Accounting for uncertainty factors in biodiversity impact assessment: lessons from a case study

For an Environmental Impact Statement (EIS) to effectively contribute to decision-making, it must include one crucial step: the estimation of the uncertainty factors affecting the impact evaluation and of their effect on the evaluation results. Knowledge of the uncertainties better orients the strat...

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Bibliographic Details
Published in:Environmental impact assessment review 2003-07, Vol.23 (4), p.471-487
Main Authors: Geneletti, D., Beinat, E., Chung, C.F., Fabbri, A.G., Scholten, H.J.
Format: Article
Language:English
Subjects:
Biodiversity
Case studies
DECISION MAKING
Ecosystem
ECOSYSTEMS
Environment
ENVIRONMENTAL IMPACT STATEMENTS
Environmental impact studies
ENVIRONMENTAL SCIENCES
EVALUATION
Impact
Road construction
SENSITIVITY
SPECIES DIVERSITY
Uncertainty
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Summary:For an Environmental Impact Statement (EIS) to effectively contribute to decision-making, it must include one crucial step: the estimation of the uncertainty factors affecting the impact evaluation and of their effect on the evaluation results. Knowledge of the uncertainties better orients the strategy of the decision-makers and underlines the most critical data or methodological steps of the procedure. Accounting for uncertainty factors is particularly relevant when dealing with ecological impacts, whose forecasts are typically affected by a high degree of simplification. By means of a case study dealing with the evaluation of road alternatives, this paper explores and discusses the main uncertainties that are related to the typical stages of a biodiversity impact assessment: uncertainty in the data that are used, in the methodologies that are applied, and in the value judgments provided by the experts. Subsequently, the effects of such uncertainty factors are tracked back to the result of the evaluation, i.e., to the relative performance of the project alternatives under consideration. This allows to test the sensitivity of the results, and consequently to provide a more informative ranking of the alternatives. The papers concludes by discussing the added-value for decision-making provided by uncertainty analysis within EIA.
ISSN:0195-9255
1873-6432
DOI:10.1016/S0195-9255(03)00045-3