Legionella spp. in UK composts—a potential public health issue?

Over the past 5 years, a number of cases of legionellosis in Scotland have been associated with compost use; however, studies investigating sources of infection other than water systems remain limited. This study delivers the first comprehensive survey of composts commonly available in the UK for the presence of Legionella species. Twenty-two store-bought composts, one green-waste compost and one home-made compost were tested for Legionella by culture methods on BCYE-α medium, and the findings were confirmed by macrophage infectivity potentiator (mip) speciation. Twenty-two of the samples were retested after an enrichment period of 8 weeks. In total, 15 of 24 composts tested positive for Legionella species, a higher level of contamination than previously seen in Europe. Two isolates of Legionella pneumophila were identified, and Legionella longbeachae serogroup 1 was found to be one of the most commonly isolated species. L. longbeachae infection would not be detected by routine Legionella urinary antigen assay, so such testing should not be used as the sole diagnostic technique in atypical pneumonia cases, particularly where there is an association with compost use. The occurrence of Legionella in over half of the samples tested indicates that compost could pose a public health risk. The addition of general hygiene warnings to compost packages may be beneficial in protecting public health.     

Natural and anthropogenic radioactivity levels and the associated radiation hazard in the soil of Oodalia Tea Estate in the hilly region of Fatickchari in Chittagong,Bangladesh

Radioactivity in the soil of a tea garden in the Fatickchari area in Chittagong, Bangladesh, was measured using a high-resolution HPGe detector. The soil samples were collected from depths of up to 20 cm beneath the soil surface. The activity concentrations of naturally occurring ²³⁸U and ²³²Th were observed to be in the range of 27 ± 7 to 53 ± 8 Bq kg⁻¹ and 36 ± 11 to 72 ± 11 Bq kg⁻¹, respectively. The activity concentration of ⁴⁰K ranged from 201 ± 78 to 672 ± 81 Bq kg⁻¹, and the highest activity of fallout ¹³⁷Cs observed was 10 ± 1 Bq kg⁻¹. The average activity concentration observed for ²³⁸U was 39 ± 8 Bq kg⁻¹, for ²³²Th was 57 ± 11 Bq kg⁻¹, for ⁴⁰K was 384 ± 79 Bq kg⁻¹ and for ¹³⁷Cs was 5 ± 0.5 Bq kg⁻¹. The radiological hazard parameters (representative level index, radium equivalent activity, outdoor and indoor dose rates, outdoor and indoor annual effective dose equivalents, and radiation hazard index) were calculated from the radioactivity in the soil.     

艾比湖湿地土壤粒度特征分析

为了探明阿拉山口大风对地表土壤粒度分布的影响，本文选取阿拉山口风向影响下的阿拉山口地区（A区域），博河、精河下游河岸带（B区域），阿奇克苏河下游河岸带（C区域）作为研究区，三个区域的表层土壤作为研究对象，以艾比湖湿地表层土壤粒度测试实验为基础，分析土壤粒度及空间分布的特征。平均粒径结果表明：阿拉山口区、博河，精河下游河岸带、阿奇克苏河下游河岸带粒径分别为101.49 μm、77.54 μm、49.82 μm；偏度特征为：三个区域的偏度均值结果显示为正偏态，分别为为4.01（阿拉山口区域）、3.71（博、精河区域）、2.77（阿其克苏河区域）。土壤质地分级结果为：阿拉山口区土壤质地以粗砂为主，博河，精河下游河岸带以沙砾和粉砂为主，阿奇克苏河下游河岸带以粉砂为主。上述结果定量地揭示了阿拉山口常年的风力侵蚀作用及其人类活动对该区域表层土壤粒度的影响。     

CHEMICAL CONTROL OF EUCALYPT VEGETATION

Methods of controlling unwanted eucalypt vegetation by chemical means were examined. Picloram was by far the best chemical tested for killing existing eucalypt coppice when applied as a foliar spray.

A number of chemicals, including 2,4,5-T, picloram, and AMS were effective in preventing coppice growth from cut stumps when applied as complete stump sprays. 2,4,5-T and picloram gave most promise of success when applied as surface treatments only. A delay of three months between the time the trees were felled and treatment was too long for cut stump treatments to be fully effective.

Sodium arsenite was the most effective arboricide tested on standing cull trees, and picloram was the best alternative.

The season of application had no apparent effect on killing or preventing coppice growth, but late winter to spring was the best time at which to treat standing cull trees.     

