RESUMEN

To study the temporal and spatial distribution characteristics of soil organic carbon density in grassland and explore the relationship between organic carbon density and influencing factors is of great significance to the management and maintenance of grassland ecosystems in Gannan Autonomous Prefecture, which is conducive to realizing the goal of "double carbon," promoting carbon sink, and mitigating climate change. Taking Gannan Tibetan Autonomous Prefecture of Gansu Province as the research object, based on data from two CMIP6 future climate scenarios (SSP126 and SSP585), the CENTURY model was used to simulate and predict the temporal and spatial changes in soil organic carbon density in grassland of Gannan during 2023-2100. The main conclusions were as follows:① From 2023 to 2100, total organic carbon density, slow organic carbon density, and inert organic carbon density all showed a downward trend, whereas active organic carbon density fluctuated first and then increased. Meanwhile, the total organic carbon density, active organic carbon density, slow organic carbon density, and inert organic carbon density under the SSP585 scenario were higher than those under the SSP126 scenario. ② Mann-Kendall mutation analysis showed that the abrupt change in the difference of soil total organic carbon density (Δsomtc) occurred in 2030. The abrupt change in the difference of soil active carbon density (Δsom1c) occurred in 2027. ③ During the study period, the average soil organic carbon density of Gannan grassland was 7 505.69 g·m-2 under the SSP126 scenario and 7 551.87 g·m-2 under the SSP585 scenario. Gannan grassland soil organic carbon density was higher in the west and lower in the east, and the coefficient of variation was relatively stable. ④ The results of partial correlation analysis showed that precipitation was positively correlated with soil organic carbon density, whereas temperature was significantly negatively correlated with soil organic carbon density under future climate scenarios. ⑤ The results of the Theil-Sen Median trend analysis and Mann-Kendall test showed that under the two climate scenarios, the soil organic carbon density in Gannan showed an overall downward trend, in which Luqu County showed the fastest downward trend and Dibe County showed the slowest.

RESUMEN

Vegetation redistribution may bring unexpected climate-soil carbon cycling in terrestrial biomes. However, whether and how vegetation redistribution alters the soil carbon pool under climate change is still poorly understood on the Tibetan Plateau. Here, we applied the G-Range model to simulate the cover of herbs, shrubs and trees, net primary productivity (NPP) and soil organic carbon density (SOCD) at the depth of 60 cm on Tibetan Plateau for the individual years 2020 and 2060, using climate projection for Representative Concentration Pathways (RCP) 4.5 and RCP8.5 scenarios with the RegCM4.6 model system. Vegetation redistribution was defined as the transitions in bare ground, herbs, shrubs and trees between 2020 and 2060, with approximately 57.9 % (RCP4.5) and 59 % (RCP8.5) of the area will redistribute vegetation over the whole Tibetan Plateau. The vegetation cover will increase by about 2.4 % (RCP4.5) and 1.9 % (RCP8.5), while the NPP and SOCD will decrease by about -14.3 g C m-2 yr-1 and -907 g C m-2 (RCP4.5), and -1.8 g C m-2 yr-1and -920 g C m-2 (RCP8.5). Shrubs and trees will expand in the east, and herbs will expand in the northwest part of the Plateau. These areas are projected to be hotspots with greater SOCD reduction in response to future climate change, and will include lower net plant carbon input due to the negative NPP. Our study indicates that the SOC pool will become a carbon source under increased air temperature and rainfall on the Tibetan Plateau by 2060, especially for the area with vegetation redistribution. These results revealed the potential risk of vegetation redistribution under climate change in alpine ecosystems, indicating the policymakers need to pay attention on the vegetation redistribution to mitigate the soil carbon emission and achieve the goal of carbon neutrality on the Tibetan Plateau.

