Enhancing the performance and interpretation of freshwater biological indices: An application in arid zone streams

We assessed the performance of biological indices developed for invertebrate assemblages occurring in arid zone streams: a multimetric index (MMI) and an O/E index of taxonomic completeness. Our overall goal was to advance our understanding of the factors that affect performance and interpretation of biological indices. Our specific objectives were to (1) develop biological indices that are insensitive to natural environmental gradients, (2) develop a general method to determine if the biological potential of an assessed site is adequately represented by the population of reference sites, (3) develop a robust method to select metrics for inclusion in MMIs that ensures maximum independence of metrics, and (4) determine if a fundamental sample property (the evenness of taxa counts within a sample) affects index performance. Random Forest modeling revealed that both individual metrics and taxa composition were strongly associated with natural environmental heterogeneity, which meant both the MMI and O/E index needed to be based on site-specific expectations. We produced a precise, responsive, and ecologically robust MMI by using principal components analysis to identify 7 statistically independent metrics from a list of 31 candidate assemblage-level metrics. However, the O/E index we developed was relatively imprecise compared with O/E indices developed for other regions. This imprecision may be the consequence of low predictability in local taxa composition associated with the relatively high spatial isolation of aquatic habitats within arid regions. We were also able to assess the likelihood that the biological potential of assessed sites were adequately characterized by the population of reference sites by developing and applying a multivariate, nearest-neighbor test that determined if an assessed site occurred within the environmental space of the reference site network. This approach is robust and applicable to all biological indices. We also demonstrate that the evenness of taxa counts within a sample is positively related to estimates of sample taxa richness and thus the scores of both indices. The relationship between richness and sample evenness can potentially compromise inferences regarding biological condition, and post hoc adjustments for the effects of evenness on index scores might be desirable. Further improvements in the performance and interpretation of biological indices will require simultaneous consideration of the effects of incomplete sampling on characterization of biological assemblages and the physical and biological factors that influence community assembly.     

Development of a benthic macroinvertebrate multimetric index (MMI) for Neotropical Savanna headwater streams

Assessing the ecological impacts of anthropogenic pressures is a key task in environmental management. Multimetric indices (MMIs), based on aquatic assemblage responses to anthropogenic pressures, have been used increasingly throughout the world. The MMI approach is a low-cost, rapid field method that produces an aquatic condition index that responds precisely to anthropogenic pressures, making it useful for conservation and environmental management. We developed four candidate MMIs based on benthic macroinvertebrate assemblages sampled at 40 randomly selected sites to assess the environmental condition of streams upstream of a hydroelectric power plant in the Brazilian Neotropical Savanna biome. Those MMIs were built from landscape-adjusted and unadjusted biological metrics as well as two alternative ways of choosing metrics. The alternative MMIs performances were tested by comparing their precision to distinguish least-disturbed areas, responsiveness to discriminate least- and most-disturbed areas, and sensitivity to anthropogenic pressures at catchment and local scales. The best performing MMI had landscape-adjusted metrics and was produced through use of principal component analysis for metric selection. It included 4 metrics: Ephemeroptera richness, average tolerance score per taxon, percentage of predator individuals, and percentage of Odonata individuals adjusted by elevation. This index discriminated well the anthropogenic pressures at local- and catchment-scales, and at both scales simultaneously, as indicated by an integrated disturbance index. Our methodological development included statistical criteria for identifying least- and most-disturbed sites, calibrating for natural landscape variability, and use of non-redundant metrics. Therefore, we expect it will provide a model for environmental assessment of water resources elsewhere in Brazil and in other nations.     

