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.     

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.     

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.     

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.     

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.     

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 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.     

Should landscape variation in population status be assessed with individual- or population-level indicators?

Monitoring trends in wildlife populations is essential to effective management. Evaluating only a single metric can be cost-effective; however, how a given metric responds to environmental variation may differ from other population- or individual-level metrics. Consequently, conclusions about the effect of environmental variation on a species should consider the relationship between different metrics. We investigated how population-level metrics (occupancy and relative abundance) and an individual-level metric (body condition) responded to landscape variation in 3 semi-aquatic salamander species. In the summer of 2015 and 2016, we conducted repeated count surveys at 71 streams on the Cumberland Plateau, Tennessee, USA, actively counting and measuring salamanders. We estimated occupancy and abundance of larval and post-metamorphic animals using community-occupancy and community-N mixture models, respectively. We estimated body condition of the most observed life stage for each species using a standardized mass index. All models included the same set of covariates for comparison. Occupancy and abundance responses for each life stage-by-species combination were positively correlated for 4 of 6 combinations, with salamander abundance responding to a larger suite of covariates. Body condition was not linked to covariates in the same fashion as population-level metrics, although consistency across species was detected for 1 covariate, watershed size. Our results indicate that inter-specific and inter-life stage variation in evaluated metrics is present within salamanders of this study system. Management for populations of salamanders in the region should consider monitoring multiple response metrics, to capture both population- and individual-level responses, as these may not always be correlated.     

A new procedure for comparing class boundaries of biological assessment methods: A case study from the Danube Basin

For the implementation of the European Water Framework Directive class boundaries of biological assessment methods need to be intercalibrated. The most commonly applied intercalibration approach of national river assessment methods in Europe requires data on near-natural reference sites; however, these data are generally scarce. We developed an alternative approach based on sites impacted by similar levels of disturbance and tested it with national assessment methods based on diatoms and benthic invertebrates from countries in the Danube River Basin. Using environmental variables we screened for sampling sites of at least good environmental status. Relations between different assessment methods were established by common metrics, and we standardized these metrics by “biological benchmarks” obtained from the screened datasets. This approach allows for intercalibration even if near-natural reference sites are absent; relatively few and easily available data are required.     

Macroinvertebrate-based multimetric predictive models for evaluating the human impact on biotic condition of Bolivian streams

We developed and validated a single multimetric index based on predictive models that could evaluate anthropogenic disturbances in streams of three disparate ecoregions of Bolivia. To do so, we examined 45 candidate metrics reflecting different aspects of macroinvertebrate assemblage structure and function gleaned from available literature and for their potential to indicate degradation. More importantly, we integrated functional trait metrics to improve the sensitivity of our index. To quantify possible deviation from reference conditions, we first established and validated statistical models describing metric responses to natural environmental differences in the absence of any significant anthropogenic disturbance. We considered that the residual distributions of these models described the response range of each metric, independently of natural environmental influence. After testing the sensitivity of these residuals to a gradient of anthropogenic disturbance, we retained eight metrics that were used in the final assemblage index, four metrics based on richness and composition and four metrics based on biological traits. Our index performed well in discriminating between reference and disturbed sites, giving a significant negative linear response to a gradient of physical and chemical anthropogenic disturbances. After employing a probability survey design and sampling a relatively small number of sites throughout all major ecoregions of Bolivia, we believe our methodology can be used to develop a monitoring tool to evaluate status and trends in biological condition for streams of the entire country despite its complex and heterogeneous geology and climate.     

Bird based Index of Biotic Integrity: Assessing the ecological condition of Atlantic Forest patches in human-modified landscape

Wooded biomes converted to human-modified landscapes (HML) are common throughout the tropics, yielding small and isolated forest patches surrounded by an agricultural matrix. Diverse anthropogenic interventions in HMLs influence patches in complex ways, altering natural dynamics. Assessing current condition or ecological integrity in these patches is a challenging task for ecologists. Taking the Brazilian Atlantic Forest as a case study, we used the conceptual framework of the Index of Biotic Integrity (IBI), a multimetric approach, to assess the ecological integrity of eight small forest patches in a highly disturbed HML with different configurations and histories. The IBI was developed using bird assemblages found in these patches, and its performance was compared with analytical approaches commonly used in environmental assessment, such as general richness and Shannon’s diversity index. As a first step, the IBI procedure identifies an existing gradient of human disturbance in the study region and checks which biotic characteristics (candidate metrics) vary systematically across the gradient. A metric is considered valid when its’ relationship with the gradient provides an ecological interpretation of the environment. Then, the final IBI is elaborated using each valid metric, obtaining a score for each site. Over one year of sampling, 168 bird species were observed, providing 74 different bird candidate metrics to be tested against the disturbance gradient. Seven of them were considered valid:richness of threatened species; richness of species that use both “forest and non-forest” habitats; abundance of endemics, abundance of small understory-midstory insectivores, abundance of exclusively forest species; abundance of non-forest species, and abundance of species that forage exclusively in the midstory stratum. Each metric provided complementary information about the patch’s ecological integrity. The resulting IBI showed a significant linear relationship with the gradient of human disturbance, while total species richness and Shannońs diversity index did not. Application of numerical approaches, such as total species richness and Shannon’s diversity, did not distinguish ecological traits among species. The IBI proved better for assessing and interpreting ecological and environmental condition of small patches in highly disturbed HML. The IBI framework, its multimetric character, and the ease with which it can be adapted to diverse situations, make it an effective approach for assessing environmental conditions in the Atlantic Forest region, and also for many other small forest patches in the tropics.     

