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
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Prospect Theory: An Analysis of Decision under Risk
Kahneman, D., & Tversky, A. (1979) · Econometrica · doi:10.2307/1914185 · Cited by 48,524
Equation of State Calculations by Fast Computing Machines
Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., & Teller, E. (1953) · The Journal of Chemical Physics · doi:10.1063/1.1699114 · Cited by 37,192
The Framing of Decisions and the Psychology of Choice
Tversky, A., & Kahneman, D. (1981) · Science · doi:10.1126/science.7455683 · Cited by 18,497
Judgment under Uncertainty: Heuristics and Biases
(1982) · doi:10.1017/cbo9780511809477 · Cited by 8,240
Kahneman, D., & Tversky, A. (1984) · American Psychologist · doi:10.1037/0003-066x.39.4.341 · Cited by 6,544
The Stakeholder Theory of the Corporation: Concepts, Evidence, and Implications
Donaldson, T., & Preston, L. E. (1995) · The Academy of Management Review · doi:10.2307/258887 · Cited by 5,846
GPOWER: A general power analysis program
Erdfelder, E., Faul, F., & Buchner, A. (1996) · Behavior Research Methods, Instruments, & Computers · doi:10.3758/bf03203630 · Cited by 4,864
Belief in the law of small numbers.
Tversky, A., & Kahneman, D. (1971) · Psychological Bulletin · doi:10.1037/h0031322 · Cited by 3,246
Inference by Eye: Confidence Intervals and How to Read Pictures of Data.
Cumming, G., & Finch, S. (2005) · American Psychologist · doi:10.1037/0003-066x.60.2.170 · Cited by 1,449
Statistical data analysis in the computer age
Efron, B., & Tibshirani, R. (1991) · Science · doi:10.1126/science.253.5018.390 · Cited by 1,192
Cited by
A Guide to Understanding Social Science Research for Natural Scientists
MOON, K., & BLACKMAN, D. (2014) · Conservation Biology · doi:10.1111/cobi.12326 · Cited by 678
A guide to eliciting and using expert knowledge in Bayesian ecological models
Kuhnert, P. M., Martin, T. G., & Griffiths, S. P. (2010) · Ecology Letters · doi:10.1111/j.1461-0248.2010.01477.x · Cited by 441
Multidimensional evaluation of managed relocation
Richardson, D. M., Hellmann, J. J., McLachlan, J. S., Sax, D. F., Schwartz, M. W., Gonzalez, P., Brennan, E. J., Camacho, A., Root, T. L., Sala, O. E., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0902327106 · Cited by 382
Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars
Mayo, D. G. (2018) · doi:10.1017/9781107286184 · Cited by 376
Risk assessment for invasive species produces net bioeconomic benefits
Keller, R. P., Lodge, D. M., & Finnoff, D. C. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0605787104 · Cited by 369
Metadata
- Authors
- Burgman, M.
- Venue
- Cambridge University Press eBooks
- Publisher
- Cambridge University Press
- Published
- 2005-04-07
- OpenAlex
- W4298180043
- Cited by
- 498
- References
- 13
- FWCI
- 9.89
- Type
- book
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- 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.