scholarly journals Towards a representation of priming on soil carbon decomposition in the global land biosphere model ORCHIDEE (version 1.9.5.2)

2016 ◽  
Vol 9 (2) ◽  
pp. 841-855 ◽  
Author(s):  
Bertrand Guenet ◽  
Fernando Esteban Moyano ◽  
Philippe Peylin ◽  
Philippe Ciais ◽  
Ivan A Janssens

Abstract. Priming of soil carbon decomposition encompasses different processes through which the decomposition of native (already present) soil organic matter is amplified through the addition of new organic matter, with new inputs typically being more labile than the native soil organic matter. Evidence for priming comes from laboratory and field experiments, but to date there is no estimate of its impact at global scale and under the current anthropogenic perturbation of the carbon cycle. Current soil carbon decomposition models do not include priming mechanisms, thereby introducing uncertainty when extrapolating short-term local observations to ecosystem and regional to global scale. In this study we present a simple conceptual model of decomposition priming, called PRIM, able to reproduce laboratory (incubation) and field (litter manipulation) priming experiments. Parameters for this model were first optimized against data from 20 soil incubation experiments using a Bayesian framework. The optimized parameter values were evaluated against another set of soil incubation data independent from the ones used for calibration and the PRIM model reproduced the soil incubations data better than the original, CENTURY-type soil decomposition model, whose decomposition equations are based only on first-order kinetics. We then compared the PRIM model and the standard first-order decay model incorporated into the global land biosphere model ORCHIDEE (Organising Carbon and Hydrology In Dynamic Ecosystems). A test of both models was performed at ecosystem scale using litter manipulation experiments from five sites. Although both versions were equally able to reproduce observed decay rates of litter, only ORCHIDEE–PRIM could simulate the observed priming (R2  =  0.54) in cases where litter was added or removed. This result suggests that a conceptually simple and numerically tractable representation of priming adapted to global models is able to capture the sign and magnitude of the priming of litter and soil organic matter.

2015 ◽  
Vol 8 (10) ◽  
pp. 9193-9227
Author(s):  
B. Guenet ◽  
F. E. Moyano ◽  
P. Peylin ◽  
P. Ciais ◽  
I. A. Janssens

Abstract. Priming of soil carbon decomposition encompasses different processes through which the decomposition of native (already present) soil organic matter is amplified through the addition of new organic matter, with new inputs typically being more labile than the native soil organic matter. Evidence for priming comes from laboratory and field experiments, but to date there is no estimate of its impact at global scale and under the current anthropogenic perturbation of the carbon cycle. Current soil carbon decomposition models do not include priming mechanisms, thereby introducing uncertainty when extrapolating short-term local observations to ecosystem and regional to global scale. In this study we present a simple conceptual model of decomposition priming, called PRIM, able to reproduce laboratory (incubation) and field (litter manipulation) priming experiments. Parameters for this model were first optimized against data from 20 soil incubation experiments using a Bayesian framework. The optimized parameter values were evaluated against another set of soil incubation data independent from the ones used for calibration and the PRIM model reproduced the soil incubations data better than the original, CENTURY-type soil decomposition model, whose decomposition equations are based only on first order kinetics. We then compared the PRIM model and the standard first order decay model incorporated into the global land biosphere model ORCHIDEE. A test of both models was performed at ecosystem scale using litter manipulation experiments from 5 sites. Although both versions were equally able to reproduce observed decay rates of litter, only ORCHIDEE-PRIM could simulate the observed priming (R2 = 0.54) in cases where litter was added or removed. This result suggests that a conceptually simple and numerically tractable representation of priming adapted to global models is able to capture the sign and magnitude of the priming of litter and soil organic matter.


2013 ◽  
Vol 10 (4) ◽  
pp. 2379-2392 ◽  
Author(s):  
B. Guenet ◽  
T. Eglin ◽  
N. Vasilyeva ◽  
P. Peylin ◽  
P. Ciais ◽  
...  

Abstract. Soil is the major terrestrial reservoir of carbon and a substantial part of this carbon is stored in deep layers, typically deeper than 50 cm below the surface. Several studies underlined the quantitative importance of this deep soil organic carbon (SOC) pool and models are needed to better understand this stock and its evolution under climate and land-uses changes. In this study, we tested and compared three simple theoretical models of vertical transport for SOC against SOC profiles measurements from a long-term bare fallow experiment carried out by the Central-Chernozem State Natural Biosphere Reserve in the Kursk Region of Russia. The transport schemes tested are diffusion, advection and both diffusion and advection. They are coupled to three different formulations of soil carbon decomposition kinetics. The first formulation is a first order kinetics widely used in global SOC decomposition models; the second one, so-called "priming" model, links SOC decomposition rate to the amount of fresh organic matter, representing the substrate interactions. The last one is also a first order kinetics, but SOC is split into two pools. Field data are from a set of three bare fallow plots where soil received no input during the past 20, 26 and 58 yr, respectively. Parameters of the models were optimised using a Bayesian method. The best results are obtained when SOC decomposition is assumed to be controlled by fresh organic matter (i.e., the priming model). In comparison to the first-order kinetic model, the priming model reduces the overestimation in the deep layers. We also observed that the transport scheme that improved the fit with the data depended on the soil carbon mineralisation formulation chosen. When soil carbon decomposition was modelled to depend on the fresh organic matter amount, the transport mechanism which improved best the fit to the SOC profile data was the model representing both advection and diffusion. Interestingly, the older the bare fallow is, the lesser the need for diffusion is, suggesting that stabilised carbon may not be transported within the profile by the same mechanisms than more labile carbon.