基于底栖动物预测模型构建生物完整性指数评价河流健康

提高生物完整性指数(integrity of biotic index,IBI; 又称多参数指数multi-metric index, MMI)在时间和空间尺度的稳定性是水生态完整性评价和水环境管理实践的重要内容.本研究利用2004—2011年在浙江省多个河流采集的227个点位的底栖动物和水质理化数据,利用地理信息系统(GIS)提取样点及其对应流域的自然预测因子(如地理形态学、气候学)和土地利用数据,通过随机森林模型方法定量时间和空间尺度自然变量对生物群落的影响,构建基于预测模型控制自然因子影响方法和常规方法的MMI,并比较它们的表现力.结果表明: 基于预测模型法和基于常规方法构建的MMI的核心组成参数存在差异,随机森林模型中自然预测因子对预测模型MMI构成生物参数的解释量介于11.4%～61.2%.预测模型方法提高了MMI的精确度和准确度,但其敏感性和响应性低于常规方法的MMI.最近距离方法表明,9个评价点位和1个严重受损点位的自然属性与参照点位的自然属性存在差异性.在计算参照点位自然属性代表性范围的基础上,采用预测模型方法控制自然变量可以提高MMI的精确度和准确度,同时降低评价结果出现Ⅰ型(将健康水体误判为受损水体)或者Ⅱ型(将受损水体误判为健康水体)错误的可能性.研究结果可以为提高完整性指数评价稳定性和表现力提供方法支持.     

An improved macroinvertebrate multimetric index for the assessment of wadeable streams in the neotropical savanna

Multimetric indices (MMIs) have been successfully used to assess ecological conditions in freshwater ecosystems worldwide, and provide an important management tool especially in countries where biological indicators are fostered by environmental regulations. Nonetheless, for the neotropics, the few published papers are limited to small local scales and lack standardized sampling protocols. To fill the gaps left by previous studies, we propose a stream MMI that reflects anthropogenic impacts by using macroinvertebrate assemblage metrics from a data set of 190 sites collected from four hydrologic units in the Paraná and São Francisco River Basins, southeastern Brazil. Sites were selected through use of a probabilistic survey design allowing us to infer ecological condition to the total of 9432 kilometers of wadeable streams in the target population in the four hydrologic units. We used a filtering process to determine the least- and most-disturbed sites based on their water quality, physical habitat structure, and land use. To develop the MMI, we followed a stepwise procedure to screen our initial set of biological metrics for influence of natural variation, responsiveness and discriminance to disturbances, sampling variability, and redundancy. The final MMI is the sum of 7 scaled assemblage metrics describing different aspects of macroinvertebrate assemblage characteristics: Ephemeroptera richness, % Gastropoda individuals, Shannon-Wiener diversity index, % sensitive taxa richness, % scraper individuals, temporarily attached taxa richness, and gill respiration taxa richness. The MMI clearly distinguished the least-disturbed sites from the most-disturbed sites and showed a significant negative response to anthropogenic stressors. Of the total length of wadeable streams in the study area, 38%, 35%, and 27% were classified by the MMI as being in good, fair, and poor condition, respectively. By reducing the subjectivity of site selection, rigorously selecting the set of reference sites, and following a standardized metric screening method, we developed a robust MMI to assess and monitor ecological condition in neotropical savanna streams. This improved MMI provides an effective ecological tool to guide decision makers and managers in developing and implementing improved, cost-effective environmental policies, regulations, and monitoring of those systems.     

Constructing multimetric indices and testing ability of landscape metrics to assess condition of freshwater wetlands in the Northeastern US

Using data collected for the Environmental Protection Agency's (EPA) 2011 National Wetland Condition Assessment (NWCA), we developed separate multimetric indices (MMIs) for vegetation, soil, algae taxa, and water to assess condition of freshwater wetlands in the northeastern US. This study represents the first attempt at developing multiple biotic and abiotic MMIs of wetland condition over this large of an area, and is only possible because of the high quality data collected by the NWCA. We chose metrics that distinguished between reference and most disturbed sites, had a signal:noise ratio > 2, and were not strongly correlated with other metrics, latitude, or longitude. The vegetation and soil MMIs were the best performing indices, with good separation between reference and most disturbed sites, and included commonly used condition metrics (e.g., pH and P concentration for soil, and percent cover of exotic species for vegetation). The algae MMI was the weakest index, with considerable overlap between reference and most disturbed sites. For areas smaller than our study, algae taxa may be suitable for wetland MMIs. However, in our study area, many algae taxa followed strong latitudinal or longitudinal gradients, and could not be considered for the algae MMI. Small sample size and several metrics with a high signal:noise ratio were the major limitations of the water MMI. We also examined how well landscape (level 1) and rapid assessment (level 2) metrics predicted MMIs using random forest regression. Agricultural land use surrounding wetlands was an important predictor for all four MMIs, although the soil, algae and water MMI models performed best when intensive (level 3) vegetation metrics were also included in the random forest regression models. Based on these results, we recommend wetland assessment programs employ a combination of landscape and rapid assessment monitoring at many sites, along with level 3 monitoring at a subset of sites. We developed these MMIs to evaluate freshwater wetland condition for a long-term monitoring program in Acadia National Park. These MMIs are also applicable to a range of wetland types covering 11 states in the northeastern United States and can be calculated using a downloadable spreadsheet that calculates and rates each MMI using raw metric values.     

