The apportionment of quadratic entropy: a useful alternative for partitioning diversity in ecological data

Many methods that study the diversity within hierarchically structured populations have been developed in genetics. Among them, the analysis of molecular variance (AMOVA) (Excoffier et al., 1992) has the advantage of including evolutionary distances between individuals. AMOVA is a special case of a far more general statistical scheme produced by Rao (1982a; 1986) and called the apportionment of quadratic entropy (APQE). It links diversity and dissimilarity and allows the decomposition of diversity according to a given hierarchy. We apply this framework to ecological data showing that APQE may be very useful for studying diversity at various spatial scales. Moreover, the quadratic entropy has a critical advantage over usual diversity indices because it takes into account differences between species. Finally, the differences that can be incorporated in APQE may be either taxonomic or functional (biological traits), which may be of critical interest for ecologists.     

Reach‐Scale Geomorphic and Biological Effects of Localized Streambank Armoring

Armoring of streambanks is a common management response to perceived threats to adjacent infrastructure from flooding or erosion. Despite their pervasiveness, effects of reach‐scale bank armoring have received less attention than those of channelization or watershed‐scale hydromodification. In this study, we explored mechanistic ecosystem responses to armoring by comparing conditions upstream, within, and downstream of six stream reaches with bank armoring in Southern California. Assessments were based on four common stream‐channel assessment methods: (1) traditional geomorphic measures, (2) the California Rapid Assessment Method for wetlands, (3) bioassessment with benthic macroinvertebrates, and (4) bioassessment with stream algae. Although physical responses varied among stream types (mountain, transitional, and lowland), armored segments generally had lower slopes, more and deeper pools and fewer riffles, and increased sediment deposition. Several armored segments exhibited channel incision and bank toe failure. All classes of biological indicators showed subtle, mechanistic responses to physical changes. However, extreme heterogeneity among sites, the presence of catchment‐scale disturbances, and low sample size made it difficult to ascribe observed patterns solely to channel armoring. The data suggest that species‐level or functional group‐level metrics may be more sensitive tools than integrative indices of biotic integrity to local‐scale effects.     

热排放对湘江大型底栖无脊椎动物的影响

湘潭电厂温排水对湘江湘潭电厂江段大型底栖无脊椎动物 (以下简称底栖动物 )种类组成和数量变化的影响表明 ,在强增温区底栖动物不能生存 ;自然水温在 2 6℃以下的季节里 ,中、低增温区底栖动物种类和数量比自然水体要丰富 ,多样性指数值相应增高 ;突然停止温排 ,增温区内喜温动物有可能受冷冲击而死亡。     

Influence of Ambient pH on Freshwater Invertebrates under Experimental Conditions

In experimental mesocosms differing in water pH, the communities of macroinvertebrates demonstrated marked differences in their species composition and the quantitative ratios between the main groups of members (oligochaetes, chironomids, mollusks, etc.). The highest species diversity was recorded at pH 4.09–8.65. It proved to decrease at pH below 4 and above 9. In experiments on determining tolerance to water pH, seven groups of invertebrates differing in their adaptive potential were distinguished among 40 species found en masse in the freshwater zoobenthos and zooperiphyton of the Upper Volga basin.     

A Quantitative Tool for Assessing the Integrity of Southern Coastal California Streams

We developed a benthic macroinvertebrate index of biological integrity (B-IBI) for the semiarid and populous southern California coastal region. Potential reference sites were screened from a pool of 275 sites, first with quantitative GIS landscape analysis at several spatial scales and then with local condition assessments (in-stream and riparian) that quantified stressors acting on study reaches. We screened 61 candidate metrics for inclusion in the B-IBI based on three criteria: sufficient range for scoring, responsiveness to watershed and reach-scale disturbance gradients, and minimal correlation with other responsive metrics. Final metrics included: percent collector-gatherer + collector-filterer individuals, percent noninsect taxa, percent tolerant taxa, Coleoptera richness, predator richness, percent intolerant individuals, and EPT richness. Three metrics had lower scores in chaparral reference sites than in mountain reference sites and were scored on separate scales in the B-IBI. Metrics were scored and assembled into a composite B-IBI, which was then divided into five roughly equal condition categories. PCA analysis was used to demonstrate that the B-IBI was sensitive to composite stressor gradients; we also confirmed that the B-IBI scores were not correlated with elevation, season, or watershed area. Application of the B-IBI to an independent validation dataset (69 sites) produced results congruent with the development dataset and a separate repeatability study at four sites in the region confirmed that the B-IBI scoring is precise. The SoCal B-IBI is an effective tool with strong performance characteristics and provides a practical means of evaluating biotic condition of streams in southern coastal California.     

