Lotic Ecosystem Health Assessments Using
an Integrated Analytical Approach of Physical
Habitat, Chemical Water Quality, and Fish
Multi-Metric Health Metrics

Lee, Sang Jae; Lee, Eui-Haeng; An, Kwang-Guk

doi:10.15244/pjoes/78044

Cited by 12 publications

(14 citation statements)

References 24 publications

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“…CHL, TSS, TNI, AI, N:P were the most important factors for the prediction of IBI value in the watershed. Our present study suggested that the statistical learning approach ANN is one of the good tools to predict the ecological health of the river system, which is concurred with the previous studies of Lee et al 2018 [28].…”

Section: Prediction Of Chemical Pollution Index and Index Of Biotic Isupporting

confidence: 92%

“…A total of 44 species were observed in the mainstream of the Geum River watershed. The dominated species in the watershed were Zacco platypus (32.99%), Zacco koreanus (12.43%), and Squalidus chankaensis tsuchigae (11.19%), etc., which was similar with some previous studies on watershed [28]. One endangered species (Pseudopungtungia nigra) was found in the upstream of the watershed.…”

Section: Fish Community Analysissupporting

confidence: 92%

“…The abundance of tolerant species, carnivores, omnivores were dominant in downstream, indicating that the downstream health condition was deteriorated because of organic and nutrient pollutants and excessive chlorophyll growth. The present results are similar to that of Atique and An (2018) and Lee et al (2018) [16,28].…”

Section: Principal Component Analysis (Pca) In Relation To Chemicals supporting

confidence: 91%

“…Each metric had been assigned as scored 5, 3, and 1. The Geum River health condition was evaluated based on the obtained scores and the categories are excellent (36)(37)(38)(39)(40), good (28)(29)(30)(31)(32)(33)(34), fair (20)(21)(22)(23)(24)(25)(26), poor (14)(15)(16)(17)(18), and very poor (8-13).…”

Section: Index Of Biotic Integrity (Ibi) Modelmentioning

confidence: 99%

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Ecological River Health Assessments Using Chemical Parameter Model and the Index of Biological Integrity Model

HaRa

Mamun

2019

Water

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River health is one of the important issues today because of various threats by multiple anthropogenic stressors that have long-term impacts on the physical habitats, biodiversity, ecological functions, and their services. The main objectives of this study is to diagnose the chemical and biological river health in the watershed of Geum River with regard to the chemical regimes (N, P) and fish community using multi-metric chemical pollution index (CPI), and the index of biotic integrity model (IBI), respectively. The empirical models of sestonic chlorophyll, nutrients (N, P), and nutrient ratios of N:P indicated that the watershed, including all sampling sites, was a phosphorus-limited system. Analysis of fish trophic and tolerance guilds showed that the omnivore fish species and tolerant fish species were dominant in the watershed, while the sensitive fish species decreased downstream because of nutrient enrichments (such as TN, TP) and organic matter pollutions (such as BOD, COD). The chemical model of CPI showed that 11 sampling sites were in the fair—good condition, and 8 sites were in poor—very poor condition. Species composition analysis indicated that Zacco platypus was most widely distributed in the watersheds and dominated the fish community. The biological health of the watershed, based on the multimetric IBI model, was in poor condition and was getting worse downstream. The degradation of the river health was matched with the chemical health and showed a decreased abundance of insectivores and sensitive fish species. The outcomes of the river health were supported by principal component analysis (PCA) and cluster analysis (CA) of fish model metrics and the physicochemical parameters. Overall, our study suggests that river health was directly influenced by the chemical pollutions of nutrients and organic matter inputs.

