meta Analysis ◽  
Rhizosphere Priming Effect

scholarly journals ORCHIMIC (v1.0), a microbe-driven model for soil organic matter decomposition designed for large-scale applications

2018 ◽  
Author(s):  
Ye Huang ◽  
Bertrand Guenet ◽  
Philippe Ciais ◽  
Ivan A. Janssens ◽  
Jennifer L. Soong ◽  
...  
Keyword(s):  
Organic Matter ◽  
Microbial Biomass ◽  
Input Data ◽  
Priming Effect ◽  
Temporal Dynamics ◽  
Litter Input ◽  
Decomposition Models ◽  
Soc Stock ◽  
Global Vegetation ◽  
Soc Decomposition

Abstract. The role of soil microorganisms in regulating soil organic matter (SOM) decomposition is of primary importance in the carbon cycle, and in particular in the context of global change. Modelling soil microbial community dynamics to simulate its impact on soil gaseous carbon (C) emissions and nitrogen (N) mineralization at large spatial scales is a recent research field with the potential to improve predictions of SOM responses to global climate change. We here present a SOM model called ORCHIMIC whose input data that are consistent with those of global vegetation models. The model simulates decomposition of SOM by explicitly accounting for enzyme production and distinguishing three different microbial functional groups: fresh organic matter (FOM) specialists, SOM specialists, and generalists, while implicitly also accounting for microbes that do not produce extracellular enzymes, i.e. cheaters. This ORCHIMIC model and two other organic matter decomposition models, CENTURY (based on first order kinetics and representative for the structure of most current global soil carbon models) and PRIM (with FOM accelerating the decomposition rate of SOM) were calibrated to reproduce the observed respiration fluxes from FOM and SOM and their possible interactions from incubation experiments of Blagodatskaya et al. (2014). Among the three models, ORCHIMIC was the only one that captured well both the temporal dynamics of the respiratory fluxes and the magnitude of the priming effect observed during the incubation experiment. ORCHIMIC also reproduced well the temporal dynamics of microbial biomass. We then applied different idealized changes to the model input data, i.e. a 5 K stepwise increase of temperature and/or a doubling of plant litter inputs. Under 5 K warming, ORCHIMIC predicted a 0.002 K−1 decrease in the C use efficiency (defined as the ratio of C allocated to microbial growth to the sum of C allocated to growth and respiration) and a 3 % loss of SOC. Under the double litter input scenario, ORCHIMIC predicted a doubling of microbial biomass, while SOC stock increased by less than 1 % due to the priming effect. This limited increase in SOC stock contrasted with the proportional increase in SOC stock as modelled by the conventional SOC decomposition model (CENTURY), which cannot reproduce the priming effect. If temperature increased by 5 K and litter input is doubled, the model predicted almost the same loss of SOC as when only temperature was increased. These tests suggest that the responses of SOC stock to warming and increasing input may differ a lot from those simulated by conventional SOC decomposition models, when microbial dynamics is included. The next step is to incorporate the ORCHIMIC model into a global vegetation model to perform simulations for representative sites and future scenarios.

scholarly journals Pyrogenic organic matter from palaeo-fires during the Holocene: A case study in a sequence of buried soils at the Central Ebro Basin (NE Spain)

2019 ◽  
Vol 241 ◽  
pp. 558-566 ◽  
Author(s):  
Cecilia María Armas-Herrera ◽  
Fernando Pérez-Lambán ◽  
David Badía-Villas ◽  
José Luis Peña-Monné ◽  
José Antonio González-Pérez ◽  
...  
Keyword(s):  
Organic Matter ◽  
Buried Soils ◽  
Ebro Basin ◽  
The Holocene ◽  
Pyrogenic Organic Matter ◽  
Ne Spain

Priming mechanisms with additions of pyrogenic organic matter to soil

2018 ◽  
Vol 238 ◽  
pp. 329-342 ◽  
Author(s):  
Silene DeCiucies ◽  
Thea Whitman ◽  
Dominic Woolf ◽  
Akio Enders ◽  
Johannes Lehmann
Keyword(s):  
Organic Matter ◽  
Pyrogenic Organic Matter

Assessing the priming effect of dissolved organic matter from typical sources using fluorescence EEMs-PARAFAC

Chemosphere ◽  
2021 ◽  
Vol 264 ◽  
pp. 128600
Author(s):  
Wan-E Zhuang ◽  
Wei Chen ◽  
Qiong Cheng ◽  
Liyang Yang
Keyword(s):  
Organic Matter ◽  
Dissolved Organic Matter ◽  
Priming Effect

scholarly journals Regulation of priming effect by soil organic matter stability over a broad geographic scale

