Search Results (15)

Globally, arid and semi-arid agricultural land is characterized by low soil organic carbon (SOC) content. This impacts on the abundance and diversity of soil microorganisms in such environments. We therefore examined SOC and bacterial community structure dynamics in the single plots of the conventional (PC), improved fertilization (PA) and unimproved control (PT) at El Hmadna experimental station (Northwest Algeria) during five-time intervals T(0), T(15), T(70), T(104) and T(147 days). The SOC content was determined using the modified Walkley and Black method. The 16S rRNA genes were isolated from soils and sequenced using the Illumina sequencing platform. Over time, OC levels increased by more than 15%, especially in the improved plot. The highest OC stock was observed for the unmanaged control plot (47 Mg ha⁻¹), also associated with higher bacterial biomass. However, taxonomic analysis revealed that bacterial diversity was higher in PA and PC, with Actinobacteria (42%) and Firmicutes (15%) dominating. Soil salinity did negatively influence SOC but the imposed management practices such as organic amendments did improve both carbon retention and bacterial diversity. The results underline the importance of imposing sustainable agricultural practices to improve carbon sequestration and soil health in semi-arid regions. Full article

Urban green spaces are increasingly recognized for their potential to mitigate climate change by reducing atmospheric concentrations of greenhouse gases, especially carbon dioxide (CO₂). However, enhancing carbon sequestration efficiency in limited urban green areas remains a significant challenge for sustainable urban planning. Trees are among the most cost-effective and efficient natural carbon sinks, surpassing other types of land cover in terms CO₂ absorption and storage. The present study aimed to evaluate the carbon sequestration potential of four native tree species, Pongamia pinnata, Azadirachta indica, Melia azedarach, and Dalbergia sissoo, in urban parks across Multan City, Pakistan. A total of 456 trees of selected species within six parks of Multan City were inventoried to estimate the biomass and carbon stock using species-specific allometric equations. Soil organic carbon at two soil depths beneath the canopy of each tree was also estimated using Walkley–Black method. The findings revealed that the highest mean tree biomass (2.16 Mg ha⁻¹), carbon stock (1.04 Mg ha⁻¹) and carbon sequestration (3.80 Mg ha⁻¹) were estimated for Dalbergia sissoo, while Melia azedarach exhibited the lowest (0.12 Mg ha⁻¹, 0.06 Mg ha⁻¹ & 0.23 Mg ha⁻¹, respectively) across all six parks. The soil carbon stocks ranged from 48.86 Mg ha⁻¹ to 61.68 Mg ha⁻¹ across all study sites. These findings emphasize the importance of species selection in urban green planning for carbon sequestration. Strategic planting of effective native trees like Dalbergia sissoo can mitigate climate change and provide urban forest ecosystem services. Full article

Disentangling the responses of total soil organic carbon (SOC), organic carbon fractions and soil aggregate stability to various vegetation types is essential for better understanding the carbon cycling process in terrestrial ecosystems, maintaining soil quality and mitigating global warming. To study the effects of vegetation types on soil aggregates in a specific area, the desert riverbanks of arid regions were studied. We set up experiments using three typical vegetation types in the arid zone of the Tarim River Basin (TRB), including Forestland, Shrubland, and Grassland. The total SOC content in the bulk soil and different soil aggregates was determined by oxidation with K₂Cr₂O₇ and H₂SO₄, and three carbon fractions (F1, very labile; F2, inert; F3, oxidizable resistant) were classified according to the degree of oxidation using the modified Walkley-Black method. The total SOC and three carbon fractions in the soil were significantly greater in the Forestland than in the other vegetation types, and the effect was more pronounced in macro-aggregate (MA) than in the other aggregates. In the bulk soil and soil aggregates, the percentages of F1, F2 and F3 in the total SOC with mean values of 0.36%, 0.28% and 0.36%, respectively, at soil depths of 0–20 cm, indicated that stabilizing carbon is the major carbon fraction of the SOC. The stability of the SOC in the aggregates across each vegetation type was greater in the lower layer (10–20 cm) than in the topsoil layer (0–10 cm). The SOC stability and MA content were positively related to the SOC in the soil aggregates and its F2 and F3 fractions (p < 0.05). In summary, the Forestland significantly increased the SOC content and enhanced SOC stability. Conservation measures for poplar forests in vulnerable arid zones can sustainably accumulate SOC sequestration. Full article

