Soil organic carbon stocks and flows in New Zealand: System development, measurement and modelling

2005 ◽  
Vol 85 (Special Issue) ◽  
pp. 481-489 ◽  
Author(s):  
K. R. Tate ◽  
R. H. Wilde ◽  
D. J. Giltrap ◽  
W. T. Baisden ◽  
S. Saggar ◽  
...  
Keyword(s):  
Land Use ◽  
Steady State ◽  
New Zealand ◽  
Organic Carbon ◽  
Land Use Changes ◽  
Soil Organic C ◽  
Organic C ◽  
Soil C ◽  
C Stocks ◽  
Stocks And Flows

An IPCC-based Carbon Monitoring System (CMS) was developed to monitor soil organic C stocks and flows to assist New Zealand to achieve its CO2 emissions reduction target under the Kyoto Protocol. Geo-referenced soil C data from 1158 sites (0.3 m depth) were used to assign steady-state soil C stocks to various combinations of soil class, climate, and land use. Overall, CMS soil C stock estimates are consistent with detailed, stratified soil C measurements at specific sites and over larger regions. Soil C changes accompanying land-use changes were quantified using a national set of land-use effects (LUEs). These were derived using a General Linear Model to include the effects of numeric predictors (e.g., slope angle). Major uncertainties a rise from estimates of changes in the areas involved, the assumption that soil C is at steady state for all land-cover types, and lack of soil C data for some LUEs. Total national soil organic C stocks estimated using the LUEs for 0–0.1, 0.1–0.3, and 0.3–1 m depths were 1300 ± 20, 1590 ± 30, and 1750 ± 70 Tg, respectively. Most soil C is stored in grazing lands (1480 ± 60 Tg to 0.3 m depth), which appear to be at or near steady state; their conversion to exotic forests and shrubland contributed most to the predicted national soil C loss of 0.6 ± 0.2 Tg C yr-1 during 1990–2000. Predicted and measured soil C changes for the grazing-forestry conversion agreed closely. Other uncertainties in our current soil CMS include: spatially integrated annual changes in soil C for the major land-use changes, lack of soil C change estimates below 0.3 m, C losses from erosion, the contribution of agricultural management of organic soils, and a possible interaction between land use and our soil-climate classification. Our approach could be adapted for use by other countries with land-use-change issues that differ from those in the IPCC default methodology. Key words: Soil organic carbon, land-use change, stocks, flows, measurement, modelling, IPCC

scholarly journals Effect of deforestation and subsequent land-use management on soil carbon stocks in the South American Chaco

2018 ◽  
Author(s):  
Natalia Andrea Osinaga ◽  
Carina Rosa Álvarez ◽  
Miguel Angel Taboada
Keyword(s):  
Land Use ◽  
Land Use Changes ◽  
Warm Season ◽  
Native Forest ◽  
Continuous Cropping ◽  
Organic C ◽  
Soil C ◽  
C Stocks ◽  
Chaco Region ◽  
The Impact

Abstract. Abstract. The sub-humid Chaco region of Argentina, originally covered by dry sclerophyll forest, has been subjected to clearing since the end of the '70 and replacement of the forest by no till farming. Land use changes produced a decrease in aboveground carbon stored in forests, but little is known about the impact on soil organic C stocks. The aim of this study was to evaluate soil C stocks and C fractions up to 1 m depth in soils under different land use:  20 yr continuous cropping, warm season grass pasture and native forest in 32 sites distributed over the Chaco region. The organic C stock content up to 1 m depth expressed as equivalent mass varied as follows: forest (119.3 Mg ha−1) > pasture (87.9 Mg ha−1) > continuous cropping (71.9 and 77.3 Mg ha−1), with no impact of the number of years under cropping. The most sensitive organic carbon fraction was the coarse particle fraction (2000 μm–212 μm) at 0–5 cm and 5–20 cm depth layers. Resistant carbon (

scholarly journals Effect of deforestation and subsequent land use management on soil carbon stocks in the South American Chaco

SOIL ◽  
2018 ◽  
Vol 4 (4) ◽  
pp. 251-257 ◽  
Author(s):  
Natalia Andrea Osinaga ◽  
Carina Rosa Álvarez ◽  
Miguel Angel Taboada
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Warm Season ◽  
Continuous Cropping ◽  
Soil Organic C ◽  
Organic C ◽  
Soil C ◽  
C Stocks ◽  
C Stock ◽  
The Impact

