钝化剂对土壤重金属镉含量及其在川麦冬中累积的影响

目的 通过盆栽实验,综合评价不同钝化材料对土壤镉的钝化以及对川麦冬Cd含量降解的影响。方法 以一年生川麦冬为供试材料,采用土壤盆栽实验方法研究了钝化材料汉白玉（Ar）、秸秆生物炭（Br）、粉煤灰（Fh）、菌渣（Me）、硅藻土（Dm）对土壤总Cd、有效Cd和川麦冬各部Cd吸收累积的影响。结果 2种Cd污染程度土壤,不同钝化材料处理下均能提高土壤pH值;土壤阳离子交换量均极显著高于对照组,与土壤pH值成正相关;土壤总Cd含量和土壤有效Cd、麦冬地上部和地下部Cd含量较对照均极显著降低。综合各项指标发现,Ar对重金属Cd的钝化效果最佳,Br和Fh效果其次。结论 结合盆栽实验结果来看,Ar、Br、Fh、Me和Dm能够有效降低土壤总Cd含量、有效Cd含量和麦冬各部Cd含量,还能促进麦冬的稳收增产;综合分析,Ar、Fh和Br对重金属Cd钝化效果最好,可作为涪城麦冬种植区土壤钝化修复首选材料。     

枯萎病对菊花根际土壤微生物群落结构的影响

目的 探究患枯萎病菊花与健康菊花根际土壤微生物群落的差异。方法 以患病菊花植株和健康菊花植株根际土壤为研究材料,采用高通量测序技术对患病植株和健康植株样本的细菌16S rDNA和真菌内部转录间隔区（ITS）基因进行序列测定并进行数据分析。结果 枯萎病的发生降低了菊花根际土壤中细菌种群的丰富度和多样性程度,但对根际土壤中的真菌α-多样性无明显影响。菊花健康植株根际土壤细菌微生物中酸杆菌门、芽单胞菌门、硝化螺旋菌门占比高于患病植株,而变形菌门、拟杆菌门占比低于患病植株（P<0.05）。菊花患病植株根际土壤中镰刀菌属（Fusarium）真菌占比分别为27.49%,14.53%,11.94%,而健康植株镰刀菌属真菌占比分别为0.47%,1.01%,0.67%。菊花患病植株根际土壤中会出现细菌性致病菌果胶杆菌属（Pectobacterium）和菊迪基氏菌属（Dickeya）,而健康植株根际土壤中硝化类细菌、解毒类细菌、光合细菌等丰度高于患病植株。结论 患有枯萎病地块菊花植株根际土壤微生物中细菌的物种多样性和丰富度降低,并大量富集镰刀菌属致病真菌和积累果胶杆菌属与菊迪基氏菌属致病细菌,而健康菊花植株根际土壤微生物有益菌占比明显高于患病植株。     

Effect of Low Zeolite Doses on Plants and Soil Physicochemical Properties

Thousands of tons of zeolitic materials are used yearly as soil conditioners and components of slow-release fertilizers. A positive influence of application of zeolites on plant growth has been frequently observed. Because zeolites have extremely large cation exchange capacity, surface area, porosity and water holding capacity, a paradigm has aroused that increasing plant growth is caused by a long-lasting improvement of soil physicochemical properties by zeolites. In the first year of our field experiment performed on a poor soil with zeolite rates from 1 to 8 t/ha and N fertilization, an increase in spring wheat yield was observed. Any effect on soil cation exchange capacity (CEC), surface area (S), pH-dependent surface charge (Qv), mesoporosity, water holding capacity and plant available water (PAW) was noted. This positive effect of zeolite on plants could be due to extra nutrients supplied by the mineral (primarily potassium—1 ton of the studied zeolite contained around 15 kg of exchangeable potassium). In the second year of the experiment (NPK treatment on previously zeolitized soil), the zeolite presence did not impact plant yield. No long-term effect of the zeolite on plants was observed in the third year after soil zeolitization, when, as in the first year, only N fertilization was applied. That there were no significant changes in the above-mentioned physicochemical properties of the field soil after the addition of zeolite was most likely due to high dilution of the mineral in the soil (8 t/ha zeolite is only ~0.35% of the soil mass in the root zone). To determine how much zeolite is needed to improve soil physicochemical properties, much higher zeolite rates than those applied in the field were studied in the laboratory. The latter studies showed that CEC and S increased proportionally to the zeolite percentage in the soil. The Qv of the zeolite was lower than that of the soil, so a decrease in soil variable charge was observed due to zeolite addition. Surprisingly, a slight increase in PAW, even at the largest zeolite dose (from 9.5% for the control soil to 13% for a mixture of 40 g zeolite and 100 g soil), was observed. It resulted from small alterations of the soil macrostructure: although the input of small zeolite pores was seen in pore size distributions, the larger pores responsible for the storage of PAW were almost not affected by the zeolite addition.     

