查看更多>>摘要：Winter snowfall is an important water resource for organisms in desert ecosystems. Changing snow depth is expected to exert a potential influence on growth and ecological functions of biological soil crusts (BSCs), which are known as a dominant functional vegetation unit of desert ecosystems. However, limited attention has been paid to this potential effect on BSCs. A field simulation experiment was conducted to measure the water content, nutrient concentrations (organic carbon; total nitrogen; available nitrogen; available phosphorus; available potassium; ammonium nitrate; and nitrate nitrogen), and microbial biomass (carbon, nitrogen, and phosphorus) in samples (cyanobacterial and lichen crusts and subcrust soil) under snow cover of different depths after a four year experiment (from October 2013 to April 2017) in the Gurbantunggut Desert. The results showed that water content increased with increasing snow depth (P < 0.05). Snow removal and snow cover reduction decreased nutrient and microbial biomass concentrations in both biocrust types (P < 0.05). The concentrations of most measured nutrients and microbial biomass decreased significantly when snow depth was increased to twice ambient conditions (P < 0.05). Moreover, the concentrations of nutrients and microbial biomass were significantly influenced by snow depth (P < 0.05), crust type (P < 0.001), and their interaction (P < 0.05). The results demonstrated that variation in snow depth adversely affect the carbon and nutrient availability and microbial biomass in BSCs. Such changes might lead to a cascading effect in species composition and function of BSC communities in arid regions.
查看更多>>摘要：Sampling design plays a key role in digital soil mapping (DSM). Efficient sampling design for multiple soil properties is increasingly needed for multivariate soil survey and mapping. However, most of the present sampling methods are not developed for multiple soil properties. Different soil properties have different influential covariates, but usually only one set of covariates is used in designing samples for multiple soil properties which makes simultaneously mapping multiple soil properties accurately difficult. This paper proposed a multiple soil properties oriented representative sampling strategy (MPRS) by considering the influential environmental covariates for each soil property. The method first selects the most influential set of environmental covariates for each soil property, then uses fuzzy c-means (FCM) clustering to generate environmental clusters relating to spatial variation patterns for each soil property, and the selected samples are representative of as many typical locations of environmental clusters for multiple soil properties as possible. The proposed sampling method was applied for mapping soil sand content and soil organic matter content at surface (0-20 cm) and subsurface (20-40 cm) layers in a study area with 5900 km(2) located in Anhui Province, China, and compared with two methods, the purposive sampling (PS) method and integrative hierarchical stepwise sampling (IHS) method. The results showed that the proposed sampling method achieved the most accurate prediction for most of the four soil properties over different sample sizes. The proposed sampling method also has an advantage to extract representative samples which can better cover multiple soil properties with a limit of a small sample size. On average, the improvement of prediction accuracy by using the MPRS method was 38.1% and 36.3% compared with PS and IHS in terms of R2, 4.8% and 4.6% in terms of RMSE, and 11.7% and 13.7% in terms of CCC, respectively. Our case study confirmed the necessity to consider the difference of the influential environmental variable combinations for the multiple soil properties oriented sampling design. We conclude that MPRS is a potential effective method for supporting DSM for multiple soil properties.
查看更多>>摘要：Organic carbon sequestered in soil aggregate contributes significantly to the carbon preservation on the earth's surface. However, the turnover of soil aggregate in high latitudes and cold zones is strongly affected by the frequency of freeze-thaw cycles and may be disturbed by climate change. Although the effects of recurrent freeze-thaw cycles on the size, structure, and stability of soil aggregate have been well studied, the aggregation of individual mineral particles adsorbed by organic carbon and its mechanism are not yet conclusive. Here, we report that more than 97 wt% of the humic acid-coated goethite (goethite-HA) particles can aggregate into aggregates of different sizes and morphologies through one freeze-thaw cycle (freezing at -24 degrees C for 12 h and thawing at 4 degrees C for 12 h). Combining electron microscopy, infrared absorption spectroscopy and thermogravimetric analysis, we revealed that goethite-HA particles could strongly complex with each other after one freeze-thaw cycle. Compared with previous studies, our results showed that both electrostatic repulsion and steric hindrance (known to prevent aggregation) were overcome by the internal thrust of ice exclusion during freezing, then goethite-HA particles could be interconnected through the carboxyl-iron and hydrogen bonding to form aggregates. We believe that aggregates formed during the freeze-thaw cycles in soils rich in iron (hydr) oxides can serve as shelters for soil organic carbon and may reduce CO2 emissions in these soils.
