National Soil Organic Carbon Stocks Inventories under Different Mangrove Forest Types in Gabon

Gabonese’s estuary is an important coastal mangrove setting and soil plays a key role in mangrove carbon storage in mangrove forests. However, the spatial variation in soil organic carbon (SOC) storage remain unclear. To address this gap, determining the SOC spatial variation in Gabonese’s estuarine is essential for better understanding the global carbon cycle. The present study compared soil organic carbon between northern and southern sites in different mangrove forest, Rhizophora racemosa and Avicennia germinans. The results showed that the mean SOC stocks at 1 m depth were 256.28 ± 127.29 MgC ha−1. Among the different regions, SOC in northern zone was significantly (p p < 0.001). The deeper layers contained higher SOC stocks (254.62 ± 128.09 MgC ha−1) than upper layers (55.42 ± 25.37 MgC ha−1). The study highlights that low deforestation rate have led to less CO2 (705.3 Mg CO2e ha−1 - 922.62 Mg CO2e ha−1) emissions than most sediment carbon-rich mangroves in the world. These results highlight the influence of soil texture and mangrove forest types on the mangrove SOC stocks. The first national comparison of soil organic carbon stocks between mangroves and upland tropical forests indicated SOC stocks were two times more in mangroves soils (51.21 ± 45.00 MgC ha−1) than primary (20.33 ± 12.7 MgC ha−1), savanna and cropland (21.71 ± 15.10 MgC ha−1). We find that mangroves in this study emit lower dioxide-carbon equivalent emissions. This study highlights the importance of national inventories of soil organic carbon and can be used as a baseline on the role of mangroves in carbon sequestration and climate change mitigation but the variation in SOC stocks indicates the need for further national data.

Mapping Soil Organic Carbon Stocks of Northeastern China Using Expert Knowledge and GIS-based Methods

The main aim of this paper was to calculate soil organic carbon stock(SOCS) with consideration of the pedogenetic horizons using expert knowledge and GIS-based methods in northeastern China.A novel prediction process was presented and was referred to as model-then-calculate with respect to the variable thicknesses of soil horizons(MCV).The model-then-calculate with fixed-thickness(MCF),soil profile statistics(SPS),pedological professional knowledge-based(PKB) and vegetation type-based(Veg) methods were carried out for comparison.With respect to the similar pedological information,nine common layers from topsoil to bedrock were grouped in the MCV.Validation results suggested that the MCV method generated better performance than the other methods considered.For the comparison of polygon based approaches,the Veg method generated better accuracy than both SPS and PKB,as limited soil data were incorporated.Additional prediction of the pedogenetic horizons within MCV benefitted the regional SOCS estimation and provided information for future soil classification and understanding of soil functions.The intermediate product,that is,horizon thickness maps were fluctuant enough and reflected many details in space.The linear mixed model indicated that mean annual air temperature(MAAT) was the most important predictor for the SOCS simulation.The minimal residual of the linear mixed models was achieved in the vegetation type-based model,whereas the maximal residual was fitted in the soil type-based model.About 95% of SOCS could be found in Argosols,Cambosols and Isohumosols.The largest SOCS was found in the croplands with vegetation of Triticum aestivum L.,Sorghum bicolor(L.) Moench,Glycine max(L.) Merr.,Zea mays L.and Setaria italica(L.) P.Beauv.

Spatial-temporal variations and driving factors of soil organic carbon in forest ecosystems of Northeast China