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Section: Prediction Of Chemical Pollution Index and Index Of Biotic Isupporting

confidence: 92%

Section: Fish Community Analysissupporting

confidence: 92%

Section: Principal Component Analysis (Pca) In Relation To Chemicals supporting

confidence: 91%

Section: Index Of Biotic Integrity (Ibi) Modelmentioning

confidence: 99%

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Ecological River Health Assessments Using Chemical Parameter Model and the Index of Biological Integrity Model

HaRa

Mamun

2019

Water

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“…The water quality in these ecosystems is determined by various interactions of natural and anthropogenic factors [Lake et al 2017]. The increase in industrial, fishing, agricultural and recreational activities generate changes in water quality due to cumulative effects, causing great economic and ecological losses [Lee et al 2018].…”

Section: Introductionmentioning

confidence: 99%

Variability of the Water Quality Characterizing High Andean Lagoons for Tourist Use Evaluated Through Multivariate Statistical Methods, Junín, Peru

et al. 2019

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The spatial-temporal variability characterizing the water quality of high Andean lagoons for tourist use was evaluated using multivariate statistical methods during 2017 and 2018. The water samples were collected from 14 sampling sites, with three replicates each. The water quality indicators determined were: pH, temperature, DO, COD, BOD 5 , P, N, Fe, Cu, Cr, Cd, Pb, Zn and chlorophyll-a. The flat cluster analysis (k R cluster) according to Ward's algorithm showed six significantly differentiated groups (α=0.01). In turn, the real similarity profile (SIMPROF) moves markedly away from the obtained low permutation with a large excess of Euclidean similarity with a Pi value of 0.627. The PCA showed that the first two components recommended by the sedimentation analysis (Scree test) indicated 61.52% of the total variation of the observations. According to the Spearman range correlation selection criterion, the variables that best interpret the sample distributions are COD, DTS, P, Cd and Zn with a correlation of 0.893, the DTS being the most important variable with a correlation value of 0.795. The PERMANOVA analysis according to the flat cluster factor indicated that at least one of the groups is different from the others in relation to the levels of physicochemical characteristics studied. Therefore, all the configured groups are statistically different, demonstrating that each lagoon is different in relation to its physicochemical indicators, according to the season in which it is found.

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Application of a One Welfare‐Based Ecosystem Model to assess wild collection for public aquariums

Fischer,

Pempek,

Flint

et al. 2024

Aquatic Conservation

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Abstract1. Public aquariums are organizations that offer their visitors an opportunity to engage with, gain knowledge of, and contribute to the conservation of species and ecosystems. Unfortunately, the ways many aquariums maintain their populations include primarily sourcing marine species from the wild. This creates the potential for negative impacts to stressed aquatic environments and a need for a holistic approach to quantify the impacts of aquarium population management. 2. The objective of this study was to implement a developed One Welfare‐Based Ecosystem Model to predict impacts of aquarium population management on humans, animals, and the environment. Ecosystem indicators were selected and grouped into physical–chemical, biological, and socio‐economic categories. Data included measurements of environmental and animal indicators at field sites frequently visited by aquariums to collect animals from, aquarium visitor surveys, and publicly available data. Model development included comparing field data to reference information and then adding weightings based on indicator significance and alpha‐testing of the model. 3. At model completion, each institution was allocated a One Welfare status. Confidence ratings of measured indicators and reference data occurred for each field site to determine the appropriateness of use of the model for each aquarium. 4. Findings included a positive One Welfare status, with collaborating institutions scoring in the good and excellent categories (81.92/100 and 92.51/100). Confidence ratings showed positive results (62/100 and 78/100) for model applicability for the field sites studied as well as future use by other institutions assessing similar parameters. 5. To maintain their recognition as leaders in conservation, public aquariums must objectively assess their direct and indirect influence on marine ecosystems moving forward.

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Lotic Ecosystem Health Assessments Using an Integrated Analytical Approach of Physical Habitat, Chemical Water Quality, and Fish Multi-Metric Health Metrics

Cited by 12 publications

References 24 publications

Ecological River Health Assessments Using Chemical Parameter Model and the Index of Biological Integrity Model

Ecological River Health Assessments Using Chemical Parameter Model and the Index of Biological Integrity Model

Variability of the Water Quality Characterizing High Andean Lagoons for Tourist Use Evaluated Through Multivariate Statistical Methods, Junín, Peru

Application of a One Welfare‐Based Ecosystem Model to assess wild collection for public aquariums

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