Breure, Mirjam S.Van Eynde, EliseKempen, BasComans, Rob N. J....
9页
查看更多>>摘要：Multi-element soil extractions such as Mehlich 3 (M3) have gained popularity in recent years, but comparing outcomes to other soil testing methods is not always straightforward. In this study, extraction mechanisms of M3, Olsen and neutral 1 M ammonium acetate (AA) soil tests were explored and transfer functions were derived between P-Olsen and P-M3 as well as between K-AA and K-M3. Soils from tropical and temperate areas were used to derive these P and K transfer functions and were evaluated separately. The application of these transfer functions for tropical soils was evaluated by using them as input for the Quantitative Evaluation of the Fertility of Tropical Soils (QUEFTS). AA and M3 generally extracted similar amounts of K, but relations between K-AA and K-M3 were different for tropical and temperate soils. For tropical soils, the transfer function did not require additional parameters besides K-M3 to predict K-AA, but for temperate soils inclusion of clay content and pH was needed. This difference between tropical and temperate soils was explained by clay mineralogy. The relation between P-Olsen and P-M3 in tropical soils was found to be dependent on pH, Al-M3, Fe-M3 and Ca-M3. P-Olsen and K-AA values, calculated with their respective transfer functions, were used as input for QUEFTS. The yields predicted with measured P-Olsen and Exch. K were used as benchmark. For 63 out of 81 soil samples, predicted maize yields with transfer functions deviated less than 10% from the benchmark. The largest deviations from the benchmark were found for low P-Olsen and K-AA values, which corresponds to QUEFTS maize yield predictions up to 3000 kg ha(-1). We conclude that a M3 extraction results and soil pH can reliably be transferred to, and thus replace P-Olsen and K-AA determinations with the functions developed for tropical soils. The transfer functions can be used to generate input for the QUEFTS model with minor effects on yield predictions, thus expanding its applicability in cases where only M3 extraction results are available.
查看更多>>摘要：Scanning electron microscopy coupled with microanalysis (SEM-EDX) is an important analytical tool for the morphological and chemical characterization of different types of materials. In many applications, SEM-EDX elemental maps are usually used and processed as images, thus flattening and reducing the spectroscopic information contained in EDX hyperspectral data cubes. The exploitation of the full hyperspectral dataset could be indeed very useful for the study of complex matrices like soil. In order to maximize the information attainable by SEM-EDX data cubes analysis, the software package "Datamuncher Gamma" was implemented and applied to study soil aggregates. By using this approach, different phases (silicates, aluminosilicates, Ca-carbonates, Ca-phosphates, organic matter, iron oxides) inside soil aggregates were successfully identified and segmented. The advantages of this method over the common ROI imaging approach are presented. Finally, this method was used to compare different aggregates in a Cr-polluted soil and understand their possible pedological history. The present method can be used for the analysis of every type of SEM-EDX data cubes, allowing its application to different types of samples and fields of study.
Tenorio Firmino, Francis HenriqueCamelo, Danilo de Limado Nascimento, Alexandre Ferreirade Souza Lima, Jose Romualdo...
