Summer fish communities in northern Gulf of Mexico estuaries: Indices of ecological condition

Jordan, Stephen J.; Lewis, Michael A.; Harwell, Linda C.; Goodman, Larry R.

doi:10.1016/j.ecolind.2009.09.003

Cited by 18 publications

(10 citation statements)

References 28 publications

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“…Fish Community Index (FCI) was developed by Jordan et al (2010) with the purpose of evaluating estuarine environments within the Gulf of Mexico. The conditions that FCI was developed for are similar to those for the EMFI.…”

Section: Fish Community Indexmentioning

confidence: 99%

“…The conditions that FCI was developed for are similar to those for the EMFI. However, the FCI only uses three metrics (Jordan et al, 2010) compared to the fourteen used for the EMFI (Harrison and Kelly, 2013). The metrics used for the FCI include: number of species, species abundance, and trophic index (Jordan et al, 2010).…”

Section: Fish Community Indexmentioning

confidence: 99%

“…However, the FCI only uses three metrics (Jordan et al, 2010) compared to the fourteen used for the EMFI (Harrison and Kelly, 2013). The metrics used for the FCI include: number of species, species abundance, and trophic index (Jordan et al, 2010). Each metric is given a score of 0, 1, or 2 with 0 representing degraded sites and 2 representing non-degraded sites (Jordan et al, 2010).…”

Section: Fish Community Indexmentioning

confidence: 99%

“…The metrics used for the FCI include: number of species, species abundance, and trophic index (Jordan et al, 2010). Each metric is given a score of 0, 1, or 2 with 0 representing degraded sites and 2 representing non-degraded sites (Jordan et al, 2010). The individual metric scores are summed to provide the health score for each site (Jordan et al, 2010).…”

Section: Fish Community Indexmentioning

confidence: 99%

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A review of macroinvertebrate- and fish-based stream health indices

Herman

Nejadhashemi

2015

Ecohydrology & Hydrobiology

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The focus of this review is to discuss the current uses and developments of macroinvertebrate and fish indicators in riverine ecosystems. Macroinvertebrates and fish are commonly used indicators of stream heath, due to their ability to represent degradation occurring at the local or regional scales, respectively. A total of 78 macroinvertebrate and fish indices were reviewed, and the frequently used macroinvertebrate and fish indices are discussed in detail in the context of aquatic ecosystem health evaluation. This review also discusses several types of common components, or metrics, used in the creation of indices. Following this, the review will focus on the different methods used for macroinvertebrate and fish collection, in both wadeable and non-wadeable aquatic ecosystems. With the basics of macroinvertebrate and fish indices discussed, emphasis will be placed on the application of indices and the different regions for which they are developed. The final section will provide a summary of the benefits and limitations of macroinvertebrate and fish indices. In general, the majority of studies have been performed in wadeable streams; therefore, our knowledge about these indices in non-wadeable streams is limited, which should be the subject of future research.

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Section: Fish Community Indexmentioning

confidence: 99%

Section: Fish Community Indexmentioning

confidence: 99%

Section: Fish Community Indexmentioning

confidence: 99%

Section: Fish Community Indexmentioning

confidence: 99%

See 2 more Smart Citations

A review of macroinvertebrate- and fish-based stream health indices

Herman

Nejadhashemi

2015

Ecohydrology & Hydrobiology

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“…Water quality indices have been developed and used to characterize a wide variety of phenomena including drinking water (Beamonte Córdoba et al, 2010), bioassessment (Aguiar et al 2014;Blanchet et al, 2008;Kanno et al, 2010;Stoddard et al, 2008), fresh water habitat (Pinto et al, 2009;Simaika and Samways, 2011), effect of agriculture on stream water (Justus et al, 2010;Shiels, 2010), river water quality (Feio et al, 2009;Navarro-Llácer et al, 2010), ecological condition (Jordan et al, 2010;Marchini et al, 2009;Seilheimer et al, 2009;Tran et al, 2008) and variable reduction for selection of variables to monitor (Kantoussan et al, 2010). A recent survey of approaches for constructing indices (Bierman et al, 2011) cite the techniques of cluster analysis (Hargiss et al, 2008;Khalil et al, 2010;Styers et al, 2010), principal components analysis, factor analysis (Blocksom and Johnson, 2009;Leunda et al, 2009;Liou et al, 2004;Ou et al, 2010;Tran et al, 2010), discriminant analysis (Feio et al, 2009;Kane et al, 2009), and fuzzy logic (Ghosh and Mujumdar, 2010).…”

Section: Introductionmentioning

confidence: 99%