Regional fish community indicators of landscape disturbance to catchments of the conterminous United States

Biological assessments of river conditions are increasingly conducted at regional and continental scales that match the extent of large-scale river management efforts. Multimetric indices composed of biological community indicators are commonly used to assess ecological condition and indices have recently been applied in large regions. Methods for large-scale multimetric index creation emphasize repeatability, comparability across regions, and objective selection of candidate metrics. Here we used an extensive fish dataset to create a large pool of fish community metrics which were screened to create multimetric indices (MMIs) in eight ecoregions covering the conterminous U.S. Candidate metrics were tested for metric range, corrected for natural gradients using boosted regression trees, and then tested for repeatability and sensitivity to landscape disturbance. Temporally stable and repeatable metrics were then evaluated for redundancy and used to compose MMIs for each region. Our MMIs were significantly correlated to independently developed MMIs, accurately reproducing prior index values with moderate to high precision and little bias. Our study demonstrates the utility of boosted regression tree models for correcting metric values for natural abiotic gradients and shows that the order of screening tests has a potentially important influence on metric selection. The resultant regional indices and component metrics provide a basis for assessing condition and testing hypotheses about landscape influences on aquatic ecosystems at a national scale in the US.     

Effects of fixed-count size on macroinvertebrate richness,site separation,and bioassessment of Chinese monsoonal streams

Subsampling that counts and identifies a random subset of individuals from field samples is widespread yet controversial. We evaluated the effects of fixed-count size on macroinvertebrate richness, site separation, and performance of modeled and null (i.e., natural variation adjusted and unadjusted, respectively) biological indices in Chinese monsoonal stream sites. To do so, we estimated the fixed-count size that was adequate to collect 95% of the estimated true regional macroinvertebrate taxa richness, and we also evaluated the effects of fixed-count size on site and group (reference vs test) separation, and the precision, sensitivity and responsiveness of modeled and null multimetric indices (MMI) and observed/expected (O/E) indices. Random subsamples of individual fixed-count sizes ranged from 50 to 500. Mean cumulative taxa richness continued to increase with increasing fixed-count size. We found that 150 and 200 individuals were needed to collect 75% of estimated true species richness 75% and 95% of the time, respectively. We estimated that at least 1500 individuals per site were required for collecting 95% of estimated true species richness. Site and group separation and classification strength also improved with increased fixed-count size. Larger fixed-count sizes improved the performance of modeled and null O/E₅₀ (O/E calculated using taxa with probabilities of capture ≥0.5); however, they showed no significant difference for modeled and null MMIs and O/E₀ (O/E calculated using all taxa). Overall, we found that fixed-counts affected richness and site/group separation, but not index performance. Until China develops standard sampling methods, we recommend using fixed-count sizes of 500 individuals and rarefaction of ≥200 individuals to limit the effects of sampling error for site and group separation and for precise and accurate bioassessment, respectively.     

Development and application of benthic macroinvertebrate-based multimetric indices for the assessment of streams and rivers in the Taihu Basin,China