14页
查看更多>>摘要：The occurrence of lamellae in soils and sediments has direct implications for agricultural production, and for stratigraphic and geomorphological studies. Although lamellae have been studied for more than a century, their origin remains controversial. The aim of this study was to identify the origin and formation mechanisms of lamellae in autochthonous soils developed from metamorphic rocks in a semi-arid area of Northeast Brazil. As such, the spatial organization of soil profiles was evaluated in a topolithosequence, through structural analysis of the pedological coverage for subsequent soil sampling. Morphological, chemical, physical, sedimentological, mineralogical, and micromorphological analyses were carried out on the studied slope and in greater detail in four soil profiles. The results indicated that clay particles predominantly smaller than 0.2 mu m are eluviated in a sandy soil matrix, infilling voids and coating quartz grains, which are organized in layers of densely packed fine sand, impeding clay translocation and helping form lamellae. Although the micromorphological properties of the lamellae demonstrate their pedogenic origin, the contribution of strips of polycrystalline quartz constitutes a petrogenic component of the illuviation process. Therefore, the genesis of the lamellae is better described based on a petro-pedogenic origin. We suggest a restructuring of the concept of petro-pedogenic origins, including the structural influence of metamorphic rocks, as illuviated clay deposition occurs in accordance with a physical barrier provoked by the increase and organization of fine sand particles, distributed horizontally and in parallel, arising from the disintegration of polycrystalline quartz grains, which indicates geological control in the genesis of lamellae, corresponding to petrogenic evidence. Furthermore, the morphological distinction of the lamellae seems to be more associated with the fine sand content (<0.25 mm), and its packing with larger grains of quartz in the soils.
Davari, MasoudFahmideh, SoheylaMosaddeghi, Mohammad Reza
12页
查看更多>>摘要：Soil water repellency (SWR) is an important soil physical property that may restrict water infiltration and soil water retention. Common laboratory and field techniques for assessing SWR are laborious, time-consuming, and costly. Meanwhile, Visible-Near-Infrared (Vis-NIR) spectroscopy has been reported as a rapid, cost-effective, and alternative technique to estimate several soil properties. To investigate the efficacy of this technique for predicting SWR indices [soil water repellency index (RI) and soil-water contact angle (beta)] at dry condition, 100 soil samples collected from farmlands, orchards, rangelands and forests of Zrebar lake watershed in Kurdistan province, Iran, were measured by Vis-NIR spectroscopy within the 350-2500 nm range. The Savitzky-Golay first derivative method was applied for denoising the spectral data. The RI and beta were measured by the intrinsic sorptivity method (using water and ethanol as absorbing liquids). The other basic soil properties were also measured by standard laboratory methods. Stepwise multiple linear regression (SMLR) and partial least squares regression (PLSR) were utilized to establish pedo-transfer functions (PTFs) and spectro-transfer functions (STFs) using basic soil properties and spectral absorbance data, respectively, to estimate soil organic matter (SOM) content and SWR indices. We obtained good predictions for SOM with R-2 = 0.67 and RPIQ (the ratio of performance to interquartile range) = 1.92 using the PLSR-based STF. The results also revealed that although the SMLR-based STFs achieved slightly better estimates of the SWR indices (RI and beta) than the SMLR-based PTFs (R-2 values of 0.28 to 0.39 vs. 0.19 to 0.23, respectively); but, overall, none of these transfer functions for estimating these indices showed acceptable predictive capability. However, the PLSR-based STFs could provide a reasonable prediction for the studied SWR indices (R-2 > 0.52 and RPIQ > 2.27). The majority of important adsorption bands in the Vis-NIR PLSR models for the SWR prediction was related to both the quantity and quality of SOM. Overall, the results demonstrated that the Vis-NIR PLSR could be applied to predict SOM and SWR indices rapidly, non-destructively, and with fair accuracy.
查看更多>>摘要：Catchment asymmetry is a fairly frequent phenomenon on a global scale but the main causes leading to its formation are still not well understood. Where the intervention of structural or tectonic causes is not relevant, asymmetry seems to result from differential erosion between opposite slopes that flow into the same channel, which is frequently associated with contrasted biocrust and/or vegetation covers. Biocrusts are known to be important surface stabilizing agents. However, their geomorphological consequences at the landscape scale are little known. In this study we combined field measurements with digital elevation models and image analysis to determine whether catchment asymmetry in the Tabernas Desert (semi-arid SE of Spain) is a local or general phenomenon, and to explore the main factors determining asymmetry occurrence, magnitude and direction. We pay special attention to the role of biocrusts. We found that catchment asymmetry is a very common phenomenon in the area; only 25% of the catchments are symmetrical, while approximately 40% present asymmetry with the relatively shady hillslope having a lower gradient, and 35% with that hillslope being the steeper. Solar radiation reaching the soil, surface area and channel gradient in the considered catchment stretch, as well as the total catchment area upstream from the lower point of the considered stretch were the main abiotic factors controlling the formation of the asymmetry. Microclimatic differentiation due to differences in radiation input caused by the uneven topography favoured the relative stabilization of the shadier hillslope and its colonization by biocrusts and later by plants. The effect of the biocrusts and vegetation protection against water erosion on shadier hillslopes is often stronger than that of the set of abiotic factors and gives rise to asymmetries with lower gradients in the shady hillslope by promoting lateral displacement of the channel. We hypothesised that the opposite pattern, with the sunnier hillslope having a lower gradient, occurs when abiotic factors control the development of asymmetry formation. In these conditions, the effect of biocrusts and plants would act in the opposite direction. We propose a conceptual model of feedbacks generating catchment asymmetry, with biocrust playing a crucial role.
