Aggregate-associated changes in nutrient properties,microbial community and functions in a greenhouse vegetable field based on an eight-year fertilization experiment of China

Soil aggregation,microbial community,and functions(i.e.,extracellular enzyme activities;EEAs)are critical factors affecting soil C dynamics and nutrient cycling.We assessed soil aggregate distribution,stability,nutrients,and microbial characteristics within>2,0.25-2,0.053-0.25,and<0.053 mm aggregates,based on an eight-year field experiment in a greenhouse vegetable field in China.The field experiment includes four treatments:100%N fertilizer(CF),50%substitution of N frtilizer with manure(M),straw(S),and manure plus straw(MS).The amounts of nutrient(N,P20,and K20)input were equal in each treatment.Results showed higher values of mean weight diameter in organic amended soils(M,MS,and S,2.43-2.97)vs.CF-amended soils(1.99).Relative to CF treatment,organic amendments had positive effects on nutrient(i.e.,available N,P,and soil organic C(SOC))conditions,microbial(e.g,bacterial and fungal)growth,and EEAs in the>0.053 mm aggregates,but not in the<0.053 mm aggregates.The 0.25-0.053 mm aggregates exhibited better nutrient conditions and hydrolytic activity,while the<0.053 mm aggregates had poor nutrient conditions and higher oxidative activity among aggregates,per SOC,available N,available P,and a series of enzyme activities.These results indicated that the 0.25-0.053 mm(<0.053 mm)aggregates provide suitable microhabitats for hydrolytic(oxidative)activity.Interestingly,we found that hydrolytic and oxidative activities were mainly impacted by fertilization(58.5%,P<0.01)and aggregate fractions(50.5%,P<0.01),respectively.The hydrolytic and oxidative activities were significantly(P<0.01)associated with nutrients(SOC and available N)and pH,electrical conductivity,respectively.Furthermore,SOC,available N,and available P closely(P<0.05)afected microbial communities within>0.25,0.25-0.053,and<0.053 mm aggregates,respectively.These findings provide several insights into microbial characteristics within aggregates under dfferent frilization modes in the greenhouse vegetable production system in China.

Spatial analysis of snail distribution in Jiangning county

Objective: To explore the spatial distribution of oncomelenia snails in Jiangning County. Methods: Cluster analysis and the Spatial Scan Statistics were performed based on the density of alive-snails in habitats and its rate infected by the 5. japonicum. Results : Although areas of snail habitats and density of the alive-snails in marshland in 2000 are higher significantly than that in mountain areas in Jiangning County, the numbers of habitats in mountain are more than that in marshland and they distributed sporadically. The snail habitats were classified into 4 in marshlands and 3 classes in mountain areas respectively in cluster analysis. Although they are mainly the one with low density of alive and infected snails, we should alert that there are also some habitats with high snail density and infection rate, which is important for the transmission of schis-tosomia. The analysis of Spatial Scan Statistics detected 2 significant spatial aggregations for alive-snail in marshland and 4 in mountain areas respectively with p-values less than 0. 01. There are also 2 significant spatial aggregations for infected snails in marshland. Conclusion: The significant spatial aggregations for alive-snails and infected snails indicated that there are some factors in the habitats suitable for the survival of snails and the transmission of schistosomia.

Relationship between Abundance and Area of Pinus tabulaeformis and Quercus liaotungensis Koidz in Lingkong Mountain Nature Reserve

The spatial distribution and species abundance of Pinus tabulaeformis and Quercus liaotungensis Koidz were analyzed with random distribution abundance model and aggregated distribution abundance model,and evaluation goodness was evaluated based on related information of sample area at 4 hm2 in Shanxi Lingkong Mountain with altitude at 1500-1 800 m.The results showed that of the 30 xylophyta plants,abundance of 20 plants was increasing in sequence and the covered spaces extended accordingly,except of 10 plant species.As pixel area extended,curve of abundance-area tended to be volatile if area in abundance sequence was smaller than that of the front one;the curve tended to be stable if the fluctuating point was removed.For the same species,the higher pixel area is,the larger the covered area of the species in corresponding pixel would be.The results of evaluation goodness indicated that aggregated distribution model is better for prediction on relationship between abundance and area,compared with random distribution abundance model.Both of the two models rely on value of m,namely,number of covered pixel given the pixel is fixed.For the species distribute dispersedly,the prediction results would be more accurate if both of the two models are made use of,or the prediction errors would be larger.Given that the total area of sample plot is fixed,the smaller the pixel area is,the more accurate the prediction would be.

