scholarly journals Global soil organic carbon stock projection uncertainties relevant to sensitivity of global mean temperature and precipitation changes

2013 ◽  
Vol 4 (2) ◽  
pp. 1035-1064 ◽  
Author(s):  
K. Nishina ◽  
A. Ito ◽  
D. J. Beerling ◽  
P. Cadule ◽  
P. Ciais ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Carbon Accumulation ◽  
Series Data ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Soc Stock ◽  
Global Mean ◽  
Biome Model ◽  
Soc Decomposition

Abstract. Soil organic carbon (SOC) is the largest carbon pool in terrestrial ecosystems and may play a key role in biospheric feedback to elevated atmospheric carbon dioxide (CO2) in the warmer future world. We examined seven biome models with climate projections forced by four representative-concentration-pathways (RCPs)-based atmospheric concentration scenarios. The goal was to specify uncertainty in global SOC stock projections from global and regional perspectives. Our simulations showed that SOC stocks among the biome models varied from 1090 to 2650 Pg C even in historical periods (ca. 2000). In a higher forcing scenario (RCP8.5), inconsistent estimates of impact on the total SOC (2099–2000) were obtained from different model simulations, ranging from a net sink of 347 Pg C to a net source of 122 Pg C. In all models, the elevated atmospheric CO2 concentration in the RCP8.5 scenario considerably contributed to carbon accumulation in SOC. However, magnitudes varied from 93 to 264 Pg C by the end of the 21st century. Using time-series data of total global SOC estimated by biome biome model, we statistically analyzed the sensitivity of the global SOC stock to global mean temperature and global precipitation anomalies (ΔT and ΔP respectively) in each biome model using a state-space model. This analysis suggests that ΔT explained global SOC stock changes in most models with a resolution of 1–2 °C, and the magnitude of global SOC decomposition from a 2 °C rise ranged from almost 0 Pg C yr−1 to 3.53 Pg C yr−1 among the biome models. On the other hand, ΔP had a negligible impact on change in the global SOC changes. Spatial heterogeneity was evident and inconsistent among the changes in SOC estimated by the biome models, especially in boreal to arctic regions. Our study revealed considerable climate change impact uncertainty in SOC decomposition among biome models. Further research is required to improve our understanding and ability to estimate biospheric feedback through SOC-relevant processes as well as vegetation processes.

scholarly journals Quantifying uncertainties in soil carbon responses to changes in global mean temperature and precipitation

2014 ◽  
Vol 5 (1) ◽  
pp. 197-209 ◽  
Author(s):  
K. Nishina ◽  
A. Ito ◽  
D. J. Beerling ◽  
P. Cadule ◽  
P. Ciais ◽  
...  
Keyword(s):  
Time Series Data ◽  
Carbon Accumulation ◽  
Series Data ◽  
Climate Projections ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Soc Stock ◽  
Global Mean ◽  
Biome Model ◽  
Soc Decomposition

Abstract. Soil organic carbon (SOC) is the largest carbon pool in terrestrial ecosystems and may play a key role in biospheric feedbacks with elevated atmospheric carbon dioxide (CO2) in a warmer future world. We examined the simulation results of seven terrestrial biome models when forced with climate projections from four representative-concentration-pathways (RCPs)-based atmospheric concentration scenarios. The goal was to specify calculated uncertainty in global SOC stock projections from global and regional perspectives and give insight to the improvement of SOC-relevant processes in biome models. SOC stocks among the biome models varied from 1090 to 2650 Pg C even in historical periods (ca. 2000). In a higher forcing scenario (i.e., RCP8.5), inconsistent estimates of impact on the total SOC (2099–2000) were obtained from different biome model simulations, ranging from a net sink of 347 Pg C to a net source of 122 Pg C. In all models, the increasing atmospheric CO2 concentration in the RCP8.5 scenario considerably contributed to carbon accumulation in SOC. However, magnitudes varied from 93 to 264 Pg C by the end of the 21st century across biome models. Using the time-series data of total global SOC simulated by each biome model, we analyzed the sensitivity of the global SOC stock to global mean temperature and global precipitation anomalies (ΔT and ΔP respectively) in each biome model using a state-space model. This analysis suggests that ΔT explained global SOC stock changes in most models with a resolution of 1–2 °C, and the magnitude of global SOC decomposition from a 2 °C rise ranged from almost 0 to 3.53 Pg C yr−1 among the biome models. However, ΔP had a negligible impact on change in the global SOC changes. Spatial heterogeneity was evident and inconsistent among the biome models, especially in boreal to arctic regions. Our study reveals considerable climate uncertainty in SOC decomposition responses to climate and CO2 change among biome models. Further research is required to improve our ability to estimate biospheric feedbacks through both SOC-relevant and vegetation-relevant processes.

