Inhibiting soil loss and runoff from small plots induced by an individual freeze-thaw cycle using three rangeland species

This study investigated the role of three rangeland species viz. Agropyron trichophorum, Medicago sativa, and Lolium prenne on mitigating of effects of a freeze-thaw (FT) cycle on runoff generation and soil loss from small experimental plots. Small plots (0.5 × 0.5m) were prepared in three replicates for control (i.e., under a FT cycle only) and treatments (i.e., individually planted with the study species and subject to a FT cycle). The treated plots were then placed at a slope of 20% and subjected to simulated rainfall with intensity of 70 mm h⁻¹ and 30 min duration. The results of the study showed a significant effect (P < 0.05) of the plants on controlling runoff and soil loss after a FT cycle. Also, the detrimental effects of the FT cycle due to performance of ice lenses and formation of an active melting layer in the soil surface were ameliorated by the presence of litter on the soil and root-binding effect of the plants. Time to runoff increased by 54, 111 and 10%, runoff volume decreased by 27, 68 and 0.4% and soil loss changed by −34, −62, and +6.5% in the plots planted with A. trichophorum, L. prenne and M. sativa, respectively. The results of the current study indicated that L. prenne had the maximum benefit on reducing runoff and soil loss from the plots undergoing a FT cycle.     

Effect of time resolution of rainfall measurements on the erosivity factor in the USLE in China

Rainfall erosivity, one of the factors in the Universal Soil Loss Equation, quantifies the effect of rainfall and runoff on soil erosion. High-resolution data are required to compute rainfall erosivity, but are not widely available in many parts of the world. As the temporal resolution of rainfall measurement decreases, computed rainfall erosivity decreases. The objective of the paper is to derive a series of conversion factors as a function of the time interval to compute rainfall erosivity so that the R factor computed using data at different time intervals could be converted to that computed using 1-min data. Rainfall data at 1-min intervals from 62 stations over China were collected to first compute the ‘true’ R factor values. Underestimation of the R factor was systematically evaluated using data aggregated at 5, 6, 10, 15, 20, 30, and 60-min to develop conversion factors for the R factor and the 1-in-10-year storm EI₃₀ values. Compared with true values, the relative error in R factor using data at fixed intervals of ≤10min was <10% for at least 44 out of 62 stations. Errors increased rapidly when the time interval of the rainfall data exceeded 15 min. Relative errors were >10% using 15-min data for 66.1% of stations and >20% using 30-min data for 61.3% of stations. The conversion factors for the R factor, ranging from 1.051 to 1.871 for 5 to 60-min data, are higher than those for the 1-in-10-years storm EI₃₀, ranging from 1.034 to 1.489 for the 62 stations.     

Study on a soil erosion sampling survey in the Pan-Third Pole region based on higher-resolution images

Soil erosion is one of the most severe global environmental problems, and soil erosion surveys are the scientific basis for planning soil conservation and ecological development. To improve soil erosion sampling survey methods and accurately and rapidly estimate the actual rates of soil erosion, a Pan-Third Pole region was taken as an example to study a methodology of soil erosion sampling survey based on high-spatial-resolution remote sensing images. The sampling units were designed using a stratified variable probability systematic sampling method. The spatiotemporal characteristics of soil erosion and conservation were taken into account, and finer-resolution freely available and accessible images in Google Earth were used. Through the visual interpretation of the free high-resolution remote sensing images, detailed information on land use and soil conservation measures was obtained. Then, combined with the regional soil erosion factor data products, such as rainfall-runoff erosivity factor (R), soil erodibility factor (K), and slope length and steepness factor (LS), the soil loss rates of some sampling units were calculated. The results show that, based on these high-resolution remote sensing images, the land use and soil conservation measures of the sampling units can be quickly and accurately extracted. The interpretation accuracy in 4 typical cross sections was more than 80%, and sampling accuracy, described by histogram similarity in 11 large sampling sites, show that the landuse of sampling uints can represent the structural characteristics of regional land use. Based on the interpretation of data from the sample survey and the regional soil erosion factor data products, the calculation of the soil erosion rate can be completed quickly. The calculation results can reflect the actual conditions of soil erosion better than the potential soil erosion rates calculated by using the coarse-resolution remote sensing method.     

