Structure and Dynamics of a Benthic Invertebrate Community in an Intertidal Area of the Tagus Estuary, Western Portugal: A Six Year Data Series

A predictive model, incorporating macroinvertebrate and environmental data, similar to that developed for Australian rivers (AUSRIVAS) and British rivers (RIVPACS) was constructed using a dataset collected from 23 reference (least altered) wetlands on the Swan Coastal Plain, Western Australia, sampled in summer and spring, 1989 and spring, 1990. Four main groups of reference wetlands were identified by UPGMA classification (using the Bray–Curtis dissimilarity measure). Distinguishing environmental variables identified by Stepwise Multiple Discriminant Function Analysis were: calcium, colour (gilvin), latitude, longitude, sodium and organic carbon. Observed to expected ratios of taxa with a >50% chance of occurrence (OE50) derived from the model for a suite of 23 test wetlands sampled in spring, 1997, were significantly correlated with pH and the depth of the sampling sites. Greater discrimination between the test wetlands was provided by the OE50 ratios than either raw richness (number of families) or a biotic index (SWAMPS). Results obtained for a subset of 11 test wetlands sampled with both a rapid bioassessment protocol (incorporating field picking of 200 invertebrates collected in 2 min sweeps from selected habitats) and a semi-quantitative protocol (incorporating laboratory picking of all invertebrates collected in sweeps along 10 m transects at randomly allocated sites) were not significantly different, indicating that the former could be used to reduce the time and costs associated with macroinvertebrate-based wetland monitoring programs. In addition to providing an objective method of assessing wetland condition, predictive modelling provides a list of taxa expected to occur under reference conditions, which can be used as a target in wetland restoration programs. The probable impediment to widespread adoption of predictive modelling for wetland bioassessment is the need to produce models tailored to specific geographic regions and specific climatic conditions. This may incur significant costs in countries, such as Australia, which span a wide range of climatic zones.     

Evaluating the relative contributions of hydroperiod and soil fertility on growth of south Florida mangroves

The requirements of the European Water Framework Directive (WFD), aimed at an integrative assessment methodology for evaluating the ecological status of water bodies are frequently being achieved through multimetric techniques, i.e. by combining several indices, which address different stressors or different components of the biocoenosis. This document suggests a normative methodology for the development and application of Multimetric Indices as a tool with which to evaluate the ecological status of running waters. The methodology has been derived from and tested on a European scale within the framework of the AQEM and STAR research projects, and projects on the implementation of the WFD in Austria and Germany. We suggest a procedure for the development of Multimetric Indices, which is composed of the following steps: (1) selection of the most suitable form of a Multimetric Index; (2) metric selection, broken down into metric calculation, exclusion of numerically unsuitable metrics, definition of a stressor gradient, correlation of stressor gradients and metrics, selection of candidate metrics, selection of core metrics, distribution of metrics within the metric types, definition of upper and lower anchors and scaling; (3) generation of a Multimetric Index (general or stressor-specific approach); (4) setting class boundaries; (5) interpretation of results. Each step is described by examples.     

