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Cited by 498

The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.

Risks and Decisions for Conservation and Environmental Management

Burgman, Mark·2005·Cambridge University Press eBooks

Abstract

This book outlines how to conduct a complete environmental risk assessment. The first part documents the psychology and philosophy of risk perception and assessment, introducing a taxonomy of uncertainty and the importance of context. It provides a critical examination of the use and abuse of expert judgement and goes on to outline approaches to hazard identification and subjective ranking that account for uncertainty and context. The second part of the book describes technical tools that can assist risk assessments to be transparent and internally consistent. These include interval arithmetic, ecotoxicological methods, logic trees and Monte Carlo simulation. These methods have an established place in risk assessments in many disciplines and their strengths and weaknesses are explored. The last part of the book outlines some new approaches, including p-bounds and information-gap theory, and describes how quantitative and subjective assessments can be used to make transparent decisions.

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Metadata

Authors
Burgman, M.
Venue
Cambridge University Press eBooks
Published
2005-04-07
OpenAlex
W4298180043
Cited by
498
References
13
FWCI
9.89
Type
book
Language
en
Open access
closed

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CoChat. (2026). Citation check: Risks and Decisions for Conservation and Environmental Management. https://app.cochat.ai/papers/10.1017/cbo9780511614279
The paper
Burgman, M. (2005). Risks and Decisions for Conservation and Environmental Management. Cambridge University Press eBooks. https://doi.org/10.1017/cbo9780511614279

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.