Abstract. The subhumid Chaco region of Argentina, originally covered by dry sclerophyll forest, has been subjected to clearing since the end of the 1970s and replacement of the forest by no-till farming. Land use changes produced a decrease in aboveground carbon (C) stored in forests, but little is known about the impact on soil organic C stocks. The aim of this study was to evaluate soil C stocks and C fractions up to 1 m depth in soils under different land use: <10-year continuous cropping, >20-year continuous cropping, warm-season grass pasture and native forest in 32 sites distributed over the Chaco region. The organic C stock content up to 1 m depth expressed as equivalent mass varied as follows: forest (119.3 Mg ha−1) > pasture (87.9 Mg ha−1) > continuous cropping (71.9 and 77.3 Mg ha−1), with no impact of the number of years under cropping. The coarse particle fraction (2000–212 µm) at 0–5 and 5–20 cm depth layers was the most sensitive organic carbon fraction to land use change. Resistant carbon (<53 µm) was the main organic matter fraction in all sample categories except in the forest. Organic C stock, its quality and its distribution in the profile were responsive to land use change. The conversion of the Chaco forest to crops was associated with a decrease of organic C stock up to 1 m depth and with the decrease of the labile fraction. The permanent pastures of warm-season grasses allowed higher C stocks to be sustained than cropping systems and so could be considered a sustainable land use system in terms of soil C preservation. As soil organic C losses were not restricted to the first few centimetres of the soil, the development of models that would allow the estimation of soil organic C changes in depth would be useful to evaluate the impact of land use change on C stocks with greater precision.

scholarly journals Uncertainties in the land-use flux resulting from land-use change reconstructions and gross land transitions

2017 ◽  
Vol 8 (1) ◽  
pp. 91-111 ◽  
Author(s):  
Anita D. Bayer ◽  
Mats Lindeskog ◽  
Thomas A. M. Pugh ◽  
Peter M. Anthoni ◽  
Richard Fuchs ◽  
...  
Keyword(s):  
Land Use ◽  
Agricultural Land ◽  
Land Use Changes ◽  
Terrestrial Ecosystem ◽  
Grid Cell ◽  
Carbon Stocks ◽  
Dynamic Global Vegetation Model ◽  
Soil C ◽  
Tropical Regions ◽  
C Stocks

Abstract. Land-use and land-cover (LUC) changes are a key uncertainty when attributing changes in measured atmospheric CO2 concentration to its sinks and sources and must also be much better understood to determine the possibilities for land-based climate change mitigation, especially in the light of human demand on other land-based resources. On the spatial scale typically used in terrestrial ecosystem models (0.5 or 1°) changes in LUC over time periods of a few years or more can include bidirectional changes on the sub-grid level, such as the parallel expansion and abandonment of agricultural land (e.g. in shifting cultivation) or cropland–grassland conversion (and vice versa). These complex changes between classes within a grid cell have often been neglected in previous studies, and only net changes of land between natural vegetation cover, cropland and pastures accounted for, mainly because of a lack of reliable high-resolution historical information on gross land transitions, in combination with technical limitations within the models themselves. In the present study we applied a state-of-the-art dynamic global vegetation model with a detailed representation of croplands and carbon–nitrogen dynamics to quantify the uncertainty in terrestrial ecosystem carbon stocks and fluxes arising from the choice between net and gross representations of LUC. We used three frequently applied global, one recent global and one recent European LUC datasets, two of which resolve gross land transitions, either in Europe or in certain tropical regions. When considering only net changes, land-use-transition uncertainties (expressed as 1 standard deviation around decadal means of four models) in global carbon emissions from LUC (ELUC) are ±0.19, ±0.66 and ±0.47 Pg C a−1 in the 1980s, 1990s and 2000s, respectively, or between 14 and 39 % of mean ELUC. Carbon stocks at the end of the 20th century vary by ±11 Pg C for vegetation and ±37 Pg C for soil C due to the choice of LUC reconstruction, i.e. around 3 % of the respective C pools. Accounting for sub-grid (gross) land conversions significantly increased the effect of LUC on global and European carbon stocks and fluxes, most noticeably enhancing global cumulative ELUC by 33 Pg C (1750–2014) and entailing a significant reduction in carbon stored in vegetation, although the effect on soil C stocks was limited. Simulations demonstrated that assessments of historical carbon stocks and fluxes are highly uncertain due to the choice of LUC reconstruction and that the consideration of different contrasting LUC reconstructions is needed to account for this uncertainty. The analysis of gross, in addition to net, land-use changes showed that the full complexity of gross land-use changes is required in order to accurately predict the magnitude of LUC change emissions. This introduces technical challenges to process-based models and relies on extensive information regarding historical land-use transitions.