The development of biological indicators for assessing ecological conditions in streams and rivers is urgently needed in China, particularly in heavily impacted regions. The aim of this study was to develop and apply benthic macroinvertebrate-based multimetric indices (MMIs) for the assessment of streams and rivers in the western hill and eastern plain aquatic ecoregions of the Taihu Basin. MMIs were based on samples collected from October 16 to November 8 2012 at 120 sites in streams and rivers. Least disturbed sites defined the reference conditions. Chemical water quality, physical habitat, and land use were used as criteria to identify reference sites in the basin. Metrics related to benthic macroinvertebrate richness, composition, diversity and evenness, pollution tolerance, and functional feeding groups were screened by range, sensitivity, responsiveness, and redundancy tests. Total number of taxa; percentage of Ephemeroptera, Trichoptera and Odonata (% ETO); Berger–Parker’s index (BP); Biotic index (BI); and percentage of filterers–collectors (% FC) were used to construct the MMI for the western hill aquatic ecoregion (MMI_W). Total number of taxa, percentage of Crustacea and Odonata (% CO), BP, BI, and % FC were used to construct the MMI for the eastern plain aquatic ecoregion (MMI_E). The MMI scores were obtained by combining the rating categories (excellent, good, fair, poor, and very poor). The MMIs were tested using a separate subset of the data, and the results indicated that the newly developed MMIs were robust in terms of percentage of sites correctly classified, coefficient of variation, box-separation ratios, and separation powers. The ecological status was then evaluated based on the MMI scores. The results indicated that the general ecological status of streams and rivers in the Taihu Basin was rated lower than “good”, the western hill aquatic ecoregion was rated “fair” and the eastern plain aquatic ecoregion was rated “poor”. Moreover, the MMIs showed a significant negative response to an increasing gradient of disturbance. Therefore, these preliminary MMIs can be used as assessment tools in ecological biomonitoring and management of the Taihu Basin.     

A multi-assemblage,multi-metric biological condition index for eastern Amazonia streams

Multimetric indices (MMIs) are widely used for assessing ecosystem condition and they have been developed for a variety of biological assemblages. However, when multiple assemblages are assessed at sites, the assessment results may differ because of differing physiological sensitivities to particular stressor gradients, different organism size and guilds, and the effects of different scales of disturbances on the assemblages. Those differences create problems for managers seeking to avoid type-1 and type-2 statistical errors. To alleviate those problems, we used an anthropogenic disturbance index for selecting and weighting metrics, modeled metrics against natural variability to reduce the natural variability in metrics, and developed an MMI based on both fish and aquatic insect metrics. We evaluated eight different ways of calibrating and combining candidate metrics and found that MMIs with unweighted and modeled aquatic insect and fish metrics were the preferred MMI options.     

An algorithmic and information-theoretic approach to multimetric index construction

The use of multimetric indices (MMIs), such as the widely used index of biological integrity (IBI), to measure, track, summarize and infer the overall impact of human disturbance on biological communities has been steadily growing in recent years. Initially, MMIs were developed for aquatic communities using pre-selected biological metrics as indicators of system integrity. As interest in these bioassessment tools has grown, so have the types of biological systems to which they are applied. For many ecosystem types the appropriate biological metrics to use as measures of biological integrity are not known a priori. As a result, a variety of ad hoc protocols for selecting metrics empirically has developed. However, the assumptions made by proposed protocols have not be explicitly described or justified, causing many investigators to call for a clear, repeatable methodology for developing empirically derived metrics and indices that can be applied to any biological system. An issue of particular importance that has not been sufficiently addressed is the way that individual metrics combine to produce an MMI that is a sensitive composite indicator of human disturbance. In this paper, we present and demonstrate an algorithm for constructing MMIs given a set of candidate metrics and a measure of human disturbance. The algorithm uses each metric to inform a candidate MMI, and then uses information-theoretic principles to select MMIs that capture the information in the multidimensional system response from among possible MMIs. Such an approach can be used to create purely empirical (data-based) MMIs or can, optionally, be influenced by expert opinion or biological theory through the use of a weighting vector to create value-weighted MMIs. We demonstrate the algorithm with simulated data to demonstrate the predictive capacity of the final MMIs and with real data from wetlands from Acadia and Rocky Mountain National Parks. For the Acadia wetland data, the algorithm identified 4 metrics that combined to produce a −0.88 correlation with the human disturbance index. When compared to other methods, we find this algorithmic approach resulted in MMIs that were more predictive and comprise fewer metrics.     

