A histopathological survey of shore crab (Carcinus maenas) and brown shrimp (Crangon crangon) from six estuaries in the United Kingdom

Invertebrates show considerable potential as sentinel organisms for the monitoring of the health status of aquatic systems. They are generally small, abundant, relatively sessile, and may readily bioaccumulate toxins. Cascade-like stress responses can occur following acute or chronic exposures to contaminated environments and as such, the overall health status of individuals within those environments, both in terms of histopathological lesions and the presence of infecting organisms, may ultimately reflect the general health status of these sites. The current study provides baseline multi-organ histopathological data for two common crustacean species, the shore crab (Carcinus maenas) and the brown shrimp (Crangon crangon) collected from six UK estuarine sites. Changes in the metabolic condition of crustaceans from these sites (measured in terms of connective tissue storage cell status) were interpreted in relation to other health measures (including parasite load and the presence of microbial pathogens). The relative ease at which a holistic assessment of health can be made using histopathology and the suitability of these species as environmental sentinels provide support for the inclusion of crustaceans as indicators of aquatic environmental health. Studies linking disease status to burdens of industrial contamination in these environments are now required.     

Aquatic biota as potential biological indicators of the contamination,bioaccumulation and health risks caused by organochlorine pesticides in a large,shallow Chinese lake (Lake Chaohu)

Aquatic biota have long been recognized as bioindicators of the contamination caused by hydrophobic organic contaminants (HOCs) in aquatic environments. The primary purpose of the present study is to identify which species of aquatic biota are the most sensitive to organochlorine pesticides (OCPs) in Lake Chaohu and can therefore serve as indicators of the lake's health and assist in the assessment of OCPs risks to human health. OCP levels in eight species of aquatic biota were measured using GC–MS, and the relationships between the biota and OCP levels in the water and suspended solids were studied. DDTs pose potential human health risks and were the predominant OCP components found in the aquatic biota. DDT had the highest mean bioaccumulation factor (BAF) and biota suspended solids accumulation factor (BSSAF) of all of the studied OCP components. The food web magnification factors (FWMF) for p, p′-DDT were greater than 1, implying that biomagnification occurred. This finding indicates that DDTs still pose a serious threat to the ecosystem and human health in Lake Chaohu, even though the agricultural application of DDT powder has been officially banned since 1983. There were significant positive relationships between OCPs levels in Culter erythropterus and those in both water and suspended solids, as well as between OCPs levels in Protosalanx hyalocranius and those in suspended solids. This finding suggests that C. erythropterus and P. hyalocranius are the most sensitive aquatic biota to OCPs and may serve as the most effective bioindicators for monitoring OCP contamination in the water and suspended solids of Lake Chaohu. Megalobrama amblycephala, which contained the highest wet weight mean OCP concentration, is the most sensitive OCP indicator and can be used to assess the human carcinogenic risk of OCPs in Lake Chaohu.     

Parasites of the superorganism: are they indicators of ecosystem health?

The concept of ecosystem health is derived from analogies with human health, which subsequently leads to the implication that the ecosystem has organismal properties, a 'superorganism' in the Clementsian sense. Its application and usefulness has been the subject of a contentious debate; yet, the term 'ecosystem health' has captured the public's imagination and woven its way into the current lexicon, even incorporated into public policy. However, the application of parasites as bioindicators of ecosystem health poses a curious conundrum. Perceptions of parasites range from mild distaste to sheer disgust among the general public, the media, environmental managers and non-parasitologists in the scientific community. Nevertheless, the biological nature of parasitism incorporates natural characteristics that are informative and useful for environmental management. The helminths in particular have evolved elegant means to ensure their transmission, often relying on complex life cycle interactions that include a variety of invertebrate and vertebrate hosts. The assemblage of these diverse parasites within a host organism potentially reflect that host's trophic position within the food web as well as the presence in the ecosystem of any other organisms that participate in the various parasite life cycles. Perturbations in ecosystem structure and function that affect food web topology will also impact upon parasite transmission, thus affecting parasite species abundance and composition. As such, parasite populations and communities are useful indicators of environmental stress, food web structure and biodiversity. In addition, there may be useful other means to utilise parasitic organisms based on their biology and life histories such as suites or guilds that may be effective bioindicators of particular forms of environmental degradation. The challenge for parasitology is to convince resource managers and fellow scientists that parasites are a natural part of all ecosystems, each species being a potentially useful information unit, and that healthy ecosystems have healthy parasites.     

