Accounting for regional variation in both natural environment and human disturbance to improve performance of multimetric indices of lotic benthic diatoms

Striving for consistent bioassessment across diverse landscapes: Using land use matters for classifying reference and disturbed sites for index development

Consistency in ecological assessments is challenging across large diverse landscapes because natural geological, climatic, and hydrological factors vary greatly. As a result, large landscapes are often subdivided into ecoregions and assessments are based on ecoregion specific indices. In the present study, we developed and compared multimetric indices (MMIs) using benthic diatom data from the 2008-2009 dataset from the United States (US) National Rivers and Streams Assessment. Nationwide and separate ecoregion specific MMIs were developed with reference, moderately disturbed, and highly disturbed sites selected using criteria based on physicochemical condition of the habitat or based on watershed land use (% agriculture and % urban). Metrics were adjusted to account for variation in natural conditions when needed. We found only land use criteria selected reference sites with consistently low median % watershed disturbance (%WD) and large differences in %WD between reference and highly disturbed sites. <38 % of sites were identified as reference or highly disturbed by both physicochemical and land use criteria. All MMIs displayed substantial discrimination ability between reference and highly disturbed sites. At the national scale, MMIs based on land use outperformed MMIs based on physicochemical conditions for all performance attributes tested. When national scale MMIs were applied to ecoregions, MMIs based on land use were again better than MMIs based on physicochemical conditions for most performance attributes and even had better or comparable performance to the land use MMIs developed separately for each ecoregion. Our findings show that developing MMIs using land use criteria and adjusting metrics for natural variation could improve assessment consistency without losing MMI performance across large, diverse landscapes as in the US National Rivers and Streams Assessment.

European river typologies fail to capture diatom, fish, and macrophyte community composition

Typology systems are frequently used in applied and fundamental ecology and are relevant for environmental monitoring and conservation. They aggregate ecosystems into discrete types based on biotic and abiotic variables, assuming that ecosystems of the same type are more alike than ecosystems of different types with regard to a specific property of interest. We evaluated whether this assumption is met by the Broad River Types (BRT), a recently proposed European river typology system, that classifies river segments based on abiotic variables, when it is used to group biological communities. We compiled data on the community composition of diatoms, fishes, and aquatic macrophytes throughout Europe and evaluated whether the composition is more similar in site groups with the same river type than in site groups of different river types using analysis of similarities, classification strength, typical species analysis, and the area under zeta diversity decline curves. We compared the performance of the BRT with those of four region-based typology systems, namely, Illies Freshwater Ecoregions, the Biogeographic Regions, the Freshwater Ecoregions of the World, and the Environmental Zones, as well as spatial autocorrelation (SA) classifications. All typology systems received low scores from most evaluation methods, relative to predefined thresholds and the SA classifications. The BRT often scored lowest of all typology systems. Within each typology system, community composition overlapped considerably between site groups defined by the types of the systems. The overlap tended to be the lowest for fishes and between Illies Freshwater Ecoregions. In conclusion, we found that existing broad-scale river typology systems fail to delineate site groups with distinct and compositionally homogeneous communities of diatoms, fishes, and macrophytes. A way to improve the fit between typology systems and biological communities might be to combine segment-based and region-based typology systems to simultaneously account for local environmental variation and historical distribution patterns, thus potentially improving the utility of broad-scale typology systems for freshwater biota.

How good is good ecological status? A test across river typologies, diatom indices and biological elements

Good ecological status is the environmental objective of EU water legislation to be achieved by all European water bodies. However, good ecological status varies depending on national criteria, typology approach, and classification systems used. Since nutrient enrichment is the main cause of river degradation, it is important to establish nutrient criteria that consistently support good ecological status across these influential factors. This study analyzes good ecological status, depending on the typology, classification system and biological element used, and it discusses potential implications of the results for river management. We used a database of 425 sites from northern Spain, corresponding to 11 river types of the Spanish typology derived from physiographic data, or to the four river types resulting from NORTIdiat predictive model, derived from regional diatom reference assemblages. PERMANOVA analysis found significant differences among diatom assemblages across the four river types derived from the NORTIdiat system. Among the classification systems currently in use, or of potential use in the area, the upper P-PO₄^3- threshold, established as the P₉₅ of the class distribution for good ecological status, both NORTIdiat (50.7 μg l^-1) and the Multimetric Diatom index (MDIAT; 26.4 μg l^-1) were close to proposed thresholds for good status at the EU level. However, this value was much higher for the Specific Polluosensitivity Index (IPS; 118.1 μg l^-1). Nutrient thresholds for good status also varied among bioindicators, since the predictive invertebrate-based model NORTI classified 67% of samples with high P-PO₄^3- content in good ecological status, whereas the NORTIdiat classified only 33% of them in good status. Results suggest that current nutrient criteria used to establish good ecological status should be revised, accounting for biological specificity and response of biological elements, to provide a more ecologically coherent approach to preserving or restoring good ecological status.

