Moe, S. J. | Search bioRxiv

bioRxiv2019

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

A 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.\n\nHighlightsO_LIA Bayesian network (BN) was developed to predict the toxicity of chemicals to fish\nC_LIO_LIThe BN uses fish embryo toxicity data in a quantitative weight-of-evidence approach\nC_LIO_LIThe BN integrates physical, chemical and toxicological properties of chemicals\nC_LIO_LICorrect toxicity intervals were predicted for 69-80% of test cases\nC_LIO_LIThe BN is publicly available for demonstration and testing through a web interface\nC_LI

pharmacology and toxicology↗

bioRxiv2019

A 50-year series of mark-recapture data of large-sized brown trout (Salmo trutta) from Lake Mjosa, Norway

BackgroundLong-term data from marked animals provide a wealth of opportunities for studies with high relevance to both basic ecological understanding and successful management in a changing world. The key strength of such data is that they allow to quantify individual variation in vital rates (e.g. survival, growth, reproduction) and then link it mechanistically to dynamics at the population level. However, maintaining the collection of individual-based data over long time periods comes with large logistic efforts and costs, and studies spanning over decades are therefore rare. This is the case particularly for migratory aquatic species, many of which are in decline despite their high ecological, cultural, and economical value. New informationThis paper describes two unique publicly available time series of individual-based data originating from a 51-year mark-recapture study of a land-locked population of large-sized migratory brown trout (Salmo trutta) in Norway: the Hunder trout. In the period 1966-2015, nearly 14,000 adult Hunder trout have been captured and individually marked during their spawning migration from Lake Mjosa to the river Gubrandsdalsl[a]gen. Almost a third of those individuals were later recaptured alive during a later spawning run and/or captured by fishermen and reported dead or alive. This has resulted in the first data series: a mark-recapture-recovery dataset spanning half a century and more than 18,000 capture records. The second data series consists of additional data on juvenile and adult growth and life-history schedules from half of the marked individuals, obtained by means of scale sample analysis. The two datasets offer a rare long-term perspective on individuals and population dynamics and provide unique opportunities to gain insights into questions surrounding management, conservation, and restoration of migratory salmonid populations and freshwater ecosystems.

ecology↗