A probabilistic model characterizing fish assemblages of French rivers: a framework for environmental assessment

1. Management of running waters and assessment of water quality trends require the use of biological methods. Among potential indicators, fish assemblages are of particular interest because of their ability to integrate environmental variability at different spatial scales. 2. The French Water Agencies and the Ministry of the Environment initiated a research programme to develop a fish-based index that would be applicable nation-wide. Such an index should encompass the relative importance of geographic, ecoregional and local factors influencing the distribution of riverine fishes. 3. An effective way of using the information available from fish assemblages to establish such an index is through the use of the 'reference condition approach' which involves testing a fish assemblage exposed to a potential stress against a reference condition that is unexposed to such a stress. 4. Logistic regression procedures were applied, using a fish data set of 650 reference sites fairly evenly distributed across French rivers and defined by some easily measured regional and local characteristics, to elaborate the simplest possible response model that adequately explains the observed patterns of occurrence for each species of a fish assemblage at a given site of any given river. This allows us to predict a 'theoretical' assemblage at a site. 5. The models were validated using a second independent data set of 88 reference sites. Using a third data set of 88 disturbed sites, the observed assemblages were then compared against the reference condition as defined by the 'theoretical' assemblages. The amount of deviation between the expected and observed assemblages within these sites is used as a measure of degradation. 6. This approach could be used as a framework for adapting and calibrating a multimetric index, thereby serving as a practical technical reference for conducting cost-effective biological assessments of lotic systems.     

Improving the performance of ecological indices by balancing reference site quality and representativeness

Reference site networks should consist of minimally disturbed sites that collectively characterize the ranges of natural settings within a region. Compromise between reference-quality and representativeness is required. We evaluated how tradeoffs between reference-quality and regional representativeness affected applicability, performance, and interpretation of multi-metric (MMI) and Observed/Expected (O/E) indices developed for streams in eastern China. We emphasized reference-quality by applying the most-stringent objective criteria and expert-judgment to select reference-group1 (G1). We emphasized representativeness by applying the least-stringent criteria to select reference-group2 (G2) sites from different strata based on watershed size. We balanced reference-quality and representativeness in G3 by applying intermediate stringent criteria from each watershed size stratum used previously. Increasing representativeness using G2 improved index applicability to almost more than twice the number of test sites than when reference-quality maximized using G1. Bias in O/E index was almost eliminated only when reference-quality and representativeness balanced using G3. MMIs developed when reference-quality maximized using G1 eliminated all bias and had the highest precision. High-quality reference with limited representativeness affected the metrics selected for inclusion in MMIs and restricted the sites to which both types of indices could be applied. A balanced approach worked best in this instance and similar approaches should be tested in other regions.

     

Development of a RIVPACS-type predictive model for bioassessment of wadeable streams in Wyoming

RIVPACS models produce a community-level measure of biological condition known as O/E, which is derived from a comparison of the observed (O) biota with those expected (E) to occur in the absence of anthropogenic stress. We used benthic macroinvertebrate and environmental data collected at 925 stream monitoring stations, from 1993 to 2001, to develop, validate, and apply a RIVPACS model to assess the biological condition of wadeable streams in Wyoming. From this dataset, 296 samples were identified as reference, 157 of which were used to calibrate the model, 46 to validate it, and 93 to examine temporal variability in reference site O/E-values. We used cluster analyses to group the model development reference sites into biologically similar classes of streams and multiple discriminant function analysis to determine which environmental variables best discriminated among reference groups. A suite of 14 categorical and continuous environmental variables best discriminated among 15 reference groups and explained a large proportion of the natural variability in biota within the reference dataset. Eleven of the predictor variables were derived from GIS. As expected, mean O/E-values for reference sites used in model development and validation were near unity and statistically similar. Temporal variability in O/E-values for reference sites was low. Test site values ranged from 0 to 1.45 (mean = 0.73). The model was accurate in both space and time and precise enough (S.D. of O/E-values for calibration data = 0.17) to detect modest alteration in biota associated with anthropogenic stressors. Our model was comparable in performance to other RIVPACS models developed in the United States and can produce effective assessments of biological condition over a broad, ecologically diverse region. We also provide convincing evidence that RIVPACS models can be developed primarily with GIS-based predictor variables. This framework not only simplifies the extraction of predictor variable information while potentially reducing expenditures of time and money in the collection of predictor variable information, but opens the door for development and/or application of RIVPACS models in regions where there is a paucity of local-scale, abiotic information.     