Assessing spatial variability and erosion susceptibility of soils in hilly agricultural areas in Southern Italy

Soil erosion is one of the main environmental problems in the Mediterranean area. This problem is becoming even more important especially in Italy, in the Apennines, where severe erosive processes occur due to the action of concentrated running water. The erodibility (K-Factor) of a soil, estimated using the Revised Universal Soil Loss Equation (RUSLE), is a measure of its susceptibility to erosion and depends on several soil properties such as organic matter, texture and permeability and structure.To assess the spatial variability of soil properties and soil erodibility in hilly agricultural areas and to investigate the relationships between soil features and landscape morphodynamics, a detailed study in Molise region (southern Italy), in a small drainange basin located along its hilly Adriatic flank, was carried out. In this catchment, 63 topsoil samples (A horizons) were collected and 10 soil profiles, forming a catena crossing 3 land units, were sampled. The calculated K-Factors ranges between 0.012 and 0.048 t ha h ha⁻¹ MJ⁻¹ mm⁻¹ indicating a complex spatial distribution, due to the several local pedological and geomorphological factors affecting soil erodibility. The results give clear evidence about the relationships among soil characteristics, soil erodibility and landscape morpho-dynamics (land units).Comparing the soil loss rates estimated for the study area with those reported in literature, a good correspondence can be observed only for the more stable land unit, not characterized by intense erosive processes. The proposed methodology is suitable to highlight areas characterized by similar morphodynamics features, and comparable soil erodibility, for a more effective spatialization of K factor.     

The use of remote sensing to detect the consequences of erosion in gypsiferous soils

Tillage practices on sloping ground often result in unsustainable soil losses impairing soil functions such as crop productivity, water and nutrients storage, and soil organic carbon (SOC) sequestration. A sloping olive grove (10%) was planted in shallow gypsiferous soils in 2004. It was managed by minimum tillage; the most frequent management practice in central Spain. The consequences of erosion were studied in soil samples (at 0–10, 10–20, and 20–30 cm depths) by analyzing SOC, available water and gypsum content, and by detecting spectral signatures using an ASD FieldSpecPro® VIS/NIR-spectroradiometer. The Brightness index (BI), Shape index (FI), and Normalized Difference Vegetation Index (NDVI) were derived from the ASD spectral signatures and from remote sensing (Sentinel-2 image) data. The development of these young olive trees was estimated from the measured diameter of the trunks (17 ± 18 cm diameter). In 20–30 cm of the soil, the carbon stock (38 ± 18 Mg ha⁻¹) as well as the available water content (12 ± 6%) was scarce, affecting the productivity of the olive grove. The above-mentioned indices obtained from the laboratory samples and the pixels of the Sentinel-2 image were significantly (p < 0.01) correlated, with a correlation coefficient of around 0.4. The BI was related to the gypsum content and the slope of the plot. The FI was related to the carbon and water contents. The NDVI derived from the satellite image identified the influence of soil degradation on the trees and the carbon content. The spatial-temporal changes of the indices might help in tracking soil changes over time.     

甘肃民乐栽培当归的品质与土壤相关性分析

本研究通过对民乐县种植的当归药材和种植土壤分别进行采样测定,结果表明民乐县人工种植当归的质量稳定,受重金属污染的风险低,符合药典标准规定。相关性分析结果表明:浸出物与土壤pH值呈极显著正相关,与有机质呈极显著负相关;阿魏酸与土壤pH值呈极显著正相关,与全磷呈显著负相关。挥发油与测定的土壤因子之间无显著相关性。灰色关联度分析结果表明:土壤pH是影响当归浸出物、挥发油的重要因子,土壤有机质是影响当归阿魏酸含量的重要因子;且磷、全氮和有机质对浸出物、挥发油、阿魏酸的影响程度不同。综上所述,本研究结果揭示了土壤因子对民乐县种植当归品质的影响规律,可为民乐县规范化种植当归药材提供理论依据。     

