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Int. J. Environ. Res. Public Health 2012, 9, 3599-3628; doi:10.3390/ijerph9103599 OPEN ACCESS

International Journal of Environmental Research and Public Health ISSN 1660-4601 www.mdpi.com/journal/ijerph Article

A Multimetric Benthic Macroinvertebrate Index for the Assessment of Stream Biotic Integrity in Korea Yung-Chul Jun 1, Doo-Hee Won 2 , Soo-Hyung Lee 3, Dong-Soo Kong 4 and Soon-Jin Hwang 1,* 1

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Department of Environmental Science, Konkuk University, Seoul 143-701, Korea; E-Mail: [email protected] Doohee Institute of Ecological Research, Korea Ecosystem Service Inc., Seoul 153-768, Korea; E-Mail: [email protected] The National Institute of Environmental Research, Inchon 404-170, Korea; E-Mail: [email protected] Department of Biology, Kyonggi University, Suwon 443-760, Korea; E-Mail: [email protected]

* Author to whom correspondence should be addressed; E-mail: [email protected]; Tel.: +82-2-450-3748; Fax: +82-2-456-5062. Received: 27 August 2012; in revised form: 17 September 2012 / Accepted: 25 September 2012 / Published: 15 October 2012

Abstract: At a time when anthropogenic activities are increasingly disturbing the overall ecological integrity of freshwater ecosystems, monitoring of biological communities is central to assessing the health and function of streams. This study aimed to use a large nation-wide database to develop a multimetric index (the Korean Benthic macroinvertebrate Index of Biological Integrity—KB-IBI) applicable to the biological assessment of Korean streams. Reference and impaired conditions were determined based on watershed, chemical and physical criteria. Eight of an initial 34 candidate metrics were selected using a stepwise procedure that evaluated metric variability, redundancy, sensitivity and responsiveness to environmental gradients. The selected metrics were number of taxa, percent EphemeropteraPlecoptera-Trichoptera (EPT) individuals, percent of a dominant taxon, percent taxa abundance without Chironomidae, Shannon’s diversity index, percent gatherer individuals, ratio of filterers and scrapers, and the Korean saprobic index. Our multimetric index successfully distinguished reference from impaired conditions. A scoring system was established for each core metric using its quartile range and response to anthropogenic disturbances. The multimetric index was classified by aggregating the individual

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metric ..scores and the value range was quadrisected to provide a narrative criterion (Poor, Fair, Good and Excellent) to describe the biological integrity of the streams in the study. A validation procedure showed that the index is an effective method for evaluating stream conditions, and thus is appropriate for use in future studies measuring the long-term status of streams, and the effectiveness of restoration methods. Keywords: multimetric index; benthic macroinvertebrates; biological integrity; stream health; bio-assessment

1. Introduction Streams and rivers are among the most threatened ecosystems worldwide, affected by increasing water demands by the human population and a variety of development pressures [1–3]. Such anthropogenic activities generally alter hydrology, water quality, physical in-stream and riparian environments, and aquatic biota, consequently leading to the overall ecological integrity of aquatic ecosystems. The practices of restoring ecological integrity, therefore, are going to be major tools for mitigating, arresting and reversing the adverse effects human activity has had on the aquatic system. Particularly, biological assessments have been increasingly recognized to be among the most underpinning procedure of the remediation practice [4–7]. Biological assessments intend to characterize the current status of stream ecosystems by monitoring changes in the aquatic communities associated with anthropogenic disturbance. Since the so-called “Saprobien system” [8,9], a large number of studies of aquatic communities have been undertaken to establish the effective methods for the assessment of stream water quality. Initially, assessments of the status of streams involved simple qualitative systems based only on the absence or presence of indicator species according to the gradient of environmental factors [10]. However, the indicator species concept is an inadequate measure of overall ecological integrity because the cause–effect relationships of indicator organisms are not fully established, and are often confusing [11,12]. Thus, alternative bio-assessment approaches, such as multimetric indices, have been developed to reflect all types of degradation and cumulative impacts at the ecosystem level. A multimetric index is composed of several metrics associated with biological attributes (i.e., taxa richness, composition, pollution tolerance and trophic structure) that change in a predictable fashion with increasing anthropogenic disturbance [13]. This approach had the potential for broad use in the assessment of stream ecosystems because it involved various types of measurement and provided comprehensive comparative information relative to pre-determined criteria derived from non-impacted reference conditions [14–16]. Since the first multimetric method which was developed based on fish communities for assessing the biological integrity of streams [14], various types of multimetric indices have been subsequently proposed in other aquatic habitats and also in terrestrial environments, using different biological communities including periphyton [17], benthic macroinvertebrates [13,16,18], fishes [19,20], plants [21], birds [22], amphibians [23] and terrestrial invertebrates [24]. Of the organisms used as biological indicators in research and monitoring programs, benthic macroinvertebrates are the most commonly used