RESUMEN

The Qinghai-Tibet Plateau has low anthropogenic carbon emissions and large carbon stock in its ecosystems. As a crucial region in terrestrial ecosystems responding to climate change, an accurate understanding of the distribution characteristics of soil carbon density holds significance in estimating the soil carbon storage capacity in forests and grasslands. It performs a crucial role in achieving carbon neutrality goals in China. The distribution characteristics of carbon and carbon density in the surface, middle, and deep soil layers are calculated, and the main influencing factors of soil carbon density changes are analyzed. The carbon density in the surface soil ranges from a minimum of 1.62 kg/m2 to a maximum of 52.93 kg/m2. The coefficient of variation for carbon is 46%, indicating a considerable variability in carbon distribution across different regions. There are substantial disparities, with geological background, land use types, and soil types significantly influencing soil organic carbon density. Alpine meadow soil has the highest carbon density compared with other soil types. The distribution of soil organic carbon density at three different depths is as follows: grassland > bare land > forestland > water area. The grassland systems in the Qinghai-Tibet Plateau have considerable soil carbon sink and storage potential; however, they are confronted with the risk of grassland degradation. The grassland ecosystems on the Qinghai-Tibet Plateau harbor substantial soil carbon sinks and storage potential. However, they are at risk of grassland degradation. It is imperative to enhance grassland management, implement sustainable grazing practices, and prevent the deterioration of the grassland carbon reservoirs to mitigate the exacerbation of greenhouse gas emissions and global warming. This highlights the urgency of implementing more studies to uncover the potential of existing grassland ecological engineering projects for carbon sequestration.

Asunto(s)

RESUMEN

Gravel (>2 mm) is one of the main parameters for estimating soil carbon pool. To assess the effects of gravel on soil bulk density (BD) and organic carbon density (SOCD) in Pinus massoniana plantations, we estimated the BD and SOCD at the 0-10, 10-20 and 20-40 cm soil depths of 131 plots under two different conditions, with and without removing gravel. The BD of each soil layer after removing gravel was 0.58-1.57, 0.60-1.67, and 0.59-1.75 g·cm-3, respectively, which was significantly lower than that before removing gravel. Gravel increased the BD by 6.5%-6.8%. The SOCD of each soil layer before removing gravel was 8.93-65.97, 7.63-59.08, and 8.79-94.53 t·hm-2, respectively, which was higher than that after removing gravel. Overall, by neglecting the effect of gravel, SOCD was overestimated by 4.9%-11.8%. As gravel content increased, the relative deviation in the estimated BD and SOCD among different methods increased. When the gravel content was higher than 20%, the estimated SOCD at soil layer of 0-40 cm showed a significant difference between neglecting gravel and removing gravel, with the former being 29.7%-47.4% higher than the latter. In conclusion, gravel markedly affected the estimations of BD and SOCD. It was recommended that SOCD should be estimated by the method that not only uses the BD after removing gravel but also considers gravel as a correction factor (especially when gravel content is above 20.0%) to avoid overestimation of soil carbon pool.

Asunto(s)

