Richard H. Norris

The reference condition: a comparison of multimetric and multivariate approaches to assess water-quality impairment using benthic macroinvertebrates

Traditional methods of establishing control sites in field-oriented biomonitoring studies of water quality are limited. The reference-condition approach offers a powerful alternative because sites serve as replicates rather than the multiple collections within sites that are the replicates in traditional designs using inferential statistics. With the reference-condition approach, an array of reference sites characterises the biological condition of a region; a test site is then compared to an appropriate subset of the reference sites, or to all the reference sites with probability weightings. This paper compares the procedures for establishing reference conditions, and assesses the strengths and deficiencies of multimetric (as used in the USA) and multivariate methods (as used in the UK, Canada, and Australia) for establishing water-quality status. A data set of environmental measurements and macroinvertebrate collections from the Fraser River, British Columbia, was used in the comparison. Precision and accuracy of the 2 multivariate methods tested (AUStralian RIVer Assessment Scheme: AusRivAS, BEnthic Assessment of SedimenT: BEAST) were consistently higher than for the multimetric assessment. Classification by ecoregion, stream order, and biotic group yielded precisions of 100% for the AusRivAS, 80-100% for the BEAST, and 40-80% for multimetrics; and accuracies of 100%, 100%, and 38-88%, respectively. Multimetrics are attractive because they produce a single score that is comparable to a target value and they include ecological information. However, not all information collected is used, metrics are often redundant in a combination index, errors can be compounded, and it is difficult to acquire current procedures. Multivariate methods are attractive because they require no prior assumptions either in creating groups out of reference sites or in comparing test sites with reference groups. However, potential users may be discouraged by the complexity of initial model construction. The complementary emphases in the multivariate methods examined (presence / absence in AusRivAS cf. abundance in BEAST) lead us to recommend that they be used together, and in conjunction with, multimetric studies.

DEVELOPMENT AND EVALUATION OF PREDICTIVE MODELS FOR MEASURING THE BIOLOGICAL INTEGRITY OF STREAMS

The ratio of the number of observed taxa to that expected to occur in the absence of human-caused stress (OIE) is an intuitive and ecologically meaningful measure of biological integrity. We examined how OIE ratios derived from stream invertebrate data varied among 234 unimpaired reference sites and 254 test sites potentially impaired by past logging. Data were collected from streams in three montane ecoregions in California. Two sets of River Invertebrate Prediction and Classification System (RIVPACS) predictive mod- els were built: one set of models was based on near-species taxonomic resolution; the other was based on family identifications. Two models were built for each level of taxonomic resolution: one calculated 0 and E based on all taxa with probabilities of capture (Pj) > 0; the other calculated 0 and E based on only those taxa with Pc ? 0.5. Evaluations of the performance of each model were based on three criteria: (1) how well models predicted the taxa found at unimpaired sites, (2) the degree to which OIE values differed among unimpaired reference sites and potentially impaired test sites, and (3) the degree to which test site OIE values were correlated with independent measures of watershed alteration. Predictions of species models were more accurate than those of family models, and pre- dictions of the PC ? 0.5 species model were more robust than predictions of the PC > 0 model. OIE values derived from both species models were related to land use variables, but only assessments based on the Pc > 0.5 model were insensitive to naturally occurring differences among streams, ecoregions, and years.

Taxonomic resolution of benthic macroinvertebrate communities in bioassessments

BRIDGES is a recurring feature of J-NABS intended to provide a forum for the interchange of ideas and information between basic and applied researchers in benthic science. Articles in this series focus on topical research areas and linkages between basic and applied aspects of research, monitoring, policy, and education. Readers with ideas for topics should contact Associate Editors, Nick Aumen and Marty Gurtz. The issue of taxonomic resolution has been a topic of interest in benthological studies for a long time, but the increasing use of aquatic insects—and more recently algae—in assessing water quality has heightened the importance of understanding the tradeoffs associated with different levels of taxonomy. Bailey and co-authors lead off this set of papers with a review of the types of studies and questions for which species identifications are essential, but then examine whether there are circumstances—e.g., in some bioassessments—in which taxonomic information at a higher (e.g., family) level is sufficient, or may even be better. They propose a 2-tiered approach for taxonomy used in bioassessment studies: family-level identifications for multivariate analyses or index calculation, and species identification for a short list of indicator taxa that are appropriate for a particular study. Lenat and Resh review a variety of uses of taxonomic information for aquatic insects and recommend levels of taxonomy that are appropriate for different situations. They conclude that biological monitoring studies yield the greatest benefits using genus- or species-level taxonomy. Hill et al. examine issues of taxonomic resolution for diatom studies, using results from a large set of diatom assemblage data collected from 199 streams over a 3-y period. They found that genus-level taxonomy appears to adequately describe the response of some diatom assemblage attributes to environmental gradients, especially for those gradients that involve morphological (motility) or physiological (pH tolerance) adaptations that are related to evolved genus-level characteristics. Nick Aumen, nick_aumen@nps.gov Marty Gurtz, megurtz@usgs.gov Co-editors