局地尺度高寒草原土壤真菌多样性对地上植物多样性与生产力关系的调控作用

为研究局地尺度高寒草原土壤真菌多样性对地上植物多样性与生产力关系的调控作用，本研究以青海省湟源县局地尺度高寒草原为研究对象，对不同植物多样性梯度的地上生产力、土壤理化性状和土壤真菌多样性等指标进行调查、采样和分析。通过偏回归分析（partial least squares regression，PLSR）、方差分解分析（variance partitioning analysis，VPA）、构建结构方程模型（structural equation model，SEM）等分析手段，分析了土壤真菌多样性对地上植物多样性与生产力关系的调控作用。结果表明，高寒草原植物多样性与地上生产力存在显著线性正相关关系；土壤真菌多样性分别与植物多样性和地上生产力呈显著正相关关系；通过PLSR，VPA，SEM等方法控制土壤非生物因子效应后，真菌多样性与二者的显著正相关关系仍存在。综上所述，局地尺度下青海省湟源县高寒草原土壤真菌多样性是调控地上植物多样性与生产力正向关系的关键生物因子。     

黄土高原人工灌草系统不同立地条件土壤种子库特征

本研究通过野外调查取样与室内试验相结合，连续两年对黄土高原人工灌草系统不同坡向、坡位进行取样，以期对该区土壤种子库的物种组成、密度特征及其物种多样性进行初步了解。研究结果表明：该人工灌草生态系统土壤种子库共有9科，15种，其组成因坡位、坡向以及年份而异；坡向、坡位均显著影响土壤种子库物种多样性指数、丰富度指数与土壤种子库密度（P<0.05），土壤种子库密度为3 218～5 492粒·m^-2，总体呈现为阴坡显著高于阳坡（P<0.05），下坡位显著高于上坡位（P<0.05）；坡位和坡向均对物种均匀性系数无显著影响；年份对土壤种子库无显著影响。上述研究可为黄土高原人工灌草系统的可持续利用与恢复提供参考依据。     

不同发育阶段日本落叶松人工林枯落物层微生物群落特征

为探寻日本落叶松人工林在中龄林或近熟林阶段地力衰退的机制，以分子生物学实验手段与常规实验分析方法结合，分别对不同发育阶段林分枯落物未分解层、半分解层以及全分解层微生物的数量、群落结构以及理化性质进行分析，并采用冗余分析法探索枯落物层微生物群落结构与理化性质的相关性。结果表明：枯落物储量及养分储量随林分发育呈倒“V”字型变化趋势，在近熟林阶段最大，微生物数量、均匀度指数在中龄林或近熟林最低。不同发育阶段林分优势细菌种类基本相同，但相对含量不同；优势真菌的种类明显不同，尤其是在近熟林半分解层。中龄林与近熟林未、半分解层受环境因素影响较大，主要受pH、有效磷、碱解氮、速效钾、全钾、C/N以及林下植被生物量影响。因此，日本落叶松纯林在中龄林与近熟林阶段需强化植被管理，适时开展修枝间伐等经营措施，促进林下植被发育、改善枯落物性质，加速养分循环，缓解地力衰退。     

内蒙古高原紫花苜蓿土壤氮素丰缺指标和推荐施氮量

为了给内蒙古高原紫花苜蓿（Medicago sativa L.）测土施氮奠定科学基础，本研究采用“零散实验数据整合法”和“养分平衡-地力差减法”新应用公式，开展了该自然区域紫花苜蓿土壤氮素丰缺指标和推荐施氮量研究。结果表明：内蒙古高原生长第1年紫花苜蓿土壤碱解氮第1~6级丰缺指标为≥48，20~48，8~20，4~8，2~4和<2 mg·kg^-1，土壤全氮第1~5级丰缺指标为≥1.4，0.8~1.4，0.4~0.8，0.2~0.4和<0.2 g·kg^-1，土壤有机质第1~6级丰缺指标为≥17，10~17，6~10，3~6，2~3和<2 g·kg^-1。当紫花苜蓿目标产量9~18 t·hm^-2、氮肥利用率40%时，内蒙古高原紫花苜蓿第1~6级土壤推荐施氮量分别为0，68~135，135~270，203~405，270~540和338~675 kg·hm^-2。