Soil Aggregation and Its Relationship with Organic Carbon of Purple Soils in the Sichuan Basin,China

The interaction of soil aggregate dynamics with soil organic carbon is complex with varied spatio-temporal processes in macro-and micro-aggregates. This paper is to determine the aggregation of soil aggregates in purple soils （Regosols in FAO Taxonomy or Entisols in USDA Taxonomy） for four types of land use, cropland [corn （Zea mays L.）], orchard （citrus）, forestland （bamboo or cypress）, and barren land （wild grass）, and to explore their relationship with soil organic carbon in the Sichuan basin of southwestern China. Procedures and methods, including manual dry sieving procedure, Yoder＇s wet sieving procedure, pyrophosphates solution method, and Kachisky method, are used to acquire dry, wet, and chemically stable aggregates, and microaggregates. Light and heavy fractions of soil organic carbon were separated using 2.0 g·mL^-1 HgI2-KI mixed solution. The loosely, stably, and tightly combined organic carbon in heavy fraction were separated by extraction with 0.1 M NaOH and 0.1 M NaOH-0.1M Na4P2O7 mixed solution （pH 13）. The results show that the contents of dry and wet macroaggregates 〉0.25 mm in diameter were 974.1 and 900.0 g·kg^-1 highest in red brown purple soils under forestland, while 889.6 and 350.6 g·kg^-1 lowest in dark purple soil and lowest in grey brown purple soils under cropland, respectively. The chemical stability of macroaggregates was lowest in grey brown purple soil with 8.47% under cropland, and highest in red brown purple soil with 69.34% under barren land. The content of microaggregates in dark purple soils was 587g·kg^-1 higher than brown purple soils, while 655g·kg^-1 in red brown purple soils was similar to grey brown purple soils （651g·kg^-1）. Cropland conditions, only 38.4% of organic carbon was of the combined form, and 61.6% of that existed in light fraction. Forestland conditions, 90.7% of organic carbon in red brown purple soil was complexed with minerals as a form of humic substances. The contents and stability of wet aggregates 〉 0.25 mm, contents and stability of chemically stable aggregates 〉0.25 mm, contents of microaggregates 〉 0.01 mm, contents of aggregated primary particle （d〈0.01 mm） and degree of primary particles （d 〈0.01 mm） aggregation were closely related to the concentrations of total soil organic carbon, and loosely and tightly combined organic carbon in heavy fraction. Soil microaggregation could be associated with organic carbon concentration and its combined forms in heavy fraction. There was a direct relationship between microaggregation and macroaggregation of soil primary particles, because the contents of wet aggregates 〉 0.25 mm and its water stability of aggregates were highly correlated with the contents of aggregated primary particle （d 〈 0.01 mm） and the degree of primary particles （d 〈 0.01 mm） aggregation.

On the Distributions of Two Classes of Multiple Dependent Aggregate Claims

In this paper we examine two classes of correlated aggregate claims distributions, with univariate claim counts and multivariate claim sizes. Firstly, we extend the results of Hesselager [ASTIN Bulletin, 24： 19-32（1994）] and Wang ＆ Sobrero＇s [ASTIN Bulletin, 24：161-166 （1994）] concerning recursions for compound distributions to a multivariate situation where each claim event generates a random vector. Then we give a multivariate continuous version of recursive algorithm for calculating a family of compound distribution. Especially, to some extent, we obtain a continuous version of the corresponding results in Sundt [ASTIN Bulletin, 29：29-45 （1999）] and Ambagaspitiya [Insurance： Mathematics and Economics, 24：301-308 （1999）]. Finally, we give an example and show how to use the algorithm for aggregate claim distribution of first class to compute recursively the compound distribution.

A Method of Assessing Parameters of Air-Void Structure in Air-Entrained Concretes

The air-void size distribution and number of air voids are crucial characteristics of air-entrainment. The standard spacing factor L is based on the Powers model, in which considerable simplifications are assumed. A better solution is provided by the Philleo factor, which determines the percentage content of protected paste located at a distance S from the edge of the nearest air void. Developing the concept put forward by Philleo, a method of determining the volume of protected paste on the basis of images generated from the numerical model of concrete grain structure including layout of aggregate-paste-air, is proposed. It is the ratio of the volume of the paste protected by air voids to the total paste volume. The PPV （protected paste volume） index accounts not only for sizes and number of air voids, but also for the role of aggregate particles in the placement of these pores, which is often disregarded in analyses. The PPV results obtained from image analysis were compared with standard spacing factor L and with the parameter developed by Philleo. The analyses conducted by the authors shows that accounting for aggregate grains in calculations substantially affects the assessment of the quality of the air-pore structure.

Aggregate sizes regulate the microbial community patterns in sandy soil profile

Soil microorganisms play a key role in the function of soil ecosystem,yet our knowledge about how microbial communities respond to the typically sandy soil environmental properties along the soil profile is still insufficient.We investigated the soil microbial community patterns from top(0–20 cm)to clay-layer(>80 cm)of the typical sandy soils in three regions in China with different levels of precipitation,including Lishu County in Jilin Province(LS),Langfang City in Hebei Province(LF)and Zhengzhou City in Henan Province(ZZ).Our findings showed that small-size aggregates(<0.5 mm)rather than large ones(³0.5 mm)dominated the soil profile.The relative abundances of Actinobacteria,Crenarchaeota and Firmicutes were highly related to aggregate proportions of the deep clay-layer soil.The network analysis revealed the distinct community patterns among modules,evidencing niche differentiation along the soil profile.The keystone species OTU_11292 was observed having migrated clearly into the other module of the clay-layer soil.Different roles of the OTU_30(belonging to Gemmatimonadetes)in soil processes might partly explain the different microbial distribution between top-and clay-layer soils.These findings provided new insights into the candidate mechanisms of microbial diversity maintenance and community patterning of sandy soils,which were necessary for better understanding of ecological rules guiding long-term agricultural practice.

