Simulation of the population-level effects of 4-nonylphenol on wild Japanese medaka (Oryzias latipes)

Meng, Yaobin; Lin, Bin‐Le; Tominaga, Mamoru; Nakanishi, Junko

doi:10.1016/j.ecolmodel.2006.03.022

Cited by 17 publications

(17 citation statements)

References 18 publications

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“…However, there is currently a relative paucity of information regarding the effect of genetic variation on the response to toxicants and positive correlations between multi-locus heterozygosity and fitness are not unanimous (Hansson and Westerberg 2002). A central principle of ecotoxicological studies is the extrapolation of findings and conclusions derived from laboratory studies to wild populations, particularly in situations where population-level effects are being modelled or predicted (Meng et al 2006;Miller and Ankley 2004). Reduced or unrepresentative levels of genetic variation in standard laboratory strains of model species, such as the zebrafish, may make such extrapolations difficult or inappropriate, although it may increase the precision of the results (Chia et al 2005;Forbes 1998).…”

Section: Resultsmentioning

confidence: 98%

Genetic variation in strains of zebrafish (Danio rerio) and the implications for ecotoxicology studies

et al. 2008

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There is substantial evidence that genetic variation, at both the level of the individual and population, has a significant effect on behaviour, fitness and response to toxicants. Using DNA microsatellites, we examined the genetic variation in samples of several commonly used laboratory strains of zebrafish, Danio rerio, a model species in toxicological studies. We compared the genetic variation to that found in a sample of wild fish from Bangladesh. Our findings show that the wild fish were significantly more variable than the laboratory strains for several measures of genetic variability, including allelic richness and expected heterozygosity. This lack of variation should be given due consideration for any study which attempts to extrapolate the results of ecotoxicological laboratory tests to wild populations.

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Section: Resultsmentioning

confidence: 98%

Genetic variation in strains of zebrafish (Danio rerio) and the implications for ecotoxicology studies

et al. 2008

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“…However, both concentrations and PNEC values in an environment are varied and the point estimate may not include the variation in concentrations and PNEC values. Several reported PNEC values have ranged from 0.021 to 6.6 μg/l for NP, and from 0.11 to 1.0 for NP 1 EO and NP 2 EO (ECB and European Chemicals 2002;Fenner et al 2002;Iguchi et al 2002;Environment Canada 2005;U.S.EPA 2005;Meng et al 2006;Press-Kristensen et al 2007). …”

Section: Introductionmentioning

confidence: 98%

Ecological Risk, Mass Loading, and Occurrence of Nonylphenol (NP), NP Mono-, and Diethoxylate in Kaoping River and its Tributaries, Taiwan

Chen¹,

Yeh²

2009

Water Air Soil Pollut

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Biochemically, nonylphenol ethoxylates (NPnEOs) and its breakdown products nonylphenol (NP), NP monoethoxylate (NP 1 EO), and NP diethoxylate (NP 2 EO) are considered endocrine disrupting compounds. These NPnEOs have been detected in aquatic environments and are of concern. NP, NP 1 EO, and NP 2 EO were detected in water samples collected from the main watercourse and polluted tributaries of Kaoping River, Taiwan. Concentrations were below the detection limit (

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“…From the perspective of chemicals managers, the impacts on a higher level, such as population-level or community-level is more favorable; nonetheless, the impacts on higher levels are subjected to more ecological and environmental variations and hence become less tractable. The compromise between the ecological relevance and the feasibility engenders the prominence of population-level ecological risk assessment (PLERA) for chemical risk management, and PLERA has been advocated in recent years [1][2][3][4][5].…”

Section: A Population-level Ecological Risk Assessment and Criterionmentioning

confidence: 99%

Deriving an Ecological Risk Assessment Criterion Concentration for Populations with Seasonal Variation: Reconsidering and Improving the Algorithm

Meng

Shi

2009

2009 3rd International Conference on Bioinformatics and Biomedical Engineering

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Population-level ecological risk assessment (PLERA) for chemicals has been advocated for broader application in chemicals' risk management. The persistence capability, indicated by the finite growth rate (λ) of certain population is scientifically soundly founded and is an appropriate risk assessment endpoint. In accordance, the concentration by which a population vitality is so stressed that its λ value is reduced to be one, can serve as a criterion concentration, denoted as C λ=1 . Nonetheless, seasonal variation is desirably taken into account when deriving C λ=1 for better ecological relevance. This paper revisited the algorithm for C λ=1 derivation and proposed an improved algorithm for faster calculation. Specifically, in the algorithm, the age-structured projection matrix (namely Leslie matrix) was collapsed into a much smaller stage-structured projection matrix. The new algorithm was compared to the normal algorithm with a case study of nonylphenol on Japanese medaka (Oryzias latipes), and the simulation results suggest that the new algorithm can save computation time by around three quarters with a small underestimation of the variance and slight bias. The proposed algorithm is considered useful for a fast or screening stage of PLERA.

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Simulation of the population-level effects of 4-nonylphenol on wild Japanese medaka (Oryzias latipes)

Cited by 17 publications

References 18 publications

Genetic variation in strains of zebrafish (Danio rerio) and the implications for ecotoxicology studies

Genetic variation in strains of zebrafish (Danio rerio) and the implications for ecotoxicology studies

Ecological Risk, Mass Loading, and Occurrence of Nonylphenol (NP), NP Mono-, and Diethoxylate in Kaoping River and its Tributaries, Taiwan

Deriving an Ecological Risk Assessment Criterion Concentration for Populations with Seasonal Variation: Reconsidering and Improving the Algorithm

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