Environmental Erosion Research Journal

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Extended abstract
1- Introduction
Addition of biochar to soil has been recently considered as an amendment to reduce soil erosion. Biochar contains pyrogenic carbon, which is produced by heating residue of various crops, woods (or in other words various biomass) in restriction or absence of oxygen. Biochar can affect soil organic matter level and aggregate stability. Reduction of soil erosion through maintenance and  the increase of organic matter, increase of aggregate stability and improvement of hydraulic conductivity, and enhancement of moisture retention as a result of biochar application should be considered as an important achievement. It is important to study the effect of the different methods of biochar addition to the soil. The method of uniformly mixing biochar with surface soil which has been used in most studies can disturb the natural structure and lead to soil degradation. Therefore, it is an important issue to introduce a practical method that is associated with minimal soil manipulation, especially in erosion-prone soils. The effect of the biochar addition as suspension in water has never been reported in previous studies. Therefore, the aim of this study was to investigate the effects of adding different levels of biochar produced from two types of feedstocks (horticulture and agriculture wastes) in form of aqueous suspension on the properties of two types of erosion-prone soils in southern Guilan.
 
2- Methodology
Two erosion-prone soils which were undisturbed, were sampled by metal cylenders (diameter and height of 25 and15 cm, respectively) of marl lands located in southern guilan. These soils were named as SL and L. Texture of SL and L were sandy loam and loam, respectively. Two types of biochar were produced from different feedstocks including pruned branches of ash tree (Fraxinus excelsior) and rice husk by slow pyrolysis at a temperature of 550 °C in a muffle furnace, titled as WB and RB respectively. The yield of biochar was determined based on weight of biochar produced per unit weight of raw material. The amount of ash in the biochar was determined by heating five grams of biochar at 500 °C for more than 8 hours and weighing it again. The pH and electrical conductivity were measured in a mixture of biochar and deionized water with a weight ratio of 1: 20 (biochar: water). The total amount of carbon, hydrogen, and nitrogen in biochars was determined by dry combustion. Two types of produced biochars were milled with a particle size of 63-250 microns, at levels of 0.7 and 1.4% by weight. Three repetitions in the form of aqueous suspensions were added to the cylinders containing undisturbed soil. Three cylinders of soil without biochar were also considered as control treatment. Soil cylinders were placed in a greenhouse for six months at a temperature range of 20-25°C and underwent several cycles of drying and wetting. At the end of incubation period, soil samples were obtained from cylinders. Soil properties including pH, electrical conductivity, organic carbon, hydraulic conductivity and aggregate stability were also measured. Thin sections were also taken out of soils and state of soil structure and voids were studied. The effect of two factors, including biochar type and biochar application level were analyzed as factorial in a completely randomized design by SAS statistical software. The comparison of the means was done by Duncan's test at the probability level of five percent.
3- Results
The WB compared to RB, had a higher yield, and less ash content, pH, electrical conductivity and H/C and O/C. More mineral ash in biochar is likely to provide more electrical conductivity in RB. Both biochar had an alkaline pH (more than 7). The biochar used in previous studies were usually alkaline, but biochar can be produced with any pH in the range of 4 to 12. The raw biomass has a H/C  molar ratio of about 1.5, but with the pyrolysis, this ratio decreases. WB had less H/C compared to RB. Therefore, it can be concluded that WB had more aromatic carbon and it can probably be a more effective tool for carbon sequestration in soil. Presence of a lot of pores in biochar, especially WB which were visible in SEM photos, are very effective on vital soil functions such as aeration and hydrology. The organic carbon content of SL and L soils were significantly higher at biochar treatments compared to control. The hydraulic conductivity of SL soil at both application levels of WB and RB was significantly lower than the control. However, both application levels of WB and 1.4% of RB led to significant increase and decreases of hydraulic conductivity of L soil, respectively. The mean comparison showed no difference between bulk density of treatments and application levels of biochar to control treatment of SL soil. However, Bulk density of biochar treated L soils were less than control. Biochar treatment also result in significant increase of: mean weight and geometric mean diameter and decrease of fractal dimension of aggregates in L Soil.
4- Discussion & Conclusions
WB and RB biochars had no significant effects on indexes of soil aggregate stability and bulk density of SL soil, but they led to significant improvement of bulk density and aggregate stability of L Soil. Although, assessment of thin section showed partial improvement of soil structure of both SL and L soils. Therefore, more time than 6 months of incubation probably is needed to significant improve of aggregate stability of SL. Application of both biochars led to increase of organic carbon of both SL and L soils. Hydraulic conductivity was decreased in SL soil as result of both biochar application which can lead to the increase of water retention. Although the increase of hydraulic conductivity of  L soils due to WB can be considered as a suitable approach for the decrease of  the runoff, Generally, it can be concluded that due to the significant effect of feedstock type on biochar characteristics and different characteristics of soils, various types of biochar do not have a similar effect on a particular soil, therefore, a type of biochar cannot have the same effect on different types of soil.