Sample Variability Influences on the Precision of Predictive Bioassessment

The rapid bioassessment technique we investigate (AUSRIVAS) requires a nationally standardized sampling protocol that uses a single collection of macroinvertebrates (without replication) taken from 10 m of specific habitats (e.g. stream edge and/or riffle) and sub-samples of 200 animals. The macroinvertebrate data are run through predictive models that provide an assessment of biological condition based on a comparison of the animals found in the collection (the observed) and those expected to be there given the site-specific characteristics of the stream (the O/E taxa score). The important questions are related to the conclusions regarding river condition that can be drawn from the biological assessment. Rapid bioassessment studies are generally of two types: those for assessment of individual sites and those where many sites are selected to collectively assess the potential impacts of some human activity such as forestry or agriculture. We wanted to identify the effects of sample variability on the outputs of this predictive bioassessment technique. We found that a single collection of benthic macroinvertebrates was sufficient for bioassessment when taken from a site that had a large area of nearly uniform substrate and was in good condition. Also, collections taken from a larger and smaller area of substrate (1.75, 3.5 or 7 m²) gave the same bioassessment. In other sites, not in such good condition, the variability in bioassessment from different collections could result in different interpretations of biological condition. For all sites, regardless of condition, much of the variation in bioassessment was derived from sub-sampling the macroinvertebrates. We develop a statistical sub-sampling and solver algorithm that provides a measure of variability and a statistically valid probability of impairment for a single site, without the need to actually collect the hundreds of replicated collections needed for this study. We found that assessment at impaired sites, where only 1 collection and 1 sub-sample are taken (a common situation in rapid assessment), the 95% confidence level for O/E taxa scores is estimated to be as much as ±0.22. At sites in reference condition, the 95% confidence interval may be much narrower (~±0.1 O/E units). Therefore, assessments of sites at, or near, reference condition will be more precise than for impaired sites. Power analysis revealed that where single sites are being assessed we recommend a sample collected from 3.5 m² of habitat, but replicate collections should be taken at a site (rather than one only) and we recommend replicate sub-samples of each collection (total of six sub-samples from a site). However, this would remove a ‘rapid’ component of the bioassessment. We recommend the addition of sub-sampling and solver algorithms to the predictive models such as AUSRIVAS to provide a statistical measure of probability of impairment. An adaptive sub-sampling regime could then be used to optimize sampling effort. For example, a single sub-sample may be sufficient for screening or the agency could use the sub-sample and solver algorithms to sub-sample the parent sample for a more precise estimate of the biological condition. Replication should be maximized at the spatial scale required for reporting: site, or regional. But as a general rule, catchment or land-use scale studies should maximize replicate sites, and site-scale assessments should maximize replication within sites.     

ANNA: A new prediction method for bioassessment programs

1. Cluster analysis of reference sites with similar biota is the initial step in creating River Invertebrate Prediction and Classification System (RIVPACS) and similar river bioassessment models such as Australian River Assessment System (AUSRIVAS). This paper describes and tests an alternative prediction method, Assessment by Nearest Neighbour Analysis (ANNA), based on the same philosophy as RIVPACS and AUSRIVAS but without the grouping step that some people view as artificial. 2. The steps in creating ANNA models are: (i) weighting the predictor variables using a multivariate approach analogous to principal axis correlations, (ii) calculating the weighted Euclidian distance from a test site to the reference sites based on the environmental predictors, (iii) predicting the faunal composition based on the nearest reference sites and (iv) calculating an observed/expected (O/E) analogous to RIVPACS/AUSRIVAS. 3. The paper compares AUSRIVAS and ANNA models on 17 datasets representing a variety of habitats and seasons. First, it examines each model's regressions for Observed versus Expected number of taxa, including the r², intercept and slope. Second, the two models’ assessments of 79 test sites in New Zealand are compared. Third, the models are compared on test and presumed reference sites along a known trace metal gradient. Fourth, ANNA models are evaluated for western Australia, a geographically distinct region of Australia. The comparisons demonstrate that ANNA and AUSRIVAS are generally equivalent in performance, although ANNA turns out to be potentially more robust for the O versus E regressions and is potentially more accurate on the trace metal gradient sites. 4. The ANNA method is recommended for use in bioassessment of rivers, at least for corroborating the results of the well established AUSRIVAS‐ and RIVPACS‐type models, if not to replace them.     