A web-based tool for assessing the condition of benthic diatom assemblages in streams and rivers of the conterminous United States

Benthic diatom assemblages are known to be indicative of water quality but have yet to be widely adopted in biological assessments in the United States due to several limitations. Our goal was to address some of these limitations by developing regional multi-metric indices (MMIs) that are robust to inter-laboratory taxonomic inconsistency, adjusted for natural covariates, and sensitive to a wide range of anthropogenic stressors. We aggregated bioassessment data from two national-scale federal programs and used a data-driven analysis in which all-possible combinations of 2-7 metrics were compared for three measures of performance. After ranking the best-performing MMIs, we selected the final MMIs by evaluating stress-response relations in independent regional datasets of diatom samples paired with measures of several water-quality stressors, including herbicides and streamflow flashiness. Each regional MMI performed well at calibration sites and represented diverse aspects of the structure and function of diatom communities. Most metrics included in the best MMIs were modeled to account for natural variation including climate, topography, soil characteristics, lithology, and groundwater influence on streamflow. MMI performance improved with higher numbers of component metrics, but this effect diminished beyond six metrics. Component metrics of MMIs were associated with a broad suite of measured stressors in every region, including salinity, nutrients, herbicides, and streamflow flashiness. We provide a web-based software application that allows users in the conterminous United States to apply our MMIs to their own datasets and compare MMI scores from their sites to a broader regional context.

Improving biological condition assessment accuracy by multimetric index approach with microalgae in streams and lakes

Multimetric index (MMI) approach is a broadly used in ecological assessment because it can integrate information of various kinds of ecologically related metrics of freshwater ecosystems and provide an easily understandable score for purpose of further evaluation and managements. Accounting for natural variation and disentangling covariation between natural environmental factors and human disturbance factors are imperative for an accurate assessment. Lots of progress has been made recently on the aforementioned two aspects. Three approaches, a priori classification of sites by regions or typologies, site-specific modeling of expected reference condition and varying metrics in site groups, have been tested in lakes and streams to improve assessment accuracy. All existed studies support that site-specific modeling can efficiently account for natural variation and generate a MMI with good performance. However, until now, no strong evidence has shown that diatom/blue-algae typologies are better than regionalization frameworks on accounting for natural variation either in lakes or in streams. To separate the natural variation explained by site specific modeling from that of varying metrics is necessary for a thorough and accurate evaluation on the valuableness of site-grouping by typologies. Different performance of varying metrics among site groups of streams and lakes was most probably caused by the lack of representativeness of diatom metrics on biological condition rather than the complex multi-stressor gradients in streams and rivers. A recent study showed that blue-green algae enhanced performance of diatom-based MMI on defining lake condition under high level of human disturbance. On the other hand, with more and more extensive and intensive use of statistics techniques in developing MMI, we also discussed some statistical challenges faced by scientists in field of ecological assessment, especially on setting significance level of a statistical test and multiple comparison issue in MMI performance comparison.

Spatial and temporal variations of the diatom communities in megacity streams and its implications for biological monitoring

Diatoms have been proven to be good indicators of natural stream conditions, but little is known about the seasonal variability of diatom communities in megacity streams. We investigated the spatial and temporal variation of diatom communities along an urban-to-rural gradient in megacity streams, Beijing, China. We found that the composition and diversity of diatom community was significantly different along the urban-to-rural gradient in streams of Beijing city. The diatom community was subtle temporal variation in the reference stream and urban upstream, but the temporal variation of diatoms was relatively greater in the urban downstream. Overall, the composition of the diatom community was relatively stable in the streams among different seasons, and the dominant species did not change much over seasons. For example, during the sampling periods, the species Achnanthidium minutissimum in reference streams had the average relative abundance of 20.3 ± 3.5%; the species Pseudostaurosira brevistriata and Staurosira construens var. venter in urban upstream had average relative abundances of 17.0% ± 0.9% and 17.3% ± 1.2%, respectively; and the species Nitzschia palea in urban downstream had average relative abundances of 18.8 ± 4.7%. There were significant correlations between the relative abundances of the dominant species and environmental variables, suggesting that the environmental variables had significant effects on the diatom distribution. Our results demonstrate that the diatom communities are relatively stable among seasons in different sampling areas, suggesting that diatoms can be used as reliable indicators for the biological monitoring of water quality in megacity streams across seasons.

