Temporal and Spatial Changes of Soil Organic Carbon Stocks in the Forest Area of Northeastern China

Forest soil organic carbon (SOC) accounts for a large portion of global soil carbon stocks. Accurately mapping forest SOC stocks is a necessity for quantifying forest carbon cycling and forest soil sustainable management. In this study, we used a boosted regression trees (BRT) model to predict the spatial distribution of SOC stocks during two time periods (1990 and 2015) and calculated their spatiotemporal changes during 25 years in Liaoning Province, China. A total of 367 (1990) and 539 (2015) sampling sites and 9 environmental variables (climate, topography, remote sensing) were used in the BRT model. The ten-fold cross-validation technique was used to evaluate the prediction performance and uncertainty of the BRT model in two periods. It was found that the BRT model could account for 65% and 59% of SOC stocks, respectively for the two periods. MAP and NDVI were the main environmental variables controlling the spatial variability of SOC stocks. Over the 25-year period, the average SOC stocks increased from 5.66 to 6.61 kg m−2. In the whole study area, the SOC stocks were the highest in the northeast, followed by the southwest, and the lowest in the middle of the spatial distribution pattern in the two periods. Our accurate mapping of SOC stocks, their spatial distribution characteristics, influencing factors, and main controlling factors in forest areas will assist soil management and help assess environmental changes in the region.

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Soil organic carbon stocks in the Limpopo National Park, Mozambique: Amount, spatial distribution and uncertainty

Geoderma ◽

10.1016/j.geoderma.2013.07.015 ◽

2014 ◽

Vol 213 ◽

pp. 46-56 ◽

Cited By ~ 34

Author(s):

A.H. Cambule ◽

D.G. Rossiter ◽

J.J. Stoorvogel ◽

E.M.A. Smaling

Keyword(s):

Spatial Distribution ◽

Organic Carbon ◽

Soil Organic Carbon ◽

National Park ◽

Carbon Stocks ◽

Soil Organic Carbon Stocks

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Biochar Effects on Carbon Stocks in the Coffee Agroforestry Systems of the Himalayas

Sustainable Agriculture Research ◽

10.5539/sar.v7n4p103 ◽

2018 ◽

Vol 7 (4) ◽

pp. 103 ◽

Cited By ~ 1

Author(s):

Ngamindra Dahal ◽

Roshan Man Bajracharya ◽

Lal Mani Wagle

Keyword(s):

Organic Carbon ◽

Soil Organic Carbon ◽

Low Income ◽

Smallholder Farmers ◽

Carbon Stocks ◽

Agricultural Practice ◽

Coffee Agroforestry ◽

Incremental Change ◽

C Stocks ◽

Soc Stocks

Coffee agroforestry is an emerging agricultural practice in the mid hills of Nepal. Smallholder farmers of low-income strata have progressively adopted coffee as a perennial crop over seasonal crops. A multi-year study was conducted to test effects of locally produced biochar derived from coffee wastes, e.g., pulp and husks, on carbon stocks of: i) coffee trees, and, ii) soil organic carbon (SOC) in selected coffee growing pockets. We conducted on-farm experimental trials in three different physiographical locations of the Nepal mid-hills, namely, Chandanpur (Site I at 1475masl), Panchkhal (Site II at 1075masl), and Talamarang (Site III at 821masl) where smallholders grow coffee together with other cereal crops and vegetables. We applied biochar to the soil at a rate of 5 Mgha-1, then, monitored the SOC and biomass growth of the coffee trees in the three treatment plots at sites I, II and III over two years beginning in 2013. The average stocks of aboveground carbon in coffee trees increased from 6.2±4.3 Mgha-1 to 9.1±5.2 Mgha-1 over the trial period of two years in biochar treated plots. The same in control plots increased from 5.6±2.8 Mgha-1 to 6.7±4.7 Mgha-1. In the biochar plots, the average increments of ABG carbon was 0.73 Mgh-1 while in the control it was 0.29 Mgh-1. Analysis of soil organic carbon of the plots indicated overall incremental change in carbon stocks in the coffee farms. During the base year, the average SOC stocks in the top 0-15cm layer of the soil at sites I, II, and III were estimated 74.88 ± 15.93; 63.96 ±16.71 and 33.05 ±4.42 Mgha-1 respectively. Although both the biochar treated and control plot registered incremental change in SOC stocks, the volumes were remarkably higher in the former than the latter. Compared to the baseline data, the changes in SOC stocks in the three biochar treated plots were 19.8, 49.8 and 45.3 Mgha-1, respectively, whereas in the control plots these were 8.3, 29.3 and 11.3 Mgha-1, respectively. The higher incremental rates of C-stocks in all the biochar treated plots in comparison to the corresponding control plots of the coffee agroforestry implies that application of biochar can enhance accumulation of carbon in the form of aboveground biomass and soil organic carbon.