Land‐use change with pasture and short rotation eucalypts impacts the soil C emissions and organic C stocks in the Cerrado biome

2020 ◽  
Vol 31 (7) ◽  
pp. 909-923 ◽  
Author(s):  
Rafael da Silva Teixeira ◽  
Ricardo Cardoso Fialho ◽  
Daniela Cristina Costa ◽  
Rodrigo Nogueira Sousa ◽  
Rafael Silva Santos ◽  
...  
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Organic C ◽  
Soil C ◽  
Cerrado Biome ◽  
Short Rotation ◽  
C Stocks

scholarly journals Evaluation of terrestrial pan-Arctic carbon cycling using a data-assimilation system

2019 ◽  
Vol 10 (2) ◽  
pp. 233-255 ◽  
Author(s):  
Efrén López-Blanco ◽  
Jean-François Exbrayat ◽  
Magnus Lund ◽  
Torben R. Christensen ◽  
Mikkel P. Tamstorf ◽  
...  
Keyword(s):  
The Arctic ◽  
Soil Organic C ◽  
Area Index ◽  
Organic C ◽  
Soil C ◽  
Transit Times ◽  
C Cycle ◽  
C Stocks ◽  
Data Assimilation System ◽  
Assimilation System

Abstract. There is a significant knowledge gap in the current state of the terrestrial carbon (C) budget. Recent studies have highlighted a poor understanding particularly of C pool transit times and of whether productivity or biomass dominate these biases. The Arctic, accounting for approximately 50 % of the global soil organic C stocks, has an important role in the global C cycle. Here, we use the CARbon DAta MOdel (CARDAMOM) data-assimilation system to produce pan-Arctic terrestrial C cycle analyses for 2000–2015. This approach avoids using traditional plant functional type or steady-state assumptions. We integrate a range of data (soil organic C, leaf area index, biomass, and climate) to determine the most likely state of the high-latitude C cycle at a 1∘ × 1∘ resolution and also to provide general guidance about the controlling biases in transit times. On average, CARDAMOM estimates regional mean rates of photosynthesis of 565 g C m−2 yr−1 (90 % confidence interval between the 5th and 95th percentiles: 428, 741), autotrophic respiration of 270 g C m−2 yr−1 (182, 397) and heterotrophic respiration of 219 g C m−2 yr−1 (31, 1458), suggesting a pan-Arctic sink of −67 (−287, 1160) g Cm−2 yr−1, weaker in tundra and stronger in taiga. However, our confidence intervals remain large (and so the region could be a source of C), reflecting uncertainty assigned to the regional data products. We show a clear spatial and temporal agreement between CARDAMOM analyses and different sources of assimilated and independent data at both pan-Arctic and local scales but also identify consistent biases between CARDAMOM and validation data. The assimilation process requires clearer error quantification for leaf area index (LAI) and biomass products to resolve these biases. Mapping of vegetation C stocks and change over time and soil C ages linked to soil C stocks is required for better analytical constraint. Comparing CARDAMOM analyses to global vegetation models (GVMs) for the same period, we conclude that transit times of vegetation C are inconsistently simulated in GVMs due to a combination of uncertainties from productivity and biomass calculations. Our findings highlight that GVMs need to focus on constraining both current vegetation C stocks and net primary production to improve a process-based understanding of C cycle dynamics in the Arctic.

