Effects of Introduced Groundwater on Water Chemistry and Fish Assemblages in Central Florida Lakes

We assessed effects of groundwater pumping to elevate lake levels on lake water chemistry and fish population metrics at seven Florida lakes. Following groundwater pumping, lake level fluctuation was reduced and lake water samples increased in mean pH, total alkalinity, total phosphorus, chloride and Secchi depth compared to historical means, indicating a close resemblance to the chemistry of aquifer water in the region. Fish community metrics from the augmented lakes were compared to 36 non-augmented lakes in Florida. The mean values for catch per unit effort, species richness and biomass of harvestable fishes, determined by electrofishing, were lower in augmented lakes compared to non-augmented lakes. Canonical correspondence analysis (CCA) indicated a high probability of a low abundance of individual species in augmented lakes compared to a majority of non-augmented lakes. The augmented lake with the lowest pumping rate exhibited less of a shift in limnological variables from historical values, and had fish population characteristics more closely resembling those of non-augmented lakes. Thus, reduced volumes of groundwater introduction could lower impacts to limnological and fish population characteristics. Augmentation allows for lakes to be utilized for recreational activities, and without augmentation some lakes in central Florida would likely go dry due to groundwater withdrawals for water supply. Therefore, allowing more natural water level fluctuations and possible reductions in total pumpage are recommended to reduce impacts to limnological and fish population characteristics, while still allowing sufficient groundwater pumping to preserve lake habitats.     

The PERLA system in the Czech Republic: a multivariate approach for assessing the ecological status of running waters

The assessment of running water quality has a long tradition in the Czech Republic, but in the past it focused on the evaluation of organic pollution using the saprobic system. Considering the modern trends of stream ecological status evaluation in water management a new assessment system named PERLA was developed. The system is a complex of biological methods of ecological status assessment of running waters and connected activities in the Czech Republic. It involves 300 reference sites with respective biotic and abiotic data and a prediction model using a newly developed software HOBENT. The model generally follows the published mathematical principles of RIVPACS and represents the site specific and stressor non-specific approaches. The HOBENT software allows the prediction of the target assemblage of benthic macroinvertebrates for any site based on a set of environmental variables (latitude, longitude, distance from source, altitude, slope, catchment area, and stream order) which characterise the site. The predicted assemblage can be compared with the fauna observed at the same site. The comparison makes it possible to evaluate the extent of disturbance, expressed by index B. The model allows to evaluate spring, summer, and autumn seasonal data of the majority of wadable streams in the Czech Republic. The practical application of the PERLA system has started in 2001.     

Chemometric tools for classification and elucidation of protein secondary structure from infrared and circular dichroism spectroscopic measurements

Protein classification and characterization often rely on the information contained in the protein secondary structure. Protein class assignment is usually based on X-ray diffraction measurements, which need the protein in a crystallized form, or on NMR spectra, to obtain the structure of a protein in solution. Simple spectroscopic techniques, such as circular dichroism (CD) and infrared (IR) spectroscopies, are also known to be related to protein secondary structure, but they have seldom been used for protein classification. To see the potential of CD, IR, and combined CD/IR measurements for protein classification, unsupervised pattern recognition methods, Principal Component Analysis (PCA) and cluster analysis, are proposed first to check for natural grouping tendencies of proteins according to their measured spectra. Partial Least Squares Discriminant Analysis (PLS-DA), a supervised pattern recognition method, is used afterwards to test the possibility to model explicitly each protein class and to test these models in class assignment of unknown proteins. Determination of the protein secondary structure, understood as the prediction of the abundance of the different secondary structure motifs in the biomolecule, was carried out with the local regression method interval Partial Least Squares (iPLS). CD, IR, and CD/IR measurements were correlated to the fraction of the motif to be predicted, determined from X-ray measurements. iPLS builds models extracting the spectral information most correlated to a specific secondary motif and avoids the use of irrelevant spectral regions. Spectral intervals chosen by iPLS models provide structural information which can be used to confirm previous biochemical assignments or identify new motif-related spectral features. The predictive ability of the models built with the selected spectral regions has a quality similar to previous classical approaches.     

Method to classify xylem cell types using cross sectionsof 1-year-old branches in Mediterranean woody species

Measurements of anatomical parameters of wood are of great interest both for eco-physiological purposes and for technological applications. The aim of this paper is to describe a new method for classifying and measuring cell lumen of xylem, analysing cross sections under the light microscope. The proposed method is based on the application of digital image analysis on images of the cross sections of xylem in combination with graphical and statistical methods. The methodology was tested on 1-year-old branches of several woody species, both trees and shrubs, occurring in a Mediterranean natural ecosystem in southern Italy. The development of the procedure was based on statistical comparison between data collected according to four procedures: (a) manual identification and measurement of lumen diameter of conduits on longitudinal sections; (b) manual identification and measurement of lumen diameter of conduits on cross sections; (c) manual identification and measurement of lumen area of conduits on cross sections; and (d) automatic measurement of lumen area of conduits on cross sections. The influence of image resolution and that of the position of the selected area on cell classification and measurements were ascertained. The proposed method was proved to be specific to woody structures and allowed the construction of a model-graph that is species-specific. Interpretation of the model-graphs allows classification and hence measurement of identified cells.     