Forest soil carbon is a major carbon pool of terrestrial ecosystems,and accurate estimation of soil organic carbon(SOC)stocks in forest ecosystems is rather challenging.This study compared the prediction performance of three empirical model approaches namely,regression kriging(RK),multiple stepwise regression(MSR),random forest(RF),and boosted regression trees(BRT)to predict SOC stocks in Northeast China for 1990 and 2015.Furthermore,the spatial variation of SOC stocks and the main controlling environmental factors during the past 25 years were identified.A total of 82(in 1990)and 157(in 2015)topsoil(0–20 cm)samples with 12 environmental factors(soil property,climate,topography and biology)were selected for model construction.Randomly selected80%of the soil sample data were used to train the models and the other 20%data for model verification using mean absolute error,root mean square error,coefficient of determination and Lin's consistency correlation coefficient indices.We found BRT model as the best prediction model and it could explain 67%and 60%spatial variation of SOC stocks,in 1990,and 2015,respectively.Predicted maps of all models in both periods showed similar spatial distribution characteristics,with the lower SOC in northeast and higher SOC in southwest.Mean annual temperature and elevation were the key environmental factors influencing the spatial variation of SOC stock in both periods.SOC stocks were mainly stored under Cambosols,Gleyosols and Isohumosols,accounting for 95.6%(1990)and 95.9%(2015).Overall,SOC stocks increased by 471 Tg C during the past 25 years.Our study found that the BRT model employing common environmental factors was the most robust method for forest topsoil SOC stocks inventories.The spatial resolution of BRT model enabled us to pinpoint in which areas of Northeast China that new forest tree planting would be most effective for enhancing forest C stocks.Overall,our approach is likely to be useful in forestry management and ecological restoration at and beyond the regional scale.

Soil Organic Carbon Stock and Soil Quality under Four Major Agroecosystems in the Eastern Flank of Mount Bambouto (West-Cameroon)

Assessing soil organic carbon stock (SOCS) and soil quality (SQ) helps design better agricultural practices to improve environmental sustainability and productivity. The purpose of the study is to assess SOCS and soil quality SQ in the main agroecosystems (AES) of the eastern flank of Mount Bambouto (West, Cameroon). Using multiple statistics tests and principal component analysis (PCA), SOCS and Soil Quality Index (SQI) were computed for each AES. SOCS and SQI were computed based on soil chemical properties and analysis of variance. Topsoil samples (0 - 30 cm) were collected in a different AES and analyzed in the laboratory. The four AES identified and selected are cultivated land (CL), forest areas (FA), mixed areas (MA), and bush areas (BA). Further, multiple comparison tests were used to compare soils from different AES. PCA was used to select the most appropriate indicators that control SOCS and SQ. Several soil properties showed high to very high coefficient of variation within the AES. Organic matter (OM) was significantly high in FA. SOCS and SQ differ significantly (p = 0.000) between the AES. The study further indicates that the main variables controlling SQ within the eastern flank of Mount Bambouto are OM, pHw, N, C/N, and CEC. While the main soil parameters controlling SOCS are OM, OC, BD, C/N, S, and pHKCl.

Soil Organic Carbon Stock as Affected by Land Use/Cover Changes in the Humid Region of Northern Iran

【Title】【Author】This study was conducted to determine the changes in the soil carbon stocks as influenced by land use in a humid zone of Deylaman district （10,876 ha）, a mountainous region of northern Iran. For this, land use maps were produced from TM and ETM＋ images for 1985, 2000 and 2010 years; and this was supplemented by field measurement of soil carbon in 2010. The results showed that the mean soil organic carbon （SOC） density was 6.7±1.8 kg C m-2, 5.2±3.4 kg C m-2 and 3.2±1.8 kg C m-2 for 0-20 cm soil layer and 4.8±1.9 kg C m-2, 3.1±2 kg C m-2 and 2.7±1.8 kg C m-2 for 20-40 cm soil layer in forest, rangeland and cultivated land, respectively. During the past 25 years, 14.4% of the forest area had been converted to rangeland; and 28.4% of rangelands had been converted to cultivated land. According to the historical land use changes in the study area, the highest loss of SOC stocks resulted from the conversion of the forest to rangeland （0.45×104 Mg C in 0-40 cm depth layer）; and the conversion of rangeland to cultivated land （0.37×104 Mg C in 0-40 cm）, which typically led to the loss of soil carbon in the area studied. The knowledge on the historical land use changes and its influence on overall SOC stocks could be helpful for making management decision for farmers and policy managers in the future, for enhancing the potential of C sequestration in northern Iran.