This investigation presents a new approach for evaluating soil organic carbon (SOC) content in farming soils using a photocatalytic chemical oxygen demand (PeCOD) analyzer combined with geographic information system (GIS) technology for spatial analysis. Soil samples were collected at various sites throughout Canada and were analyzed using sieve analysis, followed by further SOC evaluation using three distinct techniques: loss on ignition (LOI), Walkley-Black, and PeCOD. The PeCOD system, which relies on the photochemical oxidation of organic carbon, showed an exciting correlation between its evaluations and SOC content, making it a prompt and reliable method to evaluate SOC. In this investigation, finer materials such as clayey soils (soil fractions of (<50 µm)) demonstrated high SOC content compared to coarser ones (soil fractions of (>75 µm)) and decreased SOC content with increased soil depth, generally below the 30 cm mark. It should be noted that this investigation revealed that other variables, such as land management practices, precipitation, and atmospheric temperature, have drastic effects on the formation and residence time of SOC. GIS georeferencing еnablеd mapping of the SOC distribution and identification of hotspot areas with high SOC content. The results of this study have implications for sustainable farming, climate change mitigation, and soil health operations by providing farmers with schemes that amplify carbon sequestration while simultaneously improving soil health. Full article

Water-level fluctuation (WLF) can destroy soil aggregates and induce soil organic carbon (SOC) loss, potentially triggering impacts on the concentration of atmospheric carbon dioxide. However, responses of soil aggregate content and aggregate-associated organic carbon to WLF have not been well studied, especially in the water-level fluctuation zone (WLFZ) of the Three Gorges Reservoir (TGR). Therefore, samples from different elevations (145 m, 155 m and 165 m) in the WLFZ of the TGR were collected for experiments. The wet sieving method was used to divide soil into silt and clay (<0.053 mm), micro-aggregate (0.053–0.25 mm) and macro-aggregate (>0.25 mm). The K₂Cr₂O₇-H₂SO₄ oxidation method was used to measure total SOC content in different soil aggregates. A modified Walkley and Black method was used to measure labile carbon in different soil aggregates. Results showed that macro-aggregate content substantially decreased, while micro-aggregate content remained stable and silt and clay fraction accumulated with a decrease in water-level elevations. Moreover, total SOC content and labile carbon in macro-aggregate were obviously higher than those in the micro-aggregate and the silt and clay fraction. Macro-aggregate contributed the most to SOC sequestration, while micro-aggregate contributed the least, and the contribution of macro-aggregate increased with a decrease in water-level elevations. We concluded that the macro-aggregate was the most active participant in the SOC sequestration process, and preferentially increasing the macro-aggregate content of the lowest water-level elevation was conducive to an improvement in soil carbon sequestration potential and would mitigate climate change. Full article

Soil organic carbon (SOC) is a crucial factor influencing soil quality and fertility. In this particular investigation, we aimed to explore the possibility of using diffuse reflectance infrared fourier transform spectroscopy (DRIFT-FTIR) in conjunction with machine-learning models, such as partial least squares regression (PLSR), artificial neural networks (ANN), support vector regression (SVR) and random forest (RF), to estimate SOC in Sohag, Egypt. To achieve this, we collected a total of ninety surface soil samples from various locations in Sohag and estimated the total organic carbon content using both the Walkley-Black method and DRIFT-FTIR spectroscopy. Subsequently, we used the spectral data to develop regression models using PLSR, ANN, SVR, and RF. To evaluate the performance of these models, we used several evaluation parameters, including root mean square error (RMSE), coefficient of determination (R²), and ratio of performance deviation (RPD). Our survey results revealed that the PLSR model had the most favorable performance, yielding an R² value of 0.82 and an RMSE of 0.006%. In contrast, the ANN, SVR, and RF models demonstrated moderate to poor performance, with R² values of 0.53, 0.27, and 0.18, respectively. Overall, our study highlights the potential of combining DRIFT-FTIR spectroscopy with multivariate analysis techniques to predict SOC in Sohag, Egypt. However, additional studies and research are needed to improve the accuracy or predictability of machine-learning models incorporated into DRIFT-FTIR analysis and to compare DRIFT-FTIR analysis techniques with conventional soil chemical measurements. Full article