RESUMEN

As the largest terrestrial carbon pool, the spatial distribution characteristics and influencing factors of soil organic carbon have important implications for global carbon cycle processes. Soil organic carbon density (SOCD) and influencing factors were predicted in the Yellow River basin using a mixed geographically weighted regression (MGWR) model based on soil organic carbon density data and environmental factors. The results showed that:① the SOCD ranged from 0-14.82 kg·m-2 and 0-32.39 kg·m-2 for the soil depths of 0-20 cm and 0-100 cm, with mean values of 3.48 kg·m-2 and 8.07 kg·m-2 and reserves of 2.76 Pg and 6.48 Pg, respectively. The high SOCD value areas were mainly located in the southern part of the Qinghai-Tibet Plateau and Loess Plateau, and the low value areas were located in the eastern part of the upper Yellow River and the inland flow area. ②Among the ecosystem types, the SOCD of soil depth in 0-20 cm was in the descending order of:forest>water body and wetland>other>grassland>farmland>settlement>desert, with mean values of 4.52, 4.31, 3.84, 3.73, 2.89, 2.78, and 2.22 kg·m-2, respectively, and the SOCD of the 0-100 cm soil depth was in the descending order of:water bodies and wetlands>forest>other>grassland>farmland>settlement>desert, with mean values of 9.58, 9.58, 8.85, 8.66, 7.07, 6.81, and 5.29 kg·m-2, respectively. The SOCR in descending order was:grassland>farmland>forest>desert>water bodies and wetlands>settlement>others, with 1.40, 0.60, 0.47, 0.11, 0.07, 0.06, and 0.05 Pg at a soil depth of 0-20 cm and 3.31, 1.49, 0.99, 0.26, 0.17, 0.14, and 0.12 Pg at a soil depth of 0-100 cm, respectively. ③ The main factors affecting the SOCD distribution were intercept, profile curvature, NDVI, and precipitation; in addition, curvature and silt also had important effects on the deep SOCD distribution in the Yellow River basin. Among the ecosystem types, precipitation and NDVI were the main factors affecting the SOCD distribution. The intercept also had important effects on the SOCD distribution in the all ecosystems except forests, whereas curvature and silt only had important effects on deserts and other ecosystems. These results revealed the spatial distribution of SOCD, influencing factors, and SOCR in the Yellow River basin and can provide a scientific basis for carbon balance, soil quality evaluation, and ecological management restoration and consolidation in the region.

RESUMEN

Deserts are important components of the terrestrial ecosystem, and significantly affect the terrestrial carbon cycle. However, their carbon storage is poorly understood. To evaluate the topsoil carbon storage in Chinese deserts, we systematically collected topsoil samples (to a depth of 10 cm) from 12 deserts in northern China and analyzed their organic carbon storage. We used partial correlation and boosted regression tree (BRT) analysis to analyze the factors influencing the spatial distribution of soil organic carbon density based on climate, vegetation, soil grain-size distribution, and element geochemistry. The total organic carbon pool of Chinese deserts was 4.83 × 108 t, the mean soil organic carbon density was 1.37 ± 0.18 kg C m-2, and the mean turnover time was 16.50 ± 2.66 yr. With the largest area, the Taklimakan Desert had the highest topsoil organic carbon storage (1.77 × 108 t). The organic carbon density was high in the east and low in the west, whereas the turnover time showed the opposite trend. The soil organic carbon density was >2 kg C m-2 in the four sandy lands in the eastern region, and was greater than the values for the eight deserts (0.72 to 1.22 kg C m-2). Grain-size (i.e., the silt and clay contents) had the strongest influence on the organic carbon density in Chinese deserts, followed by element geochemistry. Precipitation was the main climatic factor that affected the distribution of organic carbon density in the deserts. Based on climate and vegetation cover trends during the past 20 years, Chinese deserts have a high potential for future organic carbon sequestration.

RESUMEN

Using wastewaters in irrigated agriculture can cause heavy metal accumulation as well as salinity in soil. A practical way of minimizing accumulation in soil is to use irrigation techniques that require less water and consequently introduce less heavy metals into the feeding chain in silage maize cultivation with wastewater irrigation. The objective of this study is to address this issue. A factorial field experiment was carried out for two years in a completely randomized design with three replicates. Experimental plots were irrigated with three different irrigation methods (subsurface and surface drip, and furrow) applying three different levels (full irrigation and 33 and 67% deficit irrigations) of recycled wastewater and freshwater. The results showed that soil heavy metal contents, salinity, macro nutrients, organic matter, cation exchange capacity, porosity and wet aggregate stability were significantly higher in full irrigation with wastewater, while pH, carbonates, bulk and particle densities were significantly lower. Drip methods reduced salinity and heavy metal contents significantly. Heavy metal pollution indexes also indicated that drip methods are more effective in reducing metal pollution in soil. However, considerable accumulations of Cd and Ni were found with all methods while deficit irrigation decreased accumulations. The highest cation exchange capacity and K2O contents and the lowest exchangeable sodium percentage were determined with the subsurface drip method. The subsurface drip method saved 20.7 and 49% more irrigation water than the surface drip and furrow methods under fully irrigated conditions. Therefore, it can be concluded that using the subsurface drip method with recycled wastewater can be used in silage maize cultivation because soil productivity and water savings increased while metal pollution and salinity in soil decreased. Moreover, using 33% less wastewater can be a useful practice to decrease Cd and Ni accumulation.