Soil organic carbon dynamics as affected by climate warming in a semiarid alpine region

2020 ◽  
Author(s):  
Meng Zhu ◽  
Wei Liu ◽  
Qi Feng ◽  
Bing Jia ◽  
Chengqi Zhang
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Climate Warming ◽  
Qilian Mountains ◽  
Carbon Accumulation ◽  
Future Climate ◽  
Future Climate Change ◽  
Alpine Regions ◽  
Soc Stock ◽  
The Mean

<p>An evaluation to soil organic carbon (SOC) stock dynamics in alpine regions is crucial for the adaptive management of regional carbon budget under the elevation-dependent warming in mountainous regions. Here, we evaluated the dynamics of SOC stock to 60 cm depth in the Qilian Mountains (1700~5100 m a.s.l.) by combining systematic measurements from 138 sampling sites with a machine learning technique (i.e. random forest, RF). Our results revealed that the combination of systematic measurements with the RF model allowed spatially explicit estimates to be made. The average SOC density (SOC amount per unit area, SOCD) in the middle Qilian Mountains will decrease under future climate change. However, the size and direction of carbon change are elevation- or vegetation-dependent. Specifically, in comparison with the baseline year (1970~2000), the mean annual precipitation will increase by 18.37, 19.80 and 30.80 mm, and the mean annual temperature will increase by 1.9, 2.4 and 2.9°C, respectively, under the RCP2.6 (representative concentration pathway), RCP4.5 and RCP8.5 scenarios in 2050s. Accordingly, the mean SOCD decreased by 0.59, 0.93 and 1.05 kg C m<sup>-2</sup>, the SOC stock decreased by 6.23, 9.75 and 11.07 Tg C, respectively under the RCP2.6, RCP4.5 and RCP8.5 scenarios. In addition, the mid-elevation zones (3100-3900 m), especially the subalpine shrub-meadow zone, will be characterized by the strongest carbon loss due to the high standing organic carbon stock under climate warming. By contrast, the high elevation zones (> 3900 m), especially the alpine desert zone, which will experience increase in accumulative temperature, prolongation in growing season, and consequently enhancement in plant productivity due to future climate warming, will be characterized by significant carbon accumulation in the future. Thus, the mid-elevation zones, especially the subalpine shrub-meadow zone should be given priority in terms of reducing CO<sub>2</sub> emissions under future warming in alpine regions.</p>

scholarly journals Organic mulching promotes soil organic carbon accumulation to deep soil layer in an urban plantation forest

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Xiaodan Sun ◽  
Gang Wang ◽  
Qingxu Ma ◽  
Jiahui Liao ◽  
Dong Wang ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Carbon Content ◽  
Fine Roots ◽  
Soil Layer ◽  
Carbon Accumulation ◽  
Bulk Soil ◽  
Organic Mulch ◽  
The Impact ◽  
Soc Fractions

Abstract Background Soil organic carbon (SOC) is important for soil quality and fertility in forest ecosystems. Labile SOC fractions are sensitive to environmental changes, which reflect the impact of short-term internal and external management measures on the soil carbon pool. Organic mulching (OM) alters the soil environment and promotes plant growth. However, little is known about the responses of SOC fractions in rhizosphere or bulk soil to OM in urban forests and its correlation with carbon composition in plants. Methods A one-year field experiment with four treatments (OM at 0, 5, 10, and 20 cm thicknesses) was conducted in a 15-year-old Ligustrum lucidum plantation. Changes in the SOC fractions in the rhizosphere and bulk soil; the carbon content in the plant fine roots, leaves, and organic mulch; and several soil physicochemical properties were measured. The relationships between SOC fractions and the measured variables were analysed. Results The OM treatments had no significant effect on the SOC fractions, except for the dissolved organic carbon (DOC). OM promoted the movement of SOC to deeper soil because of the increased carbon content in fine roots of subsoil. There were significant correlations between DOC and microbial biomass carbon and SOC and easily oxidised organic carbon. The OM had a greater effect on organic carbon fractions in the bulk soil than in the rhizosphere. The thinnest (5 cm) mulching layers showed the most rapid carbon decomposition over time. The time after OM had the greatest effect on the SOC fractions, followed by soil layer. Conclusions The frequent addition of small amounts of organic mulch increased SOC accumulation in the present study. OM is a potential management model to enhance soil organic matter storage for maintaining urban forest productivity.

