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Coping with uncertainty in ecological advice: lessons from fisheries

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Coping with uncertainty in ecological advice: lessons from fisheries. / Harwood, John; Stokes, K.

In: Trends in Ecology and Evolution, Vol. 18, No. 12, 12.2003, p. 617-622.

Research output: Contribution to journalArticle

Harvard

Harwood, J & Stokes, K 2003, 'Coping with uncertainty in ecological advice: lessons from fisheries', Trends in Ecology and Evolution, vol. 18, no. 12, pp. 617-622. https://doi.org/10.1016/j.tree.2003.08.001

APA

Harwood, J., & Stokes, K. (2003). Coping with uncertainty in ecological advice: lessons from fisheries. Trends in Ecology and Evolution, 18(12), 617-622. https://doi.org/10.1016/j.tree.2003.08.001

Vancouver

Harwood J, Stokes K. Coping with uncertainty in ecological advice: lessons from fisheries. Trends in Ecology and Evolution. 2003 Dec;18(12):617-622. https://doi.org/10.1016/j.tree.2003.08.001

Author

Harwood, John ; Stokes, K. / Coping with uncertainty in ecological advice: lessons from fisheries. In: Trends in Ecology and Evolution. 2003 ; Vol. 18, No. 12. pp. 617-622.

Bibtex - Download

@article{e371ac3b284448329ab905a2673d5456,
title = "Coping with uncertainty in ecological advice: lessons from fisheries",
abstract = "All ecologists are familiar with uncertainty, at least at the level of whether they should reject a null hypothesis. Uncertainty is, however, pervasive and its characterization is essential if we are to understand our effects on ecosystems. Traditional fisheries management has a poor track record for confronting uncertainty, but most management authorities are now committed to a precautionary approach. As a result, some of the most interesting methods for taking account of uncertainty in ecological systems have been developed by fisheries scientists. These methods evaluate the relative performance of different management procedures with the use of mathematical and statistical models that synthesize knowledge and speculation about the system of interest. Recent advances in computer-intensive statistics have made it possible to combine this approach with model fitting,. so that the uncertainties and risks associated with different outcomes of management can be quantified. We show how this methodology can be applied to a range of ecological problems where the advice that scientists provide to decision makers is likely to be clouded by uncertainty.",
keywords = "CONSERVATION BIOLOGY, BAYESIAN-APPROACH, DECISION-ANALYSIS, RISK-ASSESSMENT, MANAGEMENT, MODELS, POLICY, POPULATION, PATTERN, STOCK",
author = "John Harwood and K Stokes",
note = "This paper appeared in the {"}Opinion{"} section of the journal and is as much a mission statement for my research group as a review.",
year = "2003",
month = "12",
doi = "10.1016/j.tree.2003.08.001",
language = "English",
volume = "18",
pages = "617--622",
journal = "Trends in Ecology and Evolution",
issn = "0169-5347",
publisher = "ELSEVIER SCIENCE LONDON",
number = "12",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Coping with uncertainty in ecological advice: lessons from fisheries

AU - Harwood, John

AU - Stokes, K

N1 - This paper appeared in the "Opinion" section of the journal and is as much a mission statement for my research group as a review.

PY - 2003/12

Y1 - 2003/12

N2 - All ecologists are familiar with uncertainty, at least at the level of whether they should reject a null hypothesis. Uncertainty is, however, pervasive and its characterization is essential if we are to understand our effects on ecosystems. Traditional fisheries management has a poor track record for confronting uncertainty, but most management authorities are now committed to a precautionary approach. As a result, some of the most interesting methods for taking account of uncertainty in ecological systems have been developed by fisheries scientists. These methods evaluate the relative performance of different management procedures with the use of mathematical and statistical models that synthesize knowledge and speculation about the system of interest. Recent advances in computer-intensive statistics have made it possible to combine this approach with model fitting,. so that the uncertainties and risks associated with different outcomes of management can be quantified. We show how this methodology can be applied to a range of ecological problems where the advice that scientists provide to decision makers is likely to be clouded by uncertainty.

AB - All ecologists are familiar with uncertainty, at least at the level of whether they should reject a null hypothesis. Uncertainty is, however, pervasive and its characterization is essential if we are to understand our effects on ecosystems. Traditional fisheries management has a poor track record for confronting uncertainty, but most management authorities are now committed to a precautionary approach. As a result, some of the most interesting methods for taking account of uncertainty in ecological systems have been developed by fisheries scientists. These methods evaluate the relative performance of different management procedures with the use of mathematical and statistical models that synthesize knowledge and speculation about the system of interest. Recent advances in computer-intensive statistics have made it possible to combine this approach with model fitting,. so that the uncertainties and risks associated with different outcomes of management can be quantified. We show how this methodology can be applied to a range of ecological problems where the advice that scientists provide to decision makers is likely to be clouded by uncertainty.

KW - CONSERVATION BIOLOGY

KW - BAYESIAN-APPROACH

KW - DECISION-ANALYSIS

KW - RISK-ASSESSMENT

KW - MANAGEMENT

KW - MODELS

KW - POLICY

KW - POPULATION

KW - PATTERN

KW - STOCK

UR - http://www.scopus.com/inward/record.url?scp=0242661860&partnerID=8YFLogxK

U2 - 10.1016/j.tree.2003.08.001

DO - 10.1016/j.tree.2003.08.001

M3 - Article

VL - 18

SP - 617

EP - 622

JO - Trends in Ecology and Evolution

JF - Trends in Ecology and Evolution

SN - 0169-5347

IS - 12

ER -

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