Quantifying total and labile pools of soil organic carbon in cultivated and uncultivated soils in eastern India

Soil Research ◽  
2018 ◽  
Vol 56 (4) ◽  
pp. 413 ◽  
Author(s):  
Kumari Priyanka ◽  
Anshumali
Keyword(s):  
Land Use ◽  
Function Analysis ◽  
Land Use Changes ◽  
C Sequestration ◽  
Sensitivity Index ◽  
Organic C ◽  
Soil C ◽  
C Pools ◽  
The Impact ◽  
Land Use Practices

Loss of labile carbon (C) fractions yields information about the impact of land-use changes on sources of C inputs, pathways of C losses and mechanisms of soil C sequestration. This study dealt with the total organic C (TOC) and labile C pools in 40 surface soil samples (0–15 cm) collected from four land-use practices: uncultivated sites and rice–wheat, maize–wheat and sugarcane agro-ecosystems. Uncultivated soils had a higher total C pool than croplands. The soil inorganic C concentrations were in the range of 0.7–1.4 g kg–1 under different land-use practices. Strong correlations were found between TOC and all organic C pools, except water-extractable organic C and mineralisable C. The sensitivity index indicated that soil organic C pools were susceptible to changes in land-use practices. Discriminant function analysis showed that the nine soil variables could distinguish the maize–wheat and rice–wheat systems from uncultivated and sugarcane systems. Finally, we recommend crop rotation practices whereby planting sugarcane replenishes TOC content in soils.

scholarly journals Assessing the response of soil carbon in Australia to changing inputs and climate using a consistent modelling framework

2021 ◽  
Vol 18 (18) ◽  
pp. 5185-5202
Author(s):  
Juhwan Lee ◽  
Raphael A. Viscarra Rossel ◽  
Mingxi Zhang ◽  
Zhongkui Luo ◽  
Ying-Ping Wang
Keyword(s):  
Global Change ◽  
Future Climate Change ◽  
Natural Environments ◽  
Soil Organic C ◽  
Total N ◽  
Organic C ◽  
Soil C ◽  
Continental Scale ◽  
Modelling Framework ◽  
C Stocks

Abstract. Land use and management practices affect the response of soil organic carbon (C) to global change. Process-based models of soil C are useful tools to simulate C dynamics, but it is important to bridge any disconnect that exists between the data used to inform the models and the processes that they depict. To minimise that disconnect, we developed a consistent modelling framework that integrates new spatially explicit soil measurements and data with the Rothamsted carbon model (Roth C) and simulates the response of soil organic C to future climate change across Australia. We compiled publicly available continental-scale datasets and pre-processed, standardised and configured them to the required spatial and temporal resolutions. We then calibrated Roth C and ran simulations to estimate the baseline soil organic C stocks and composition in the 0–0.3 m layer at 4043 sites in cropping, modified grazing, native grazing and natural environments across Australia. We used data on the C fractions, the particulate, mineral-associated and resistant organic C (POC, MAOC and ROC, respectively) to represent the three main C pools in the Roth C model's structure. The model explained 97 %–98 % of the variation in measured total organic C in soils under cropping and grazing and 65 % in soils under natural environments. We optimised the model at each site and experimented with different amounts of C inputs to simulate the potential for C accumulation under constant climate in a 100-year simulation. With an annual increase of 1 Mg C ha−1 in C inputs, the model simulated a potential soil C increase of 13.58 (interquartile range 12.19–15.80), 14.21 (12.38–16.03) and 15.57 (12.07–17.82) Mg C ha−1 under cropping, modified grazing and native grazing and 3.52 (3.15–4.09) Mg C ha−1 under natural environments. With projected future changes in climate (+1.5, 2 and 5.0 ∘C) over 100 years, the simulations showed that soils under natural environments lost the most C, between 3.1 and 4.5 Mg C ha−1, while soils under native grazing lost the least, between 0.4 and 0.7 Mg C ha−1. Soil under cropping lost between 1 and 2.7 Mg C ha−1, while those under modified grazing showed a slight increase with temperature increases of 1.5 ∘C, but with further increases of 2 and 5 ∘C the median loss of TOC was 0.28 and 3.4 Mg C ha−1, respectively. For the different land uses, the changes in the C fractions varied with changes in climate. An empirical assessment of the controls on the C change showed that climate, pH, total N, the C : N ratio and cropping were the most important controls on POC change. Clay content and climate were dominant controls on MAOC change. Consistent and explicit soil organic C simulations improve confidence in the model's estimations, facilitating the development of sustainable soil management under global change.

scholarly journals Beneath the arctic greening: Will soils lose or gain carbon or perhaps a little of both?