The mitigation of global warming and conservation of biodiversity are two significant environmental challenges today. Estimating and comparing forest carbon stock and plant diversity under different management approaches provide insight into the choice of management approaches for carbon and plant diversity management. We investigated the variation in carbon stock and diversity of plant species in two forest managements under different approaches: the Kakrebihar protection forest (PF) and Sano Surkhet community forest (CF) in Karnali Province, Surkhet, Nepal. In total, 63 sample plots (30 plots in PF and 33 plots in CF) were laid out systematically across the forests. Dendrometric measurements were carried out for trees, poles, and saplings, and representative leaf litter and herb samples were collected. Soil samples were taken at 10 cm, 20 cm, and 30 cm depths using a soil auger. The existing tree volume equations of tree species of interest were used to estimate tree volume, and species-specific wood density and conversion factors were used to obtain total biomass and carbon content. Soil samples were analyzed using the Walkley-Black method to determine soil organic carbon. PF had higher carbon stock, plant species richness, and abundance at the landscape level than CF; however, the scenario differed at the plot level. At the plot level, PF had significantly higher total carbon stock and biomass carbon stock than CF. However, PF and CF were statistically indistinguishable in term of soil carbon stock. At the plot level, PF and CF were statistically indistinguishable regarding richness, Simpson diversity, and Shannon diversity, but PF had significantly higher plant abundance than CF. In conclusion, the value of PF for carbon stock and plant diversity surpassed those of CF. This study suggests that PF might be a better strategy to enhance carbon stock in forests and maintain habitat for various plant species. Full article

The present investigation evaluated the effect of continuous application (>43 years) of organic and inorganic fertilisers on soil aggregate stability, aggregate size distribution, aggregate-associated carbon and its fractions, and total macro-nutrient content under the soybean–wheat cropping system in vertisols of the semi-arid region. Seven contrasting treatments consisted of T₁ (50% NPK), T₂ (100% NPK), T₃ (150% NPK), T₄ (100% NP), T₅ (100% N), T₆ (100% NPK + FYM) and T₇ Control (crop raised without addition of any nutrient). The highest and lowest percentage of large macroaggregates (11.3%) was found in T₆ and T₇ treatments. The NPK + FYM (T₆) treatments substantially increased the proportion of the macroaggregate fractions (>2 mm and 2–0.25 mm) than other treatments. However, different manure and fertilisation treatments did not affect the proportion of silt + clay aggregates. Long-term application of 100% NPK + FYM increased mean weight diameter (MWD) and stable water aggregates (WSA) by 35.7 and 6.01% over control. The aggregate-associated SOC followed the trend of large macroaggregates > microaggregates > small macroaggregates > silt + clay fractions. Application of long-term manure plus inorganic fertiliser (T₆) has also increased Walkley Black soil organic carbon (WBSC), permanganate oxidisable carbon (KMnO₄-C), soil microbial biomass carbon (SMBC), carbon mineralisation (CM), total soil carbon (TSC), total soil N (TSN), total soil phosphorus (TSP) and total soil potassium (STK) by 82.1, 71.6, 182, 42.4, 23.9, 41.6, 117 and 18.4%, respectively, over control (T₇). The lowest metabolic quotient (MetQ) value of 5.13 mg CO₂–C mg⁻¹ MBC h⁻¹ was obtained in the control treatment (T₇). The lowest MetQ was recorded in the integrated application of manure + inorganic fertiliser, i.e., 100% NPK + FYM (T₆). Similarly, microbial quotient (MiQ) was also higher in treatment T₆ (100% NPK + FYM) and lower in T₇ (control). It is concluded that the application of inorganic fertiliser alone is insufficient to maintain soil health and sustainability so, combined application of manure plus inorganic fertilisation is the most important nutrient management practice for long-term soil sustainability because it maintains SOC levels in soils for long periods and ultimately ensures the soil health of soybean–wheat cropping systems in the vertisols of semi-arid regions. Full article

