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Books > Science & Mathematics > Biology, life sciences > Biochemistry
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Application of Uncertainty Analysis to Ecological Risks of Pesticides (Paperback)
Loot Price: R2,428
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Application of Uncertainty Analysis to Ecological Risks of Pesticides (Paperback)
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While 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 their
appropriateness for general use. The book presents specific methods
leading to probabilistic decisions concerning the registration and
application of pesticides and includes case studies illustrating
the application of statistical methods. The authors discuss
Bayesian inference, first-order error analysis, first-order
(non-hierarchical) Monte Carlo methods, second-order Bayesian and
Monte Carlo methods, interval analysis, and probability bounds
analysis. They then examine how these methods can be used in
assessments for other environmental stressors and contaminants.
There are many methods of analyzing variability and uncertainty and
many ways of presenting the results. Inappropriate use of these
methods leads to misleading results, and experts differ on what is
appropriate. Disagreement about which methods are appropriate will
result in wasted resources, conflict over findings, and reduced
credibility with decision makers and the public. There is,
therefore, a need to reach a consensus on how to choose and use
appropriate methods, and to present this in the form of guidance
for prospective users. Written in a clear and concise style, the
book examines how to use probabilistic methods within a risk-based
decision paradigm.
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