Correlation of environmental variables with patterns of distribution and abundance of common and rare freshwater macroinvertebrates

Abstract This study explores the environmental factors underlying variation in abundance of common and rare freshwater taxa. Hybrid multidimensional scaling is used to model variation in distribution and abundance of freshwater microinvertebrate taxa over 17 sample sites in the upper catchment of the LaTrobe River, Victoria, Australia. Initial analysis of 40 common taxa revealed high correlations of the ordination space with physico-chemical variables related to temperature, stream order, particle size and water chemistry. Analysis of all 269 taxa, or alternatively of the 229 rarer taxa alone, resulted in ordination spaces that showed high correlations for additional physico-chemical variables, particularly relating to water chemistry. Monte Carlo significance tests supported this finding in demonstrating that the analysis of all taxa produced a greater number of significant correlations between the ordination space and physico-chemical variables. The additional important environmental correlates revealed by the analysis of the rare taxa suggested that there might be differences in the set of environmental variables that are related to patterns of distribution and abundance of rare versus common taxa. A Monte Carlo test was carried out to test the null hypothesis that the failure to recover some environmental correlates in the analysis of common taxa simply resulted from the small (40) number of taxa involved. Results of the test generally showed that rareness versus commonness could not be implicated in the greater recovery of these water chemistry variables in the analysis of the rare taxa. The recovery of additional environmental correlates with the inclusion of rare taxa has implications for conservation studies at the community level. Ordination can be used for survey extension where complete information on distribution and abundance of taxa is unavailable. The ability of ordination methods to summarise distribution and abundance of rare taxa, and incorporate their additional information on environmental variation, suggests that representativeness of the ordination space is a useful criterion for reserve selection.

Monitoring river health

Photo 1. Richard Norris has concentrated his research on biological assessment of rivers. He recently ran an international conference on river health and has played a major role in developing Australia’s National River Health Program. He is Associate Professor in freshwater Ecology at the University of Canberra in Australia’s national capital and leads a program on water quality and ecological assessment for the Cooperative Research Centre for Freshwater Ecology

Classification and prediction of macroinvertebrate assemblages from running waters in Victoria, Australia

We constructed predictive models using 2 macroinvertebrate data sets (for both species and family) from bankside habitats at 49 undisturbed reference sites from 6 Victorian river basins; data were accumulated over 4 to 6 sampling occasions. Classification (by unweighted pair-group arithmetic averaging with the Bray-Curtis association measure) showed 3 site groups were evident at the species level and 4 at the family level. A subset of 5 of 22 environmental variables provided maximum discrimination (using stepwise discriminant analysis) between the 3 species site groups; these variables were: conductivity, altitude, substrate heterogeneity, distance of a site from source, and longitude. Four variables discriminated between the 4 family site groups: conductivity, catchment area upstream of site, mean annual discharge, and latitude. From the discriminant analysis, it was possible to predict the group into which an unknown site (specified only by measurements on the 4 or 5 variables just noted) would be placed and thus the probabilities of occurrence of taxa at this site. To test predictive ability, 4 sites were removed at random from the 2 data sets and the classification and discriminant models were recalculated. This process was repeated 5 times. The identity and number of taxa observed at each of these sites were compared with those predicted with a probability of occurrence >50% and the results expressed as a ratio of numbers observed to numbers expected (O/E). This ratio varied from 0.75 to 1.05 at the species level and from 0.83 to 1.12 at the family level, indicating that the fauna conformed with expectation (O/E near 1.0). To test such predictive models on independent data, O/E ratios were also calculated for family data collected in spring at 18 sites from a basin not used in the original models. Two new discriminant models based on single sets of samples from the reference sites taken in spring were constructed for this purpose. O/E ratios varied from 0.09 to 1.01 for the 18 sites and were inversely correlated (r = -0.4 to -0.8) with a range of water quality variables, the values of which increased as water quality deteriorated. The O/E ratio could thus be considered a sensitive measure of disturbance.