Long-term application of soil organic amendments (SOA) can improve the formation of soil organic carbon (SOC) pool as well as soil fertility and health of paddy lands. However, the effects of SOA may vary with the input amount and its characteristics. In this work, a descriptive field research was conducted during one cropping season to investigate the responses of various SOC fractions to different long-term fertilization practices in rice fields and their relationships with soil biogeochemical properties and the emission of greenhouse gases (GHG). The field sites included two conventional paddies applied with chemical fertilizer (CF) or CF + rice straw (RS) and six organic agriculture paddies applied with oilseed cake manure (OCM) + wheat straw (WS), cow manure (CM) + WS, or CM + RS. The two paddy soils treated with CM + RS had significantly higher concentrations of recalcitrant to labile C forms, such as loss-on-ignition C (LOIC; 56–73 g kg⁻¹), Walkley–Black C (WBC; 20–25 g kg⁻¹), permanganate oxidizable C (POXC; 835–853 mg kg⁻¹), and microbial biomass carbon (MBC; 133–141 mg kg⁻¹), than soils treated with other SOA. Likewise, long-term application of CM + RS seemed to be the best for regulating soil fertility parameters, such as ammonium (11–141 mg kg⁻¹); phosphate (61–106 mg kg⁻¹); and soluble Ca, K, and Mg (7–10, 0.5–1.2, and 1.9–3.8 mg kg⁻¹, respectively), although the results varied with the location and soil properties of rice fields. Additionally, the two paddy sites had the largest cumulative methane emission (754–762 kg ha⁻¹), seemingly attributed to increased microbial biomass and labile C fractions. The significant correlations of most SOC fractions with soil microbial biomass, trophic factors, and methane emissions were confirmed with multivariate data analysis. It was also possible to infer that long-term SOA application, especially with CM + RS, enhanced interaction in belowground paddy fields, contributing to soil fertility and rice production sustainability. Based on our findings, we suggest the need for analysis of various types of SOC fractions to efficiently manage soil fertility and quality of paddy fields, C sequestration, and GHG emissions. Full article

Some intensive farmers tend to expect short-term beneficial effects by applying soil amendments, but inconsistent fertilization practices are often conducted, causing economic losses and environmental problems. This study aimed at investigating the short-term application effects of different soil amendments on soil organic carbon (SOC) fractions, biogeochemical properties, and crop performance for finding the best land management approach using one-year field trial growing Chinese cabbages. This filed experiment was conducted in 2020 and included eight fertilizer treatments: control (w/o fertilizers), chemical fertilizer (CF), manure compost (MC), double MC amount (2MC), CF + MC, CF + rice husk (RH), MC + RH, and CF + MC + RH. As a result, the concentrations of recalcitrant to labile C forms, including Loss-On-Ignition C (LOIC), Walkley-Black C, permanganate oxidizable C (POXC), and microbial biomass C, were the highest in a mixture of MC and RH and 2MC. Additionally, the treatment with the largest difference from the control in key soil parameters was 2MC: bulk density (10%), total N (30%), available P (186%), and CO₂ (433%) and N₂O (825%) emissions, followed by MC + RH. Moreover, more than 20% higher fresh weight (FW) of cabbage was found in 2MC and MC + RH than in the control. Therefore, these two organic amendments appeared to benefit SOC storage and overall soil biogeochemical processes, contributing to higher biomass crop production. Moreover, LOIC significantly correlated to bulk density, available P and K, and FW, while POXC significantly correlated to N concentration in plants, indicating the short-term fertilization effects on the status of SOC fractions and the qualities of soil and plant by applying soil amendments. Overall, our findings suggest that applying MC + RH would be an alternative to replace the conventional farming practices for promoting soil quality and crop performance, but further studies to sustain the application effects of this amendment should be monitored for longer durations. Full article