EPR Spectroscopy as a Tool to Characterize the Maturity Degree of Humic Acids

The major indicator of soil fertility and productivity are humic acids (HAs) arising from decomposition of organic matter. The structure and properties of HAs depend, among others climate factors, on soil and anthropogenic factors, i.e., methods of soil management. The purpose of the research undertaken in this paper is to study humic acids resulting from the decomposition of crop residues of wheat (Triticum aestivum L.) and plant material of thuja (Thuja plicata D.Don.ex. Lamb) using electron paramagnetic resonance (EPR) spectroscopy. In the present paper, we report EPR studies carried out on two types of HAs extracted from forest soil and incubated samples of plant material (mixture of wheat straw and roots), both without soil and mixed with soil. EPR signals obtained from these samples were subjected to numerical analysis, which showed that the EPR spectra of each sample could be deconvoluted into Lorentzian and Gaussian components. It can be shown that the origin of HAs has a significant impact on the parameters of their EPR spectra. The parameters of EPR spectra of humic acids depend strongly on their origin. The HA samples isolated from forest soils are characterized by higher spin concentration and lower peak-to-peak width of EPR spectra in comparison to those of HAs incubated from plant material.     

Effect of Fine Size-Fractionated Sunflower Husk Biochar on Water Retention Properties of Arable Sandy Soil

Biochar application has been reported to improve the physical, chemical, and hydrological properties of soil. However, the information about the size fraction composition of the applied biochar as a factor that may have an impact on the properties of soil-biochar mixtures is often underappreciated. Our research shows how sunflower husk biochar (pyrolyzed at 650 °C) can modify the water retention characteristics of arable sandy soil depending on the biochar dose (up to 9.52 wt.%) and particle size (<50 µm, 50–100 µm, 100–250 µm). For comparison, we used soil samples mixed with biochar passed through 2 mm sieve and an unamended reference. The addition of sieved biochar to the soil caused a 30% increase in the available water content (AWC) in comparing to the soil without biochar. However, the most notable improvement (doubling the reference AWC value from 0.078 m³ m⁻³ to 0.157 m³ m⁻³) was observed at the lowest doses of biochar (0.95 and 2.24 wt.%) and for the finest size fractions (below 100 µm). The water retention effects on sandy soil are explained as the interplay between the dose, the size of biochar particles, and the porous properties of biochar fractions.     

The extent of soil loss across the US Corn Belt

Soil erosion in agricultural landscapes reduces crop yields, leads to loss of ecosystem services, and influences the global carbon cycle. Despite decades of soil erosion research, the magnitude of historical soil loss remains poorly quantified across large agricultural regions because preagricultural soil data are rare, and it is challenging to extrapolate local-scale erosion observations across time and space. Here we focus on the Corn Belt of the midwestern United States and use a remote-sensing method to map areas in agricultural fields that have no remaining organic carbon-rich A-horizon. We use satellite and LiDAR data to develop a relationship between A-horizon loss and topographic curvature and then use topographic data to scale-up soil loss predictions across 3.9 × 10⁵ km² of the Corn Belt. Our results indicate that 35 ± 11% of the cultivated area has lost A-horizon soil and that prior estimates of soil degradation from soil survey-based methods have significantly underestimated A-horizon soil loss. Convex hilltops throughout the region are often completely denuded of A-horizon soil. The association between soil loss and convex topography indicates that tillage-induced erosion is an important driver of soil loss, yet tillage erosion is not simulated in models used to assess nationwide soil loss trends in the United States. We estimate that A-horizon loss decreases crop yields by 6 ± 2%, causing $2.8 ± $0.9 billion in annual economic losses. Regionally, we estimate 1.4 ± 0.5 Pg of carbon have been removed from hillslopes by erosion of the A-horizon, much of which likely remains buried in depositional areas within the fields.