The Relation of Lotic Fish and Benthic Macroinvertebrate Condition Indices to Environmental Factors Across the Conterminous USA

National and regional ecological assessments are essential for making rational decisions concerning water body conservation and management at those spatial extents. We analyzed data from 4597 samples collected from 3420 different sites across the conterminous USA during the U.S. Environmental Protection Agency's 2008-2009 and 2013-2014 National Rivers and Streams Assessment. We evaluated the relationship between both fish and macroinvertebrate multimetric index (MMI) condition scores and 38 environmental factors to assess the relative importance of natural versus anthropogenic predictors, contrast site-scale versus watershed-scale predictors, and examine ecoregional and assemblage differences. We found that most of the environmental factors we examined were related to either fish and/or macroinvertebrate MMI scores in some fashion and that the factors involved, and strength of the relationship, varied by ecoregion and between assemblages. Factors more associated with natural conditions were usually less important in explaining MMI scores than factors more directly associated with anthropogenic disturbances. Local site-scale factors explained more variation than watershed-scale factors. Random forest and multiple regression models performed similarly, and the fish MMI-environment relationships were stronger than macroinvertebrate MMI-environment relationships. Among ecoregions, the strongest environmental relationships were observed in the Northern Appalachians and the weakest in the Southern Plains. The fish and macroinvertebrate MMIs were only weakly correlated with each other, and they generally responded more strongly to different groups of variables. These results support the use of multiple assemblages and the sampling of multiple environmental indicators in ecological assessments across large spatial extents.

The importance of natural versus human factors for ecological conditions of streams and rivers

Streams are influenced by watershed-scale factors, such as climate, geology, topography, hydrology, and soils, which mostly vary naturally among sites, as well as human factors, agriculture and urban development. Thus, natural factors could complicate assessment of human disturbance. In the present study, we use structural equation modeling and data from the 2008-2009 United States National Rivers and Streams Assessment to quantify the relative importance of watershed-scale natural and human factors for in-stream conditions. We hypothesized that biological condition, represented using a diatom multimetric index (MMI), is directly affected by in-stream physicochemical environment, which in turn is regulated by natural and human factors. We evaluated this hypothesis at both national and ecoregion scales to understand how influences vary among regions. We found that direct influences of in-stream environment on diatom MMIs were greater than natural and human factors at the national scale and in all but one ecoregion. Meanwhile, in-stream environments were jointly explained by natural variations in precipitation, base flow index, hydrological stability, % volcanic rock, soil water table depth, and soil depth and by human factors measured as % crops, % other agriculture, and % urban land use. The explained variance of in-stream environment by natural and human factors ranged from 0.30 to 0.75, for which natural factors independently accounted for the largest proportion of explained variance at the national scale and in seven ecoregions. Covariation between natural and human factors accounted for a higher proportion of explained variance of in-stream environment than unique effects of human factors in most ecoregions. Ecoregions with relatively weak effects by human factors had relatively high levels of covariance, high levels of human disturbance, or small ranges in human disturbance. We conclude that accounting for effects of natural factors and their covariation with human factors will be important for accurate ecological assessments.

Incorporating functional traits to enhance multimetric index performance and assess land use gradients

Taxonomic-based multimetric indices (MMIs) have been widely employed for assessing ecosystem status, particularly through the use of stream macroinvertebrate assemblages. However, the functional diversity and composition of assemblages is also important for maintaining stream ecosystem condition. Nonetheless, aquatic insect functional diversity and composition have not commonly been included in MMIs. Our goal was to advance our understanding of the performance and ecological interpretation of an MMI that potentially combined functional and taxonomic metrics. We sampled aquatic insects and natural and land-use variables at 74 temperate Chinese streams. We selected a candidate set of 36 functional and 20 taxonomic metrics that were screened by range tests, natural variation, responsiveness to anthropogenic disturbance, and redundancy for subsequent inclusion in MMIs. We determined if natural variation adjustments improved the performance of a functional-taxonomic MMI. Finally, we evaluated the degree to which the functional-taxonomic MMI served as an early-warning indicator of land use intensity. Natural variation explained between 19.62% and 71.02% of metric variability, indicating that functional metrics changed systematically along natural gradients. The final functional-taxonomic MMI adjusted for natural variation incorporated multiple aspects of assemblage characteristics: functional richness, Rao's quadratic entropy, abundance-weighted frequency of soft bodies, abundance-weighted frequency of predators, and number of Diptera taxa. In contrast to the natural variation unadjusted MMI, the functional-taxonomic adjusted MMI clearly distinguished least-disturbed sites from most-disturbed sites, exhibited high precision and low bias, and showed a significant negative response to land uses. The slope of a linear regression relative to 0-10% urban and 0-20% agriculture was significantly steeper for the functional-taxonomic adjusted MMI than that of the taxonomic adjusted MMI. We conclude that functional-taxonomic adjusted MMIs are more effective indicators of ecological condition and risks to biota from human pressures than are purely taxonomic unadjusted MMIs because functional-taxonomic MMIs are more sensitive to subtle anthropogenic pressures.

