The value of perfect and imperfect information in lake monitoring and management
Koski, V., Kotamäki, N., Hämäläinen, H., Meissner, K., Karvanen, J., & Kärkkäinen, S. (2020). The value of perfect and imperfect information in lake monitoring and management. Science of the Total Environment, 726, Article 138396. https://doi.org/10.1016/j.scitotenv.2020.138396
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Science of the Total EnvironmentAuthors
Date
2020Copyright
© 2020 the Author(s)
Uncertainty in the information obtained through monitoring complicates decision making about aquatic ecosystems management actions. We suggest the value of information (VOI) to assess the profitability of paying for additional monitoring information, when taking into account the costs and benefits of monitoring and management actions, as well as associated uncertainty. Estimating the monetary value of the ecosystem needed for deriving VOI is challenging. Therefore, instead of considering a single value, we evaluate the sensitivity of VOI to varying monetary value. We also extend the VOI analysis to the more realistic context where additional information does not result in perfect, but rather in imperfect information on the true state of the environment. Therefore, we analytically derive the value of perfect information in the case of two alternative decisions and two states of uncertainty. Second, we describe a Monte Carlo type of approach to evaluate the value of imperfect information about a continuous classification variable. Third, we determine confidence intervals for the VOI with a percentile bootstrap method. Results for our case study on 144 Finnish lakes suggest that generally, the value of monitoring exceeds the cost. It is particularly profitable to monitor lakes that meet the quality standards a priori, to ascertain that expensive and unnecessary management can be avoided. The VOI analysis provides a novel tool for lake and other environmental managers to estimate the value of additional monitoring data for a particular, single case, e.g. a lake, when an additional benefit is attainable through remedial management actions.
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https://converis.jyu.fi/converis/portal/detail/Publication/35193243
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Academy Project, AoF; Research profiles, AoFAdditional information about funding
Vilja Koski and Salme Kärkkäinen were supported by the Academy of Finland (grant number 289076). Kristian Meissner was supported by BONUS FUMARI: BONUS (art. 185), which is jointly funded by the EU, the Academy of Finland and Swedish Research Council Formas. Niina Kotamäki was supported by Strategic Research Council of Academy of Finland (Contract No. 312650 BlueAdapt). The work is related to the thematic research area “Decision analytics utilizing causal models and multiobjective optimization” (DEMO) of University of Jyväskylä supported by Academy of Finland (grant number 311877). ...License
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