Structure-based function inference using protein family-specific fingerprints

We describe a method to assign a protein structure to a functional family using family-specific fingerprints. Fingerprints represent amino acid packing patterns that occur in most members of a family but are rare in the background, a nonredundant subset of PDB; their information is additional to sequence alignments, sequence patterns, structural superposition, and active-site templates. Fingerprints were derived for 120 families in SCOP using Frequent Subgraph Mining. For a new structure, all occurrences of these family-specific fingerprints may be found by a fast algorithm for subgraph isomorphism; the structure can then be assigned to a family with a confidence value derived from the number of fingerprints found and their distribution in background proteins. In validation experiments, we infer the function of new members added to SCOP families and we discriminate between structurally similar, but functionally divergent TIM barrel families. We then apply our method to predict function for several structural genomics proteins, including orphan structures. Some predictions have been corroborated by other computational methods and some validated by subsequent functional characterization.     

A phylogenetic classification of the land plants to accompany APG III

A formal classification of the land plants that is compatible with the APG III classification is proposed. Previous classifications inflated taxonomic ranks, particularly of the angiosperms. If the major clades of green algae are recognized as classes, then all land plants, the embryophytes, should be included in a single class, here recognized as Equisitopsida. Accordingly, the 16 major clades of land plants, including the angiosperms, should all be recognized as subclasses, the angiosperms as Magnoliidae. Major clades within the angiosperms are then recognized as superorders. This classification still uses a few informal categories (e.g. eudicots, lamiids, etc.) within the angiosperms because this is convenient. Two new names are established: Amborellanae and Austrobaileyanae. © 2009 The Linnean Society of London, Botanical Journal of the Linnean Society, 2009, 161 , 122–127.     

Taxonomic significance of leaf surface morphology in Aloe section Pictae (Xanthorrhoeaceae)

Leaf surface morphology was analysed in 32 species representing the maculate species complex (the poorly resolved section Pictae) in the genus Aloe (Xanthorrhoeaceae). Few comparative morphological data are available for the complex. Leaf surface and stomatal characters observed by scanning electron microscopy show taxonomically significant interspecific variation. Most species are characterized by irregularly outlined, four‐ to six‐sided epidermal cells, the periclinal walls of which are flat and embellished with micropapillae and the anticlinal walls of which are indicated by channels on the leaf surface. The outer stomatal pore is typically sunken or plane and surrounded by four lobes on the leaf surface that may overarch the epistomatal chamber. The guard cells have distinct outer and inner stomatal ledges. Two geographical groups, comprising southern and east African species, are distinguishable by their leaf surface morphology. These characters are diagnostic in A. ellenbeckii, A. prinslooi and A. suffulta and support changes in the delimitation of A. greatheadii, A. macrocarpa and A. swynnertonii. © 2009 The Linnean Society of London, Botanical Journal of the Linnean Society, 2009, 160 , 418–428.     

Fine-structured multi-scaling long-range correlations in completely sequenced genomes—features,origin, and classification

The sequential organization of genomes, i.e. the relations between distant base pairs and regions within sequences, and its connection to the three-dimensional organization of genomes is still a largely unresolved problem. Long-range power-law correlations were found using correlation analysis on almost the entire observable scale of 132 completely sequenced chromosomes of 0.5 × 10⁶ to 3.0 × 10⁷ bp from Archaea, Bacteria, Arabidopsis thaliana, Saccharomyces cerevisiae, Schizosaccharomyces pombe, Drosophila melanogaster, and Homo sapiens. The local correlation coefficients show a species-specific multi-scaling behaviour: close to random correlations on the scale of a few base pairs, a first maximum from 40 to 3,400 bp (for Arabidopsis thaliana and Drosophila melanogaster divided in two submaxima), and often a region of one or more second maxima from 10⁵ to 3 × 10⁵ bp. Within this multi-scaling behaviour, an additional fine-structure is present and attributable to codon usage in all except the human sequences, where it is related to nucleosomal binding. Computer-generated random sequences assuming a block organization of genomes, the codon usage, and nucleosomal binding explain these results. Mutation by sequence reshuffling destroyed all correlations. Thus, the stability of correlations seems to be evolutionarily tightly controlled and connected to the spatial genome organization, especially on large scales. In summary, genomes show a complex sequential organization related closely to their three-dimensional organization. This article has been submitted as a contribution to the festschrift entitled “Uncovering cellular sub-structures by light microscopy” in honor of Professor Cremer’s 65th birthday.     

环青海湖斑头雁种群数量动态模拟及趋势分析

斑头雁是青海湖候鸟中的优势种之一,其未来种群数量的变化对青海湖的保护决策具有重要作用。利用STELLA图形化建模软件,从动力学出发,构建了青海湖地区斑头雁种群数量变化的动态模型。在该模型中,根据前人和青海湖自然保护区对斑头雁的观测研究结果,设置了班头雁的交配、产卵、孵卵、育幼、迁入、迁出、死亡等过程的模型参数。根据斑头雁在青海湖的活动时间,设置以年为模拟单位,选取1/7为模拟步长,对未来25年的青海湖斑头雁种群变化趋势进行了模拟,并进行了灾害模拟。模拟结果表明,未来青海湖斑头雁的最大种群数量,将在20 000余只的饱和数量之内变化。2006—2008年斑头雁观测数据验证表明,该模型模拟结果可信,其方法对青海湖的其他鸟类研究也具有一定的参考价值。