Nitrous oxide emissions from soils amended by cover-crops and under plastic film mulching: Fluxes, emission factors and yield-scaled emissions

Soil respiration is a biological process in microbes that convert organic carbon to atmospheric CO2. This process is considered to be one of the largest global carbon fluxes and is affected by different physicochemical and biological properties of soil, land use, vegetation types and climate patterns. Soil respiration recently received much attention, and it could be measured in two states basal respiration (BR) and substrate induced respiration (SIR) which together gives a good representation of the general soil microbial activity. The aim of this study was to estimate the BR and SIR of 150 data points obtained from soil samples collected from the surface to 20 cm of depth under different land use categories using the Artificial Neural Network (ANN) and Linear Regression Methodology (LRM). This study is bringing data from an arid area, and there is little information on this issue. Soil samples were chosen from three provinces of Iran, with humid subtropical and semi-arid climate patterns. In each soil sample a variety of characteristics were measured: soil texture, pH, electrical conductivity (EC), calcium carbonate equivalent (CCE), organic carbon (OC), OC fractionation data e.g. light fraction OC (LOC), heavy fraction OC (HOC), cold water extractable OC (COC) and warm water extractable OC (WOC), population of fungi, bacteria, actinomycete, BR and SIR. Our goal was to use the most efficient ANN-model to predict soil respiration with simple soil data and annual precipitation (AP) and mean annual temperature (MAT) and compare it with LRM. Our results indicated that for an ANN model containing all the measured soil parameters (14 variables), the R2 and RMSE values for BR prediction were 0.64 and 0.05 while these statistical indicators for SIR obtained 0.58 and 0.15, respectively; whereas the addition of AP and MAT data to this model (16 variables) caused a decrease in statistical indicators. When the R2 and RMSE values of the BR-ANN and SIR-ANN predicted using an ANN model with only 7 variables (including OC, pH, EC, CCE and soil texture) they were estimated to be 0.66, 0.043 and 0.52, 0.16, respectively. Overall, LRM in comparison to ANN had a lower R2. Therefore, the results show that ANN modeling is a reliable method for predicting soil respiration, even when based on easy to measure data. Our results revealed that highest and lowest BR and SIR were recorded in rice paddy soils and saline lands, respectively. In total, soil respiration (BR: 0.09 vs 0.06 and SIR: 0.46 vs 0.32 mg CO2 g−1 day−1) was higher in agricultural land compared to natural covered land.

Estimating the soil respiration under different land uses using artificial neural network and linear regression models

Soil organic carbon (SOC) has a high impact on the sustainability of ecosystems, global environmental processes, soil quality and agriculture. Long-term tillage usually leads to SOC depletion. The purpose of this study was to determine the impact of different land uses on water extractable organic carbon (WEOC) fractions and to evaluate the interaction between the WEOC fractions and other soil properties. Using an extraction procedure at 20°C and 80°C, two fractions were obtained: a cold water extractable organic carbon (CWEOC) and a hot water extractable organic carbon (HWEOC). The results suggest that there is a significant impact from different land uses on WEOC. A lower relative contribution of WEOC in SOC and a lower concentration of labile WEOC fractions are contained in arable soil compared to forestlands. Chernozem soil was characterized by a lower relative contribution of WEOC to the SOC and thus higher SOC stability in contrast to Solonetz and Vertisol soils. Both CWEOC and HWEOC are hig...

The sensitivity of water extractable soil organic carbon fractions to land use in three soil types

