Minimizing the cost Of environmental management decisions by optimizing statistical thresholds

Field, Scott A., Tyre, Andrew J., Jonzen, Niclas, Rhodes, Jonathan R. and Possingham, Hugh P. (2004) Minimizing the cost Of environmental management decisions by optimizing statistical thresholds. Ecology Letters, 7 8: 669-675. doi:10.1111/j.1461-0248.2004.00625.x

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Author Field, Scott A.
Tyre, Andrew J.
Jonzen, Niclas
Rhodes, Jonathan R.
Possingham, Hugh P.
Title Minimizing the cost Of environmental management decisions by optimizing statistical thresholds
Journal name Ecology Letters   Check publisher's open access policy
ISSN 1461-023X
Publication date 2004-08-01
Sub-type Article (original research)
DOI 10.1111/j.1461-0248.2004.00625.x
Open Access Status File (Author Post-print)
Volume 7
Issue 8
Start page 669
End page 675
Total pages 7
Place of publication Oxford, United Kingdom
Publisher Blackwell Publishing
Language eng
Subject 270708 Conservation and Biodiversity
230202 Stochastic Analysis and Modelling
230118 Optimisation
270700 Ecology and Evolution
230203 Statistical Theory
230200 Statistics
270706 Life Histories (incl. Population Ecology)
0602 Ecology
Abstract Environmental management decisions are prone to expensive mistakes if they are triggered by hypothesis tests using the conventional Type I error rate ( ) of 0.05. We derive optimal -levels for decision-making by minimizing a cost function that specifies the overall cost of monitoring and management. When managing an economically valuable koala population, it shows that a decision based on = 0.05 carries an expected cost over $5 million greater than the optimal decision. For a species of such value, there is never any benefit in guarding against the spurious detection of declines and therefore management should proceed directly to recovery action. This result holds in most circumstances where the species' value substantially exceeds its recovery costs. For species of lower economic value, we show that the conventional -level of 0.05 rarely approximates the optimal decision-making threshold. This analysis supports calls for reversing the statistical 'burden of proof' in environmental decision-making when the cost of Type II errors is relatively high.
Keyword Koala
Optimal monitoring
Statistical power
Statistical significance
Type I error
Type II error
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ
Additional Notes Originally published as Scott A. Field, Andrew J. Tyre, Niclas Jonzen, Jonathan R. Rhodes and Hugh P. Possingham (2004) Minimizing the cost of environmental management decisions by optimizing statistical thresholds, Ecology Letters 7 (8): 669-675. Copyright 2004 Blackwell Science. All rights reserved.

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Created: Thu, 06 Jan 2005, 10:00:00 EST by Hugh P. Possingham on behalf of Geographical Sciences & Planning