Les temps de résidence du carbone et le potentiel de stockage de carbone dans quelques sols cultivés français

In order to predict the potential of soils to store carbon in response to land use or climate changes, we measured the fluxes and distribution of residence times of C in French cultivated soils. We used the natural abundances in 13C and 14C to measure this distribution in long-term experiments of maize cultivation in France. 75% of the topsoil carbon had a mean residence time of 40 yr. Coarse particle-size fractions contained most of the younger carbon. A compartment of stable C was estimated using radiocarbon dating. Belowground plant material inputs stored as much as C as aboveground inputs. The effect of temperature on soil carbon mineralization affected only rate constants, with a Q10 = 3.1 constant in the range 1–25 °C. The data were summerized in a simple simulation model, which predicted a nil or low effect of climatic change on soil carbon storage in the next 50 yr. In France, land use changes will have more influence than atmospheric changes on C storage. Key words: France, greenhouse gases, mineralization, model, soil carbon, storage, temperature

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Effects of Different Land Use Changes and Spatial Variation in Rainfall on Soil Properties and Soil Carbon Storage in Western Rajasthan, India

Annals of Advanced Agricultural Sciences ◽

10.22606/as.2017.12001 ◽

2017 ◽

Vol 1 (2) ◽

Cited By ~ 1

Author(s):

G. Singh ◽

◽

Ritu Sharma ◽

Keyword(s):

Land Use ◽

Soil Properties ◽

Spatial Variation ◽

Soil Carbon ◽

Carbon Storage ◽

Land Use Changes ◽

Soil Carbon Storage

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Prediction and digital mapping of soil carbon storage in the Lower Namoi Valley

Soil Research ◽

10.1071/sr05136 ◽

2006 ◽

Vol 44 (3) ◽

pp. 233 ◽

Cited By ~ 125

Author(s):

Budiman Minasny ◽

Alex. B. McBratney ◽

M. L. Mendonça-Santos ◽

I. O. A. Odeh ◽

Brice Guyon

Keyword(s):

Land Use ◽

Organic Carbon ◽

Soil Carbon ◽

Carbon Storage ◽

Environmental Data ◽

Pedotransfer Functions ◽

Soil Carbon Storage ◽

Depth Function ◽

Terrain Attributes ◽

Organic Carbon Storage

Estimation and mapping carbon storage in the soil is currently an important topic; thus, the knowledge of the distribution of carbon content with depth is essential. This paper examines the use of a negative exponential profile depth function to describe the soil carbon data at different depths, and its integral to represent the carbon storage. A novel method is then proposed for mapping the soil carbon storage in the Lower Namoi Valley, NSW. This involves deriving pedotransfer functions to predict soil organic carbon and bulk density, fitting the exponential depth function to the carbon profile data, deriving a neural network model to predict parameters of the exponential function from environmental data, and mapping the organic carbon storage. The exponential depth function is shown to fit the soil carbon data adequately, and the parameters also reflect the influence of soil order. The parameters of the exponential depth function were predicted from land use, radiometric K, and terrain attributes. Using the estimated parameters we map the carbon storage of the area from surface to a depth of 1 m. The organic carbon storage map shows the high influence of land use on the predicted storage. Values of 15–22 kg/m2 were predicted for the forested area and 2–6 kg/m2 in the cultivated area in the plains.

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Modelling soil carbon stocks in semi-natural and agro-ecosystems – quantifying national scale impacts of the Anthropocene

10.5194/egusphere-egu2020-18355 ◽

2020 ◽

Author(s):

Victoria Janes-Bassett ◽

Jessica Davies ◽

Richard Bassett ◽

Dmitry Yumashev ◽

Ed Rowe ◽

...

Keyword(s):

Land Use ◽

Nutrient Cycling ◽

Soil Carbon ◽

Carbon Storage ◽

Management Practices ◽

Carbon Stocks ◽

Soil Carbon Storage ◽

National Scale ◽

Soil Carbon Stocks

Throughout the Anthropocene, the conversion of land to agriculture and atmospheric deposition of nitrogen have resulted in significant changes to biogeochemical cycling, including soil carbon stocks. Quantifying these changes is complex due to a number of influential factors (including climate, land use management, soil type) and their interactions. As the largest terrestrial store of carbon, soils are a key component in climate regulation. In addition, soil carbon storage contributes to numerous ecosystem services including food provision. It is therefore imperative that we understand changes to soil carbon stocks, and provide effective strategies for their future management.Modelling soil systems provides a means to estimate changes to soil carbon stocks. Due to linkages between the carbon cycle and other major nutrient cycles (notably nitrogen and phosphorus which often limit the productivity of ecosystems), models of integrated nutrient cycling are required to understand the response of the carbon cycle to global pressures. Simulating the impacts of land use changes requires capacity to model both semi-natural and intensive agricultural systems.In this study, we have developed an integrated carbon-nitrogen-phosphorus model of semi-natural systems to include representation of both arable and grassland systems, and a range of agricultural management practices. The model is applicable to large spatial scales, as it uses readily available input data and does not require site-specific calibration. &#160;After being validated both spatially and temporally using data from long-term experimental sites across Northern-Europe, the model was applied at a national scale throughout the United Kingdom to assess the impacts of land use change and management practices during the last two centuries. Results indicate a decrease in soil carbon in areas of agricultural expansion, yet in areas of semi-natural land use, atmospheric deposition of nitrogen has resulted in increased net primary productivity and subsequently soil carbon. The results demonstrate anthropogenic impacts on long-term nutrient cycling and soil carbon storage, and the importance of integrated nutrient cycling within models.

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