When do we need more data? A primer on calculating the value of information for applied ecologists

被引:158
作者
Canessa, Stefano [1 ,2 ]
Guillera-Arroita, Gurutzeta [2 ]
Lahoz-Monfort, Jose J. [2 ]
Southwell, Darren M. [2 ]
Armstrong, Doug P. [3 ]
Chades, Iadine [4 ]
Lacy, Robert C. [5 ]
Converse, Sarah J. [6 ]
机构
[1] Zool Soc London, Inst Zool, London NW1 4RY, England
[2] Univ Melbourne, Sch Biosci, Parkville, Vic 3010, Australia
[3] Massey Univ, Inst Nat Resources, Palmerston North 4442, New Zealand
[4] CSIRO Land & Water, Dutton Pk, Qld 4102, Australia
[5] Chicago Zool Soc, Brookfield, IL 60513 USA
[6] US Geol Survey, Patuxent Wildlife Res Ctr, Laurel, MD 20708 USA
来源
METHODS IN ECOLOGY AND EVOLUTION | 2015年 / 6卷 / 10期
关键词
adaptive management; Bayesian pre-posterior analysis; chytridiomycosis; conservation; decision analysis; experimental management; monitoring; CHYTRIDIOMYCOSIS; SURVIVAL;
D O I
10.1111/2041-210X.12423
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Applied ecologists continually advocate further research, under the assumption that obtaining more information will lead to better decisions. Value of information (VoI) analysis can be used to quantify how additional information may improve management outcomes: despite its potential, this method is still underused in environmental decision-making. We provide a primer on how to calculate the VoI and assess whether reducing uncertainty will change a decision. Our aim is to facilitate the application of VoI by managers who are not familiar with decision-analytic principles and notation, by increasing the technical accessibility of the tool. Calculating the VoI requires explicit formulation of management objectives and actions. Uncertainty must be clearly structured and its effects on management outcomes evaluated. We present two measures of the VoI. The expected value of perfect information is a calculation of the expected improvement in management outcomes that would result from access to perfect knowledge. The expected value of sample information calculates the improvement in outcomes expected by collecting a given sample of new data. We guide readers through the calculation of VoI using two case studies: (i) testing for disease when managing a frog species and (ii) learning about demographic rates for the reintroduction of an endangered turtle. We illustrate the use of Bayesian updating to incorporate new information. The VoI depends on our current knowledge, the quality of the information collected and the expected outcomes of the available management actions. Collecting information can require significant investments of resources; VoI analysis assists managers in deciding whether these investments are justified.
引用
收藏
页码:1219 / 1228
页数:10
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