2012 ◽  
Vol 9 (10) ◽  
pp. 14145-14173 ◽  
Author(s):  
B. Guenet ◽  
T. Eglin ◽  
N. Vasilyeva ◽  
P. Peylin ◽  
P. Ciais ◽  
...  

Abstract. Soil is the major terrestrial reservoirs of carbon, and a substantial part of this carbon is stored in deep layers, typically deeper than 50 cm below the surface. Several studies underlined the quantitative importance of this deep Soil Organic Carbon (SOC) pool and models are needed to better understand this stock and its evolution under climate and land-uses changes. In this study, we test and compare 3 simple theoretical models of vertical transport for SOC against SOC profiles measurements from a long-term bare fallow experiment carried out by the Central-Chernozem State Natural Biosphere Reserve named after V.V. Alekhin, in the Kursk Region of Russia. The transport schemes tested are diffusion, advection or both diffusion and advection. They are coupled to two different formulations of soil carbon decomposition kinetics. The first formulation is a first order kinetics widely used in global SOC decomposition models; the second one links SOC decomposition rate to the amount of fresh organic matter, representing a "priming effect". Field data are from a set of three bare fallow plots where soil received no input during the past 20, 26 and 58 yr respectively. Parameters of the models were optimized using a Bayesian method. The best results are obtained when SOC decomposition is assumed to be controlled by fresh organic matter. In comparison to the first-order kinetic model, the "priming" model reduces the underestimation of SOC decomposition in the top layers and the over estimation in the deep layers. We also observe that the transport scheme that improved the fit with the data depends on the soil carbon mineralization formulation chosen. When soil carbon decomposition is modelled to depend on the fresh organic matter amount, the transport mechanisms which improves best the fit to the SOC profile data is the model representing both advection and diffusion. Interestingly, the older the bare fallow is, the lesser the need for diffusion is. This suggests that stabilized carbon may not be transported within the profile by the same mechanisms than more labile carbon.


2012 ◽  
Vol 9 (8) ◽  
pp. 3013-3028 ◽  
Author(s):  
C. A. Sierra ◽  
S. E. Trumbore ◽  
E. A. Davidson ◽  
S. D. Frey ◽  
K. E. Savage ◽  
...  

Abstract. Representing the response of soil carbon dynamics to global environmental change requires the incorporation of multiple tools in the development of predictive models. An important tool to construct and test models is the incorporation of bomb radiocarbon in soil organic matter during the past decades. In this manuscript, we combined radiocarbon data and a previously developed empirical model to explore decade-scale soil carbon dynamics in a temperate forest ecosystem at the Harvard Forest, Massachusetts, USA. We evaluated the contribution of different soil C fractions to both total soil CO2 efflux and microbially respired C. We tested the performance of the model based on measurable soil organic matter fractions against a decade of radiocarbon measurements. The model was then challenged with radiocarbon measurements from a warming and N addition experiment to test multiple hypotheses about the different response of soil C fractions to the experimental manipulations. Our results showed that the empirical model satisfactorily predicts the trends of radiocarbon in litter, density fractions, and respired CO2 observed over a decade in the soils not subjected to manipulation. However, the model, modified with prescribed relationships for temperature and decomposition rates, predicted most but not all the observations from the field experiment where soil temperatures and nitrogen levels were increased, suggesting that a larger degree of complexity and mechanistic relations need to be added to the model to predict short-term responses and transient dynamics.


2001 ◽  
Vol 81 (1) ◽  
pp. 21-31 ◽  
Author(s):  
E G Gregorich ◽  
C F Drury ◽  
J A Baldock