Ecological Effects of Serial Impoundment on the Cotter River, Australia

This study examines the ecological effects of serial impoundments (three dams) on a rocky upland stream in southeastern Australia. Physical, chemical and biological changes were quantified and interpreted within a three-level hierarchy of effects model developed previously by Petts [1984, Impounded Rivers. John Wiley and Sons, New York] and the Australian Rivers Assessment System (AUSRIVAS) to predict pre-dam biota. First-order effects were decreased median monthly discharges and floods of lesser magnitude following construction of the dams. No effect on water characteristics (pH, electrical conductivity and major ions) was evident. The second-order effect on channel morphology was a decrease in bank-full cross-sectional area by up to 75% because of reduced flows. At all sites, the predominantly cobble streambed was armoured and generally highly stable. The discharge required to initiate movement of the streambed surface sediments (38.9 m³ s⁻¹) was 40% less frequent since construction of the dams, implying alteration to the natural disturbance regime for benthic biota. Benthic algal growth appeared more prolific at sites directly below dams. Fewer macroinvertebrate taxa than expected and modified assemblages within 1 km of all three dams were third-order effects. Compared to reference conditions, macroinvertebrate samples from the sites directly below the dams had relatively more Chironomidae larvae, Oligochaeta and Acarina, and fewer of the more sensitive taxa, Plecoptera, Ephemeroptera, Trichoptera and Coleoptera. Biological recovery to the macroinvertebrate assemblage was evident within 4 km downstream of the second dam.     

A stressor specific multimetric approach for monitoring running waters in Austria using benthic macro-invertebrates

We investigated four stream types in four different bioregions, classified by catchment area and altitude, and stressed by different degrees of organic pollution and habitat alteration. We examined a macro-invertebrate based multimetric approach for Austrian rivers as a potential assessment method within the European Water Framework Directive. Benthic macro-invertebrate data (100 samples including reference sites) were used to develop a multimetric index for each stream type and targeted stressors. Sites were pre-classified based on physical, chemical, and land use criteria into five ecological quality classes. More than 200 biological metrics were tested for their sensitivity to the targeted stressors, their spatial and temporal variability and their ability to discriminate between different types and degrees of stress. Metrics for index development were selected to reflect different levels of information including ecosystem, community, and individual levels (Karr, 1991; Barbour et al., 1995; Gerritsen, 1995). Combinations of metrics were selected to distinguish best between non or slightly impaired and stressed sites (evaluated by calculating discrimination efficiency values and power analysis). The resulting four indices comprised seven to nine metrics from five to seven metric categories, and distinguished reference/slightly disturbed sites from stressed sites with close to 100% efficiency. The indices can form the basis for stressor-specific assessment of stream condition.     

Prediction and assessment of local stream habitat features using large-scale catchment characteristics

1. Knowledge of what a habitat should be like, in the absence of the effects of human activities, is fundamental to local stream habitat assessment. It has been suggested that stream habitats are influenced by large-scale catchment features. This study aimed to identify these relationships so that local-scale habitat features could be predicted from larger-scale characteristics.
2. Fifty-one reference sites from the Upper Murrumbidgee River catchment, south-eastern Australia, were classified on the basis of the local features of their stream habitat. Large-scale variables, namely catchment area, stream length, relief ratio, alkalinity, percentage of volcanic rocks, percentage of metasediments, dominant geology and dominant soil type, provided sufficient information for classifying 69% of reference sites into appropriate reference site groups.
3. A model created using these large-scale catchment variables was able to predict the local habitat features that were expected (E) to occur at a site in the absence of the effects of human activities. These were compared with observed (O) local habitat features to provide an observed-to-expected (O/E) ratio, an assessment score of the habitat at a site. The departure of this ratio from 1 enables identification of those sites that may be impacted. A list of habitat features that are expected at a site can provide targets for habitat restoration or enhancement.
4. For impacted sites, when habitat assessment from the habitat predictive model was compared with biological assessment from the Australian River Assessment System (AUSRIVAS) predictive model, it was possible to identify whether habitat degradation or water quality degradation was the cause of biological impairment. Such assessment may make it possible to identify rehabilitation goals relevant to the biota.     

Toward river health assessment using species distributional modeling

The reference condition of a river ecosystem is often used as a benchmark against which restoration activities are framed. However, the reference condition approach is not suitable for all river health assessments given undisturbed reference sites similar to a test site may not exist. We tested the ability of applying individual Species Distribution Models (SDMs) to predict the “natural” fish assemblages in a regulated coastal Australian river. Environmental data and fish collections from training sites were used to generate predictive models for 21 species. Model accuracy was high with the area under the receiver operating curve greater than 0.80 for the majority of species. The SDMs were then used to determine the natural fish assemblages and the condition of the sites in the test river was then assessed as the observed to expected species ratio (O/E). We expected that the O/E ratio would decline upstream through a series of weirs that created barriers to fish passage. Results confirmed that an inverse relationship existed between the number of weirs present on the test river and the O/E ratio, largely due to the decline in diadromous species. Our study clearly demonstrates the usefulness of the SDM approach to riverine health assessment in situations where undisturbed reference sites do not exist.     