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assemblages worldwide [25]. Characteristics including high diversity, a relatively long life-span, bottom-dwelling life style, and sensitivity on environmental disturbance make them suitable for assessing the ecological status of lotic ecosystems [26,27]. As biological indicators, they can provide insights into the current and past conditions of a water body and integrate the effects of cumulative stressors [4,28]. In developing multimetric indices using benthic macroinvertebrates in various stream environments worldwide, a great number of metrics (up to 237 [29]) have been examined and accordingly evaluated in streams [4,16,29–34]. However, the practical number of metrics and their properties that have ended up being included in the developed indices vary among different multimetric indices. This indicates the possibility of metric variability responding to different environmental gradients in specific geographic regions. Moreover, robustness of selected metrics requires relatively long term validation for practical use, not only because the metric data used in the index development do not reflect the range of long term changes, but also because the streams targeted for the assessment are facing various environmental pressures. Therefore, biological indices, including multimetric indices developed in particular geographic regions or environments, are frequently used elsewhere [34]. Such metrics may be less useful when applied in regions other than that where the species–environment relationships were originally assessed [17,35]. In Korea, a variety of attempts has been made over the past 20 years to identify and assess the degree of impairment of stream ecosystems using benthic macroinvertebrates. However, most of these have used assessment methods developed for particular geographic regions in other countries, or have been focused largely on relationships to chemical variables. A number of biological methods specific to certain stream environments have been based on the indicator species concept. These include the Total Biotic Score (TBS) [36] and its revised version, the Korean Saprobic Index (KSI) [37], which are quantitative indices based on the method of Zelinka-Marvan [38]; the Group Pollution Index (GPI) [39] and the Ecological Score of Benthic macroinvertebrate community (ESB) [40], which are cost-effective qualitative methods. These methods only partially consider water quality, and their results vary with the sampling methods used. Thus, an integrated assessment method is necessary to provide information on biological integrity, and to enable measurement of the long-term health status of streams and the effectiveness of various remediation methods. The purpose of this study was to develop a multimetric index (the Korean Benthic macroinvertebrate Index for Biological Integrity—KB-IBI) using benthic macroinvertebrate communities for the assessment of the biological integrity in Korean streams, and potentially for application to streams in other countries. 2. Materials and Methods 2.1. Study Area South Korea is located between 37°00'N and 127°30'N, and has an area of approximately 100,033 km2 that encompasses the southern half of the Korean peninsula. The annual precipitation is 1,308 mm, but there is substantial variation among seasons [41]. Korean streams are affected by flooding as a consequence of high levels of precipitation during the summer monsoon period, but in other seasons