Legume-based cropping systems could help to increase crop productivity and soil organic matter levels, thereby enhancing soil quality, as well as having the additional benefit of sequestering atmospheric C. To evaluate the effects of 35 yr of maize monoculture and legume-based cropping on soil C levels and residue retention, we measured organic C and 13C natural abundance in soils under: fertilized and unfertilized maize (Zea mays L.), both in monoculture and legume-based [maize-oat (Avena sativa L.)-alfalfa (Medicago sativa L.)-alfalfa] rotations; fertilized and unfertilized systems of continuous grass (Poa pratensis L.); and under forest. Solid state 13C nuclear magnetic resonance (NMR) was used to chemically characterize the organic matter in plant residues and soils. Soils (70-cm depth) under maize cropping had about 30-40% less C, and those under continuous grass had about 16% less C, than those under adjacent forest. Qualitative differences in crop residues were important in these systems, because quantitative differences in net primary productivity and C inputs in the different agroecosystems did not account for observed differences in total soil C. Cropping sequence (i.e., rotation or monoculture) had a greater effect on soil C levels than application of fertilizer. The difference in soil C levels between rotation and monoculture maize systems was about 20 Mg C ha-1. The effects of fertilization on soil C were small (~6 Mg C ha-1), and differences were observed only in the monoculture system. The NMR results suggest that the chemical composition of organic matter was little affected by the nature of crop residues returned to the soil. The total quantity of maize-derived soil C was different in each system, because the quantity of maize residue returned to the soil was different; hence the maize-derived soil C ranged from 23 Mg ha-1 in the fertilized and 14 Mg ha-1 in the unfertilized monoculture soils (i.e., after 35 maize crops) to 6-7 Mg ha-1 in both the fertilized and unfertilized legume-based rotation soils (i.e., after eight maize crops). The proportion of maize residue C returned to the soil and retained as soil organic C (i.e., Mg maize-derived soil C/Mg maize residue) was about 14% for all maize cropping systems. The quantity of C3-C below the plow layer in legume-based rotation was 40% greater than that in monoculture and about the same as that under either continuous grass or forest. The soil organic matter below the plow layer in soil under the legume-based rotation appeared to be in a more biologically resistant form (i.e., higher aromatic C content) compared with that under monoculture. The retention of maize residue C as soil organic matter was four to five times greater below the plow layer than that within the plow layer. We conclude that residue quality plays a key role in increasing the retention of soil C in agroecosystems and that soils under legume-based rotation tend to be more “preservative” of residue C inputs, particularly from root inputs, than soils under monoculture. Key words: Soil carbon, 13C natural abundance, 13C nuclear magnetic resonance, maize cropping, legumes, root carbon


2012 ◽  
Vol 25 (1) ◽  
pp. 11-18 ◽  
Author(s):  
Juliana Vanir De Souza Carvalho ◽  
Eduardo De Sá Mendonça ◽  
Newton La Scala ◽  
César Reis ◽  
Efrain Lázaro Reis ◽  
...  

AbstractPolar Regions are the most important soil carbon reservoirs on Earth. Monitoring soil carbon storage in a changing global climate context may indicate possible effects of climate change on terrestrial environments. In this regard, we need to understand the dynamics of soil organic matter in relation to its chemical characteristics. We evaluated the influence of chemical characteristics of humic substances on the process of soil organic matter mineralization in selected Maritime Antarctic soils. A laboratory assay was carried out with soils from five locations from King George Island. We determined the contents of total organic carbon, oxidizable carbon fractions of soil organic matter, and humic substances. Two in situ field experiments were carried out during two summers, in order to evaluate the CO2-C emissions in relation to soil temperature variations. The overall low amounts of soil organic matter in Maritime Antarctic soils have a low humification degree and reduced microbial activity. CO2-C emissions showed significant exponential relationship with temperature, suggesting a sharp increase in CO2-C emissions with a warming scenario, and Q10 values (the percentage increase in emission for a 10°C increase in soil temperature) were higher than values reported from elsewhere. The sensitivity of the CO2-C emission in relation to temperature was significantly correlated with the humification degree of soil organic matter and microbial activity for Antarctic soils.


2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Cheng-Biao Fu ◽  
Hei-Gang Xiong ◽  
An-Hong Tian

Discussion on the application of fractional derivative algorithm in monitoring organic matter content in field soil is scarce. This study is aimed at improving the accuracy of soil organic matter (SOM) content estimation in arid region, and the undesirable model precision caused by the missing information associated with the larger discrepancy between conventional integer-order, i.e., first order and second order, derivative, and raw spectral data. We utilized fractional derivative (of zeroth order to second order in 0.2-order interval) processing on the field spectral reflectance (R) of the salinized soil sample from Fukang, Xinjiang, and its square root-transformed (R), log-transformed (lgR), inverse-transformed (1/R), and inverse log-transformed (1/lgR) values. The correlation coefficient of each fractional derivative of transformed value with SOM content was calculated. The simulation showed the derivative reflectance value approximates zero. When increasing from zeroth order to first order, the derivative curve gradually aligns to the first-order curve, and the destination alignment was also seen while increasing from first order to second order. The significance test of 0.05 showed initial increase and later decay of bands in the five spectral transformations as the order increases. For specific bands, the derivative algorithm clearly justifies the correlation between soil spectra and organic matter content, and all of the absolute highest correlation coefficient values were obtained at fractional orders. When compared with integer-order derivative, fractional derivative is significantly better in improving correlation, showing overall superiority. The result supports the application of fractional derivative in the hyperspectral remote monitor of SOM in arid zone, which may in turn realize the timely and accurate SOM monitor in arid zone, and provides the basis for ecological restoration.


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