Productive agricultural soils are vital for producing food for a growing global population (1–3). However, degradation of soil quality by erosion reduces crop yields, which can result in food insecurity, conflict (3), and the decline of civilizations (4). Degradation of soils leads not only to economic losses for farmers but also a loss in ecosystem services (5), which alters the ability of soils to regulate hydrologic and biogeochemical cycles. Widespread use of synthetic fertilizers to enhance the function of degraded soils increases food production costs (6) and impairs water resources (7), which negatively impacts human health (8) and aquatic ecosystems (9).Globally, the reservoir of carbon stored in soils is three times that in the atmosphere (10) and given the extent of agricultural land use (11), understanding soil carbon dynamics in agricultural systems is critical to understanding the carbon cycle (12). Whether soil erosion constitutes a net carbon sink or source depends on both the depositional fate of the eroded carbon and the ability to replace carbon in degraded soils (13–15). If biological productivity replaces eroded carbon, and decomposition of carbon stored in sedimentary deposits is halted or slowed, then soil erosion is a net sink of atmospheric carbon (14–17). However, if eroded carbon rapidly decomposes and is not replaced in eroded soil horizons, then soil erosion constitutes a carbon source. Restoring carbon to degraded soils therefore has potential to both reestablish soil function and sequester atmospheric CO₂ (10). However, quantifying the impacts of soil degradation on agricultural productivity and the carbon cycle first requires robust estimates of the magnitude of agriculturally induced soil loss (14, 16).Although thousands of soil erosion measurements have been made globally (18), the lack of a robust and scalable method for estimating the magnitude of erosion in agricultural landscapes remains a major gap in soil erosion research (19). Large-scale assessments of soil erosion are often based on model predictions (20–22) or qualitative information from soil surveys regarding the degree of soil degradation (23). In the United States, for example, nationwide soil loss trends (24) are simulated using water and wind erosion models that have been calibrated with erosion measurements made on small plots over a period of decades (21, 25). It has been debated whether upscaling such predictions to regional or national scales results in an accurate assessment of the current magnitude of soil loss in the United States (26, 27). Whereas such models are useful for assessing relative rates of erosion for soil conservation planning, the soil loss predictions do not provide information regarding the cumulative soil loss that has occurred since the initiation of cultivation, and hence the overall magnitude of agricultural soil degradation.To assess the degree of cumulative soil degradation, soil surveys conducted by the US Department of Agriculture have assigned erosion classes to soils based on the percentage of the original A horizon that has been eroded (28). Because the A horizon has the largest fraction of soil organic carbon within the soil profile, it is a key component of water and nutrient retention and soil productivity (29). Soils where 100% of the A-horizon thickness has been removed are designated as Class 4 eroded soils, and other classes represent lesser reductions in A-horizon thickness (<25%, 25 to 75%, and >75% for Classes 1, 2, and 3, respectively). A major disadvantage of the use of erosion classes is that properly assigning classes based on the percentage of A-horizon loss requires accurate determination of the original A-horizon thickness on all topographic positions (30). Hence, although soil erosion classes indicate soil degradation is widespread (23) we do not have a robust, quantitative understanding of how much soil has already been lost.Here we present results from a remote sensing method used to estimate the spatial extent of agriculturally induced loss of A-horizon soil for a major global agricultural region, the Corn Belt of the midwestern United States. Rather than simulate or measure short-term soil loss rates, we combine measurements of soil-surface reflectance in the visible spectrum (soil color) with high-resolution satellite imagery to directly measure the proportion of the agriculturally cultivated landscape that has completely lost its original A horizon. Combining our spectral analysis with relationships between A-horizon soil loss and topography derived from high-resolution LiDAR topographic data allows us to predict A-horizon soil loss in areas where images are not available. We find that historical soil erosion has completely removed A-horizon soil from approximately one-third of the Corn Belt. The spatial patterns of soil loss suggest that key erosion mechanisms are not simulated in nationwide assessments of soil erosion trends in the United States and that soil survey data greatly underestimate the extent of A-horizon loss.     

