Research Document - 2002/125
Role of Modelling in Ecological Risk Assessment and Management with Emphasis on the Offshore Oil and Gas Industry.
By Cretney, W., Sinclair, A., Wright C., and Burd, B.
Abstract
Mathematical models have become indispensable tools in Ecological Risk Assessment (ERA) and Ecological Risk Management (ERM). The human mind cannot deal with the multifold of interactions that can be encompassed by models. Modern environmental management must be based on the quantitative forecasts of models. That said, models do not capture reality. At best, they only capture the essence of reality, an essence that must be specified in the model. Furthermore, the gap between reality and models ensures that a variety of competing models may be available. Misunderstanding, misapplication, incorrect structural forms of modelled processes, and erroneous parameter estimates can lead to misrepresentation of reality in models and consequent mistakes in assessment and management. Hence, models must be tested against reality and used by those that have expertise in the reality being modelled. In addition, a range of available models and parameter values should be evaluated to probe the gap between models and reality.
ERA has been defined (Suter, 1993) as "the process of assigning magnitudes and probabilities to the adverse effects of human activities or natural catastrophes." ERM has been defined (Pittinger et al., 1998) as "the process of identifying, evaluating, selecting, and implementing cost-effective, integrated actions that manage risks to environmental systems while emphasising scientific, social, economic, cultural, technological feasibility, political, and legal considerations." ERA is the realm of the science-grounded assessor who seeks to provide objective assessments of risk, whereas ERM is the realm of the informed manager who seeks to provide balanced decisions in reducing risk. The risk assessor must know why the assessment is being done and the decisions that have to be made in order to provide answers useful to the risk manager. On the other hand the risk assessor must be free of management pressure to give predestined results.
Several paradigm shifts are looming that may greatly complicate ERA and ERM over the next decade, which may be the period leading up to the establishment of an oil and gas industry of the B.C. coast. A shift is occurring in chemical toxicology from estimating the probability of effects based on exposure medium to that based on body residue. This shift is driven to some extent by the inherent toxicity concept that holds that noncarcinogenic modes of toxicity seem to be associated with different body residue ranges of chemical toxicants within organisms. This shift also divorces uptake processes from toxic effect by moving a step closer to the site of action, i.e., from the medium (e.g., water, sediment) to the body. Another paradigm shift, also in toxicology, is driven by the re-ascendancy from the late 19th and early 20th centuries of hormesis, which is challenging the orthodoxy of the linear, non-threshold dose-response model in ERA. Hormesis, which must be distinguished from homeopathy, is a well-documented phenomenon in which low doses of a toxicant confer a benefit to an organism. Also returning from relative obscurity for most of the 20th century is Bayesian statistics. Bayesian statistics estimates the probability that a hypothesis is true, given the evidence. In the case of ERM, Bayesian statistics provides useful information about the degree of belief in different hypotheses that allows decision-makers to choose among competing outcomes. Frequentist statistics, which have held sway for the about seven decades, cannot provide such easy to understand output. Instead, these statistics are limited to probability of obtaining the evidence, given that the null hypothesis is true.
Decision analysis is a process for helping make complex decisions. The basic tool of the decision analysis process is the decision tree, which allows a complex problem to be decomposed into its component parts and recomposed in a coherent and consistent manner. Decision analysis like ERA is a service to the decision-maker.
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