Species turnover in lake littorals: spatial and temporal variation of benthic macroinvertebrate diversity and community composition

Aims Despite wide consensus that ecological patterns and processes should be studied at multiple spatial scales, the temporal component of diversity variation has remained poorly examined. Specifically, rare species may exhibit patterns of diversity variation profoundly different from those of dominant taxa. Location Southern Finland. Methods We used multiplicative partitioning of true diversities (species richness, Shannon diversity) to identify the most important scale(s) of variation of benthic macroinvertebrate communities across several hierarchical scales, from individual samples to multiple littorals, lakes and years. We also assessed the among‐scale variability of benthic macroinvertebrate community composition by using measures of between‐ and within‐group distances at hierarchical scales. Results On average, a single benthic sample contained 23% of the total regional macroinvertebrate species pool. For both species richness and Shannon diversity, beta‐diversity was clearly the major component of regional diversity, with within‐littoral beta‐diversity (β₁) being the largest component of gamma‐diversity. The interannual component of total diversity was small, being almost negligible for Shannon index. Among‐sample (within‐littoral) diversity was related to variation of substratum heterogeneity at the same scale. By contrast, only a small proportion of rare taxa was found in an average benthic sample. Thus, dominant species among lakes and years were about the same, whereas rare species were mostly detected in a few benthic samples in one lake (or year). For rare species, the temporal component of diversity was more important than spatial turnover at most scales. Main conclusions While individual species occurrences and abundances, particularly those of rare taxa, may vary strongly through space and time, patterns of dominance in lake littoral benthic communities are highly predictable. Consequently, many rare species will be missed in temporally restricted samples of lake littorals. In comprehensive biodiversity surveys, interannual sampling of littoral macroinvertebrate communities is therefore needed.     

Allelopathic Interactions Involving Phenolic Acids

A major concern regarding allelopathic interactions involving phenolic acids in no-till systems pertains to the fact that concentrations of individual phenolic acids recoverable from field soils are well below levels required for inhibition of germination and seedling growth in laboratory bioassays. Field soils contain a variety of phenolic acids as well as other toxic and nontoxic organic compounds that are available to interact with seeds and roots; whereas in laboratory bioassays, with few exceptions, single phenolic acids have been tested. Studies of mixtures of phenolic acids and other toxic (e.g., methionine) and nontoxic (e.g., glucose) organic compounds in laboratory bioassays indicate that the action of a single phenolic acid is not representative of the actions of such mixtures. Specifically, as the number of phenolic acids added to soil increased, concentrations of the individual phenolic acids required to bring about a growth inhibition declined. The addition of other organic compounds (e.g., glucose, methionine) to the soil also reduced the concentration of a phenolic acid (e.g., p-coumaric acid) required for growth inhibition. These results support the hypothesis that in the field mixtures of phenolic acids and other organic compounds can cause inhibitory effects even though the concentrations of individual compounds are well below their inhibitory levels.     

基于改进的Winnow算法的剪接位点识别

DNA序列功能位点的识别是目前生物信息学领域的一个研究热点,剪接位点的识别就是其中之一.为了充分利用剪接位点的特征模式,从而更好地识别剪接位点,建立了一个基于改进Winnow算法的剪接位点识别系统.与其他方法相比较,改进的Winnow算法具有更好的鲁棒性,适用于高维特征空间,能够融合多种模式信息,即使在包含很多不相关特征的情况下,也能有很好的性能.同时在训练的时候,对特征集进行了剪枝,把一些对识别几乎没有贡献的特征去除,这样做对结果的影响可以忽略,而且提高了算法的效率.通过实验验证,改进的Winnow算法可以很好地识别剪接位点,其多个性能指标达到或超过目前国际上流行的剪接位点识别软件.     

An automated approach for fringe frequency estimation and removal in infrared spectroscopy and hyperspectral imaging of biological samples

In infrared spectroscopy of thin film samples, interference introduces distortions in spectra, commonly referred to as fringes. Fringes may alter absorbance peak ratios, which hampers the spectral analysis. We have previously introduced extended multiplicative signal correction (EMSC) for fringes correction. In the current article, we provide a robust open-source algorithm for fringe correction in infrared spectroscopy and propose several improvements to the Fringe EMSC model. The suggested algorithm achieves a more precise fringe frequency estimation by mean centering of the measured spectrum and applying a window function prior to the Fourier transform. It selects two frequencies from a user defined number of maxima in the Fourier domain. The improved Fringe EMSC algorithm is validated on two experimental datasets, one of them being a hyperspectral image. Techniques for separating sample spectra from background spectra in hyperspectral images, and techniques to identify spectra affected by fringes are also provided.     