大型底栖动物生物评价指数比较与应用

采用不同生物指数评价河流健康,结果往往有差异,如何识别各种生物指数的关系和适用性成为亟待解决的问题.基于太子河流域大型底栖动物群落研究,比较了5种大型底栖动物生物指数评价结果的差异.结果表明,5种指数具有极显著的相关性,但由于健康等级划分标准差异,造成不同指数的健康评价等级存在一定差异.同时分析了不同指数对不同类型人为活动影响的敏感性,研究其在河流健康评价中的适用性.结果表明在太子河流域中,BI指数与土地利用类型和溶氧具有较好的相关关系,对这两类的干扰具有较好的指示作用;FBI指数对酸污染和氨氮污染具有较强的指示作用;ASPT指数与耗氧相关的水质指标有较强的负相关;B-IBI指数与总氮呈显著的负相关关系,可较好指示氮污染,而且B-IBI指数与其他类型人为干扰活动均呈显著的相关关系,对土地利用和水质污染也具有较好的指示作用.综上所述,大型底栖动物BI指数和ASPT指数应该分别适用于评价流域土地利用和水化学指标对河流生态系统的影响,而B-IBI可用于评估多种类型人为干扰活动.     

密云水库上游河流底栖动物群落结构与水质评价

于2013年5月至10月对密云水库上游河流中大型底栖无脊椎动物(以下简称底栖动物)进行了采样调查。结果表明,采集到的底栖动物隶属于4门10纲16目45科,其中以节肢动物种类最多,占总数的80%,且水生昆虫占总数的67%,出现频率最高的是节肢动物门蜉蝣目蜉蝣科的昆虫,出现频率达87%;从分布来看,白河流域采集到的底栖动物种类最多、密度最高,而潮河流域采集到的底栖动物生物量最大;以底栖动物为指示生物的水质评价结果显示,密云水库上游河流中50%采样点的水质为Ⅰ级(清洁),其余50%为Ⅱ级(轻微污染),水质整体较好,与现场生境调查和水质监测的结果相吻合。     

扬州市河网大型底栖动物群落结构及其生境特征研究

构建适用于城市大型底栖动物的生境适宜性模型,探究大型底栖动物与生境因子间的响应关系,对城市河流生态系统恢复具有重要指示意义.本文以长江下游北岸扬州市城市河网为研究对象,基于丰水期(2018年8月)和枯水期(2019年1月)的大型底栖动物调查数据,利用典范对应分析与相关性分析筛选城市河网生态健康的关键生境因子,采用GAM...     

Comparison of ecotoxicological and physico-chemical data by use of multivariate analyses and graphical displays

Bioassays allow the appreciation of the toxicity of complex effluents, which is difficult to characterize by the sole measurement of some physico-chemical parameters. We have developed a macroinvertebrate multi-test (M.M.T.) with species characteristic of different trophic levels in order to appreciate the ecotoxicological impact of various effluents (especially landfill leachates) and chemicals on aquatic environments. Our aim was: (i) to compare the sensitivity of the macroinvertebrates among themselves and with regard to those of three standard bioassays; (ii) to characterize the effluents according to their toxicity on one hand and according to their physico-chemical composition on the other hand; (iii) to search for possible correlations between the physico-chemical composition of an effluent and its toxicity. In order to achieve these objectives we used first a combination of graphical displays of the raw data, and secondly multivariate analyses: clustering techniques and scaling (ordination) techniques (Principal Components Analysis).     

Use of genetic algorithms to select input variables in decision tree models for the prediction of benthic macroinvertebrates

Predicting freshwater organisms based on machine learning is becoming more and more reliable due to the availability of appropriate datasets, advanced modelling techniques and the continuously increasing capacity of computers. A database consisting of measurements collected at 360 sampling sites in non-navigable watercourses in Flanders was applied to predict the absence/presence of benthic macroinvertebrate taxa by means of decision trees. The measured variables were a combination of physical–chemical (temperature, pH, dissolved oxygen concentration, conductivity, total organic carbon, Kjeldahl nitrogen and total phosphorus), structural (granulometric analysis of the sediment, width, depth and flow velocity of the river) and two ecotoxicological variables. The predictive power of decision trees was assessed on the basis of the number of Correctly Classified Instances (CCI). A genetic algorithm was introduced to compare the predictive power of different sets of input variables for the decision trees. The number of input variables was reduced from 15 to 2–8 variables without affecting the predictive power of the decision trees significantly. Furthermore, reducing the number of input variables allowed to ease the identification of general data trends.