2019 ◽  
Author(s):  
Jennifer W. Harden ◽  
Jonathan A. O'Donnell ◽  
Katherine A. Heckman ◽  
Benjamin N. Sulman ◽  
Charles D. Koven ◽  
...  
Keyword(s):  
Steady State ◽  
Forest Soil ◽  
The Arctic ◽  
Mean Annual Temperature ◽  
Spruce Forest ◽  
Organic C ◽  
Soil C ◽  
Community Land Model ◽  
C Stocks ◽  
And Shifts

Abstract. Ecosystem shifts related to climate change are anticipated for the next decades to centuries based on a number of conceptual and experimentally derived models of plant structure and function. Belowground, the potential responses of soil systems are less well known. We used geochemical steady state models, soil density fractionation, and soil radiocarbon data to constrain changes in soil carbon based on measurements from detrital (free light), aggregate-bound (occluded) and complexed or chemically bound (mineral associated) carbon pools and for bulk soil. We explored a space-for-time sequence of soils along a cold-to-warm climatic gradient from Alaskan Black Spruce forest soil with permafrost (Gelisols; 50 cm Mean Annual Temperature −1.5 ºC), Alaskan White Spruce forest soil lacking permafrost (Inceptisols; 50 cm MAT +3 ºC ), and Iowa Grassland soil lacking permafrost (Mollisols; 50 cm MAT +9 ºC) developed on similar geologic substrates (wind-blown loess deposits). These temperature ranges were also representative of temperatures at 50 cm soil depth from model output by the Community Land Model for the years 2014, 2100, and 2300 for Interior Alaska. Fitting an exponential equation to depth trends in soil C down to 2 m depths, we found that depth distributions of organic C were related mainly to depths of rooting and changes in bulk density. Using output from the geochemical steady state model, the direction and magnitude of the C loss or gain upon ecosystem shift was dictated by the C stocks of initial and final ecosystems. Radiocarbon measurements specific to each soil fraction (free light, occluded, and mineral associated) allowed us to constrain the timing of the potential loss or gain of C in each fraction driven by climatic shifts. Thawing from the Gelisol to Inceptisol in loess parent materials from present day to year 2100 resulted in small net gains to soil C, reflecting the net balance between loss of detrital and gain into occluded and mineral associated C. Greater warming and shifts from Inceptisol to Mollisol analogous to predicted warming from circa 2100 to 2300 resulted in net C losses from both occluded and mineral associated C, although small gains to the free light C fraction occurred throughout the depth profile. Gains to occluded and mineral associated C post- thaw likely reflect aggregate formation and physical protection of C as well as formation of organo-mineral compounds that accompany microbial processing. Greater warming and shifts from Inceptisol to Mollisol, which are analogous to predicted warming circa 2100 to 2300, resulted in net C losses from both occluded and mineral associated C resulting from enhanced decomposition, small gains to the free light C fraction occurred throughout the transition to Mollisol reflecting deeper rooting of the tallgrass prairie system.

scholarly journals Simulation of soil carbon dynamics in Australia under a framework that better connects spatially explicit data with Rᴏᴛʜ C

2020 ◽  
Author(s):  
Juhwan Lee ◽  
Raphael A. Viscarra Rossel ◽  
Zhongkui Luo ◽  
Ying Ping Wang
Keyword(s):  
C:N Ratio ◽  
Clay Content ◽  
Spatially Explicit ◽  
Natural Environments ◽  
Soil Organic C ◽  
Total N ◽  
Organic C ◽  
Soil C ◽  
Continental Scale ◽  
C Stocks