Short-term effect of oxic to anoxic transition on benthic microbial activity and solute fluxes in organic-rich phytotreatment ponds

Macroinvertebrates are one of the key components of lake ecosystems and are required to be monitored alongside other biological groups to define ecological status according to European Union legislation. Macroinvertebrate communities are highly variable and complex and respond to a diverse series of environmental conditions. The purpose of this study was to examine the relative importance of environmental variables in explaining macroinvertebrate abundance. A total of 45 sub-alpine lakes were sampled for macroinvertebrates in the shallow sublittoral. Environmental variables were grouped into four types: (1) aquatic physical and chemical parameters, (2) littoral and riparian habitat, (3) lake morphometric parameters and (4) sediment chemical characteristics. Nonparametric multiplicative regression (NPMR) was used to model the abundance of individual macroinvertebrate taxa. Significant models were produced for nine out of the 24 taxa examined. Sediment characteristics were the group most frequently included in models and also the factors to which taxa abundance was the most sensitive. Aquatic physical and chemical variables were the next group most frequently included in models although chlorophyll a was not included in any of the models and total phosphorus in only one. This indicates that many taxa may not show a direct easily interpretable response to eutrophication pressure. Lake morphometric factors were included in several of the models although the sensitivity of macroinvertebrate abundance tended to be lower than for sediment and aquatic physical and chemical factors. Habitat factors were only included in three models although riparian vegetation was found to have a significant influence on the abundance of Ephemera danica indicating that ecotone integrity is likely to play a role in its ecology. Overall, the models tended to be specific for species with limited commonality across taxa. Models produced by NPMR indicate that the response of macroinvertebrates to environmental variables can be successfully described but further research is required focussing in more detail on the response of key taxa to relevant environmental parameters and anthropogenic pressures.     

The Use of Probabilistic Risk Assessment in Establishing Drinking Water Quality Objectives

There has been a trend in recent years toward the use of probabilistic methods for the analysis of uncertainty and variability in risk assessment. By developing a plausible distribution of risk, it is possible to obtain a more complete characterization of risk than is provided by either best estimates or upper limits. We describe in this paper a general framework for evaluating uncertainty and variability in risk estimation and outline how this framework can be used in the establishment of drinking water quality objectives. In addition to characterizing uncertainty and variability in risk, this framework also facilitates the identification of specific factors that contribute most to uncertainty and variability. The application of these probabilistic risk assessment methods is illustrated using tetrachloroethylene and trihalomethanes as examples.     

Extended multiplicative signal correction for FTIR spectral quality test and pre‐processing of infrared imaging data

Spectral quality control is an important step in the analysis of infrared spectral data, however, often neglected in scientific literature. A frequently used quality test that was originally developed for infrared spectra of bacteria is provided by OPUS software from Bruker Optik GmbH. In this study, the OPUS quality test is applied to a large number of spectra of bacteria, yeasts and moulds and hyperspectral images of microorganisms. It is shown that the use of strict thresholds for parameters of the OPUS quality test leads to discarding too many spectra. A strategy for optimizing parameters thresholds of the OPUS quality test is provided and a novel approach for spectral quality testing based on extended multiplicative signal correction (EMSC) is suggested. For all the data sets considered in our study, the EMSC quality test is shown to be the best among different alternatives of OPUS quality test provided.     

An additive‐multiplicative mean residual life model for right‐censored data

Many studies have focused on determining the effect of the body mass index (BMI) on the mortality in different cohorts. In this article, we propose an additive‐multiplicative mean residual life (MRL) model to assess the effects of BMI and other risk factors on the MRL function of survival time in a cohort of Chinese type 2 diabetic patients. The proposed model can simultaneously manage additive and multiplicative risk factors and provide a comprehensible interpretation of their effects on the MRL function of interest. We develop an estimation procedure through pseudo partial score equations to obtain parameter estimates. We establish the asymptotic properties of the proposed estimators and conduct simulations to demonstrate the performance of the proposed method. The application of the procedure to a study on the life expectancy of type 2 diabetic patients reveals new insights into the extension of the life expectancy of such patients.     

Fertility Adjustments in Rectangular Field Trials

Based on Mandel's additive plus multipicative model for ANOVA, this paper presents a procedure to represent fertility differences in field trials arranged in rectangular plans. After fitting any block and treatment effects, the residuals are assigned to their positions in the rectangular planting plan, and then decomposed into orthogonal components, of which the largest ist attributed to fertility. If the variance associated with this component is significantly larger than those remaining, the observed data are then adjusted for it; the process is repeated until there is no significant component. The procedure is illustrated by data from a variety trial.