Above and below ground organic carbon stocks in a sub-tropical Pinus roxburghii Sargent forest of the Garhwal Himalayas

Accurate estimates of tree carbon, forest floor carbon and organic carbon in forest soils （SOC） are important in order to determine their contribution to global carbon （C） stocks. However, information about these carbon stocks is lacking. Some studies have investigated regional and continental scale patterns of carbon stocks in forest ecosystems; however, the changes in C storage in dif- ferent components （vegetation, forest floor and soil） as a function of elevation in forest ecosystems remain poorly understood. In this study, we estimate C stocks of vegetation, forest floor and soils of a Pinus roxburghii Sargent forest in the Garhwal Himalayas along a gradient to quantify changes in carbon stock due to differences in elevation at three sites. The biomass of the vegetation changes drastically with increasing elevation among the three sites. The above-ground biomass （AGB） and below-ground biomass （BGB） were highest at site I （184.46 and 46.386 t·ha^-1 respectively） at an elevation of 1300 m followed by site II （173.99 and 44.057 t·ha^-1 AGB and BGB respectively） at 1400 m and the lowest AGB and BGB were estimated at site III （161.72 and 41.301t·ha^-1） at 1500 m. The trend for SOC stock was similar to that of biomass. Our results suggest that carbon storage （in both soil and biomass） is nega- tively correlated with elevation.

Fractionation of Organic Carbon and Stock Measurement in the Sundarbans Mangrove Soils of Bangladesh

Mangrove soils are well known for their high capacity of storing organic carbon (SOC) in various pools;however, a relatively small change in SOC pools could cause significant impacts on greenhouse gas concentrations. Thus, for an in-depth understanding of SOC distribution and stock to predict the role of Sundarbans mangrove in mitigating global warming and greenhouse effects, different extraction methods were employed to fractionate the SOC of Sundarbans soils into cold-water (CWSC) and hot-water (HWSC) soluble, moderately labile (MLF), microbial biomass carbon (MBC), and resistant fractions (RF) using a newly developed modified-method. A significant variation in total SOC (p < 0.001), SOC stock (p < 0.001) and soil bulk density (p < 0.05) at the Sundarbans mangrove forest were observed. In most soils, bulk density increased from the surface to 100 cm depth. The total SOC concentrations were higher in most surface soils and ranged from 1.21% ± 0.02% to 8.19% ± 0.09%. However, C in lower layers may be more resistant than that of upper soils because of differences in compositions, sources and environmental conditions. SOC was predominately associated with the resistant fraction (81% - 97%), followed by MLF (2% - 10%), HWSC (1% - 4%), MBC (~0% - 4%), and CWSC (~0% - 3%). The significant positive correlations between different C fractions suggested that C pools are interdependent and need proper management plans to increase these pools in Sundarbans soils. The SOC stock of the studied areas ranged between 16.75 ± 3.83 to 135.12 ± 28.61 kg·C·m−2 in 1 m soil profile and has an average of 31.80 kg·C·m−2. The substratum soils had more carbon than the upper layers in the Sundarbans wetland due to burial and preservation of carbon by frequent tidal inundation. A higher SOC stock in the soil profile and its primary association in resistant fractions suggested that Sundarbans mangrove soil is sequestering carbon and thereby serving as a significant carbon sink in Bangladesh.

The efficiency of long-term straw return to sequester organic carbon in Northeast China＇s cropland

Black soil is one of the most precious soil resources on earth because it has abundant carbon stocks and a relatively high production capacity. However, decreasing organic matter after land reclamation, and the effects of long-term inputs of organic carbon have made it less fertile black soil in Northeast China. Straw return could be an effective method for improving soil organic carbon（SOC） sequestration in black soils. The objective of this study was to evaluate whether straw return effectively increases SOC sequestration. Long-term field experiments were conducted at three sites in Northeast China with varying latitudes and SOC densities. Study plots were subjected to three treatments： no fertilization（CK）; inorganic fertilization（NPK）; and NPK plus straw return（NPKS）. The results showed that the SOC stocks resulting from NPKS treatment were 4.0 and 5.7% higher than those from NPK treatment at two sites, but straw return did not significantly affect the SOC stocks at the third site. Furthermore, at higher SOC densities, the NPKS treatment resulted in significantly higher soil carbon sequestration rates（CSR） than the NPK treatment. The equilibrium value of the CSR for the NPKS treatment equated to cultivation times of 17, 11, and 8 years at the different sites. Straw return did not significantly increase the SOC stocks in regions with low SOC densities, but did enhance the C pool in regions with high SOC densities. These results show that there is strong regional variation in the effects of straw return on the SOC stocks in black soil in Northeast China. Additional cultivations and fertilization practices should be used when straw return is considered as an approach for the long-term improvement of the soil organic carbon pool.