A process for creating multimetric indices for large-scale aquatic surveys

Stoddard, John L.; Herlihy, Alan T.; Peck, David V.; Hughes, Robert M.; Whittier, Thomas R.; Tarquinio, Ellen

doi:10.1899/08-053.1

Cited by 359 publications

(286 citation statements)

References 47 publications

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“…Metrics that use LDC and decrease with the disturbance set the 95th percentile of the site values as the upper anchor and the 5th percentile values as the lower anchor. If the metric increased with disturbance, then the 5th percentile of the site values was set as the upper anchor, and the 95th percentile of the values was set as the lower anchor [52]. The metric was rescaled as follows [7].…”

Section: Metric Standardization and Categorizationmentioning

confidence: 99%

Assessing Aquatic Ecological Health for Lake Poyang, China: Part I Index Development

Huang

Gao

et al. 2018

Water

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Abstract:The development of an ecosystem health index to assess health status in freshwater lakes is urgently needed in China, especially in polluted lakes. This study developed a specific Ecosystem Health Index (LP-EHI) for Lake Poyang in China. LP-EHI quantified lake health from the perspectives of physical, chemical, biological integrity and social service. Physical integrity indices included hydrological conditions (water level and runoff), basic morphometric characteristics (lake area and shoreline), and tributary connectivity. Chemical integrity indices used water quality, nutrition, and toxicity to quantify chemical impairment. Biological integrity indicators covered six major components of the aquatic food chain, namely, phytoplankton, zooplankton, benthic macroinvertebrates, wetland plants, fish, and wintering birds. Social service indices included drinking water, pathogenic potential, flood storage capacity, sand mining, and dish-shaped sub-lake areas under management to measure whether the lake fulfilled the needs of human society. Reference and impaired conditions for each metric were defined by "historical" conditions, "least disturbed" conditions, national standards and expert opinions. The value of LP-EHI ranging from 0 to 1 was divided into five health conditions: excellent (≥0.8), good (0.6-0.8), fair (0.4-0.6), poor (0.2-0.4) and bad (<0.2). The metrics' reliability was further validated using a box-and-whisker plot test. The developed index (LP-EHI) is so far the most comprehensive index to evaluate ecosystem health for Lake Poyang, and is well reflected in the unique characteristics of Lake Poyang. It can enhance our understanding of lake health conditions and thus guide lake management to achieve better health conditions.

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Section: Metric Standardization and Categorizationmentioning

confidence: 99%

Assessing Aquatic Ecological Health for Lake Poyang, China: Part I Index Development

Huang

Gao

et al. 2018

Water

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“…Recently, many studies have reported biological criteria and assessments for evaluation of the ecological condition of streams (Davies and Jackson, 2006;Hering et al, 2006;Stoddard et al, 2008;Waite et al, 2008;Carlisle et al, 2009). Various biological metrics, including individual and aggregated indices of algae, macrophytes, macroinvertebrates, and fish, have been proposed for various spatial extents, mostly in North America and Europe (Osborne and Sua´rez-Seoane, 2002;Hering et al, 2006;Pont et al, 2006;Johnson et al, 2007;Ode et al, 2008;Stoddard et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

“…Various biological metrics, including individual and aggregated indices of algae, macrophytes, macroinvertebrates, and fish, have been proposed for various spatial extents, mostly in North America and Europe (Osborne and Sua´rez-Seoane, 2002;Hering et al, 2006;Pont et al, 2006;Johnson et al, 2007;Ode et al, 2008;Stoddard et al, 2008). Although uncertainties remain in applying these metrics in ecological regions and spatial scales that differ from those for which the metrics were developed and verified (Kelly et al, 2009;No˜ges et al, 2009), assessments of ecological status using biological indices and habitat condition have become drivers of water management and restoration practices.…”

Section: Introductionmentioning

confidence: 99%

Overview and application of the National Aquatic Ecological Monitoring Program (NAEMP) in Korea

Lee

Hwang

Lee

et al. 2011

Ann. Limnol. - Int. J. Lim.