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only maintain base flow or may not flow at all because of drought conditions. Detailed information about the major rivers and their watershed conditions can be found in the related studies [42,43]. The National Aquatic Ecosystem Monitoring Program (NAEMP) has undertaken a bi-annual evaluation of the ecosystem health status of Korean streams [44]. This program included a total of 720 sampling sites in 388 streams and rivers in 2009, and included more than five major river systems throughout the country (Figure 1). The number of sampling sites will be extended to 1,200 until 2015, when they will be included under regulation in the national biological monitoring network [5]. While the waterways involved range from small mountainous streams to large rivers, most sampling sites were in wadeable streams. The largest numbers of sampling sites were in the Han River watershed (n = 320), followed by the Nakdong and Geum river watersheds (n = 130 each), the Youngsan River watershed (n = 76), and the Seomjin River watershed (n = 64). This large-scale national monitoring program included the majority of stream types in Korea, providing the basis for the development of a multimetric index. Physico-chemical and biological data were compiled from the NAEMP surveys conducted during May 2009. Figure 1. Spatial distribution of study sites assigned to each of the three status categories (reference, impaired, others), according to site classification criteria.

Biological data from a total of ninety-six sampling events within two National Parks were included to complement the establishment of reference sites because the NAEMP was mostly concentrated on


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middle reach and lowland streams for monitoring and restoration activities. These streams ranged from second to fourth stream order, and are representative of reference conditions because they are well preserved by strict natural resources conservation laws [45,46]. Field samplings were performed at the same period of NAEMP survey under base flow conditions. This study used such data only for the procedures of metric selection and index development due to the lack of physico-chemical information. 2.2. Measurement of Environmental Variables Environmental parameters were measured at each study site. Regional variables included altitude and land use type for watershed characteristics. Altitude was determined using a digital elevation model (DEM), and for each sampling site a topographic map (1:50,000) was used to qualitatively characterize the watershed according to the proportions of forest, agriculture and urban land use categories. Hydraulic and physical properties at the local scale were measured at each site, including: (i) average current velocity, measured at riffles or gliding runs using a current meter, or calculated by the Craig method [47]; (ii) the percent substrate composition, which was visually estimated with respect to fine (60% forest and 0.30 mg/L in TP), high turbidity (>50 NTU) and deterioration in habitat quality (>70% fine particles and a HIS score ≤ 20). Sites that were not classified as either reference or impaired were classed as “others”. The statistical differences between reference and impaired sites for the various environmental parameters were assessed using the non-parametric MannWhitney test. 2.5. Metric Selection and Index Development Development of the macroinvertebrate-based multimetric index generally followed the procedure of Barbour et al. [13]. Thirty-four candidate metrics were screened and examined; these included properties of richness, composition, trophic/habit status and tolerance measures, which were derived from previous studies [13,16,56,57] (Table 1). Comparison of the metric values between reference and impaired streams was undertaken with the aim of selecting the most appropriate metrics for Korean streams. Metric selection was performed using a stepwise process involving assessment of their variation, redundancy and sensitivity. Table 1. Definition of 34 candidate metrics and their expected responses to increasing anthropogenic disturbance. Metric

Definition

Richness measures Number of taxa Number of species collected in the sample Number of EPT taxa Number of taxa in the orders Ephemeroptera, Plecoptera, and Trichoptera Number of Ephemeroptera Number of mayfly (Ephemeroptera) nymphs Number of Plecoptera Number of stonefly (Plecoptera) nymphs Number of Trichoptera Number of caddisfly (Trichoptera) larvae

Expected Response Decrease Decrease Decrease Decrease Decrease


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Metric Composition measures % Dominant taxon % Oligochaeta % EPT taxa

Definition Percent of individuals in the most abundant species Percent of individuals in aquatic worms Percent of individuals in the insect orders Ephemeroptera, Plecoptera, and Trichoptera Percent of individuals in mayfly nymphs Percent of individuals in stonefly nymphs Percent of individuals in caddisfly larvae Percent of individuals in chironomid midge larvae