Comparison of watershed disturbance predictive models for stream benthic macroinvertebrates for three distinct ecoregions in western US

The successful use of macroinvertebrates as indicators of stream condition in bioassessments has led to heightened interest throughout the scientific community in the prediction of stream condition. For example, predictive models are increasingly being developed that use measures of watershed disturbance, including urban and agricultural land-use, as explanatory variables to predict various metrics of biological condition such as richness, tolerance, percent predators, index of biotic integrity, functional species traits, or even ordination axes scores. Our primary intent was to determine if effective models could be developed using watershed characteristics of disturbance to predict macroinvertebrate metrics among disparate and widely separated ecoregions. We aggregated macroinvertebrate data from universities and state and federal agencies in order to assemble stream data sets of high enough density appropriate for modeling in three distinct ecoregions in Oregon and California. Extensive review and quality assurance of macroinvertebrate sampling protocols, laboratory subsample counts and taxonomic resolution was completed to assure data comparability. We used widely available digital coverages of land-use and land-cover data summarized at the watershed and riparian scale as explanatory variables to predict macroinvertebrate metrics commonly used by state resource managers to assess stream condition. The “best” multiple linear regression models from each region required only two or three explanatory variables to model macroinvertebrate metrics and explained 41–74% of the variation. In each region the best model contained some measure of urban and/or agricultural land-use, yet often the model was improved by including a natural explanatory variable such as mean annual precipitation or mean watershed slope. Two macroinvertebrate metrics were common among all three regions, the metric that summarizes the richness of tolerant macroinvertebrates (RICHTOL) and some form of EPT (Ephemeroptera, Plecoptera, and Trichoptera) richness. Best models were developed for the same two invertebrate metrics even though the geographic regions reflect distinct differences in precipitation, geology, elevation, slope, population density, and land-use. With further development, models like these can be used to elicit better causal linkages to stream biological attributes or condition and can be used by researchers or managers to predict biological indicators of stream condition at unsampled sites.     

A new criterion for confounder selection

Summary We propose a new criterion for confounder selection when the underlying causal structure is unknown and only limited knowledge is available. We assume all covariates being considered are pretreatment variables and that for each covariate it is known (i) whether the covariate is a cause of treatment, and (ii) whether the covariate is a cause of the outcome. The causal relationships the covariates have with one another is assumed unknown. We propose that control be made for any covariate that is either a cause of treatment or of the outcome or both. We show that irrespective of the actual underlying causal structure, if any subset of the observed covariates suffices to control for confounding then the set of covariates chosen by our criterion will also suffice. We show that other, commonly used, criteria for confounding control do not have this property. We use formal theory concerning causal diagrams to prove our result but the application of the result does not rely on familiarity with causal diagrams. An investigator simply need ask, “Is the covariate a cause of the treatment?” and “Is the covariate a cause of the outcome?” If the answer to either question is “yes” then the covariate is included for confounder control. We discuss some additional covariate selection results that preserve unconfoundedness and that may be of interest when used with our criterion.     

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.     

Development of metrics based on fish body size and species traits to assess European coldwater streams

During the last decade multimetric indices (MMIs) have been greatly improved by the use of appropriate criteria to define reference conditions and by the use of statistical analysis to select a consistent set of metrics. Among the large number of MMIs developed to assess the ecological status of streams based on fish communities, the emphasis was mainly put on warmwater assemblages. When compared with warmwater fish assemblages, coldwater assemblages present depauperate faunas with a limited suit of traits. Thus, very often the number of metrics used to compute MMIs for coldwater streams is lower than for warmwaters. The objective of this study was to develop new metrics specific to European coldwater assemblages that integrate both the species traits and the body size of fish. Indeed, whereas the use of size or age classes has been highly advocated for developing MMIs, it remains largely underrepresented. Therefore, we used eight biological and ecological traits to characterize species and two size classes: small and large individuals. Among the 96 metrics tested, four were successfully related to environmental gradients and three displayed a significant response to anthropogenic pressures: the number of small rheophilous individuals, the number of small oxygen-intolerant individuals, and the number of small-habitat-intolerant individuals. These results demonstrate that metrics based on size classes could be used in the development of MMIs for coldwater streams and more generally for low-species rivers.     