Effects of land use patterns on soil aggregate stability in Sichuan Basin,China

Soil aggregate stability as a key indicator of soil structure, is a product of interactions between soil environment, management practices, and land use patterns. The objective of this study was to analyze the impact of various land use patterns on soil aggregate stability in Sichuan Basin of southwestern China. The dry- and water-stable aggregate size distributions were determined by manual dry sieving procedure and Yoder＇s wet sieving procedure, respectively, while microaggregates and its mechanical and chemical stabilities by Kachisky＇s method, oscillator method, and citrate-dithionate （C-D） reagent method, separately. The results indicated that fractal dimension and surface fractal dimension were useful indicators to reflect soil aggregate distribution. Land use patterns have an obvious influence on soil aggregate stability. In the study area, water stability, mechanical stability, and chemical stability followed the sequence, Barren land 〉 forestland 〉 orchard 〉 cropland, and the original stability and collapse velocity were sensitive to soil properties and soil structure. The difference of aggregate stability under different land use patterns is mainly due to the intensity of human disturbance and cultivation. Improper land use patterns will lead to breakdown of unstable aggregates, producing finer and more-easily transportable particles and microaggregates. In the future, inappropriate cultivation and land use patterns should be changed to protect soil structure, to improve soil aggregate stability and soil fertility in Sichuan Basin.

Estimating Water Retention with Pedotransfer Functions Using Multi-Objective Group Method of Data Handling and ANNs

Pedotransfer functions （PTFs） have been developed to estimate soil water retention curves （SWRC） by various techniques. In this study PTFs were developed to estimate the parameters （θs, θr, α and λ） of the Brooks and Corey model from a data set of 148 samples. Particle and aggregate size distribution fractal parameters （PSDFPs and ASDFPs, respectively） were computed from three fractal models for either particle or aggregate size distribution. The most effective model in each group was determined by sensitivity analysis. Along with the other variables, the selected fractal parameters were employed to estimate SWRC using multi-objective group method of data handling （mGMDH） and different topologies of artificial neural networks （ANNs）. The architecture of ANNs for parametric PTFs was different regarding the type of ANN, output layer transfer functions and the number of hidden neurons. Each parameter was estimated using four PTFs by the hierarchical entering of input variables in the PTFs. The inclusion of PSDFPs in the list of inputs improved the accuracy and reliability of parametric PTFs with the exception of ~s- The textural fraction variables in PTF1 for the estimation of a were replaced with PSDFPs in PTF3. The use of ASDFPs as inputs significantly improved a estimates in the model. This result highlights the importance of ASDFPs in developing parametric PTFs. The mCMDH technique performed significantly better than ANNs in most PTFs.

Discussion on research methods of bacterial resistant mutation mechanisms under selective culture——uncertainty analysis of data from the Luria-Delbrück fluctuation experiment

Whether bacterial drug-resistance is drug-induced or results from rapid propagation of random spontaneous mutations in the flora prior to exposure, remains a long-term key issue concerned and debated in both genetics and medicinal fields. In a pio-neering study, Luria and Delbruck exposed E. coli to T1 phage, to investigate whether the number of resistant colonies fol- lowed the Poisson distribution. They deduced that the development of resistant colonies is independent of phage presence. Similar results have since been obtained on solid medium containing antibacterial agents. Luria and Delbruck＇s conclusions were long considered a gold standard for analyzing drug resistance mutations. More recently, the concept of adaptive mutation has triggered controversy over this approach. Microbiological observation shows that, following exposure to drugs of various concentrations, drug-resistant cells emerge and multiply depending on the time course, and show a process function, incon-sistent with the definition of Poisson distribution （which assumes not only that resistance is independent of drug quantity but follows no specific time course）. At the same time, since cells tend to aggregate after division rather than separating, colonies growing on drug plates arise from the multiplication of resistant bacteria cells of various initial population sizes. Thus, statisti-cal analysis based on equivalence of initial populations will yield erroneous results. In this paper, 310 data from the Lu- ria-DelbNck fluctuation experiment were reanalyzed from this perspective. In most cases, a high-end abnormal value, resulting from the non-synchronous variation of the two above-mentioned time variables, was observed. Therefore, the mean value cannot be regarded as an unbiased expectation estimate. The ratio between mean value and variance was similarly incompara-ble, because two different sampling methods were used. In fact, the Luria-Delbrtick data appear to follow an aggregated, rather than Poisson distribution. In stmnnary, the statistical analysis of Luria and Delbruck is insufficient to describe rules of resistant mutant development and multiplication. Correction of this historical misunderstanding will enable new insight into bacterial resistance mechanisms.