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1- Introduction
Carbon dioxide is one of the main greenhouse gases that affect the world's air temperature. Small changes in the amount of carbon dioxide emissions from the soil have a significant effect on the concentration of this gas in the atmosphere. Soil respiration, the process that emits carbon dioxide from the soil to the atmosphere, is one of the most important carbon flows in the ecosystem and includes two components of heterotrophic respiration (microbial respiration) and autotrophic respiration (root respiration). Researchers measure the rate of soil respiration for every 10 degrees Celsius of temperature change with an index called temperature sensitivity of soil respiration (Q₁₀). The evidence shows that the Q₁₀ value of the soil is not constant and has a negative correlation with temperature and a positive correlation with soil moisture. Also, the amount of soil organic carbon, incubation temperature and the interaction of these two have a significant effect on soil organic carbon decomposition. Accordingly, this research measures the temperature sensitivity (Q₁₀) in soil under tea cultivation and investigates its relationship with some soil chemical characteristics and topographic indices.
2- Methodology
After surveying the east and west tea gardens in Guilan province in the north of Iran, 200 samples were taken at a depth of 0 to 40 cm. The experiments were conducted to determine Organic Carbon, Labile carbon, Bulk density, PH, Cation Exchange Capacity, Microbial Biomass and soil microbial respiration. To measure Q₁₀, two temperature treatments of 25 and 35 °C were used. Elevation, slope and aspect were obtained using a DEM map in ArcGIS 10.5 and other topographical indicators such as wetness index, slope length, relative slope position, catchment area, channel network base level, vertical distance to channel network, convergence index, profile curvature and plan curvature were extracted from DEM map in Saga GIS 2.1.0. Pearson correlation was used to investigate whether there is any relationship between soil temperature sensitivity with other soil properties. Then, principal component analysis (PCA) was performed to determine a minimal data set. All the statistical analyses were done with SPSS 24. Regression charts were also drawn using Excel software.
3- Results
The Q₁₀ values varied from 1.19 to 1.58. This index has the most negative correlation with organic carbon (-0.863), Labile carbon (-0.863), microbial biomass (-0.837), respiration at 25 °C (-0.831) and 35 °C (-0.8) at 1% level and negative correlation with elevation at 5% (-0.159). The principal component analysis showed that the first six components (PC1, PC2, PC3, PC4, PC5 and PC6) have special values of more than one and were able to describe 73% of the total variance. The first main component (PC1) describes 23.125% of the total variance and includes soil organic carbon, labile carbon, microbial biomass and Q₁₀ which have the highest factor loading in this component. The second one (PC2), which explains about 12.99% of the total variance, has the highest factor loading with the vertical distance to the channel network (0.880). The third component (PC3) explains about 12.22% of the total variance. In PC3, clay has the highest factor loading. In the fourth component catchment area, convergence profile and slope length have the highest factor loading, respectively. Finally, the fifth and the sixth components are related to the elevation, slope and plan curvature.
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4- Discussion & Conclusions
The highest positive factor loading is related to soil organic carbon (0.981). Therefore, the first main component can be "part of the role of organic carbon in microbial biomass, labile carbon and temperature sensitivity". The results showed that Q₁₀ has the highest negative correlation with soil microbial biomass and organic and labile carbon. In other words, the higher the soil organic and microbial biomass carbon, the lower the amount of Q₁₀. Also, the second component can be considered as topographic indicators related to the channel network. Topographic indices can be used very strongly to model making soil organic carbon. The third component is related to clay properties. Several studies have indicated that the amount of clay has a high relationship with cation exchange capacity and it is a good indicator to determine the quality of soil. According to the results, although the correlation between some characteristics obtained from soil topographical analysis can prove the possibility of using them as auxiliary variables in predicting soil organic carbon, this point should be taken into account that other factors also play a role in the process of soil formation and development.