Challenges using extrapolated family-level macroinvertebrate metrics in moderately disturbed tropical streams: a case-study from Belize

Family-level biotic metrics were originally designed to rapidly assess gross organic pollution effects, but came to be regarded as general measures of stream degradation. Improvements in water quality in developed countries have reignited debate about the limitations of family-level taxonomy to detect subtle change, and is resulting in a shift back towards generic and species-level analysis to assess smaller effects. Although the scale of pollution characterizing past condition of streams in developed countries persists in many developing regions, some areas are still considered to be only moderately disturbed. We sampled streams in Belize to investigate the ability of family-level macroinvertebrate metrics to detect change in stream catchments where less than 30% of forest had been cleared. Where disturbance did not co-vary with natural gradients of change, and in areas characterized by low intensity activities, none of the metrics tested detected significant change, despite evidence of environmental impacts. We highlight the need for further research to clarify the response of metrics to disturbance over a broader study area that allows replication for confounding sources of natural variation. We also recommend research to develop more detailed understanding of the taxonomy and ecology of Neotropical macroinvertebrates to improve the robustness of metric use.     

From compositional to functional biodiversity metrics in bioassessment: A case study using stream macroinvertebrate communities

While compositional diversity is a common metric for assessing human impacts on aquatic communities, functional diversity is scarcely employed, though highly desirable from the perspective of the European Water Framework Directive. Using abundance data from 99 minimally disturbed sites (i.e., no or very weak anthropogenic impact) from a national survey, we studied the spatial variability of compositional and functional biodiversity metrics across a predefined ecoregional classification. Metrics of compositional diversity comprised taxonomic and EPT richness and Simpson diversity. Functional diversity metrics were based on Rao's Quadratic Entropy (RQE), which described the differences among benthic invertebrate genera in eleven biological traits (e.g., size, life cycle, reproduction types, feeding habits). Using generalized linear models we show that taxonomic richness may vary greatly across ecoregions, contrasting with Simpson diversity and functional metrics that varied weakly in response to natural environmental variability. Functional diversity metrics, because of their stability in response to natural environmental variability, may be useful tools for assessing human impairment to ecosystem function. We further tested the response of functional diversity metrics to a specific human impact (sewage) and demonstrated significant modifications of functional diversity downstream of sewage pollution. Further investigations are required to test the ability of functional diversity metrics to precisely and accurately indicate different types of human impacts.     

Method of predicting reference condition biota affects the performance and interpretation of ecological indices

1. The statistical rigour and interpretability of ecological assessments is strongly affected by how well we predict the biological assemblages expected to occur in the absence of human‐caused stress, i.e. the reference condition. In this study, we examined how the specific method used to predict the reference condition affected the performance of two commonly used types of ecological index: RIVPACS‐based O/E indices and multimetric indices (MMIs). 2. These two types of index have generally relied on different approaches to predicting the reference condition. For MMIs, some type of regionalisation is typically used to describe the range of metric values among reference sites and hence the expected range at assessed sites. For O/E indices, continuous modelling is used to predict how the biota varies among sites both among and within regions. Because the prediction method differs for these two types of index, it has been impossible to judge if differences in index performance (accuracy, precision, responsiveness and sensitivity) are caused by differences in the way reference condition biota are predicted or by differences in what the indices measure. 3. We used a common data set of 94 reference sites and 255 managed sites and the same potential set of predictor variables to compare the performance of five different MMIs and three O/E indices that were derived from different prediction methods: null models, multiple linear regression (MLR), classification and regression trees, Random Forests (RF) and linear discriminant functions models (LDM). We then calculated values of these indices for samples collected from the managed catchments as well as samples collected from 13 reference sites that were progressively altered in known ways by a simulation programme. 4. Both the type of predictor used and the type of index affected overall index performance. Modelled indices generally had the greatest sensitivity in assessing managed sites as biologically different from reference. Index sensitivity was determined by both an aspect of index precision (10th percentile of reference condition values) and responsiveness. The O/E indices showed the best scope of response to known biological alteration. All three O/E indices decreased linearly in response to simulated alteration in both overall assemblage structure (Bray‐Curtis dissimilarity) and taxa loss. The MMIs declined linearly from low to intermediate levels of assemblage alteration but were less responsive between intermediate and high levels of biological alteration. 5. Insights gained from simulations can aid in testing assumptions regarding index response to stress and help ensure that we select indices that are ecologically interpretable and most useful to resource managers.     

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.