A fish-based multimetric index for Brazilian savanna streams

Multimetric indices (MMI) have been widely used to assess ecosystem conditions because they are low-cost, employ a rapid field method, and can incorporate various biological metrics at different levels of biological organization. Our objective was to create a fish-based multimetric index applicable to all streams of the Brazilian savanna biome (Cerrado), the second largest biome in Brazil and deemed a global biodiversity hotspot. We evaluated 156 sites in two river basins (Paraná and São Francisco) and selected metrics capable of distinguishing stream-sites across a gradient of anthropogenic disturbances. We employed two different MMI approaches to determine if an MMI based on natural variation-adjusted metrics performed better than one based on unadjusted metrics. In addition, we assessed the performance of the two final MMIs and their sensitivity to anthropogenic pressures at local (LDI), catchment (CDI) and both scales integrated (IDI). Finally, we employed the power of a probability sample survey design to infer headwater stream conditions across a hydrologic region of approximately 47,000 km². Our final MMI for Brazilian savanna streams included six metrics: % common species; % characiform individuals; % loricariid individuals; % trichomycterid individuals; % invertivore species, and % Poecilia reticulata individuals. MMI₁ (unadjusted metrics) performed better than MMI₂ (natural variation-adjusted metrics) in discriminating least- and most-disturbed sites, but MMI₂ distinguished intermediate from most-disturbed sites better than MMI₁. Both indices were negatively correlated with the CDI scores; however, only MMI₂ was negatively correlated with the IDI scores. We inferred that 709 km (9.35%) of streams in the studied hydrologic region were in good condition, 8115 km (82.73%) were intermediate, and 641 km (7.91%) were in poor condition. We conclude that the MMIs proposed in this study have great potential for widespread application because they integrate data from two of the most important Brazilian river basins included in a biome that represents more than 20% of the country. Furthermore, the metrics retained in the indexes are easy to access with a rapid low-cost field method. However, their feasibility in areas influenced by mining, as well as in different biomes, should be tested.     

Incorporating natural variability in the bioassessment of stream condition in the Atlantic Forest biome,Brazil

Most bioassessment programs in Brazil face difficulties when scaling up from small spatial scales because larger scales usually encompass great environmental variability. Covariance of anthropogenic pressures with natural environmental gradients can be a confounding factor in the evaluation of biologic responses to anthropogenic pressures. The objective of this study was to develop a multimetric index (MMI) with macroinvertebrates for two stream types and two ecoregions in the Atlantic Forest biome in Rio de Janeiro state, Brazil. We hypothesized that by using two approaches – (1) testing and adjusting metrics to landscape parameters, and (2) selecting metrics using a cluster analysis to avoid metrics redundancy – the final MMI would perform better than the traditional approach (unadjusted metrics, one metric representing each category). Four MMIs were thus developed: MMI-1 – adjusted MMI with metrics selected after cluster analysis); MMI-2 – adjusted MMI with one metric from each category; MMI-3 – unadjusted MMI with metrics selected after cluster analysis; MMI-4 – unadjusted MMI with one metric from each category. We used three decision criteria to assess MMI’s performance: precision, responsiveness and sensitivity. In addition, we tested the MMI’s by using an independent set of sites to validate the results. Although all MMIs performed well in the three criteria, adjusting metrics to natural variation increased MMI response and sensitivity to impairment. In addition, the selected MMI-2 was able to classify sites of two stream types and two ecoregions. The use of cluster analysis, however, did not avoid high redundancy between metrics of different branches. The MMI-4 had the poorest performance among all tested MMIs and it was not able to distinguish adequately reference and impaired sites from both ecoregions. We present some considerations on the use of metrics and on the development of MMI’s in Brazil and elsewhere.     

Development of a biotic index using stream macroinvertebrates to assess stress from deposited fine sediment

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