Scales of Macroinvertebrate Distribution in Relation to the Hierarchical Organization of River Systems

The multiscale distribution of macroinvertebrate assemblages may correspond to the hierarchical arrangement of river systems because geomorphological processes manifest characteristic environmental conditions at different scales. Macroinvertebrates were sampled according to a nested hierarchical design incorporating 4 geomorphologically derived scales: catchment, zone, reach, and riffle. Analysis of Similarity, mean similarity dendrograms, and nested analysis of variance were used to determine the scale(s) at which macroinvertebrate assemblages differed. Macroinvertebrate assemblages were similar among riffles within a reach, but were dissimilar at the zone and catchment scales. There also was a regional-scale pattern of macroinvertebrate distribution that was larger than the geomorphologically derived catchment scale. Subsequent partitioning of macroinvertebrate data into regions revealed a relationship between macroinvertebrate distribution and the catchment and zone scales of river system organization. Consideration of the hierarchical organization of river systems from a purely physical perspective may fail to encompass scales relevant to the biota, indicating that biological information should be included as a primary hierarchical component in multiscale stream studies.

Performance of different landscape classifications for aquatic bioassessments: introduction to the series

Bioassessment is the process of determining if human activity has altered the biological properties of an ecosystem. To quantify assessments we must be able to specify those biological properties that are either expected to occur in the absence of human alteration (the pristine condition) or that are attainable given current ecological, economic, and political constraints. Because we almost always lack knowledge about the biota that existed at sites prior to human alteration, we must usually infer the biological potential of a site from other information. Such inferences are typically derived from a classification of sites that relate variation in biological properties of interest to class membership. Our ability to detect impairment is therefore largely a function of how precisely and accurately expected conditions can be inferred from the classification used (Karr and Chu 1998). Many classification systems have been developed for freshwater habitats (reviews by Hawkes 1975, Cowardin et al. 1979, Busch and Sly 1992, Maxwell et al. 1995), but it is those with the ability to predict biological properties that are of primary interest to water resource managers who must quantify the biological condition of a site. As many countries move toward the use of biological assessments as a primary means of measuring the ecological health of their surface waters, it is imperative that the most robust classification systems possible be developed and implemented. All predictive classifications are based on the idea that biological properties can be inferred from readily measured environmental or historical features. Classifications based on regional landscape descriptors have received considerable attention from water resource managers

Analyzing cause and effect in environmental assessments: using weighted evidence from the literature

Abstract.  Sound decision making in environmental research and management requires an understanding of causal relationships between stressors and ecological responses. However, demonstrating cause–effect relationships in natural systems is challenging because of difficulties with natural variability, performing experiments, lack of replication, and the presence of confounding influences. Thus, even the best-designed study may not establish causality. We describe a method that uses evidence available in the extensive published ecological literature to assess support for cause–effect hypotheses in environmental investigations. Our method, called Eco Evidence, is a form of causal criteria analysis—a technique developed by epidemiologists in the 1960s—who faced similar difficulties in attributing causation. The Eco Evidence method is an 8-step process in which the user conducts a systematic review of the evidence for one or more cause–effect hypotheses to assess the level of support for an overall question. In contrast to causal criteria analyses in epidemiology, users of Eco Evidence use a subset of criteria most relevant to environmental investigations and weight each piece of evidence according to its study design. Stronger studies contribute more to the assessment of causality, but weaker evidence is not discarded. This feature is important because environmental evidence is often scarce. The outputs of the analysis are a guide to the strength of evidence for or against the cause–effect hypotheses. They strengthen confidence in the conclusions drawn from that evidence, but cannot ever prove causality. They also indicate situations where knowledge gaps signify insufficient evidence to reach a conclusion. The method is supported by the freely available Eco Evidence software package, which produces a standard report, maximizing the transparency and repeatability of any assessment. Environmental science has lagged behind other disciplines in systematic assessment of evidence to improve research and management. Using the Eco Evidence method, environmental scientists can better use the extensive published literature to guide evidence-based decisions and undertake transparent assessments of ecological cause and effect.

Development of a Standardised Approach to River Habitat Assessment in Australia

Despite the demonstrated utility of the Australian River Assessment Scheme (AUSRIVAS) to provide national-scale information on the biological condition of rivers, there is no commensurate scheme that can provide standardised information on physical habitat. Existing habitat assessment methods are not suitable for implementation on a national scale, so we present a new habitat assessment protocol that incorporates favorable elements of existing methods. Habitat Predictive Modelling forms the basis for the protocol because it can predict the occurrence of local-scale features from large-scale data, uses the reference condition concept, can be modified to incorporate a range of biologically and geomorphologically relevant variables, and employs a rapid survey approach. However, the protocol has been augmented with geomorphological variables and incorporates principles of hierarchy and geomorphological river zonation. There are four sequential components to the implementation of the protocol: reference site selection, data collection, predictive model construction and assessment of test sites using the predictive models. Once implemented, the habitat assessment protocol will provide a standardised tool for the assessment of river habitat condition at a variety of governance levels.