scholarly journals Estimates of Uncertainty in Predictions of Global Mean Surface Temperature

2007 ◽  
Vol 20 (5) ◽  
pp. 843-855 ◽  
Author(s):  
J. A. Kettleborough ◽  
B. B. B. Booth ◽  
P. A. Stott ◽  
M. R. Allen
Keyword(s):  
Twentieth Century ◽  
Energy Balance ◽  
Temperature Change ◽  
Radiative Forcing ◽  
Balance Model ◽  
Future Climate Change ◽  
Model Parameters ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Global Mean

Abstract A method for estimating uncertainty in future climate change is discussed in detail and applied to predictions of global mean temperature change. The method uses optimal fingerprinting to make estimates of uncertainty in model simulations of twentieth-century warming. These estimates are then projected forward in time using a linear, compact relationship between twentieth-century warming and twenty-first-century warming. This relationship is established from a large ensemble of energy balance models. By varying the energy balance model parameters an estimate is made of the error associated with using the linear relationship in forecasts of twentieth-century global mean temperature. Including this error has very little impact on the forecasts. There is a 50% chance that the global mean temperature change between 1995 and 2035 will be greater than 1.5 K for the Special Report on Emissions Scenarios (SRES) A1FI scenario. Under SRES B2 the same threshold is not exceeded until 2055. These results should be relatively robust to model developments for a given radiative forcing history.

scholarly journals Analytical solution for the effect of increasing CO2 on global mean temperature

Nature ◽  
1985 ◽  
Vol 316 (6029) ◽  
pp. 657-657 ◽  
Author(s):  
T. M. L. Wigley ◽  
M. E. Schlesinger
Keyword(s):  
Analytical Solution ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Global Mean

scholarly journals Estimating soil organic carbon stocks of Swiss forest soils by robust external-drift kriging

2014 ◽  
Vol 7 (3) ◽  
pp. 1197-1210 ◽  
Author(s):  
M. Nussbaum ◽  
A. Papritz ◽  
A. Baltensweiler ◽  
L. Walthert
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Near Infrared ◽  
Likelihood Method ◽  
Standard Errors ◽  
Soil Profiles ◽  
Near Infrared Reflectance ◽  
Soc Stock ◽  
Soc Stocks ◽  
External Drift

Abstract. Accurate estimates of soil organic carbon (SOC) stocks are required to quantify carbon sources and sinks caused by land use change at national scale. This study presents a novel robust kriging method to precisely estimate regional and national mean SOC stocks, along with truthful standard errors. We used this new approach to estimate mean forest SOC stock for Switzerland and for its five main ecoregions. Using data of 1033 forest soil profiles, we modelled stocks of two compartments (0–30, 0–100 cm depth) of mineral soils. Log-normal regression models that accounted for correlation between SOC stocks and environmental covariates and residual (spatial) auto-correlation were fitted by a newly developed robust restricted maximum likelihood method, which is insensitive to outliers in the data. Precipitation, near-infrared reflectance, topographic and aggregated information of a soil and a geotechnical map were retained in the models. Both models showed weak but significant residual autocorrelation. The predictive power of the fitted models, evaluated by comparing predictions with independent data of 175 soil profiles, was moderate (robust R2 = 0.34 for SOC stock in 0–30 cm and R2 = 0.40 in 0–100 cm). Prediction standard errors (SE), validated by comparing point prediction intervals with data, proved to be conservative. Using the fitted models, we mapped forest SOC stock by robust external-drift point kriging at high resolution across Switzerland. Predicted mean stocks in 0–30 and 0–100 cm depth were equal to 7.99 kg m−2 (SE 0.15 kg m−2) and 12.58 kg m−2 (SE 0.24 kg m−2), respectively. Hence, topsoils store about 64% of SOC stocks down to 100 cm depth. Previous studies underestimated SOC stocks of topsoil slightly and those of subsoils strongly. The comparison further revealed that our estimates have substantially smaller SE than previous estimates.