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

SOIL Discussions ◽

10.5194/soild-2-871-2015 ◽

2015 ◽

Vol 2 (2) ◽

pp. 871-902 ◽

Cited By ~ 3

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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Spatial distribution of soil organic carbon stocks in Masson pine (Pinus massoniana) forests in subtropical China

CATENA ◽

10.1016/j.catena.2019.03.004 ◽

2019 ◽

Vol 178 ◽

pp. 189-198 ◽

Cited By ~ 9

Author(s):

Xiong Yao ◽

Kunyong Yu ◽

Yangbo Deng ◽

Qi Zeng ◽

Zhuangjie Lai ◽

...

Keyword(s):

Spatial Distribution ◽

Organic Carbon ◽

Soil Organic Carbon ◽

Pinus Massoniana ◽

Carbon Stocks ◽

Subtropical China ◽

Masson Pine ◽

Soil Organic Carbon Stocks

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Spatial modelling of soil organic carbon stocks with combined principal component analysis and geographically weighted regression

The Journal of Agricultural Science ◽

10.1017/s0021859618000709 ◽

2018 ◽

Vol 156 (6) ◽

pp. 774-784 ◽

Cited By ~ 2

Author(s):

Long Guo ◽

Mei Luo ◽

Chengsi Zhangyang ◽

Chen Zeng ◽

Shanqin Wang ◽

...

Keyword(s):

Principal Component Analysis ◽

Organic Carbon ◽

Soil Organic Carbon ◽

Geographically Weighted Regression ◽

Environmental Variables ◽

Prediction Models ◽

Principal Component ◽

Weighted Regression ◽

Auxiliary Variables ◽

Soc Stocks

AbstractWith the development of remote sensing and geostatistical technology, complex environmental variables are increasingly easily quantified and applied in modelling soil organic carbon (SOC). However, this emphasizes data redundancy and multicollinearity problems adding to the difficulty in selecting dominant influential auxiliary variables and uncertainty in estimating SOC stocks. The current paper considers the spatial characteristics of SOC density (SOCD) to construct prediction models of SOCD on the basis of reducing the data dimensionality and complexity using the principal component analysis (PCA) method. A total of 260 topsoil samples were collected from Chahe town, China. Eight environmental variables (elevation, aspect, slope, normalized difference vegetation index, normalized difference moisture index, nearest distance to construction area and road, and land use degree comprehensive index) were pre-analysed by PCA and then extracted as the main principal component variables to construct prediction models. Two geostatistical approaches (ordinary kriging and ordinary co-kriging) and two regression approaches (ordinary least squares and geographically weighted regression (GWR)) were used to estimate SOCD. Results showed that PCA played an important role in reducing the redundancy and multicollinearity of the auxiliary variables and GWR achieved the highest prediction accuracy in these four models. GWR considered not only the spatial characteristics of SOCD but also the related valuable information of the auxiliary attributes. In summary, PCA-GWR is a promising spatial method used here to predict SOC stocks.