Predicting long-term dynamics of soil salinity and sodicity on a global scale

Knowledge of spatiotemporal distribution and likelihood of (re)occurrence of salt-affected soils is crucial to our understanding of land degradation and for planning effective remediation strategies in face of future climatic uncertainties. However, conventional methods used for tracking the variability of soil salinity/sodicity are extensively localized, making predictions on a global scale difficult. Here, we employ machine-learning techniques and a comprehensive set of climatic, topographic, soil, and remote sensing data to develop models capable of making predictions of soil salinity (expressed as electrical conductivity of saturated soil extract) and sodicity (measured as soil exchangeable sodium percentage) at different longitudes, latitudes, soil depths, and time periods. Using these predictive models, we provide a global-scale quantitative and gridded dataset characterizing different spatiotemporal facets of soil salinity and sodicity variability over the past four decades at a ∼1-km resolution. Analysis of this dataset reveals that a soil area of 11.73 Mkm² located in nonfrigid zones has been salt-affected with a frequency of reoccurrence in at least three-fourths of the years between 1980 and 2018, with 0.16 Mkm² of this area being croplands. Although the net changes in soil salinity/sodicity and the total area of salt-affected soils have been geographically highly variable, the continents with the highest salt-affected areas are Asia (particularly China, Kazakhstan, and Iran), Africa, and Australia. The proposed method can also be applied for quantifying the spatiotemporal variability of other dynamic soil properties, such as soil nutrients, organic carbon content, and pH.

Soil salinization is one of the main land-degrading threats influencing soil fertility, stability, and biodiversity. Saline soils are ones with excess accumulation of soluble salts in the root zone (1). On the other hand, accumulation of high levels of sodium salt relative to other exchangeable cations is the main attribute of sodic soils (2). Wind, rainfall, and parent rock weathering are the main origins of these salts in “primary” soil salinization, whereas in “secondary” soil salinization excessive salt accumulation is human-induced (3). Saline and sodic soils, or in general salt-affected soils, mostly lie across arid and semiarid climates where the dominance of evaporation over precipitation concentrates the salts in the root zone (1, 4), leading to undesirable alterations in the physical, chemical, and biological functions of the soil (5, 6). Sodicity adversely influences the soil infiltration capacity (7), increases the susceptibility of water and wind-blown erosion (8), and exposes more soil organic matter to decomposing processes (9). Soil salinity, on the other side, distresses the soil respiration, nitrogen cycle, and decomposing functionality of soil microorganisms (9, 10). Salinity stress affects the vegetation growth directly by reducing the plant water uptake (osmotic stress) and/or by deteriorating the transpiring leaves (specific ion effects) (11), in turn reducing organic input to the soil and ultimately leading to desertification of lands (12, 13). Under extreme conditions, dispersion of saline dust (8, 14), poverty, migration, and high costs of soil reclamation are long-term socioeconomic consequences of soil salinization (15).Soil salinity and sodicity levels are spatially, vertically, and temporally dynamic (15, 16), particularly at the top 0- to 30-cm soil layer which is substantially affected by governing climatic conditions. Naturally occurring events, such as flash floods, El Niño and La Niña, alternative wet and dry years, and long periods of drought can considerably affect soil salinization and accumulation/leaching of the salts in/from the root zone at daily to multiyear temporal resolutions. Similarly, anthropogenic activities like irrigation and dryland management can affect soil salinization at different temporal resolutions. Given the high dynamism in soil salinization processes, updated spatial and temporal information on the extent of salt-affected soils is indispensable for devising appropriate sustainable action programs for managing land and soil resources (6, 17–19). This information can be also valuable for enhancing our understanding of terrestrial carbon dynamics (7, 20), food security and agricultural modeling (21, 22), climate change impacts (23, 24), water resources and irrigation management (25, 26), and efficiency of organic/inorganic reclamation practices (27, 28). Several statistics on the global distribution of salt-affected soils (17–19, 29–33) have been generated based on data from soil surveys and statistical extrapolation (1, 19), yet these estimations are mainly purely spatial (17, 34), not necessarily up-to-date (15, 17), and in some cases incomparable (3, 35). Therefore, there is still a need for a methodologically consistent dataset documenting long-term variations of the soil salinity and sodicity at high spatial resolutions (36)To address this need, we focused on two target variables: ground-derived measurements of soil EC_e (the ability of a water-saturated soil paste extract to conduct electrical current, representative of salinity severity) and ESP (exchangeable sodium percentage, representative of sodicity severity). We used 42,984 and 197,988 data, respectively, scattered over time from 1980 to 2018. We trained two-part predictive models for making four-dimensional (4D) predictions of soil salinity and sodicity as target variables (longitude, latitude, soil depth, and time; see Methods). Through mapping data-driven relations between soil EC_e/ESP observations and a collection of associated predictors generated from topographic, climatic, vegetative, soil, and landscape properties of the sampling locations (SI Appendix, Table S1), these two-part models enabled us to make long-term gridded predictions of soil salinity and sodicity at new locations with available predictors’ values. Note that “prediction” refers to the estimation by the trained models of soil salinity/sodicity on a global scale from 1980 to 2018 even in locations where there is no measurement available rather than to future projection of soil salinity/sodicity on the basis of current trends. The first part of the models classified the soil into saline/sodic and nonsaline/nonsodic classes (binary classification) and the second part predicted per-class severity of the salinity/sodicity issue (regression). Meaningful statistics derived from the EC_e and ESP predictions were then used to generate univariate thematic maps of the variability of different aspects of soil salinity/sodicity between 1980 and 2018 at ∼1-km spatial resolution (30 arc-seconds; e.g., Fig. 1). These were delimited to −55° and 55° latitudes, comprising tropics, subtropics, and temperate zones (see Data Availability). We focused on the topsoil layer (or surface soil), referring to the top 30 cm of the soil profile measured from the surface.Open in a separate windowFig. 1.Variability of different aspects of soil salinity and sodicity in the western United States. (A and D) SD of annually predicted soil salinity (EC_e) and sodicity (ESP), respectively, between 1980 and 2018. (B and E) Average of annually predicted EC_e and ESP, respectively (1980 to 2018). (C and F) Change in the likelihood (θ) of soils with an EC_e ≥4 dS⋅m⁻¹ or ESP ≥6% in the period 2000 to 2018 relative to 1981 to 1999 (the likelihood is dimensionelss, calculated by dividing the number of years with EC_e ≥4 dSm⁻¹ or ESP ≥6% by the total number of years in the studied period). Positive θ indicates that the likelihood has increased and negative shows that it has decreased.     