Asunto(s)

RESUMEN

Cropland soil organic carbon density (SOCD) is an important indicator for measuring soil fertility and soil quality. To understand the spatial differentiation characteristics of cropland SOCD and its influencing factors across China, a dataset on the cropland SOCD of 19 typical stations during 2005-2015 was collected from the China Ecosystem Research Network. The geodetector method was used to analyze the influencing factors affecting the spatial patterns of cropland SOCD. The results indicated that the mean cropland SOCD ranged from 0.83 kg·m-2 to 4.97 kg·m-2 in different stations across China, and was higher in humid monsoon regions than in arid and semi-arid regions. Under different land use patterns, the SOCD of paddy fields was higher than that of other croplands and showed a tendency of significant increase from 2005 to 2015, reaching 0.13 kg·(m2·a)-1. The soil physical and chemical properties and precipitation were important influencing factors that affected the spatial patterns of cropland SOCD. In particular, the soil alkaline nitrogen content had the greatest impact on the cropland SOCD patterns. Furthermore, the interaction forces between the soil alkaline nitrogen content and latitude, soil type, precipitation, and soil pH were clearly strengthened. The findings can provide an important scientific basis for reducing cropland greenhouse gas emissions and increasing soil carbon sequestration across China.

RESUMEN

Accurate spatial distribution information of soil properties would be helpful for improving the accuracy of soil organic carbon storage estimation. In this study, terrain factors were used as predictors, and the fuzzy C-means (FCM) clustering method was used to make digital soil prediction mapping for soil organic carbon content, soil bulk density, soil depth, and soil gravel content in Nanshan forest farm in Jiyuan City of Henan Province. Based on the digital mapping results, the prediction mapping of soil organic carbon density and the estimation of soil organic carbon storage were realized. The results showed that the average soil organic carbon density in the study area based on the digital soil mapping method was 4.24 kg·m-2, the mean error (ME), mean absolute error (MAE) and root mean square error (RMSE) of the prediction map were 0.08, 2.80 and 5.03 kg·m-2, respectively. The accuracy, stability and reliability of the prediction results were higher than the tradiation methods. The soil organic carbon storage in the study area was estimated to be 3.08×108 kg. Based on the digital soil mapping technology, only a small number of soil samples could be used to map and estimate the soil organic carbon density with high accuracy, which could characterize the spatial distribution characteristics of soil organic carbon density. This study provided a new way to estimate soil organic carbon storage, which would help to improve the accuracy and efficiency of soil organic carbon storage estimation.

Asunto(s)

RESUMEN

The accurate mapping of farmland soil organic carbon density (SOCD) is crucial for evaluating carbon (C) sequestration potential and forecasting climate change. Natural factors such as soil types and topographical factors are important variables in mapping soil properties. Moreover, cropping systems are important components of agricultural activities and are significantly correlated with soil properties. Therefore, integrating cropping systems and natural factors can improve the accuracy of mapping farmland SOCD. This study aimed to obtain and incorporate cropping system information in mapping SOCD in plains by combining normalized difference vegetation index (NDVI) time-series data and the regression Kriging (RK) method. We collected 230 topsoil samples in Jianghan Plain, China and (i) obtained the spatial patterns of crops in summer and winter using NDVI time-series data derived from HJ-1A/1B satellite images, (ii) investigated the differences in SOCD under different cropping systems, and (iii) evaluated the performance of the RK_CS model in integrating cropping systems and natural factors into mapping SOCD. ANOVA results showed significant differences in SOCD under different cropping systems. Specifically, the SOCD of single rice was higher than that of rice-wheat rotation and dry crops. Meanwhile, the regression results showed that SOCD was affected by natural factors and cropping system, with the latter playing a major role. The integration of soil types, slope and cropping systems explained approximately 26.3% of the variation in SOCD. Model validation results confirmed the effectiveness of the RK_CS model. The findings reveal single cropping rice sequences more C than other cropping systems. Cropping system is an important environmental variable in improving mapping farmland SOCD in plains.