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Soil Organic Carbon Depletion from Forests to Grasslands Conversion in Mexico: A Review

Agriculture ◽

10.3390/agriculture8110181 ◽

2018 ◽

Vol 8 (11) ◽

pp. 181 ◽

Cited By ~ 6

Author(s):

Deb Aryal ◽

Danilo Morales Ruiz ◽

César Tondopó Marroquín ◽

René Pinto Ruiz ◽

Francisco Guevara Hernández ◽

...

Keyword(s):

Land Use ◽

Organic Carbon ◽

Land Use Change ◽

Soil Organic Carbon ◽

Tropical Forests ◽

Soil Depth ◽

Carbon Stocks ◽

Soil Horizon ◽

Native Forests ◽

Soc Stocks

Land use change from forests to grazing lands is one of the important sources of greenhouse gas emissions in many parts of the tropics. The objective of this study was to analyze the extent of soil organic carbon (SOC) loss from the conversion of native forests to pasturelands in Mexico. We analyzed 66 sets of published research data with simultaneous measurements of soil organic carbon stocks between native forests and pasturelands in Mexico. We used a generalized linear mixed effect model to evaluate the effect of land use change (forest versus pasture), soil depth, and original native forest types. The model showed that there was a significant reduction in SOC stocks due to the conversion of native forests to pasturelands. The median loss of SOC ranged from 31.6% to 52.0% depending upon the soil depth. The highest loss was observed in tropical mangrove forests followed by highland tropical forests and humid tropical forests. Higher loss was detected in upper soil horizon (0–30 cm) compared to deeper horizons. The emissions of CO2 from SOC loss ranged from 46.7 to 165.5 Mg CO2 eq. ha−1 depending upon the type of original native forests. In this paper, we also discuss the effect that agroforestry practices such as silvopastoral arrangements and other management practices like rotational grazing, soil erosion control, and soil nutrient management can have in enhancing SOC stocks in tropical grasslands. The results on the degree of carbon loss can have strong implications in adopting appropriate management decisions that recover or retain carbon stocks in biomass and soils of tropical livestock production systems.

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Evaluation of modelling approaches for predicting the spatial distribution of soil organic carbon stocks at the national scale

Geoderma ◽

10.1016/j.geoderma.2014.01.005 ◽

2014 ◽

Vol 223-225 ◽

pp. 97-107 ◽

Cited By ~ 60

Author(s):

M.P. Martin ◽

T.G. Orton ◽

E. Lacarce ◽

J. Meersmans ◽

N.P.A. Saby ◽

...

Keyword(s):

Spatial Distribution ◽

Organic Carbon ◽

Soil Organic Carbon ◽

Carbon Stocks ◽

National Scale ◽

Soil Organic Carbon Stocks ◽

Modelling Approaches

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Spatial-Temporal Changes in Soil Organic Carbon and pH in the Liaoning Province of China: A Modeling Analysis Based on Observational Data

Sustainability ◽

10.3390/su11133569 ◽

2019 ◽

Vol 11 (13) ◽

pp. 3569 ◽

Cited By ~ 4

Author(s):

Li Qi ◽

Shuai Wang ◽

Qianlai Zhuang ◽

Zijiao Yang ◽

Shubin Bai ◽

...

Keyword(s):

