Environmental correlates of two macro-decapods distribution in Central Italy: Multi-dimensional ecological knowledge as a tool for conservation of endangered species

Using a multi-dimensional ecological design, this study aimed first to analyse whether local environmental conditions can account for the spatial segregation of two Italian native decapods, the crayfish Austropotamobius italicus and the river crab Potamon fluviatile, in Central Italy freshwater ecosystems. Second, we aimed to analyse which environmental variables were more closely associated with the presence/absence of the two decapods in specific sites within their distribution area. Following a factorial design, a total of 32 sites were selected in two neighbouring geographic areas, one occupied by crayfish and one by crabs. Within each distribution area, eight streams where the decapod was present and eight where it was not present were selected. At each site, macro-invertebrate community composition and 16 abiotic variables were recorded and analysed with multi-variate methods. Variations in physical (minimum and maximum temperatures), chemical (calcium, oxygen, nitrate and nitrite) and geomorphological (substrate composition) parameters explained spatial segregation of P. fluviatile and A. italicus in the study area. The occurrence of crayfish reflected variations of chemistry (such as pH, calcium, nitrate and nitrite concentrations), temperature, water depth and substrate composition. On the contrary, the presence of the river crab, within its occurrence zone, was not associated to any biotic and abiotic parameters and was probably affected by anthropogenic pressure and uncontrolled harvesting. These findings provide fundamental ecological data for the maintenance of the two decapod natural populations as well as for the selection of areas and streams adequate for their reintroduction.     

A phenetic analysis and lateral key of the genus Lolium (Gramineae)

88 herbarium specimens of the genus Lolium were scored for 22 characters, comprising 7 vegetative, 8 inflorescence and 7 seed characters. The aim was to review the species relationship and to produce a lateral key to the genus. The data were analysed using principal components analysis, discriminant function analysis and cluster analysis. All analyses separated L. perenne, L. multiflorum and L. temulentum from each other. The 2 varieties of L. rigidum showed varying degrees of separation from each other and from L. multiflorum. Their distinction as a species and as 2 varieties is discussed. L. perenne and L. rigidum were shown to contain the greatest similarity between species and L. temulentum was found to be the most distinct. A lateral key is proposed that separates the species on the basis of 11 morphological characters that are easily scored in the field.     

The Application of Multivariate Statistical Methods for the Evaluation of Soil Profiles (8 pp)

Background, Aim and Scope   Contamination of soils does not only occur on their surface over large areas, but also in depth. Therefore a characterization of soil state after pollution demands a three-dimensional soil sampling, by what a large number of samples has to be analyzed. Analytical results could be evaluated by multivariate statistical methods, which have already been used for the evaluation of data sets containing results from soil sampling of two dimensions like areas or single profiles. In this case study, multivariate statistical methods were applied to investigate structure and interactions between features in a data set containing results of three-dimensional soil sampling. The investigated soil profiles were contaminated by emissions of a former cement and phosphate fertilizer plant. The aim of this study was to determine the remaining extent of contamination and to analyze whether pollutants are mobilized and vertically transported within the profiles. Materials and Methods: Three soil profiles were sampled in the surroundings of the plant. Grain size, organic and carbonatic bonded carbon, pH value, and the total contents of Ca, Cd, Co, Cu, F, Fe, K, Mn, Mg, Na, Ni, P, Pb, and Zn were determined. The resulting data set was evaluated by cluster analysis, linear discriminant analysis, and principal components analysis. The sequential extraction procedure according to Zeien and Brümmer was applied to analyze the binding properties of Ca, Cd, Cu, Na, Pb, and Zn from selected samples. Results: Cd was identified as contaminant of the top soils. The pH values of the bottom soils were determined to be in alkaline range, which is unnaturally high. Variables were clustered according to enrichment of variables in top soils. The samples were classified regarding their pollution state and their substrate by cluster analysis, which was confirmed by linear discriminant analysis. Geogenic and anthropogenic sources of variables as well as relationships between variables like the binding of heavy metals at organic matter were detected by using principal components analysis. The binding of heavy metals at organic matter in the top soils was confirmed by the results of the applied sequential extraction. A vertically altered distribution of Na binding was determined. Discussion: According to the current soil conditions, the uptake of heavy metals had probably occurred by the over ground part of plants during the deposition. The distribution of Na should likely result from the vertical transport of Na, which would also explain the high pH values of the bottom soils by ion exchange. Altogether, the main amount of deposited Ca, F, Na, P, and heavy metals is likely nearly insoluble bound in the top soils. Conclusions: Ten years after the end of production, the pollution of top soils in the surroundings of the former plant is still high. However, regarding the ecotoxicological relevance the now explored interactions between several soil features and elements strongly indicate that there is no short-term to medium-term risk of a mobilization of the deposited elements with the exception of Na. Recommendations and Perspectives: The results of this case study prove that multivariate statistical methods are powerful tools to explore interactions of variables and relationships in a data set derived from three dimensional soil sampling. The methods applied in this work can be highly recommended for evaluations of large data sets resulting from two- or three-dimensional samplings. Multivariate statistical methods enable the characterization of soils and their pollution state in a simple and economic way.     

关于支持向量机VC维问题证明的研究

支持向量机是基于统计学习理论的新一代学习机器,本文主要阐述了支持向量机中关于VC维的理论,并就一类函数集的VC维的大小给出理论上的证明。     

从引文分析看《中南林学院学报》的知识层面

高校学报载文的知识内涵反映了高校的学科动向和学报为本校教学科研服务的力度。通过详细分析《中南林学院学报》十年载文所引文献的知识层面,反映出《中南林学院学报》的办刊特色和对学科动态研究的关注倾向及范围局限,在此基础上,提出了拓宽《中南林学院学报》知识层面的6条措施。     

效应分析试验设计法

By proposing the concept of the maximum effect, this paper set up a new effective method of experiments design by using simple statistical calculations. The method has improved the direct-viewing analysis and the variance analysis of the orthogonal design     

Spatial distribution of weeds in arable crops: are current sampling and analytical methods appropriate?

This paper reviews the literature concerning the spatial distribution of weeds; highlighting the limitations of our current sampling and analytical methodologies, and suggesting how these inadequacies can be addressed. Most research studies have used discrete sampling, i.e. weeds are counted within a quadrat, on a grid basis. Few have mapped weeds at a whole-field scale, either with a resolution appropriate to spraying operations or key ecological processes. Statistical analyses used to describe the data can be divided into two main types, spatially implicit (also at the scale of the sampling unit) or spatially explicit, in which the location of individuals is included in the analyses. Spatially implicit methods can be strongly affected by quadrat size and mean density and are of doubtful benefit. More attention is required to address sampling resolution issues for spatially explicit methods. Our understanding of the formation and dynamics of spatial pattern, as well as predicting the consequences of site-specific management, can be improved with models. Unfortunately, most models consider only newly expanding patches and appear incapable of predicting spatial distributions when an area has been fully invaded. More detailed biological information is required if models are to become more realistic and informative. We also need to ensure that we understand the spatial processes in the context of the whole field environment, to optimize the success of site-specific weed management in the longer term.     

农业科研单位经济核算体系研究

农业科研单位实行经济核算，必须综合动用会计核算，统计核算，业务核算，从而建立经济核算的核算体系。