Advancing evaluation of bioassessment methods: A reply to Liu and Cao

A series of three papers was written about the development of multimetric indices (MMIs) using diatoms in rivers, streams and lakes for transcontinental surveys conducted by the United States Environmental Protection Agency. Stevenson et al. (2013) used the surface sediment diatom data from the 2007 National Lake Assessment to develop national scale site specific models for MMIs to account for natural variation in condition among sites. Liu and Stevenson (2017) also used the 2007 lakes data to evaluate performance of MMIs by grouping sites by ecoregions or typologies (naturally similar types of lakes defined by similarity in diatom species composition) with site specific metric models (SSMMs) that adjust metrics for natural variability among sites. Tang et al. (2016) used benthic diatom data from the 2008-2009 National River and Stream Assessment to develop SSMMs and MMIs by ecoregion and typology. All three studies showed that SSMMs improved performance of diatom MMIs by accounting for natural variation among sites. None of the studies provided consistent evidence that grouping sites by typologies produced better MMI performance than grouping sites by ecoregions. Liu and Cao (2018) criticized the Tang et al. (2016) paper for using means and standard errors to evaluate relative performance of MMI calculation methods at the site group scale, however, their criticism is incorrect. Actually, Tang et al. (2016) only used means to summarize and report relative performance of MMI calculation methods in the body of the paper. Tang et al. (2016) appropriately used non-parametric rank sum approaches to evaluate the probability that the multiple MMI calculations for separate site groups were the same for ecoregion (n = 9) and typology (n = 7) site groups. Liu and Stevenson (2017) used this same non-parametric approach for tests of lake diatom MMIs. Liu and Cao's (2018) concerns can be addressed by distinguishing between the goals and methods used for testing and evaluation of MMI calculation methods at the national and site-group scales. Tang et al. (2016) did not aggregate data across site groups to test MMI performance at the national scale because they were following standard EPA methods that develop separate MMIs for each site group. In conclusion, Liu and Cao (2018) misunderstood the MMI evaluation in Tang et al. (2016) and added no new information to this body of work, because all the concerns they raised were discussed in Liu and Stevenson (2017).

Development of a diatom-based multimetric index for acid mine drainage impacted depressional wetlands

Acid mine drainage (AMD) from coal mining in the Mpumalanga Highveld region of South Africa has caused severe chemical and biological degradation of aquatic habitats, specifically depressional wetlands, as mines use these wetlands for storage of AMD. Diatom-based multimetric indices (MMIs) to assess wetland condition have mostly been developed to assess agricultural and urban land use impacts. No diatom MMI of wetland condition has been developed to assess AMD impacts related to mining activities. Previous approaches to diatom-based MMI development in wetlands have not accounted for natural variability. Natural variability among depressional wetlands may influence the accuracy of MMIs. Epiphytic diatom MMIs sensitive to AMD were developed for a range of depressional wetland types to account for natural variation in biological metrics. For this, we classified wetland types based on diatom typologies. A range of 4-15 final metrics were selected from a pool of ~140 candidate metrics to develop the MMIs based on their: (1) broad range, (2) high separation power and (3) low correlation among metrics. Final metrics were selected from three categories: similarity to reference sites, functional groups, and taxonomic composition, which represent different aspects of diatom assemblage structure and function. MMI performances were evaluated according to their precision in distinguishing reference sites, responsiveness to discriminate reference and disturbed sites, sensitivity to human disturbances and relevancy to AMD-related stressors. Each MMI showed excellent discriminatory power, whether or not it accounted for natural variation. However, accounting for variation by grouping sites based on diatom typologies improved overall performance of MMIs. Our study highlights the usefulness of diatom-based metrics and provides a model for the biological assessment of depressional wetland condition in South Africa and elsewhere.