Land Use ◽

Organic Carbon ◽

Soil Organic Carbon ◽

Environmental Variables ◽

Spatial Variations ◽

Liaoning Province ◽

Mean Annual Precipitation ◽

Topographic Wetness Index ◽

Infrared Band ◽

Wetness Index

Quantification of soil organic carbon (SOC) and pH, and their spatial variations at regional scales, is a foundation to adequately assess agriculture, pollution control, or environmental health and ecosystem functioning, so as to establish better practices for land use and land management. In this study, we used the random forest (RF) model to map the distribution of SOC and pH in the topsoil (0–20 cm) and estimate SOC and pH changes from 1982 to 2012 in Liaoning Province, Northeast China. A total of 10 covariates (elevation, slope gradient, topographic wetness index (TWI), mean annual temperature (MAT), mean annual precipitation (MAP), visible-red band 3 (B3), near-infrared band 4 (B4), short-wave infrared band 5 (B5), normalized difference vegetation index (NDVI), and land-use data) and a set of 806 (in 1982) and 973 (in 2012) soil samples were selected. Cross-validation technology was used to test the performance and uncertainty of the RF model. We found that the prediction R2 of SOC and pH was 0.69 and 0.54 for 1982, and 0.63 and 0.48 for 2012, respectively. Elevation, NDVI, and land use are the main environmental variables affecting the spatial variability of SOC in both periods. Correspondingly, the topographic wetness index and mean annual precipitation were the two most critical environmental variables affecting the spatial variation of pH. The mean SOC and pH decreased from 18.6 to 16.9 kg−1 and 6.9 to 6.6, respectively, over a 30-year period. SOC distribution generated using the RF model showed a decreasing SOC trend from east to west across the city in the two periods. In contrast, the spatial distribution of pH showed an opposite trend in both periods. This study provided important information of spatial variations in SOC and pH to agencies and communities in this region, to evaluate soil quality and make decisions on remediation and prevention of soil acidification and salinization.

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Impacts of fire on soil organic carbon stocks in a grazed semi-arid tropical Australian savanna: accounting for landscape variability

The Rangeland Journal ◽

10.1071/rj14044 ◽

2014 ◽

Vol 36 (4) ◽

pp. 359 ◽

Cited By ~ 7

Author(s):

D. E. Allen ◽

P. M. Bloesch ◽

R. A. Cowley ◽

T. G. Orton ◽

J. E. Payne ◽

...

Keyword(s):

Organic Carbon ◽

Soil Organic Carbon ◽

Spatial Variability ◽

Management Practices ◽

Soil Depth ◽

Carbon Stocks ◽

Soil Organic Carbon Stocks ◽

Semi Arid ◽

Soc Stocks

Fire and grazing are commonplace in Australian tropical savannas and the effects of these management practices on soil organic carbon stocks (SOC) is not well understood. A long-term (20 years) experiment studying the effects of fire on a grazed semi-arid tropical savanna was used to increase this understanding. Treatments, including frequency of fire (every 2, 4 and 6 years), season of fire [early (June) vs late (October) dry season] and unburnt control plots, were imposed on Vertosol grassland and Calcarosol woodland sites, which were grazed. Additionally long-term enclosures [unburnt (except the Calcarosol in 2001) and ungrazed since 1973] on each soil type adjacent to each site were sampled, although not included in statistical analyses. SOC stocks were measured to a soil depth of 0.3 m using a wet oxidation method (to avoid interference by carbonates) and compared on an equivalent soil mass basis. Significant treatment differences in SOC stocks were tested for, while accounting for spatial background variation within each site. SOC stocks (0–0.3 m soil depth) ranged between 10.1 and 28.9 t ha–1 (Vertosol site) and 20.7 and 54.9 t ha–1 (Calcarosol site). There were no consistent effects of frequency or season of fire on SOC stocks, possibly reflecting the limited statistical power of the study and inherent spatial variability observed. Differences in the response to frequency and season of fire observed between these soils may have been due to differences in clay type, plant species composition and/or preferential grazing activity associated with fire management. There may also have been differences in C input between treatments and sites due to differences in the herbage mass and post-fire grazing activity on both sites and changed pasture composition, higher herbage fuel load, and a reduction in woody cover on the Vertosol site. This study demonstrated the importance of accounting for background spatial variability and treatment replication (in the absence of baseline values) when assessing SOC stocks in relation to management practices. Given the absence of baseline SOC values and the potentially long period required to obtain changes in SOC in rangelands, modelling of turnover of SOC in relation to background spatial variability would enable management scenarios to be considered in relation to landscape variation that may be unrelated to management. These considerations are important for reducing uncertainty in C-flux accounting and to provide accurate and cost-effective methods for land managers considering participation in the C economy.

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