Seasonal Variability of Soil Organic Carbon Fractions Under Arable Land

The aim of this study was to evaluate the potential of short rotation alley cropping systems (SRACS) to improve the soil fertility of marginal post-mining sites in Brandenburg, Germany. Therefore, we annually investigated the crop alleys (AC) and black locust hedgerows (ABL) of a SRACS field trail under initial soil conditions to identify the short-term effects of tree planting on the storage of soil organic carbon (SOC) and its degree of stabilization by density fractionation. We detected a significant increase in SOC and hot-water-extractable organic C (HWEOC) at ABL, which was mainly restricted to the uppermost soil layer (0–10 cm). After 6 years, the SOC and HWEOC accumulation rates at ABL were 0.6 Mg and 46 kg ha−1 year−1, which were higher than those in the AC. In addition, comparatively high stocks of approximately 4.6 Mg OC and 182 kg HWEOC ha−1 were stored in the ABL litter layer. Density fractionation of the 0–3 cm soil layer at ABL revealed that the majority of the total SOC (47%) was stored in the free particulate organic matter fraction, which was more than twice that of the AC. At the same time, a higher and steadily increasing amount of SOC was stored in the occluded particulate organic matter fraction at ABL, which indicated a high efficiency for SOC stabilization. Overall, our findings support the suitability of black locust trees for increasing the soil fertility of the reclaimed mining substrate and, consequently, the high potential for SRACS to serve as an effective recultivation measure at marginal sites.

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The development of soil organic carbon under young black locust ( Robinia pseudoacacia L.) trees at a post-mining landscape in eastern Germany

The content of labile, especially water extractable organic carbon (WEOC) is a sensible indicator of soil organic matter quality. The main objectives of this study were: i) to investigate the profile changes of cold and hot water extractable organic carbon in forest and arable soils; ii) to evaluate the correlation between these labile fractions of soil organic matter and total organic carbon content. The experiments were carried out on a Gleyic Albeluvisol (ABg) in the upper part of Dniester basin, Western Ukraine. The soil samples were taken from 50-cm depth soil profile with 5-cm step. Total organic carbon (TOC), cold water extractable organic carbon (CWEOC) and hot water extractable organic carbon (HWEOC) contents in soil were determined as well as pH (H 2 O) and electrical conductivity of soil:water suspensions. The results of this study showed that in 0–50 cm layer of arable soil TOC content decreased by 32%, CWEOC – by 23% and HWEOC – by 74% compared to forest soil that confirmed a high informative role of HWEOC fraction. The profile changes of WEOC percentage were analysed. They also show that HWEOC is much more informative indicator of soil organic matter quality than CWEOC. The most prominent changes of soil chemical properties, TOC, CWEOC and HWEOC contents in response to deforestation were observed in the top 5-cm soil layer. We suggested this thin soil layer to be defined as soil stress-sensitive zone.

/pdf/total-cold-and-hot-water-extractable-organic-carbon-in-soil-9s5r1g4dvn.pdf

Total, cold and hot water extractable organic carbon in soil profile: impact of land-use change

The rhizosphere microbiome of the native Antarctic hairgrass Deschampsia antarctica from the central maritime Antarctic was investigated using 16S RNA metagenomics and compared to those of the second native Antarctic plant Colobanthus quitensis and closely related temperate D. cespitosa. The rhizosphere microbial communities of D. antarctica and D. cespitosa had high taxon richness, while that of C. quitensis had markedly lower diversity. The majority of bacteria in the rhizosphere communities of the hairgrass were affiliated to Proteobacteria, Bacteroidetes, and Actinobacteria. The rhizosphere of C. quitensis was dominated by Actinobacteria. All microbial communities included high proportions of unique amplicon sequence variants (ASVs) and there was high heterogeneity between samples at the ASV level. The soil parameters examined did not explain this heterogeneity. Bacteria belonging to Actinobacteria, Bacteroidetes, and Proteobacteria were sensitive to fluctuations in the soil surface temperature. The values of the United Soil Surface Temperature Influence Index (UTII, Iti) showed that variations in most microbial communities from Galindez Island were associated with microscale variations in temperature. Metabolic predictions in silico using PICRUSt 2.0, based on the taxonomically affiliated part of the microbiomes, showed similarities with the rhizosphere community of D. antarctica in terms of the predicted functional repertoire. The results obtained indicate that these communities are involved in the primary processes of soil development (particularly the degradation of lignin and lignin-derived compounds) in the central maritime Antarctic and may be beneficial for the growth of Antarctic vascular plants. However, due to the limitations associated with interpreting PICRUSt 2.0 outputs, these predictions need to be verified experimentally.

https://www.jstage.jst.go.jp/article/jsme2/37/2/37_ME21069/_pdf

Tymur Bedernichek

Papers

Total, cold and hot water extractable organic carbon in soil profile: impact of land-use change

Antarctic Hairgrass Rhizosphere Microbiomes: Microscale Effects Shape Diversity, Structure, and Function