Microalgae are one of the most promising sources of renewable substrates used for energy purposes. Biomass and components accumulated in their cells can be used to produce a wide range of biofuels, but the profitability of their production is still not at a sufficient level. Significant costs are generated, i.a., during the cultivation of microalgae, and are connected with providing suitable culture conditions. This study aims to evaluate the possibility of using sodium bicarbonate as an inexpensive alternative CO₂ source in the culture of Chlorella vulgaris, promoting not only the increase of microalgae biomass production but also lipid accumulation. The study was carried out at technical scale using 100 L photobioreactors. Gravimetric and spectrophotometric methods were used to evaluate biomass growth. Lipid content was determined using a mixture of chloroform and methanol according to the Blight and Dyer method, while the carbon content and CO₂ fixation rate were measured according to the Walkley and Black method. In batch culture, even a small addition of bicarbonate resulted in a significant (p ≤ 0.05) increase in the amount of biomass, productivity and optical density compared to non-bicarbonate cultures. At 2.0 g∙L^–1, biomass content was 572 ± 4 mg·L⁻¹, the maximum productivity was 7.0 ± 1.0 mg·L^–1·d^–1, and the optical density was 0.181 ± 0.00. There was also an increase in the lipid content (26 ± 4%) and the carbon content in the biomass (1322 ± 0.062 g∙dw^–1), as well as a higher rate of carbon dioxide fixation (0.925 ± 0.073 g·L^–1·d^–1). The cultivation of microalgae in enlarged scale photobioreactors provides a significant technological challenge. The obtained results can be useful to evaluate the efficiency of biomass and valuable cellular components production in closed systems realized at industrial scale. Full article

Soil organic carbon (SOC) is an important indicator of soil quality and directly determines soil fertility. Hence, understanding its spatial distribution and controlling factors is necessary for efficient and sustainable soil nutrient management. In this study, machine learning algorithms including artificial neural network (ANN), support vector machine (SVM), cubist regression, random forests (RF), and multiple linear regression (MLR) were chosen for advancing the prediction of SOC. A total of sixty (n = 60) soil samples were collected within the research area at 30 cm soil depth and measured for SOC content using the Walkley–Black method. From these samples, 80% were used for model training and 21 auxiliary data were included as predictors. The predictors include effective cation exchange capacity (ECEC), base saturation (BS), calcium to magnesium ratio (Ca_Mg), potassium to magnesium ratio (K_Mg), potassium to calcium ratio (K_Ca), elevation, plan curvature, total catchment area, channel network base level, topographic wetness index, clay index, iron index, normalized difference build-up index (NDBI), ratio vegetation index (RVI), soil adjusted vegetation index (SAVI), normalized difference vegetation index (NDVI), normalized difference moisture index (NDMI) and land surface temperature (LST). Mean absolute error (MAE), root-mean-square error (RMSE) and R² were used to determine the model performance. The result showed the mean SOC to be 1.62% with a coefficient of variation (CV) of 47%. The best performing model was RF (R² = 0.68) followed by the cubist model (R² = 0.51), SVM (R² = 0.36), ANN (R² = 0.36) and MLR (R² = 0.17). The soil nutrient indicators, topographic wetness index and total catchment area were considered an indicator for spatial prediction of SOC in flat homogenous topography. Future studies should include other auxiliary predictors (e.g., soil physical and chemical properties, and lithological data) as well as cover a broader range of soil types to improve model performance. Full article