A global review of freshwater crayfish temperature tolerance,preference, and optimal growth

Conservation efforts, environmental planning, and management must account for ongoing ecosystem alteration due to a changing climate, introduced species, and shifting land use. This type of management can be facilitated by an understanding of the thermal ecology of aquatic organisms. However, information on thermal ecology for entire taxonomic groups is rarely compiled or summarized, and reviews of the science can facilitate its advancement. Crayfish are one of the most globally threatened taxa, and ongoing declines and extirpation could have serious consequences on aquatic ecosystem function due to their significant biomass and ecosystem roles. Our goal was to review the literature on thermal ecology for freshwater crayfish worldwide, with emphasis on studies that estimated temperature tolerance, temperature preference, or optimal growth. We also explored relationships between temperature metrics and species distributions. We located 56 studies containing information for at least one of those three metrics, which covered approximately 6 % of extant crayfish species worldwide. Information on one or more metrics existed for all 3 genera of Astacidae, 4 of the 12 genera of Cambaridae, and 3 of the 15 genera of Parastacidae. Investigations employed numerous methodological approaches for estimating these parameters, which restricts comparisons among and within species. The only statistically significant relationship we observed between a temperature metric and species range was a negative linear relationship between absolute latitude and optimal growth temperature. We recommend expansion of studies examining the thermal ecology of freshwater crayfish and identify and discuss methodological approaches that can improve standardization and comparability among studies.     

An Automated and Intelligent Medical Decision Support System for Brain MRI Scans Classification

A wide interest has been observed in the medical health care applications that interpret neuroimaging scans by machine learning systems. This research proposes an intelligent, automatic, accurate, and robust classification technique to classify the human brain magnetic resonance image (MRI) as normal or abnormal, to cater down the human error during identifying the diseases in brain MRIs. In this study, fast discrete wavelet transform (DWT), principal component analysis (PCA), and least squares support vector machine (LS-SVM) are used as basic components. Firstly, fast DWT is employed to extract the salient features of brain MRI, followed by PCA, which reduces the dimensions of the features. These reduced feature vectors also shrink the memory storage consumption by 99.5%. At last, an advanced classification technique based on LS-SVM is applied to brain MR image classification using reduced features. For improving the efficiency, LS-SVM is used with non-linear radial basis function (RBF) kernel. The proposed algorithm intelligently determines the optimized values of the hyper-parameters of the RBF kernel and also applied k-fold stratified cross validation to enhance the generalization of the system. The method was tested by 340 patients’ benchmark datasets of T1-weighted and T2-weighted scans. From the analysis of experimental results and performance comparisons, it is observed that the proposed medical decision support system outperformed all other modern classifiers and achieves 100% accuracy rate (specificity/sensitivity 100%/100%). Furthermore, in terms of computation time, the proposed technique is significantly faster than the recent well-known methods, and it improves the efficiency by 71%, 3%, and 4% on feature extraction stage, feature reduction stage, and classification stage, respectively. These results indicate that the proposed well-trained machine learning system has the potential to make accurate predictions about brain abnormalities from the individual subjects, therefore, it can be used as a significant tool in clinical practice.     