The use of AUSRIVAS predictive models to assess the response of lotic macroinvertebrates to dams in south-east Australia

1. Sites immediately below seven dams in Victoria and 12 in southern New South Wales (NSW) were sampled for macroinvertebrates using rapid bioassessment techniques. Specimens were identified to the lowest taxonomic level. The dams had different operating and discharge regimes and thus potentially different downstream effects on this fauna.
2. The AUStralian RIVer Assessment Scheme (AUSRIVAS) predictive models for macroinvertebrate composition were applied to the families and genera observed at Victorian sites and to the families only at the NSW sites. Lists of predicted taxa, their probabilities of occurrence and ratios of observed to expected taxa (O/E scores) were obtained from these models.
3. The mean O/E score for Victoria was 0.46 at the genus level and 0.63 at the family level; for NSW the mean score at the family level was 0.62. There was no significant difference between family level scores for the two states. Thus about 40% of expected families were missing at all sites. Family level scores were highly correlated ( r =0.84–0.86, P  < 0.001) with numbers of families or species at a site.
4. There was no correlation between family O/E scores (or family and species richness) and the degree to which current discharge levels below a dam differ from the natural patterns. Thus increased hydrological deviation did not result in greater biological degradation. In addition, there was no association between these biological characteristics and whether dams released surface or bottom water.
5. All the dams seemed to cause much the same disruption to the fauna. Of the families predicted to have widespread occurrence, 9–12 were found at most sites (tolerant taxa), while a larger number (14–24) were missing (intolerant taxa). The limited recolonisation below dams may well be because of the fact that dams act as barriers to drift, the most prominent route for invertebrate colonists.     

用河流生物指数评价秦淮河上游水质的研究

1999～2001年用D-形网半定量法采集了南京秦淮河上游21个样点的大型底栖无脊椎动物。12个底栖生物指数值的频数分布分析、Pearson相关分析和敏感性检测表明,总分类单元数、ET分类单元数、香农多样性指数、水生昆虫分类单元数和优势分类单元％最适合于秦淮河上游水质生物评价。采用5、3、1生物指数记分法统一量纲。提出了河流生物指数(RBI)概念,其值即为累加上述5个指数后的总分值,建立了河流生物指数评价秦淮河水质的标准,并对21个样点的水质进行重新评价,效果较单项生物指数如香农多样性指数评价结果更接近实际情况。     

钱塘江中游水生昆虫群落功能多样性对土地利用变化的响应

基于11个反映水生昆虫生活史、对外界抵抗力和生理特征的生物学性状,应用目前国际上通用的fourth-corner统计方法,系统研究了浙江省钱塘江中游流域水生昆虫功能多样性对土地利用变化的响应.结果表明： 部分生物学性状对土地利用变化敏感,且其随人类干扰强度的变化所发生的改变与预期吻合,其最大个体长度逐渐下降,呼吸方式从以鳃呼吸为主转变为以表皮呼吸为主,掘穴者数量显著增加.参照点的功能多样性指数(Rao值)显著高于干扰点(P<0.001).说明人类活动引起的土地利用变化导致溪流水质和栖境质量下降,引起群落的变异和对生物性状组成的筛选,最终导致水生昆虫群落功能多样性改变.生物性状及功能多样性是未来评价生态健康的潜在指标.     

Functional indicators of stream health: a river‐basin approach

1. The efficacy of leaf‐litter decomposition, sediment respiration, biofilm biomass, growth, chlorophyll a concentration and the autotrophic index (biofilm ash‐free dry mass/chlorophyll a) and fungal biomass for detecting human‐induced change was evaluated using 24 references and 15 disturbed stream sites located in central Portugal. 2. Decomposition rates of alder (Alnus glutinosa) and oak (Quercus robur) leaves and sediment respiration rates were effective in discriminating impairment. Decomposition was negatively correlated with abiotic factors, such as ammonium and nitrite concentrations, connectivity and alterations in the hydrological regime, and positively correlated with nitrate concentration and oxygen concentration. Sediment respiration rates were correlated with organic contamination, land use and morphological changes. 3. Growth rates of biofilm, concentration of chlorophyll a and the autotrophic index, although 41–73% higher at disturbed compared to reference sites, were not significantly different. These three variables were significantly correlated with total organic carbon, oxygen concentration, pH, nitrite and the presence of dams. Fungal biomass on leaves and biofilm biomass on natural substrata did not differ between reference and disturbed sites. 4. Our findings lend support to the use of functional variables like decomposition and sediment respiration in monitoring and when used together with structural variables should give a more holistic measure of stream health.     