scholarly journals Soil Organic Carbon Stocks in Afforested Agricultural Land in Lithuanian Hemiboreal Forest Zone

Forests ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1562
Author(s):  
Iveta Varnagirytė-Kabašinskienė ◽  
Povilas Žemaitis ◽  
Kęstutis Armolaitis ◽  
Vidas Stakėnas ◽  
Gintautas Urbaitis
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Forest Floor ◽  
Agricultural Land ◽  
Forest Stand ◽  
Stand Age ◽  
Soc Stock ◽  
The Mean ◽  
Soc Stocks ◽  
Topsoil Layer

In the context of the specificity of soil organic carbon (SOC) storage in afforested land, nutrient-poor Arenosols and nutrient-rich Luvisols after afforestation with coniferous and deciduous tree species were studied in comparison to the same soils of croplands and grasslands. This study analysed the changes in SOC stock up to 30 years after afforestation of agricultural land in Lithuania, representing the cool temperate moist climate region of Europe. The SOC stocks were evaluated by applying the paired-site design. The mean mass and SOC stocks of the forest floor in afforested Arenosols increased more than in Luvisols. Almost twice as much forest floor mass was observed in coniferous than in deciduous stands 2–3 decades after afforestation. The mean bulk density of fine (<2 mm) soil in the 0–30 cm mineral topsoil layer of croplands was higher than in afforested sites and grasslands. The clear decreasing trend in mean bulk density due to forest stand age with the lowest values in the 21–30-year-old stands was found in afforested Luvisols. In contrast, the SOC concentrations in the 0–30 cm mineral topsoil layer, especially in Luvisols afforested with coniferous species, showed an increasing trend due to the influence of stand age. The mean SOC values in the 0–30 cm mineral topsoil layer of Arenosols and Luvisols during the 30 years after afforestation did not significantly differ from the adjacent croplands or grasslands. The mean SOC stock slightly increased with the forest stand age in Luvisols; however, the highest mean SOC stock was detected in the grasslands. In the Arenosols, there was higher SOC accumulation in the forest floor with increasing stand age than in the Luvisols, while the proportion of SOC stocks in mineral topsoil layers was similar and more comparable to grasslands. These findings suggest encouragement of afforestation of former agricultural land under the current climate and soil characteristics in the region, but the conversion of perennial grasslands to forest land should be done with caution.

scholarly journals On the rebound: soil organic carbon stocks can bounce back to near forest levels when agroforests replace agriculture in southern India

2015 ◽  
Vol 2 (2) ◽  
pp. 871-902 ◽  
Author(s):  
H. C. Hombegowda ◽  
O. van Straaten ◽  
M. Köhler ◽  
D. Hölscher
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Tree Species ◽  
Regional Scale ◽  
Clay Fraction ◽  
Carbon Stocks ◽  
Southern India ◽  
Reference Plot ◽  
Soc Stock ◽  
Soc Stocks

Abstract. Tropical agroforestry has an enormous potential to sequester carbon while simultaneously producing agricultural yields and tree products. The amount of soil organic carbon (SOC) sequestered is however influenced by the type of the agroforestry system established, the soil and climatic conditions and management. In this regional scale study, we utilized a chronosequence approach to investigate how SOC stocks changed when the original forests are converted to agriculture, and then subsequently to four different agroforestry systems (AFSs): homegarden, coffee, coconut and mango. In total we established 224 plots in 56 plot clusters across four climate zones in southern India. Each plot cluster consisted of four plots: a natural forest reference plot, an agriculture reference and two of the same AFS types of two ages (30–60 years and > 60 years). The conversion of forest to agriculture resulted in a large loss the original SOC stock (50–61 %) in the top meter of soil depending on the climate zone. The establishment of homegarden and coffee AFSs on agriculture land caused SOC stocks to rebound to near forest levels, while in mango and coconut AFSs the SOC stock increased only slightly above the agriculture stock. The most important variable regulating SOC stocks and its changes was tree basal area, possibly indicative of organic matter inputs. Furthermore, climatic variables such as temperature and precipitation, and soil variables such as clay fraction and soil pH were likewise all important regulators of SOC and SOC stock changes. Lastly, we found a strong correlation between tree species diversity in homegarden and coffee AFSs and SOC stocks, highlighting possibilities to increase carbon stocks by proper tree species assemblies.

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