Premium
Selection bias correction for species sensitivity distribution modeling and hazardous concentration estimation
Author(s) -
Fox David R.
Publication year - 2015
Publication title -
environmental toxicology and chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 171
eISSN - 1552-8618
pISSN - 0730-7268
DOI - 10.1002/etc.3098
Subject(s) - hazardous waste , sensitivity (control systems) , selection (genetic algorithm) , statistics , estimation , environmental science , confidence interval , ecotoxicology , econometrics , distribution (mathematics) , species distribution , ecology , biochemical engineering , computer science , biology , mathematics , engineering , habitat , machine learning , mathematical analysis , electronic engineering , systems engineering
The species sensitivity distribution (SSD) has been an important development in ecotoxicology, and despite numerous concerns having been raised over many years, it remains the preferred (and often mandated) technique for establishing “safe” concentrations of contaminants in receiving water bodies by jurisdictions around the world. Although universally recognized as a crucial prerequisite for the statistical validity of the procedure, the assumption of random selection of species for SSD modeling is invariably violated. It is shown in the present study that, under very minimal assumptions, nonrandom species selection can result in hazardous concentration estimation errors of a factor of 20 or more. Importantly, if the toxicity data are biased toward the more sensitive species, then the conventional practice of using the lower confidence interval limit for the estimated hazardous concentration may be compensating in the wrong direction. Environ Toxicol Chem 2015;34:2555–2563. © 2015 SETAC