Evaluation of approaches for measuring taxonomic completeness of lake profundal macroinvertebrate assemblages

1. Benthic macroinvertebrates (MI) are commonly used to assess freshwater ecosystems with the reference condition approach. Such assessments necessitate control for natural community variation, either by categorical typologies or by predictive models that have been widely and successfully developed for running water biota but not previously for lake profundal invertebrates. 2. We evaluated four modelling techniques [multivariate regression tree (MRT), limiting environmental differences, nonparametric multiplicative regression (NPMR) and River Invertebrate Prediction And Classification System (RIVPACS) and the operative Finnish lake typology for assessing taxonomic completeness (observed‐to‐expected number of taxa, O/E) of profundal MI assemblages. We used data from 74 and 33 minimally disturbed reference lake basins for calibration and validation of the approaches, respectively, and 72 test basins subject to various anthropogenic pressures to evaluate sensitivity to detect impact. Either all predicted taxa (threshold probability of capture P_t = 0+) or only those predicted to be captured with ≥0.25 probability were used to calculate O/E. 3. With P_t = 0.25, all four modelling approaches were accurate (mean O/E = 0.966–1.053) but imprecise (SD of O/E = 0.279–0.304) in predicting the fauna actually observed in validation sites. All models were subtly more precise than a null model (mean 1.038, SD 0.343) or the typology (1.046, 0.327). The taxon‐specific NPMR model was slightly more precise than the other three models based on site groupings. 4. The O/E values correlated relatively weakly (r = 0.55–0.86) among the approaches, which thus produced contrasting lake‐specific assessments, despite their seemingly comparable performances. Indeed, typology, suggesting that MI assemblages were impaired in 56% of test sites, was more sensitive than the other approaches (26–46%) as an indicator of human‐induced deterioration. However, this greater ostensible sensitivity seemed to be biased, as lake morphometry, a main driver of natural community variation, remained uncontrolled by the typology. 5. Generally, our exercise illustrates the inconclusiveness of the common validation criteria for the assessment methods. The apparent poor predictability of the profundal fauna, irrespective of the method, may partly stem from large observation error, which could be alleviated by more intensive sampling. However, instead of an O/E‐taxa index, some other metric encompassing quantitative aspects might be preferable for assessing these species‐poor communities.     

Predictive modelling of freshwater fish as a biomonitoring tool in New Zealand

SUMMARY 1. A challenge has been issued to ecologists to find quantitative ecological relationships that have predictive power. A predictive approach has been successful when applied to biomonitoring using stream invertebrates with the River Invertebrate Prediction and Classification System (RIVPACS). This approach, to our knowledge, has not been applied to freshwater fish assemblages.
2. This paper describes the initial results of the application of a regional predictive model of freshwater fish occurrence using 200 reference sites sampled in the Manawatu–Wanganui region of New Zealand over late summer/autumn 2000. In brief (i) sites were classified into biotic groups (ii) the physical and chemical characteristics that best describe variation among these groups were determined and (iii) the relationship between these environmental variables and fish communities was used to predict the fauna expected at a site.
3. Reference sites clustered into six groups based on fish density and community composition. Using 14 physical variables least influenced by human activities, a discriminant model allocated 70% of sites to the correct biological classification group. The variables that best separated the site groups were mainly large-scale variables including altitude, distance from the coast, lotic ecoregion and map co-ordinates.
4. The model was further validated by randomly removing 20% of the sites, rebuilding the model and then determining the number of removed sites correctly allocated to their original biotic groups using environmental variables. Using this process 67% of the removed sites were correctly reassigned to the six predetermined groups.
5. A further 30 sites were used to determine the ability of the model to detect anthropogenic impact. The observed over expected taxa ( O / E ) ratios were significantly lower than the reference site O / E ratios, indicating a response of the fish assemblages to the known stressors.     