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-This paper provides an overview of the development and application of the National Aquatic Ecological Monitoring Program (NAEMP) in Korea, which uses biological and habitat-riparian criteria for river/stream and watershed management. Development of NAEMP began in 2003, with recognition by the Korean Ministry of Environment (MOE) of the limitations of applying chemical parameters (e.g., biochemical oxygen demand (BOD)) as the principal targets of water environment management. Ecosystem health criteria under NAEMP were developed from 2003 to 2006. Candidate sites for monitoring were also screened and established across the country. NAEMP was implemented in 2007, and since then a standard protocol of nationwide monitoring based on multi-criteria has been implemented to assess the ecological condition of rivers and streams. The monitoring results indicate that many Korean rivers and streams are severely degraded, with biological conditions that are much worse than their water chemistry suggests. In 2009, 24% of rivers and streams were in classes C (Fair) and D (Poor) for BOD, but more than 71, 53, and 27% were categorized as Fair to Poor according to fish, diatom, and benthic macroinvertebrate assemblages, respectively. NAEMP is promising in that the results have already had great impacts on policy making and scientific research relevant to lotic water environment and watershed management in Korea. In the future, NAEMP results will be used to develop more aggressive regulations for the preservation and restoration of rivers/ streams, riparian buffer areas and watersheds. Another future aim of the NAEMP is to develop aquatic ecological modeling based on the monitoring results.

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“…Diversity metrics are capable of describing system properties such as complexity, stability, and functioning of ecosystems (Hacker and Gaines, 1997); therefore, they became parts of several multimetric indices used for biological quality assessment (Hering et al, 2006;Stoddard et al, 2008;Carvalho et al, 2013). Applicability of diversity-based approaches needs a clear relationship between stressors and diversity metrics as response variables (European Commission, 2010).…”

mentioning

confidence: 99%

The role of phytoplankton diversity metrics in shallow lake and river quality assessment

Borics

Görgényi

Grigorszky

et al. 2014

Ecological Indicators

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Ecological water quality problems are frequently connected to increment of phytoplankton productivity and overdominance of some phytoplankton species. Metrics that show monotonously increasing or decreasing tendencies along stressor gradients is recommended for ecological state assessment. Diversity metrics are influenced by various physical disturbances and show high within-year variability; thus, there is no agreement on the usefulness of these metrics as state indicators.To test the usefulness of phytoplankton diversity in ecological state assessment we investigated the productivity-diversity relationships for lakes and rivers in the Carpathian Basin (Hungary). We demonstrated that the shape of productivity-diversity relationship depends on the investigated water body type. Regarding lakes, hump-shaped relationship was found for all computed metrics. Parallel with the increase in phytoplankton productivity values, diversity metrics showed monotonously increasing tendencies in rhithral and decreasing tendencies in large potamal rivers. We found no systematic relationship in the case of small lowland rivers. Changes of diversity metrics calculated for species and functional groups showed similar tendencies within the types, only the slopes of regression lines differ each other. The use of diversity metrics as ecological state indicators should be restricted to water body types where diversity decreases or increases monotonously with phytoplankton biomass. Regarding the lakes the use of diversity metrics is not recommended for ecological state assessment. In rhithral and large potamal river assessment, application of diversity metrics should be strongly considered. We demonstrated that diversity metrics can be useful components of multimetric indices proposed to use by the Water Framework Directive.

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A process for creating multimetric indices for large-scale aquatic surveys

Cited by 359 publications

References 47 publications

Assessing Aquatic Ecological Health for Lake Poyang, China: Part I Index Development

Assessing Aquatic Ecological Health for Lake Poyang, China: Part I Index Development

Overview and application of the National Aquatic Ecological Monitoring Program (NAEMP) in Korea

The role of phytoplankton diversity metrics in shallow lake and river quality assessment

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