水生动物金属硫蛋白分子毒理学研究进展

随着现代工业的迅速发展,重金属污染问题日益严重。重金属离子主要通过水及食物进入生物机体并累积,对机体的生长发育与新陈代谢产生危害。金属硫蛋白（MT）是一种低分子量、富含半胱氨酸的蛋白质,广泛存在于大多数生物体内,在必需金属元素稳态调节、非必需金属元素解毒以及抗氧化等过程中具有重要作用,因此,MT可作为检测水生生态系统中重金属污染的潜在生物标记,其分子毒理学已成为研究热点。综述了MT的结构、功能、分类与分布,以及鱼类、甲壳类和软体动物的MT分子毒理学研究概况。     

The intensity and spectrum of artificial light at night alters crayfish interactions

ABSTRACT

Ecological light pollution (ELP) is quickly becoming a worldwide concern and can negatively affect aquatic ecosystems. The given intensity and spectrum of a light source can influence how organisms function within their environment. These properties of artificial lighting at night (ALAN) and their impacts on the physiology and behaviour of crayfish were examined in this work. Hemolymph was obtained from crayfish to quantify a physiological response. Behavioural data were measured as the number, duration, and maximum intensity of agonistic fights. Exposure to higher intensities of light and the presence of ultraviolet light induced a behavioural trend, resulting in significantly altered social interactions within both species of crayfish. The number and maximum intensity of lights significantly decreased, whereas the duration of time spent fighting significantly increased. Due to the importance of freshwater environments and the role crayfish play as a keystone species, examining how crayfish are impacted from ALAN is imperative to maintaining the health of aquatic ecosystems.     

Comparative study of SVM methods combined with voxel selection for object category classification on fMRI data

Background

Support vector machine (SVM) has been widely used as accurate and reliable method to decipher brain patterns from functional MRI (fMRI) data. Previous studies have not found a clear benefit for non-linear (polynomial kernel) SVM versus linear one. Here, a more effective non-linear SVM using radial basis function (RBF) kernel is compared with linear SVM. Different from traditional studies which focused either merely on the evaluation of different types of SVM or the voxel selection methods, we aimed to investigate the overall performance of linear and RBF SVM for fMRI classification together with voxel selection schemes on classification accuracy and time-consuming.

Methodology/Principal Findings

Six different voxel selection methods were employed to decide which voxels of fMRI data would be included in SVM classifiers with linear and RBF kernels in classifying 4-category objects. Then the overall performances of voxel selection and classification methods were compared. Results showed that: (1) Voxel selection had an important impact on the classification accuracy of the classifiers: in a relative low dimensional feature space, RBF SVM outperformed linear SVM significantly; in a relative high dimensional space, linear SVM performed better than its counterpart; (2) Considering the classification accuracy and time-consuming holistically, linear SVM with relative more voxels as features and RBF SVM with small set of voxels (after PCA) could achieve the better accuracy and cost shorter time.

Conclusions/Significance

The present work provides the first empirical result of linear and RBF SVM in classification of fMRI data, combined with voxel selection methods. Based on the findings, if only classification accuracy was concerned, RBF SVM with appropriate small voxels and linear SVM with relative more voxels were two suggested solutions; if users concerned more about the computational time, RBF SVM with relative small set of voxels when part of the principal components were kept as features was a better choice.     

Behavioural, ventilatory and respiratory responses of epigean and hypogean crustaceans to different temperatures

Impact of temperature (from -2 to 28 degrees C) on survival, oxygen consumption, locomotory and ventilatory activities was measured in two aquatic subterranean crustaceans (Niphargus rhenorhodanensis and Niphargus virei) and in a morphologically close surface-dwelling crustacean (Gammarus fossarum). The hypogean N. virei presented all characteristics of a stenothermal organism: it showed small thermal plasticity and optimised its performance on a narrow range of temperature. In contrast, the epigean G. fossarum and more surprisingly the hypogean N. rhenorodanensis can be both characterized as eurythermal organisms: they exhibited important survival times and conserved their performance optimum throughout a large range of temperature. Such differences of survival and performance patterns in two hypogean organisms were unexpected since they both live in very thermally buffered biotopes. Our data suggest fresh hypotheses about the role of glaciations in the history and adaptation of hypogean crustaceans.     