Improving assessment accuracy for lake biological condition by classifying lakes with diatom typology, varying metrics and modeling multimetric indices

Site grouping by regions or typologies, site-specific modeling and varying metrics among site groups are four approaches that account for natural variation, which can be a major source of error in ecological assessments. Using a data set from the 2007 National Lakes Assessment project of the USEPA, we compared performances of multimetric indices (MMI) of biological condition that were developed: (1) with different lake grouping methods, ecoregions or diatom typologies; (2) by varying or not varying metrics among site groups; and (3) with different statistical techniques for modeling diatom metric values expected for minimally disturbed condition for each lake. Hierarchical modeling of MMIs, i.e. grouping sites by ecoregions or typologies and then modeling natural variability in metrics among lakes within groups, substantially improved MMI performance compared to using either ecoregions or site-specific modeling alone. Compared with MMIs based on ecoregion site groups, MMI precision and sensitivity to human disturbance were better when sites were grouped by diatom typologies and assessing performance nationwide. However, when MMI performance was evaluated at site group levels, as some government agencies often do, there was little difference in MMI performance between the two site grouping methods. Low numbers of reference and highly impacted sites in some typology groups likely limited MMI performance at the group level of analysis. Varying metrics among site groups did not improve MMI performance. Random forest models for site-specific expected metric values performed better than classification and regression tree and multiple linear regression, except when numbers of reference sites were small in site groups. Then classification and regression tree models were most precise. Based on our results, we recommend hierarchical modeling in future large scale lake assessments where lakes are grouped by ecoregions or diatom typologies and site-specific metric models are used to establish expected metric values.

Relative roles of spatial processes, natural factors and anthropogenic stressors in structuring a lake macroinvertebrate metacommunity

Studies of aquatic metacommunities have so far been focused almost entirely on relatively isolated systems, such as a set of streams, lakes or ponds. Here, we aimed to quantify the relative importance of spatial processes, natural factors and anthropogenic stressors in structuring of a macroinvertebrate metacommunity within a large, highly-connected shallow lake system. The roles of different drivers were evaluated for the entire metacommunity, 10 trait-based deconstructed metacommunities and four common species by incorporating extensive sampling and a large number of abiotic explanatory variables. Contrary to our expectations, we found that variation in community structure among sites was mostly correlated to spatial and wind-wave variables rather than anthropogenic disturbance factors even though the lake presented strong environmental gradients associated with long-term human pressures. In addition, the relative importance of the three groups of drivers varied slightly among the deconstructed trait matrices (i.e. based on dispersal ability, feeding mode and degree of occurrence). Importantly, the distributions of the most common species showed significant and strong spatial autocorrelation, indicating the prominent role of high dispersal rate for their distributions. These findings suggest that the influences of high dispersal rates and natural disturbance may even override the roles of anthropogenic stressors in metacommunity organization in highly-connected aquatic systems. Hence, we strongly encourage that spatial processes and natural drivers are taken into account in the development of bioassessment approaches in highly-connected aquatic systems.

Benthic algal assessment of ecological status in European lakes and rivers: Challenges and opportunities

This opinion paper introduces a special series of articles dedicated to freshwater benthic algae and their use in assessment and monitoring. This special series was inspired by talks presented at the 9th International Congress on the Use of Algae for Monitoring Rivers and Comparable Habitats (Trento, Italy, 2015), the latest of a series of meetings started in 1991. In this paper, we will first provide a brief overview of phytobenthos methods in Europe. Then, we will turn towards the 'dark side' of phytobenthos and describe four particular problems for phytobenthos assessment in the European Union: (1) over-reliance on a single group of algae (mostly diatoms) to the exclusion of other groups; (2) relatively low adoption of benthic algae for ecological assessments in lakes; (3) absence of measures of phytobenthos abundance; (4) approaches used to define boundaries between ecological classes. Following this, we evaluate the strengths and limitations of current phytobenthos assessment methods against 12 criteria for method evaluation addressing four areas: ecological rationale, performance, feasibility of implementation, and use in communication and management. Using these criteria, we identify and discuss three general challenges for those developing new methods for phytobenthos-based assessment: a weak ecological rationale and insufficient consideration of the role of phytobenthos as a diagnostic tool and for communicating ecosystem health beyond a narrow group of specialists. The papers in the special series allow a comparison with the situation and approaches in the USA, present new methods for the assessment of ecological status and acidification, provide tools for an improved management of headwaters and petrifying springs, discuss the utility of phytobenthos for lake assessments, and test the utility of functional measures (such as biofilm phosphorus uptake capacity, PUC).