Soil animals alter plant litter diversity effects on decomposition

Most of the terrestrial net primary production enters the decomposer system as dead organic matter, and the subsequent recycling of C and nutrients are key processes for the functioning of ecosystems and the delivery of ecosystem goods and services. Although climatic and substrate quality controls are reasonably well understood, the functional role of biodiversity for biogeochemical cycles remains elusive. Here we ask how altering litter species diversity affects species-specific decomposition rates and whether large litter-feeding soil animals control the litter diversity-function relationship in a temperate forest ecosystem. We found that decomposition of a given litter species changed greatly in the presence of litters from other cooccurring species despite unaltered climatic conditions and litter chemistry. Most importantly, soil fauna determined the magnitude and direction of litter diversity effects. Our data show that litter species richness and soil fauna interactively determine rates of decomposition in a temperate forest, suggesting a combination of bottom-up and top-down controls of litter diversity effects on ecosystem C and nutrient cycling. These results provide evidence that, in ecosystems supporting a well developed soil macrofauna community, animal activity plays a fundamental role for altered decomposition in response to changing litter diversity, which in turn has important implications for biogeochemical cycles and the long-term functioning of ecosystems with ongoing biodiversity loss.     

2013年泰州市医药高新区居民主要死因监测结果分析

目的：了解泰州市医药高新区2013年居民主要死亡原因及顺位,为疾病防控工作的决策、制定干预措施及评价干预效果提供依据。方法：数据来源于2013年1月1日-2013年12月31日录入中国疾病预防控制信息死因登记报告系统中的人口死亡数据,死因分类依据国际疾病分类ICD-10进行疾病分类,各死因构成从大到小进行顺位,将监测数据转换成DeathReg系统数据,用死因统计软件DeathReg2005进行统计分析。结果：2013年泰州市医药高新区居民死亡率为664.61/10万,其中男性死亡率为766.54/10万,女性死亡率为563.46/10万,男女死亡性别比为1.35∶1。慢性非传染性疾病占据主要死因位置,其中,循环系统疾病占慢性病死亡构成比最高,为43.82%,肿瘤为38.07%、呼吸系统疾病为4.87%,三者合计占慢性病死亡的86.76%。结论：慢性病防治工作的重点应加强对恶性肿瘤及循环系统疾病的干预,以减少慢性病对人群健康的危害。     

石墨炉原子吸收法测定土壤中的微量镉

目的探讨用石墨炉原子吸收分光光度法测定土壤中的微量镉。方法在选定的微波条件下,通过硝酸一氢氟酸一盐酸对土壤进行样品的消解,然后用石墨炉原子吸收进行测定。结果在0～5．0μg／L浓度范围内,线性关系良好,相关系数r=0．9996,检出限为0．110μg／L,变异系数〈5％,样品加标回收率为96％～106％。结论该方法具有简单、分析速度快,结果准确等优点。     

不同秸秆还田量对旱地全膜双垄沟播土壤水分及玉米生长的影响

在通渭半干旱区通过试验研究了不同秸秆还田量对全膜双垄沟播玉米生长形状、土壤水分状况及产量的影响。试验设计了3个还田量梯度,即玉米秸秆按6 000 kg·hm^-2（低量还田处理）、9 000 kg·hm^-2（中量还田处理）、12 000 kg·hm^-2（高量还田处理）整秆还田,不还田处理作为对照。结果表明,在生育前期时,0～200 cm土壤水分呈现出还田量越高土壤含水量越高的趋势,在出苗期最为明显,高、中、低还田量处理较对照土壤含水量分别高出6.07%、1.24%、0.31%,而在抽雄期后,则表现为低量还田处理>中量还田处理>不还田处理>高量还田处理,叶面积大小表现为高量还田处理>中量还田处理>低量还田处理>不还田处理。耗水量表现为低量还田处理<中量还田处理<不还田处理<高量还田处理。产量及水分利用效率以6 000 kg·hm^-2还田量处理最高,适宜在半干旱旱作区进行推广。