天津蓟县山区药用植物根际及自然土壤无机元素含量测定

[目的] 通过对天津蓟县山区8个代表区域的土壤以及常用重点药材根际土壤中无机元素[铁、锰、铜、锌、钾、钙、镁、铅、镉(Fe、Mn、Cu、Zn、K、Ca、Mg、Pb、Cd)]的含量测定,分析与评价土壤背景质量,为天津野生中药扩大种植奠定基础。[方法] 电热板湿法消解,火焰原子吸收光谱法测定Fe、Mn、Cu、Zn、K、Ca、Mg的含量,石墨炉原子吸收光谱法测定Pb、Cd的含量。[结果] 8个区域自然土壤样品中大量元素Fe、K、Ca、Mg的含量较多,Cu、Zn、Pb的含量水平相当。重金属元素Cu、Zn、Pb的含量均未超出标准,1个区域中Cd的含量稍有超标,但尚未对生态环境造成影响。药用植物根际土壤无机元素水平与蓟县山区自然土壤相当。[结论] 天津蓟县土壤无机元素含量适中,均达到自然背景水平,土壤整体质量较优。     

生草和树枝覆盖对果园土壤持水性能的影响--测试文章

针对黄土高原枣园普遍盛行传统清耕制,将生草及覆盖技术引入枣园生产中,于2011—2013年采用人工土槽模拟研究方法,探讨不同生草和覆盖措施对枣树地土壤持水性能的影响。结果表明：生草与枣树枝覆盖能有效改善土壤物理结构、提高土壤孔隙度、降低土壤容重;各处理土壤水分蓄持能力及比水容量均按枣树枝半覆盖+白三叶生草、枣树枝全覆盖、白三叶生草覆盖和清耕处理依次递减,处理间的差异在高吸力阶段更为明显;与清耕处理相比,生草与覆盖处理土壤饱和含水量、田间持水量、凋萎系数均有提高,枣树枝半覆盖+白三叶生草处理增加最为明显,分别增加9%、20%、33%。     

微咸水灌溉条件下施用不同改良剂对盐渍化土壤盐分离子分布的影响--测试文章

利用5种不同的土壤改良剂,对矿化度在2～3 g·L^-1的微咸水灌溉棉田土壤进行改良效果研究。结果表明：五种改良剂均降低土壤pH值和总盐含量,并能有效控制土体Na⁺、Ca²⁺、SO₄^2-、HCO₃^-积累;其中,磷石膏能显著降低土体Na⁺、Ca²⁺、SO₄^2-总含量（P＜0.05）,DS1997能显著降低土体Na⁺、HCO₃^-总含量（P＜0.05）,酸碱平衡剂显著降低土体Ca²⁺、SO₄^2-总含量（P＜0.05）,禾康改良剂有效控制土体SO₄^2-、HCO₃^-含量;改良剂对土体中Cl^-改良效果不显著（P＞0.05）。研究得出：微咸水灌溉导致土壤pH值升高和含盐量增加,造成土壤盐分的积累;土壤改良剂可有效减少微咸水灌溉引起的盐分积累,改善土壤理化特性和盐分离子分布。     

Pattern of in-hospital pediatric mortality over a 3-year period at University teaching hospitals in Iran

Introduction:

Causes of death are different and very important for policy makers in different regions. This study was designed to analyze the data for our in-patient children mortality.

Materials and Methods:

In this cross-sectional study from March 2011 to March 2013, all patients from 2 months to 18 years who died in pediatric intensive care unit, emergency room or medical pediatric wards in the teaching hospitals were studied.

Results:

From a total of 18,915 admissions during a 2-year-period, 256 deaths occurred with a mean age of 4.3 ± 5 years and mortality 1.35%. An underlying disease was present in 70.7% of the patients and in 88.5% of them the leading causes of death were related to the underlying diseases. The most common underlying diseases were congenital heart disease and cardiomyopathy in 50 (27.6%). The four main causes of deaths were sepsis (14.8%), pneumonia (14.5%), congestive heart failure (9.8%), and hepatic encephalopathy (9.8%).

Conclusion:

We may conclude that after sepsis and pneumonia, congestive heart failure, and hepatic encephalopathy are the leading causes of death. Most patients who died had underlying diseases including malignancies, heart and liver diseases as the most common causes.