Macroinvertebrate assemblage response to highway crossings in forested wetlands: implications for biological assessment

Despite the mandate of the Clean Water Act to protectthe physical, chemical, and biological integrity ofthe USA's wetlands, the use of biota to assess wetlandcondition has not been well explored. During June,1996, we evaluated the response of macroinvertebrateassemblages to fill-culvert highway crossings in twobottomland forested wetlands in North Carolina. Ourobjective was to apply biological assessment methodsand metrics that have been effectively used in streamsto explore their applicability in forested wetlands.We found significant changes in several metrics as afunction of distance from the highway crossings. Arealand numerical taxon richness increased within at least40 m of highway when compared to control locations.Percent dominant taxon values were lowest within 10 mof the highway. Percent herbivores also increasedsignificantly within at least 40 m of the highway,reflecting the lower % crown closure and associatedshift in primary production from trees to herbaceousmacrophytes and algae. The North Carolina BioticIndex, a metric of tolerance, did not reflectassemblage changes near the highway. Ordination andpermutation tests revealed that assemblage compositionwas significantly different from controls at 10 and 40 mdistances from the highway crossings. In particular,algal grazers such as the mayflies Caenissp.and Callibaetissp. responded positively and thedamselflies Ischnuraspp. and the fingernailclams Sphaeriumspp. responded negatively to thecrossings. Favorable algal and herbaceous detritalresources, greater patchiness and habitat complexity,and overall high tolerance to natural stressorsprobably contributed to the increase in taxon richnessnear the highway. However, significant deviation fromcontrol locations indicated the highway was a sourceof perturbation. Our findings illustrate the potentialutility of macroinvertebrate assemblages for wetlandassessment, but suggest the importance of defining thereference condition as well as the need fordevelopment of metrics for specific classes ofwetlands.     

Bacteria used in the biological control of plant-parasitic nematodes: populations, mechanisms of action, and future prospects

As a group of important natural enemies of nematode pests, nematophagous bacteria exhibit diverse modes of action: these include parasitizing; producing toxins, antibiotics, or enzymes; competing for nutrients; inducing systemic resistance of plants; and promoting plant health. They act synergistically on nematodes through the direct suppression of nematodes, promoting plant growth, and facilitating the rhizosphere colonization and activity of microbial antagonists. This review details the nematophagous bacteria known to date, including parasitic bacteria, opportunistic parasitic bacteria, rhizobacteria, Cry protein-forming bacteria, endophytic bacteria and symbiotic bacteria. We focus on recent research developments concerning their pathogenic mechanisms at the biochemical and molecular levels. Increased understanding of the molecular basis of the various pathogenic mechanisms of the nematophagous bacteria could potentially enhance their value as effective biological control agents. We also review a number of molecular biological approaches currently used in the study of bacterial pathogenesis in nematodes. We discuss their merits, limitations and potential uses.     

Minimizing Cognitive Errors in Site-Specific Causal Assessments

Interest in causal investigations in aquatic systems has been a natural outgrowth of the increased use of biological monitoring to characterize the condition of resources. Although biological monitoring approaches are critical tools for detecting whether effects are occurring, they do not identify the cause of the observed effects. Formal approaches to causal evaluation can provide a mechanism to build on expert knowledge, increasing the likelihood that remedial efforts will achieve the desired environmental improvement. This paper examines how formal approaches to causal investigations minimize common errors. We reviewed common cognitive errors reported in the literature, and compared them with considerations suggested for strength-of-evidence approaches. Many of the causal considerations are directed toward distinguishing spurious correlations from true causal relationships. However, this is only one type of error; others include hypothesis dependence, confirmation bias, hypothesis tenacity and anchoring. We suggest three general principles for minimizing error in site-specific investigations: (1) Conduct the causal evaluation as a fair, transparent comparison among alternatives; (2) Carefully describe and quantify the conjunction of cause and effect; and (3) Consider that conjunction between cause and effect is spurious, or that a real conjunction was masked.