RESUMEN

Soil organic carbon pool is an important component of terrestrial carbon pool. Soil organic carbon pool and its dynamic change have important influence on carbon cycle in terrestrial ecosystem. Soil organic carbon density (SOCD) is an important parameter of soil carbon storage, and it is also an important index to evaluate farmland soil quality. Accurate prediction of regional organic carbon density spatial distribution is of great significance to the development of precision agriculture. A total of 242 farmland soil samples collected from the Jianghan Plain were used to explore the effects of land use types on the spatial distribution of SOCD in plain areas. Moreover, in the presence of spatial heterogeneity and spatial outliers of SOCD, three Kriging approaches combining land use types were used for the spatial prediction of SOCD. They were dummy variable regression Kriging (DV_RK), mean centering ordinary Kriging (MC_OK1) and median centering ordinary Kriging (MC_OK2). Results showed that the difference of land use types between paddy field and irrigable land was one of the reasons for the spatial heterogeneity of SOCD in the study area, resulting in spatial non-stationary characteristics of SOCD and lowering the performance of OK. DV_RK, MC_OK1 and MC_OK2, however, eliminating the impacts of SOCD spatialheterogeneity caused by land use types while modeling, enhancing the model stability. Therefore, the prediction accuracy of these three models was higher than that of ordinary Kriging (OK). Moreover, MC_OK2 outperformed the others in terms of model reliability, prediction accuracy and the ability to explain the total variance of SOCD. In summary, as an easily accessed auxiliary variable, land use type could effectively decrease the effects of spatial heterogeneity and spatial outliers on SOCD spatial interpolation model, improving the prediction performance and reducing the model uncertainty. SOCD map with higher quality could also be achieved to help reveal the spatial characteristics of SOCD for guiding the agricultural production.

Asunto(s)

RESUMEN

BACKGROUND: Soil organic carbon (SOC) is fundamental for mitigating climate change as well as improving soil fertility. Databases of SOC obtained from soil surveys in 1981 and 2011 were used to assess SOC change (0-20 cm) in croplands of Heilongjiang Province in northeast China. Three counties (Lindian, Hailun and Baoqing) were selected as typical croplands representing major soil types and land use types in the region. RESULTS: The changes in SOC density (SOCD) between 1981 and 2001 were -6.6, -14.7 and 5.7 Mg C ha(-1) in Lindian, Hailun and Baoqing Counties respectively. The total SOC storage (SOCS) changes were estimated to be -11.3, -19.1 and 16.5% of those in 1981 in the respective counties. The results showed 22-550% increases in SOCS in rice (Oryza sativa L.) paddies in the three counties, but 28-33% decreases in dry cropland in Lindian and Hailun Counties. In addition, an increase of 11.4 Mg C ha(-1) in SOCD was observed in state-owned farms (P < 0.05), whereas no significant change was observed in family-owned farms. CONCLUSION: Soil C:N ratio and initial SOCD related to soil groups were important determinants of SOCD changes. Land use and residue returning greatly affected SOC changes in the study region. To increase the topsoil SOCD, the results suggest the conversion of dry croplands to rice paddies and returning of crop residue to soils.

Asunto(s)