Use of microcosm and fish toxicity data to select mesocosm treatment concentrations

1995 ◽  
Vol 28 (4) ◽  
Author(s):  
F.S. Stay ◽  
A.W. Jarvinen
Keyword(s):  
Toxicity Data ◽  
Fish Toxicity

scholarly journals Evaluation of a Bayesian Network for Strengthening the Weight of Evidence to Predict Acute Fish Toxicity from Fish Embryo Toxicity Data

2020 ◽  
Vol 16 (4) ◽  
pp. 452-460 ◽  
Author(s):  
Adam Lillicrap ◽  
S Jannicke Moe ◽  
Raoul Wolf ◽  
Kristin A Connors ◽  
Jane M Rawlings ◽  
...  
Keyword(s):  
Bayesian Network ◽  
Weight Of Evidence ◽  
Toxicity Data ◽  
Fish Embryo ◽  
Fish Toxicity ◽  
Embryo Toxicity

scholarly journals Development of a hybrid Bayesian network model for predicting acute fish toxicity using multiple lines of evidence

2019 ◽  
Author(s):  
S. Jannicke Moe ◽  
Anders L. Madsen ◽  
Kristin A. Connors ◽  
Jane M. Rawlings ◽  
Scott E. Belanger ◽  
...  
Keyword(s):  
Bayesian Network ◽  
Expert Knowledge ◽  
Weight Of Evidence ◽  
List Type ◽  
Toxicity Data ◽  
Web Interface ◽  
Fish Embryo ◽  
Fish Toxicity ◽  
Embryo Toxicity ◽  
Lines Of Evidence

AbstractA Bayesian network was developed for predicting the acute toxicity intervals of chemical substances to fish, based on information on fish embryo toxicity (FET) in combination with other information. This model can support the use of FET data in a Weight-of-Evidence (WOE) approach for replacing the use of juvenile fish. The BN predicted correct toxicity intervals for 69%-80% of the tested substances. The model was most sensitive to components quantified by toxicity data, and least sensitive to components quantified by expert knowledge. The model is publicly available through a web interface. Further development of this model should include additional lines of evidence, refinement of the discretisation, and training with a larger dataset for weighting of the lines of evidence. A refined version of this model can be a useful tool for predicting acute fish toxicity, and a contribution to more quantitative WOE approaches for ecotoxicology and environmental assessment more generally.HighlightsA Bayesian network (BN) was developed to predict the toxicity of chemicals to fishThe BN uses fish embryo toxicity data in a quantitative weight-of-evidence approachThe BN integrates physical, chemical and toxicological properties of chemicalsCorrect toxicity intervals were predicted for 69-80% of test casesThe BN is publicly available for demonstration and testing through a web interface

scholarly journals Mixed phylogenetic signal in fish toxicity data across chemical classes

2018 ◽  
Vol 28 (3) ◽  
pp. 605-611 ◽  
Author(s):  
Andrew Hylton ◽  
Ylenia Chiari ◽  
Isabella Capellini ◽  
Mace G. Barron ◽  
Scott Glaberman
Keyword(s):  
Phylogenetic Signal ◽  
Toxicity Data ◽  
Fish Toxicity

Nature and Origin of Micropollutants

1982 ◽  
Vol 14 (12) ◽  
pp. 5-14 ◽  
Author(s):  
D Mackay
Keyword(s):  
Adverse Effects ◽  
Toxicity Data ◽  
Low Level ◽  
Environmental Models ◽  
Toxic Event ◽  
And Control

The origins of “micropollutants” are discussed and classified. It is suggested that assessing the risk and ensuring an acceptably low level of adverse effects from these substances requires information or control of three factors (exposure, toxicity and characteristics of the victim or organism) which combine to generate the toxic event. Methods of estimating exposure are discussed, especially environmental models. Ultimately, it should be possible to couple these models to toxicity data in a rational, rigorous manner to elucidate the extent of risk and control it to acceptable levels.

Marine Quality Standards: Their Derivation and Application in the United Kingdom

1985 ◽  
Vol 17 (6-7) ◽  
pp. 1187-1198 ◽  
Author(s):  
G. Mance ◽  
A. R. O'Donnell
Keyword(s):  
Coastal Waters ◽  
Sublethal Effects ◽  
Quality Standards ◽  
Toxicity Data ◽  
Marine Life ◽  
Nickel Zinc ◽  
The United Kingdom ◽  
The Common ◽  
Lead Nickel ◽  
The Impact

This paper discusses the derivation of environmental quality standards for coastal waters and the difficulties of using such standards for controlling industrial discharges. Attention is focused on the common List II substances, copper, chromium, lead, nickel, zinc and arsenic - and their effects on marine life. The adequacy of existing toxicity data is discussed and it is concluded that long exposure tests are required to provide information on sublethal effects. Such data are currently limited. It is also important that consideration be given to the effects that reducing salinities and increasing temperatures have in increasing the toxicity of these substances. The complexity of interpreting the results of laboratory toxicity data to coastal waters is discussed with reference to a study of the impact of an industrial discharge.

A New Approach for the Analysis of Mixture Toxicity Data

1992 ◽  
Vol 26 (9-11) ◽  
pp. 2345-2348 ◽  
Author(s):  
C. N. Haas
Keyword(s):  
Quantitative Analysis ◽  
Mixture Toxicity ◽  
New Method ◽  
Metal Exposure ◽  
Positive Interactions ◽  
Toxicity Data ◽  
Data Set ◽  
New Approach ◽  
Negative Interactions

A new method for the quantitative analysis of multiple toxicity data is described and illustrated using a data set on metal exposure to copepods. Positive interactions are observed for Ni-Pb and Pb-Cr, with weak negative interactions observed for Ni-Cr.

Sign in / Sign up

Export Citation Format

Share Document