A careful reading of Bonnail et al. (2019)’s work points out some issues in the description of the Ganges River, e.g., describing it in a way that gives impression to the readers unfamiliar with the Indian rivers that it flows by the national capital New Delhi, after reading “it receives inputs from highly populated cities of India, including New Delhi and …”. However, as a matter of fact, it is not the Ganges, but the Yamuna River, a tributary of the Ganges, that passes through the National Capital Region of Delhi. Moreover, authors identify the studied river as the Ganges, whereas it is one of the distributaries of the Ganges called Hooghly (anglicized version of its local name Hugli). They have referred to the seasonality of the studied river; however, the flow of the studied (Hooghly) river is controlled by a barrage on the Ganges River. Moreover, Hooghly River receives input from its own tributaries; viz., Mayurakshi and Damodar, flowing through highly mineralized and coaliferous areas of Jharkhand state of India. Bonnail et al. (2019) have attributed the contamination of the river sediments to anthropogenic activities alone, by not evaluating likely natural sources. A correction factor for the underestimated total organic carbon (TOC) content obtained using Walkley-Black method should have been applied before using TOC values for factor analysis to overcome the underestimation issue with this method. This work intends to serve as a compendium, rather than a critique, to otherwise commendable work by Bonnail et al. (2019). Full article

The Kyoto Protocol includes agroforestry practices as a suggested approach for mitigating global atmospheric CO₂. Agroforestry systems are a desirable option for mitigating atmospheric CO₂, as they provide numerous secondary benefits, including food, fodder, fuel, increased farm income, biodiversity maintenance, and soil conservation. This research was planned to assess the current carbon storage status and future potential of agroforestry systems in Pakistan through a nondestructive approach (allometric equations) in 14 subdivisions (tehsils) of three selected districts located in the irrigated plains of Punjab, Pakistan. A total of 1750 plots of 0.405 ha each were selected in a randomized, unbiased sampling to estimate the total number of trees, tree species diversity, diameters at breast height (DBHs), and tree heights. Soil carbon was also measured at 0–30 cm using the Walkley–Black method in a subset of plots. It was found that the current number of trees in farms in the study area varied from 18 to 51 trees/ha, which can be increased to 42–83 trees/ha if all the farmers plant the maximum permissible number of trees along with their crops. The estimated total tree carbon stock ranged from 0.0003 to 8.79 Mgha⁻¹, with the smallest mean value of 0.39 Mgha⁻¹ for tehsil Faisalabad, and the largest mean value of 1.41 Mgha⁻¹ for tehsil Chiniot. The whole study area had an estimated woody vegetation carbon stock of 950,470 Mg and a soil carbon stock of 22,743,008 Mg. If farmers in the study area all increased tree stocking to their average maximum desired stocking, the total tree carbon stock would more than double to 2,497,261 Mg. These results highlight both the current and potential carbon sequestration potential of agroforestry in Pakistan and can be further used in devising strategies for implementing tree planting programs on agricultural lands and designing future carbon sequestration projects in Pakistan. Full article

Soil organic carbon (SOC) is an important indicator of soil quality; an elevated percentage of SOC indicates very high-quality soil, physically as well as chemically. As such, the principal objective of the present study was to determine the concentration of SOC at different depths, as well as its accumulation through the entire soil profile. The Carrizal-Chone system (SCCH) area was stratified by agricultural use. Sixty-three soil samples were taken from different depths of up to a maximum of 150 cm. The physical and chemical properties of the soil were determined. SOC was determined by the Walkley and Black method. The following results are highlighted: (1) 21 different varieties of soil management were identified; (2) the largest area was livestock grazing land, which had the greatest concentration of SOC; (3) the type of soil with the greatest SOC sequestration capacity was silty clay loam; (4) the area cultivated with corn presented the highest accumulation of total carbon; and (5) the highest concentration of SOC was found in the top 40 cm, with a tendency to decrease with depth. It is concluded that soil management influences the concentration and accumulation of SOC in the topsoil layers and the entire soil profile. Full article