An Ecosystem Health Index for a large and variable river basin: Methodology,challenges and continuous improvement in Queensland’s Fitzroy Basin

Report cards are an increasingly popular method for summarising and communicating relative environmental performance and ecosystem health, including in aquatic environments. They are usually underpinned by an Ecosystem Health Index (EHI) that combines various individual indicators to produce an overall ecosystem health “score”. As a result of public water quality concerns, an integrated means of monitoring and reporting on aquatic ecosystem health was needed for the Fitzroy Basin in central Queensland, Australia. The Fitzroy Partnership for River Health was formed to address this need, and developed an EHI and report card for the Basin using existing monitoring data collected from various third parties including regulated companies operations and government. At 142,000 square kilometres, the Fitzroy Basin is the largest catchment draining to the World Heritage Listed Great Barrier Reef. The Fitzroy Basin provides an example of how to deliver an effective aquatic ecosystem health reporting system in a large and complex river basin. We describe the methodology used to develop an adaptive EHI for the Fitzroy Basin that addresses variability, complexity and scale issues associated with reporting across large areas. As well, we report how to manage the design and reporting stages given limitations in data collection and scientific understanding.     

洞庭湖浮游生物群落DNA指纹拓扑结构与物种组成对应关系

对东洞庭湖7个采样站点的浮游生物群落进行了DNA多态性的RAPD指纹分析和物种组成的分类鉴定,并通过聚类分析探讨了DNA指纹拓扑结构与物种组成对应关系。结果如下:(1)筛选出的11条随机引物共获得148条长度在180~2000bp的谱带,多态率为98.6%,各引物扩增谱带数在11~16不等;各站点平均有57.6条谱带,其中站最多(70条),站最少(45条),而站的特有带最多(7条),站最少(2条);(2)共观察到54种/类浮游生物,其中站出现的最多(27),其它各站点在7~13不等,分布概率在85%以上的只有直链硅藻(Melosirasp.)。相似性聚类分析表明:7个站点的浮游生物群落可以划分为两大类——站作为单独的一类而明显有别于其它6站;并且,RAPD分析在此基础上将、、站和、、站进一步分作两小类。因此,研究说明浮游生物群落DNA指纹拓扑结构与物种组成是密切相关的,这类资料的积累将会为生态系统功能、机理的解释或阐明提供一些启示。     

Subsurface Dwelling Crustaceans as Indicators of Hydrological Conditions,Oxygen Concentrations,and Sediment Structure in an Alluvial Aquifer

The relation between environmental conditions and the species composition and individual abundance of crustaceans was investigated in a shallow alluvial aquifer, located in the Danube wetlands (Lobau, Austria). Samples, consisting of groundwater, sediment, and fauna, were taken from permanent installed wells by means of a piston pump five times in a year cycle. The results show that the spatial and temporal distribution, individual abundance, and species richness of crustacean fauna is related to hydrological conditions, oxygen concentrations, and geologic structures in the alluvial aquifer. Therefore, crustaceans, divided in stygoxene, stygophile, and stygobite species, can be used as bioindicators of these environmental conditions in an aquifer. It is suggested that beside physicochemical analyses also the crustacean fauna should be considered to characterise a groundwater ecosystem.     

Operational Effect Variables and Functional Ecosystem Classifications – a Review on Empirical Models for Aquatic Systems along a Salinity Gradient

This paper presents a comparative study based on a very comprehensive set of empirical data from many international data bases including fresh water systems, coastal brackish water areas and marine coastal areas. We present a general trophic level classification system (oligotrophic, mesotrophic, eutrophic and hypertrophic categories) for sites/areas characterised by a wide range of salinities. This classification system targets on the following operational effect variables (bioindicators), which are meant to reflect key structural and functional aspects of aquatic ecosystems and characteristic (median) values for entire defined areas (the ecosystem scale) for the growing season: Secchi depth (as a standard measure of water clarity), chlorophyll‐a concentrations (a measure of primary phytoplankton biomass), the oxygen saturation in the deep‐water zone (an indicator reflecting sedimentation, oxygen consumption, oxygen concentrations and the habitat conditions for zoobenthos, an important functional group) and the macrophyte cover (an important variable for the bioproduction potential, including fish production, and the “biological value” of aquatic systems). For a wide range of systems, these bioindicators can be predicted using practically useful models, i.e., models based on variables that can be accessed from standard monitoring programs and maps. These bioindicators are regulated by a set of abiotic factors, such as salinity, suspended particulate matter (SPM), nutrient concentrations (N and P), morphometry and water exchange. Empirical data ultimately form the basis for most ecological/environmental studies and this work uses maybe the most comprehensive data set ever related to trophic level conditions. It also gives compilations of empirically‐based (statistical) models quantifying how the variables are interrelated and how they reflect fundamental aspects of aquatic ecosystems. (© 2007 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Evaluation of ecosystem health for the coastal wetlands at the Yangtze Estuary, Shanghai

