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Development and application of the SSD approach in scientific case studies for ecological risk assessment
Author(s) -
Del Signore Anastasia,
Hendriks A. Jan,
Lenders H.J. Rob,
Leuven Rob S.E.W.,
Breure A.M.
Publication year - 2016
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.3474
Subject(s) - construct (python library) , percentile , hazard , risk assessment , computer science , toxicology , environmental science , statistics , ecology , biology , mathematics , computer security , programming language
Species sensitivity distributions (SSDs) are used in ecological risk assessment for extrapolation of the results of toxicity tests with single species to a toxicity threshold considered protective of ecosystem structure and functioning. The attention to and importance of the SSD approach has increased in scientific and regulatory communities since the 1990s. Discussion and criticism have been triggered on the concept of the approach as well as its technical aspects (e.g., distribution type, number of toxicity endpoints). Various questions remain unanswered, especially with regard to different endpoints, statistical methods, and protectiveness of threshold levels, for example. In the present literature review (covering the period 2002–2013), case studies are explored in which the SSD approach was applied, as well as how endpoint types, species choice, and data availability affect SSDs. How statistical methods may be used to construct reliable SSDs and whether the lower 5th percentile hazard concentrations (HC5s) from a generic SSD can be protective for a specific local community are also investigated. It is shown that estimated protective concentrations were determined by taxonomic groups rather than the statistical method used to construct the distribution. Based on comparisons between semifield and laboratory‐based SSDs, the output from a laboratory SSD was protective of semifield communities in the majority of studies. Environ Toxicol Chem 2016;35:2149–2161. © 2016 SETAC