Expected Response Increase Increase Decrease

% Ephemeroptera Decrease % Plecoptera Decrease % Trichoptera Decrease % Chironomidae Increase Composition measures % Taxa abundance without Percent of individuals in taxa abundance without chironomid midge larvae Decrease Chironomidae % Non-insects and Percent of individuals in non-insects and chironomid midge larvae Increase Chironomidae % Non-insects Percent of individuals in non-insects Increase Total density Total abundance converted to number per square meter Variable Ratio of EPT to Ratio of pollution sensitive EPT taxa to pollution tolerant chironomid Decrease Chironomidae midge larvae McNaughton’s dominance McNaughton’s dominance index [58] Increase index Shannon’s diversity index Shannon’s diversity index [59] Decrease Margalef’s richness index Value of Margalef’s species richness index [60] Decrease Pielou’s evenness index Value of Pielou’s evenness index [61] Decrease Trophic/habit measures % Shredders Percent of individuals in the shredder functional feeding group Decrease % Scrapers Percent of individuals in the scraper functional feeding group Decrease % Filterers Percent of individuals in the collector-filterer functional feeding group Decrease % Gatherers Percent of individuals in the collector-gatherer functional feeding group Variable % Predators Percent of individuals in the predator functional feeding group Variable Ratio of filterers and Ratio of collector-filterers and scrapers to total density Decrease scrapers Ratio of scrapers to Ratio of scrapers to collector-filterer functional feeding group Decrease filterers Number of clingers Number of the clinger functional habit group Decrease Number of clingers and Number of the clinger and sprawler functional habit groups Decrease sprawler % Clingers Percent of individuals in the clinger functional habit group Decrease % Clingers and sprawlers Percent of individuals in the clinger and sprawler functional habit groups Decrease Tolerance measures Sum of assigned ecological scores for each occurring species in the Decrease ESB macroinvertebrate assemblage [40,62] KSI Value of Korean saprobic index [37] Increase


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Metric

Definition

Expected Response

Composition measures % Taxa abundance without Percent of individuals in taxa abundance without chironomid midge larvae Decrease Chironomidae % Non-insects and Percent of individuals in non-insects and chironomid midge larvae Increase Chironomidae % Non-insects Percent of individuals in non-insects Increase Total density Total abundance converted to number per square meter Variable Ratio of EPT to Ratio of pollution sensitive EPT taxa to pollution tolerant chironomid Decrease Chironomidae midge larvae McNaughton’s dominance McNaughton’s dominance index [58] Increase index Shannon’s diversity index Shannon’s diversity index [59] Decrease Margalef’s richness index Value of Margalef’s species richness index [60] Decrease Pielou’s evenness index Value of Pielou’s evenness index [61] Decrease Trophic/habit measures % Shredders Percent of individuals in the shredder functional feeding group Decrease % Scrapers Percent of individuals in the scraper functional feeding group Decrease % Filterers Percent of individuals in the collector-filterer functional feeding group Decrease % Gatherers Percent of individuals in the collector-gatherer functional feeding group Variable % Predators Percent of individuals in the predator functional feeding group Variable Ratio of filterers and Ratio of collector-filterers and scrapers to total density Decrease scrapers Ratio of scrapers to Ratio of scrapers to collector-filterer functional feeding group Decrease filterers Number of clingers Number of the clinger functional habit group Decrease Number of clingers and Number of the clinger and sprawler functional habit groups Decrease sprawler % Clingers Percent of individuals in the clinger functional habit group Decrease % Clingers and sprawlers Percent of individuals in the clinger and sprawler functional habit groups Decrease Tolerance measures ESB Sum of assigned ecological scores for each occurring species in the Decrease macroinvertebrate assemblage [40,62] KSI Value of Korean saprobic index [37] Increase EPT, Ephemeroptera–Plecoptera–Trichoptera; ESB, Ecological Score of Benthic macroinvertebrate community; KSI, Korean Saprobic Index.