查看更多>>摘要：Cover crops are promoted to improve soil health and soil carbon (C) sequestration in agroecosystems, yet responses of various soil organic carbon (SOC) and nitrogen (N) components to cover cropping have not been quantified for water-limited environments. This study evaluated the response of SOC and N components to different cover crops and mixtures in limited irrigation winter wheat (Triticum aestivum L.)-sorghum (Sorghum bicolor L. Moench)-fallow rotation. Cover cropping treatments included pea (Pisum sativum L.), oats (Avena sativa L.), and canola (Brassica napus L.); mixtures of pea + oats (POmix), pea + canola (PCmix), pea + oats + canola (POCmix), and a six-species mixture (SSmix) of pea + oats + canola + hairy vetch (Vida vinosa Roth) + forage radish (Raphanus sativus L.) + barley (Hordeum vulgare L.); and a fallow. Cover crop treatments were arranged in a randomized complete block design within each phase of the crop rotation. Soil samples were collected in the summer of 2019 and 2020 from the 0-15 cm depth of study plots established in fall 2015 and analyzed for various soil organic matter (SOM) components. Soil inorganic N was 7-36% lower with cover crops than fallow. The PCmix had 48-73% greater 24-h-carbon dioxide-carbon (CO2-C) than fallow, canola, and SSmix at termination time. Thirty-six days after termination, particulate organic carbon (OC) content was 61-69% higher with pea, SSmix, and POCmix than fallow. The SOC content was 9.3-22% greater with oats than pea, canola, POmix, and SSmix. Similarly, total N content with oats was 10% and 22% higher than with SSmix and canola, respectively. The increase in SOC and total N were primarily observed in intermediate-size aggregates (250 mu m-2 mm and 53-250 mu m). However, the minimum data set of soil health included SOC, soil pH, labile organic nitrogen (LON), mineral-associated organic nitrogen (MAON), and microbial biomass carbon (MBC). While this study showed a diverse response of SOC and N components to various cover crop treatments, oats and their mixture as cover crops had greater SOC and total N than other cover crops. Cover cropping could improve soil health in crop-fallow rotations in water-limited environments.
查看更多>>摘要：An increasing number of soil spectral libraries are being developed at larger extents, including at national, continental, and global scales. However, the prediction accuracy of these libraries was often fairly poor when used on local scales. This study evaluates different strategies to improve the model accuracy of a regional spectral library for soil organic carbon prediction in four different local target areas. In total, five strategies using the Partial least squares regression (PLSR) were compared, including the use of local, spiked-regional, spiked-subsetregional and two localized models (memory based learning (MBL) and localized PLSR). MBL derives a new local prediction model based on a subset of the regional spectra similar to the new sample to be predicted. A localized PLSR calibrates a linear regression model using projected scores of the local samples derived from a pre-trained regional PLSR model. Validation results showed that the performances of the spiked models were not much better than those derived from the local and localized models. With >20 local samples, the localized PLSR model performed better than both the local and spiked-regional models. MBL model achieved similar performance to the localized PLSR model. Nevertheless, the accuracy of the models was heavily affected by both the spectral similarity of the data and the statistics of the predictand. Therefore, we recommend localizing the prediction models. Our results also suggest that spiking affected the regression coefficients of the PLSR models but not the loadings, which enabled the compression of spectra data into informative PLS scores. If the local spectra have low similarity to the regional spectral library, building a local spectral library would be more beneficial, assuming the sample size is large enough (>30).
NSTL
Elsevier