Despite the growing awareness of the important ecological functions and values provided by coastal and estuarine wetlands, wetland degradation continues worldwide due to increasing anthropogenic disturbances. Chongming Dongtan wetlands, adjacent to Shanghai, the largest city and industrial and trading port in China in rapid urban expansion and socioeconomic development are currently threatened with biodiversity reduction, wetland loss, contamination, and invasion of exotic plant. Sustainable protection and management of Dongtan Nature Reserve necessitate research to develop diagnostic tools and indicators for a comprehensive and objective assessment of wetland ecosystem health condition. Based on the pressure-state-response framework and ecological and environmental surveys at the Dongtan wetlands, an indicator system was established for evaluating the coastal wetlands ecosystem health, using indicators detected from satellite imagery and current field surveys. Through the establishment of health assessment units and spatial quantification of the indicators, the spatial clustering analysis, integrated with remote sensing and geographic information system technique was applied to make an accurate diagnosis of ecosystem health for Chongming Dongtan wetlands and highlight the areas in subhealthy and unhealthy condition and urgent need of conservation and management. The results from this research indicated that the ecosystem health condition at the Dongtan wetlands showed spatial variation, to a certain extent, corresponding to the distributions of elevation and land cover types. More than 75 % of the total study area was at a relatively healthy level, with 34.19 km² for the very healthy zone and 41.08 km² for the healthy zone, while the subhealthy and unhealthy zones covered 18.23 and 4.76 km², respectively. This study demonstrated the potential for this integrated approach to give objective and effective evaluation of ecosystem health for the dynamic coastal and estuarine wetlands and provide up-to-date information to assist with early warning for ecological security and management decisions for Chongming Dongtan Nature Reserve.     

Systematic benchmarking of microarray data classification: assessing the role of non-linearity and dimensionality reduction

MOTIVATION: Microarrays are capable of determining the expression levels of thousands of genes simultaneously. In combination with classification methods, this technology can be useful to support clinical management decisions for individual patients, e.g. in oncology. The aim of this paper is to systematically benchmark the role of non-linear versus linear techniques and dimensionality reduction methods. RESULTS: A systematic benchmarking study is performed by comparing linear versions of standard classification and dimensionality reduction techniques with their non-linear versions based on non-linear kernel functions with a radial basis function (RBF) kernel. A total of 9 binary cancer classification problems, derived from 7 publicly available microarray datasets, and 20 randomizations of each problem are examined. CONCLUSIONS: Three main conclusions can be formulated based on the performances on independent test sets. (1) When performing classification with least squares support vector machines (LS-SVMs) (without dimensionality reduction), RBF kernels can be used without risking too much overfitting. The results obtained with well-tuned RBF kernels are never worse and sometimes even statistically significantly better compared to results obtained with a linear kernel in terms of test set receiver operating characteristic and test set accuracy performances. (2) Even for classification with linear classifiers like LS-SVM with linear kernel, using regularization is very important. (3) When performing kernel principal component analysis (kernel PCA) before classification, using an RBF kernel for kernel PCA tends to result in overfitting, especially when using supervised feature selection. It has been observed that an optimal selection of a large number of features is often an indication for overfitting. Kernel PCA with linear kernel gives better results.     