Metric suitability was initially assessed for discrimination of reference from impaired conditions. We discarded metrics with low values and large variability from the reference site group, because of their poor discrimination ability. For all combinations of the metrics found to be suitable according to this criterion, a redundancy test was performed to detect redundant metrics in the index, using Pearson’s correlation analysis. High correlation coefficients (r > 0.80, p < 0.05) were interpreted as


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indicating redundant metrics, and in these cases only one metric was retained for further assessment in the index development procedure. Box-and-whisker plots, which enabled visualization of variations in the metric ranges, were used to estimate the ability of metrics to discriminate reference and impaired sites. The discriminatory power of each remaining metric was determined according to the degree of overlap of medians and interquartile ranges [13]. Metrics with no overlap of interquartile ranges were considered to have good discriminatory power for both reference and impaired sites. A multimetric index should include metrics reflecting ecological characteristics, and be able to indicate potential stressor–specific relationships [16]. Thus, the responsiveness of each remaining metric to anthropogenic disturbance was evaluated using Pearson’s correlation analysis. Those metrics that correlated with at least one of the environmental variables at p < 0.01 were accepted. The final multimetric index was constructed from a combination of the core metrics selected through the metric selection procedure. A scoring system of 1, 3 or 5 points was adopted using threshold values (the minimum, the 25th percentile, the 75th percentile, and the maximum) for each component metric, according to its response to environmental degradation [13,55,56]. The index value for each sampling site was obtained by aggregating the individual core metric scores. The index range was then quadrisected to generate four classes: Class A (Excellent), which indicated the site was comparable in condition to the reference biological conditions; Class B (Good) indicating slight disturbance; Class C (Fair), indicating moderate disturbance; and Class D (Poor), indicating severely disturbed biological integrity. 2.6. Index Validation The sensitivity of the multimetric index was determined by assessing whether there was clear discrimination among the classified site groups (reference, impaired and others) using box-andwhisker plots. Pearson’s correlation analysis was also used to identify relationships between the index scores and environmental variables. Principle components analysis (PCA) was used to examine the responsiveness of the multimetric index to environmental variables, as illuminating the distribution of sites in the ordination space and statistical correlations. PCA was performed using PC-ORD software (version 4.25) [63]. 3. Results 3.1. Site Classification and Environmental Characteristics The site classification screening procedure identified 135 reference sites (39 sites from NAEMP database and 96 from two National Parks), most of which were distributed over the Han River watershed, and 236 impaired sites. There were significant differences in environmental parameters between the reference and impaired sites except for pH, DO and turbidity (p < 0.05) (Table 2).


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Table 2. Summary statistics of environmental variables for reference and impaired sites, showing the average (standard deviation) and range (minimum and maximum values) for each variable. Variable 1 pH DO (mg L−1) BOD (mg L−1) EC (mS m−1) TN (mg L−1) TP (mg L−1) Turbidity (NTU) Altitude (m) % Urban % Agriculture % Forest Velocity (cm sec−1) % Fine % Coarse HIS

Reference site (n = 39) Average Range 8.1 (0.7) 7.0–9.5 9.9 (1.7) 6.0–12.6 1.1 (0.5) 0.5–2.7 122.0 (136.7) 31–818 1.51 (0.62) 0.38–2.96 0.02 (0.02) 0.00–0.11 5.7 (3.8) 0–11 285.6 (181.5) 33–718 5.9 (4.8) 0–15 10.5 (11.2) 0–30 83.3 (12.9) 60.0–100.0 65.7 (25.4) 18.7–105.7 11.2 (9.1) 0–30 88.8 (9.1) 70–100 41.5 (4.2) 31–50

Impaired site (n = 236) Average Range 8.0 (0.8) 6.6–11.1 9.5 (3.0) 2.4–17.3 4.9 (4.1) 0.3–37.5 1,172.5 (4,637.5) 82.4–40,600.0 4.76 (3.81) 0.32–27.71 0.30 (0.48) 0.00–5.59 15.3 (35.2) 0.0–400.0 37.7 (36.8) 0.0–233.0 36.4 (36.6) 0.0–100 40.4 (35.1) 0.0–100 15.9 (23.4) 0.0–100 24.5 (22.6) 0.0–95.8 67.2 (31.6) 0.0–100 32.4 (31.3) 0.0–100 32.5 (7.0) 0.0–50

P 0.481 0.536