Abstract. We simulated soil organic carbon (C) dynamics across Australia with the Rothamsted carbon model (Rᴏᴛʜ C) under a framework that connects new spatially-explicit soil measurements and data with the model. Doing so helped to bridge the disconnection that exists between datasets used to inform the model and the processes that it depicts. Under this framework, we compiled continental-scale datasets and pre-processed, standardised and configured them to the required spatial and temporal resolutions. We then calibrated Rᴏᴛʜ C and run simulations to predict the baseline soil organic C stocks and composition in the 0–0.3 m layer at 4,043 sites in cropping, modified grazing, native grazing, and natural environments across Australia. The Rᴏᴛʜ C model uses measured C fractions, the particulate, humus, and resistant organic C (POC, HOC and ROC, respectively) to represent the three main C pools in its structure. The model explained 97–98 % of the variation in measured total organic C in soils under cropping and grazing, and 65 % in soils under natural environments. We optimised the model at each site and experimented with different amounts of C inputs to predict the potential for C accumulation in a 100-year simulation. With an annual increase of 1 Mg C ha−1 in C inputs, the model predicted a potential soil C increase of 13.58 (interquartile range 12.19–15.80), 14.21 (12.38–16.03), and 15.57 (12.07–17.82) Mg C ha−1 under cropping, modified grazing and native grazing, and 3.52 (3.15–4.09) Mg C ha−1 under natural environments. Soils under native grazing were the most potentially vulnerable to C decomposition and loss, while soils under natural environments were the least vulnerable. An empirical assessment of the controls on the C change showed that climate, pH, total N, the C:N ratio, and cropping were the most important controls on POC change. Clay content and climate were dominant controls on HOC change. Consistent and explicit soil organic C simulations improve confidence in the model's predictions, contributing to the development of sustainable soil management under global change.

scholarly journals Uncertainties in the land use flux resulting from land use change reconstructions and gross land transitions

2016 ◽  
Author(s):  
Anita D. Bayer ◽  
Mats Lindeskog ◽  
Thomas A. M. Pugh ◽  
Richard Fuchs ◽  
Almut Arneth
Keyword(s):  
Land Use ◽  
Agricultural Land ◽  
Land Use Changes ◽  
Terrestrial Ecosystem ◽  
Co2 Concentration ◽  
Carbon Stocks ◽  
Dynamic Global Vegetation Model ◽  
Soil C ◽  
Tropical Regions ◽  
C Stocks

Abstract. Land-use and land-cover (LUC) changes are a key uncertainty when attributing changes in measured atmospheric CO2 concentration to its sinks and sources, and must also be much better understood to determine possibilities for land-based climate change mitigation, especially in the light of human demand on other land-based resources. On the spatial scale typically used in terrestrial ecosystem models (0.5 or 1 degrees) changes in LUC over time periods of a few years or more can include bi-directional changes on the sub-grid level, such as the parallel expansion and abandonment of agricultural land (e.g. in shifting cultivation), or cropland-grassland conversion (and vice versa). These complex changes between classes within a gridcell have often been neglected in previous studies, and only net changes of land between natural vegetation cover, cropland and pastures accounted for, mainly because of a lack of reliable high-resolution historical information on gross land transitions. In the present study we applied a state-of-the-art dynamic global vegetation model with a detailed representation of croplands and carbon-nitrogen dynamics to quantify the uncertainty in terrestrial ecosystem carbon stocks and fluxes arising from the choice between net and gross representations of LUC. We used three frequently applied global and one recent European LUC datasets, two of which resolve gross land transitions, either in Europe or in tropical regions. When considering only net changes, land-use-transition uncertainties (expressed as one standard deviation around decadal means) in global carbon emissions from LUC (ELUC) are &amp;pm;0.23, &amp;pm;0.76 and &amp;pm;0.49 Pg C a−1 in the 1980s, 1990s and 2000s, respectively, or between 17 % and 42 % of mean ELUC. Carbon stocks at the end of the 20th century vary by &amp;pm;13 Pg C for vegetation and &amp;pm;41 Pg C for soil C due to the choice of LUC reconstruction, i.e. around 3 % of the respective C pools. Accounting for sub-grid (gross) land conversions significantly increased the effect of LUC on global and European carbon stocks and fluxes, most noticeably enhancing global cumulative ELUC by 33 Pg C (1750–2014) and entailing a significant reduction in carbon stored in vegetation, although the effect on soil C stocks was limited. Simulations demonstrated that assessments of historical carbon stocks and fluxes are highly uncertain due to the choice of LUC reconstruction and that the consideration of different contrasting LUC reconstructions is needed to account for this uncertainty. The analysis of gross in addition to net land changes showed that the full complexity of gross land-use changes is required in order to accurately predict the magnitude of LUC change emissions. This introduces technical challenges to the process-based models and relies on extensive information on historical land use transitions.

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