LEADER 03357oam 2200637I 450 001 9910784945303321 005 20230725023816.0 010 $a0-429-13064-3 010 $a1-138-11481-2 010 $a1-4398-0735-3 024 7 $a10.1201/EBK1439807347 035 $a(CKB)2670000000032193 035 $a(EBL)555719 035 $a(OCoLC)652654248 035 $a(SSID)ssj0000411986 035 $a(PQKBManifestationID)11268564 035 $a(PQKBTitleCode)TC0000411986 035 $a(PQKBWorkID)10365598 035 $a(PQKB)10280300 035 $a(MiAaPQ)EBC555719 035 $a(Au-PeEL)EBL555719 035 $a(CaPaEBR)ebr10400631 035 $a(CaONFJC)MIL693202 035 $a(EXLCZ)992670000000032193 100 $a20180331d2010 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aApplication of uncertainty analysis to ecological risk of pesticides /$feditors, William J. Warren-Hicks, Andy Hart 210 1$aBoca Raton :$cCRC Press,$d2010. 215 $a1 online resource (230 p.) 300 $aDescription based upon print version of record. 311 $a1-322-61920-4 311 $a1-4398-0734-5 320 $aIncludes bibliographical references and index. 327 $aFront cover; SETAC Publications; Contents; List of Figures; List of Tables; Foreword; Acknowledgments; About the Editors; Workshop Participants and Contributing Authors; Chapter 1. Introduction and Objectives; Chapter 2. Problem Formulation for Probabilistic Ecological Risk Assessments; Chapter 3. Issues Underlying the Selection of Distributions; Chapter 4. Monte Carlo, Bayesian Monte Carlo, and First-Order Error Analysis; Chapter 5. The Bayesian Vantage for Dealing with Uncertainty; Chapter 6. Bounding Uncertainty Analyses 327 $aChapter 7. Uncertainty Analysis Using Classical and Bayesian Hierarchical ModelsChapter 8. Interpreting and Communicating Risk and Uncertainty for Decision Making; Chapter 9. How to Detect and Avoid Pitfalls, Traps, and Swindles; Chapter 10. Conclusions; Glossary; Index; Back cover 330 $aWhile current methods used in ecological risk assessments for pesticides are largely deterministic, probabilistic methods that aim to quantify variability and uncertainty in exposure and effects are attracting growing interest from industries and governments. Probabilistic methods offer more realistic and meaningful estimates of risk and hence, potentially, a better basis for decision-making. Application of Uncertainty Analysis to Ecological Risks of Pesticides examines the applicability of probabilistic methods for ecological risk assessment for pesticides and explores the 606 $aPesticides$xEnvironmental aspects$xMathematical models 606 $aEcological risk assessment 606 $aProbabilities 615 0$aPesticides$xEnvironmental aspects$xMathematical models. 615 0$aEcological risk assessment. 615 0$aProbabilities. 676 $a577.27/9015118 701 $aWarren-Hicks$b William J$01520531 701 $aHart$b Andy$f1956-$01520532 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910784945303321 996 $aApplication of uncertainty analysis to ecological risk of pesticides$93759154 997 $aUNINA