Uncertainties in biotic indicators and a corrigendum to : Implications for biomonitoring

Many bioindicators based on species composition have been proposed during the past 30 years in both terrestrial and freshwater ecosystems. Kelly (2011) raised the need to better communicate the usefulness and meaning of the indices and their uncertainties. A survey of European bioindicators of freshwater ecosystems has recently highlighted that most indices have not even considered uncertainties. While recording errors have sometimes been taken into account into the calculation of index uncertainties, the reliability of biotic indices in terms of causality and predictability between a given environmental pressure and bioindicator response have seldom been considered. This has led to serious misunderstanding of what bioindicators may be able to achieve. Here a correction to Ponader et al. (2007) is presented showing that the tolerance (ecological niche) of individual species of diatoms along nutrient enrichment gradients is much wider than formerly presented. The correction, together with the comments by Kelly (2011) and recent whole ecosystem experiments seriously question the reliability of diatoms as nutrient indicators, similarly to recent findings with aquatic macrophytes. A more mechanistic basis for biomonitoring is needed based on current ecological science, rather than early 20th century community ecology.     

Crayfish invasion facilitates dispersal of plants and invertebrates by gulls

相似文献   

Aquatic macroinvertebrates are poor indicators of agricultural activity in northern prairie pothole wetlands

The Northern Prairie Pothole Region (NPPR) of Alberta, Canada, contains numerous shallow marshes that serve as important habitat for wildlife and provide essential ecosystem services. Many of these wetlands have been destroyed or degraded by human activity and the majority of remaining wetlands occur in landscapes affected by crop and cattle production. Alberta has implemented a conservation policy which requires the creation of wetland assessment tools. Aquatic macroinvertebrates are frequently used as indicators of environmental condition in rivers, but their effectiveness as indicators in prairie pothole wetlands is not clear. To evaluate the capacity of aquatic macroinvertebrates identified to family-level resolution to serve as regional bioindicators of agricultural disturbance in NPPR wetlands, we sampled macroinvertebrates at 64 fishless wetlands. The wetlands spanned a gradient in the extent of agriculture from 0 to 100% cover within a 500 m buffer around each wetland. We discovered that, contrary to our predictions, macroinvertebrate family richness and community composition could not predict agricultural disturbance (cropping or cattle grazing). We conclude that efforts to develop bioindicators for NPPR wetlands should be redirected to other taxa that are less costly to identify to species and that exhibit sensitivity to agricultural disturbance.     

Helminths and protozoans of aquatic organisms as bioindicators of chemical pollution

There is no doubt that the aquatic environments receive large quantities of chemicals as consequence of human activities and that those substances have a detrimental effect on human health. Despite the obvious need for effective disposal of these substances, we need to understand and prevent the outcome of harmful environmental exposures. Thus, we need biomarkers and bioindicators to advance our understanding to these harmful exposures and their biological effects. In the last three decades a large number of publications has suggested that aquatic organisms and their parasites (mainly helminths and ciliate protozoans) are useful bioindicators of chemical pollution. However, the main weakness of this approach is that after exposure the population size of these parasites can increase or decrease without a consistent pattern. I suggest that this is in part due to the lack of focus on the correct spatial or temporal scales at which the environment is acting over our study object. Thus, I propose to use spatially explicit (= georeferenced) data for determining whether there is spatial structure in our study area. Spatial structure is the tendency of nearby samples to have attribute values more similar than those farther apart. These attributes are shaped by environmental variables acting at specific spatial and temporal scales. Thus, I suggest to consider these tools for determining the correct spatial or temporal scales of study, but also to record pollutant concentrations, bioindicators, biomarkers and parasites at individual host level. Combining this information with long-term monitoring programs is likely to improve our understanding of the effects of chemical pollutants over the aquatic environments.     

支持向量机与神经网络的关系研究

支持向量机是一种基于统计学习理论的新颖的机器学习方法,由于其出色的学习性能,该技术已成为当前国际机器学习界的研究热点,该方法已经广泛用于解决分类和回归问题．本文将结构风险函数应用于径向基函数网络学习中,同时讨论了支持向量回归模型和径向基函数网络之间的关系．仿真实例表明所给算法提高了径向基函数网络的泛化性能．