Näytä suppeat kuvailutiedot

dc.contributor.authorKoski, Vilja
dc.contributor.authorKotamäki, Niina
dc.contributor.authorHämäläinen, Heikki
dc.contributor.authorMeissner, Kristian
dc.contributor.authorKarvanen, Juha
dc.contributor.authorKärkkäinen, Salme
dc.date.accessioned2020-05-05T07:17:00Z
dc.date.available2020-05-05T07:17:00Z
dc.date.issued2020
dc.identifier.citationKoski, V., Kotamäki, N., Hämäläinen, H., Meissner, K., Karvanen, J., & Kärkkäinen, S. (2020). The value of perfect and imperfect information in lake monitoring and management. <i>Science of the Total Environment</i>, <i>726</i>, Article 138396. <a href="https://doi.org/10.1016/j.scitotenv.2020.138396" target="_blank">https://doi.org/10.1016/j.scitotenv.2020.138396</a>
dc.identifier.otherCONVID_35193243
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/68827
dc.description.abstractUncertainty 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.en
dc.format.mimetypeapplication/pdf
dc.languageeng
dc.language.isoeng
dc.publisherElsevier
dc.relation.ispartofseriesScience of the Total Environment
dc.rightsCC BY 4.0
dc.subject.otherdecision making
dc.subject.otherenvironmental management
dc.subject.otherimperfect information
dc.subject.otherlakes
dc.subject.otherperfect information
dc.subject.othervalue of information
dc.titleThe value of perfect and imperfect information in lake monitoring and management
dc.typeresearch article
dc.identifier.urnURN:NBN:fi:jyu-202005053041
dc.contributor.laitosMatematiikan ja tilastotieteen laitosfi
dc.contributor.laitosBio- ja ympäristötieteiden laitosfi
dc.contributor.laitosDepartment of Mathematics and Statisticsen
dc.contributor.laitosDepartment of Biological and Environmental Scienceen
dc.contributor.oppiaineTilastotiedefi
dc.contributor.oppiaineAkvaattiset tieteetfi
dc.contributor.oppiaineStatisticsen
dc.contributor.oppiaineAquatic Sciencesen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.relation.issn0048-9697
dc.relation.volume726
dc.type.versionacceptedVersion
dc.rights.copyright© 2020 the Author(s)
dc.rights.accesslevelopenAccessfi
dc.type.publicationarticle
dc.relation.grantnumber289076
dc.relation.grantnumber311877
dc.subject.ysopäätöksenteko
dc.subject.ysojärvet
dc.subject.ysoympäristönhoito
dc.subject.ysoympäristövalvonta
dc.subject.ysoinformaatio
dc.subject.ysotilastolliset mallit
dc.subject.ysomonitorointi
dc.subject.ysovesien tila
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p8743
jyx.subject.urihttp://www.yso.fi/onto/yso/p9374
jyx.subject.urihttp://www.yso.fi/onto/yso/p3162
jyx.subject.urihttp://www.yso.fi/onto/yso/p12002
jyx.subject.urihttp://www.yso.fi/onto/yso/p14428
jyx.subject.urihttp://www.yso.fi/onto/yso/p26278
jyx.subject.urihttp://www.yso.fi/onto/yso/p3628
jyx.subject.urihttp://www.yso.fi/onto/yso/p37934
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/
dc.relation.doi10.1016/j.scitotenv.2020.138396
dc.relation.funderResearch Council of Finlanden
dc.relation.funderResearch Council of Finlanden
dc.relation.funderSuomen Akatemiafi
dc.relation.funderSuomen Akatemiafi
jyx.fundingprogramAcademy Project, AoFen
jyx.fundingprogramResearch profiles, AoFen
jyx.fundingprogramAkatemiahanke, SAfi
jyx.fundingprogramProfilointi, SAfi
jyx.fundinginformationVilja 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).
dc.type.okmA1


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