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Leiyi Chen ◽  
Li Liu ◽  
Shuqi Qin ◽  
Guibiao Yang ◽  
Kai Fang ◽  
...  
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Priming Effect ◽  
Basal Respiration ◽  
Soil Conditions ◽  
The Tibetan Plateau ◽  
Geographic Scale ◽  
Soil C ◽  
Chemical Structures ◽  
C Dynamics

Abstract The modification of soil organic matter (SOM) decomposition by plant carbon (C) input (priming effect) represents a critical biogeochemical process that controls soil C dynamics. However, the patterns and drivers of the priming effect remain hidden, especially over broad geographic scales under various climate and soil conditions. By combining systematic field and laboratory analyses based on multiple analytical and statistical approaches, we explore the determinants of priming intensity along a 2200 km grassland transect on the Tibetan Plateau. Our results show that SOM stability characterized by chemical recalcitrance and physico-chemical protection explains more variance in the priming effect than plant, soil and microbial properties. High priming intensity (up to 137% of basal respiration) is associated with complex SOM chemical structures and low mineral-organic associations. The dependence of priming effect on SOM stabilization mechanisms should be considered in Earth System Models to accurately predict soil C dynamics under changing environments.

Meta-analysis of the effects of organic matter on polychaetes of the east coast of South America

2019 ◽  
Vol 149 ◽  
pp. 148-156
Author(s):  
Vanessa Fernández-Rodríguez ◽  
Cinthya S.G. Santos ◽  
Aliny P.F. Pires
Keyword(s):  
Organic Matter ◽  
South America ◽  
East Coast ◽  
Meta Analysis

scholarly journals ORCHIMIC (v1.0), a microbe-mediated model for soil organic matter decomposition

2018 ◽  
Vol 11 (6) ◽  
pp. 2111-2138 ◽  
Author(s):  
Ye Huang ◽  
Bertrand Guenet ◽  
Philippe Ciais ◽  
Ivan A. Janssens ◽  
Jennifer L. Soong ◽  
...  
Keyword(s):  
Organic Matter ◽  
Microbial Biomass ◽  
Input Data ◽  
Priming Effect ◽  
Temporal Dynamics ◽  
Litter Input ◽  
Decomposition Models ◽  
Soc Stock ◽  
Global Vegetation ◽  
Soc Decomposition

Abstract. The role of soil microorganisms in regulating soil organic matter (SOM) decomposition is of primary importance in the carbon cycle, in particular in the context of global change. Modeling soil microbial community dynamics to simulate its impact on soil gaseous carbon (C) emissions and nitrogen (N) mineralization at large spatial scales is a recent research field with the potential to improve predictions of SOM responses to global climate change. In this study we present a SOM model called ORCHIMIC, which utilizes input data that are consistent with those of global vegetation models. ORCHIMIC simulates the decomposition of SOM by explicitly accounting for enzyme production and distinguishing three different microbial functional groups: fresh organic matter (FOM) specialists, SOM specialists, and generalists, while also implicitly accounting for microbes that do not produce extracellular enzymes, i.e., cheaters. ORCHIMIC and two other organic matter decomposition models, CENTURY (based on first-order kinetics and representative of the structure of most current global soil carbon models) and PRIM (with FOM accelerating the decomposition rate of SOM), were calibrated to reproduce the observed respiration fluxes of FOM and SOM from the incubation experiments of Blagodatskaya et al. (2014). Among the three models, ORCHIMIC was the only one that effectively captured both the temporal dynamics of the respiratory fluxes and the magnitude of the priming effect observed during the incubation experiment. ORCHIMIC also effectively reproduced the temporal dynamics of microbial biomass. We then applied different idealized changes to the model input data, i.e., a 5 K stepwise increase of temperature and/or a doubling of plant litter inputs. Under 5 K warming conditions, ORCHIMIC predicted a 0.002 K−1 decrease in the C use efficiency (defined as the ratio of C allocated to microbial growth to the sum of C allocated to growth and respiration) and a 3 % loss of SOC. Under the double litter input scenario, ORCHIMIC predicted a doubling of microbial biomass, while SOC stock increased by less than 1 % due to the priming effect. This limited increase in SOC stock contrasted with the proportional increase in SOC stock as modeled by the conventional SOC decomposition model (CENTURY), which can not reproduce the priming effect. If temperature increased by 5 K and litter input was doubled, ORCHIMIC predicted almost the same loss of SOC as when only temperature was increased. These tests suggest that the responses of SOC stock to warming and increasing input may differ considerably from those simulated by conventional SOC decomposition models when microbial dynamics are included. The next step is to incorporate the ORCHIMIC model into a global vegetation model to perform simulations for representative sites and future scenarios.

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