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dc.contributor.authorKotamäki, Niina
dc.contributor.authorArhonditsis, George
dc.contributor.authorHjerppe, Turo
dc.contributor.authorHyytiäinen, Kari
dc.contributor.authorMalve, Olli
dc.contributor.authorOvaskainen, Otso
dc.contributor.authorPaloniitty, Tiina
dc.contributor.authorSimilä, Jukka
dc.contributor.authorSoininen, Niko
dc.contributor.authorWeigel, Benjamin
dc.contributor.authorHeiskanen, Anna-Stiina
dc.date.accessioned2024-06-05T11:14:32Z
dc.date.available2024-06-05T11:14:32Z
dc.date.issued2024
dc.identifier.citationKotamäki, N., Arhonditsis, G., Hjerppe, T., Hyytiäinen, K., Malve, O., Ovaskainen, O., Paloniitty, T., Similä, J., Soininen, N., Weigel, B., & Heiskanen, A.-S. (2024). Strategies for integrating scientific evidence in water policy and law in the face of uncertainty. <i>Science of the Total Environment</i>, <i>931</i>, Article 172855. <a href="https://doi.org/10.1016/j.scitotenv.2024.172855" target="_blank">https://doi.org/10.1016/j.scitotenv.2024.172855</a>
dc.identifier.otherCONVID_213450380
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/95543
dc.description.abstractUnderstanding how human actions and environmental change affect water resources is crucial for addressing complex water management issues. The scientific tools that can produce the necessary information are ecological indicators, referring to measurable properties of the ecosystem state; environmental monitoring, the data collection process that is required to evaluate the progress towards reaching water management goals; mathematical models, linking human disturbances with the ecosystem state to predict environmental impacts; and scenarios, assisting in long-term management and policy implementation. Paradoxically, despite the rapid generation of data, evolving scientific understanding, and recent advancements in systems modeling, there is a striking imbalance between knowledge production and knowledge utilization in decision-making. In this paper, we examine the role and potential capacity of scientific tools in guiding governmental decision-making processes and identify the most critical disparities between water management, policy, law, and science. We demonstrate how the complex, uncertain, and gradually evolving nature of scientific knowledge might not always fit aptly to the legislative and policy processes and structures. We contend that the solution towards increased understanding of socio-ecological systems and reduced uncertainty lies in strengthening the connections between water management theory and practice, among the scientific tools themselves, among different stakeholders, and among the social, economic, and ecological facets of water quality management, law, and policy. We conclude by tying in three knowledge-exchange strategies, namely - adaptive management, Driver-Pressure-Status-Impact-Response (DPSIR) framework, and participatory modeling - that offer complementary perspectives to bridge the gap between science and policy.en
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherElsevier
dc.relation.ispartofseriesScience of the Total Environment
dc.rightsCC BY 4.0
dc.titleStrategies for integrating scientific evidence in water policy and law in the face of uncertainty
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-202406054302
dc.contributor.laitosBio- ja ympäristötieteiden laitosfi
dc.contributor.laitosDepartment of Biological and Environmental Scienceen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.type.coarhttp://purl.org/coar/resource_type/c_dcae04bc
dc.description.reviewstatuspeerReviewed
dc.relation.issn0048-9697
dc.relation.volume931
dc.type.versionpublishedVersion
dc.rights.copyright© 2024 The Authors. Published by Elsevier B.V.
dc.rights.accesslevelopenAccessfi
dc.relation.grantnumber856506
dc.relation.grantnumber856506
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/856506/EU//LIFEPLAN
dc.subject.ysoympäristövaikutukset
dc.subject.ysovesivarat
dc.subject.ysotieteellinen tieto
dc.subject.ysovesihuolto
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p9862
jyx.subject.urihttp://www.yso.fi/onto/yso/p16771
jyx.subject.urihttp://www.yso.fi/onto/yso/p7837
jyx.subject.urihttp://www.yso.fi/onto/yso/p9681
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/
dc.relation.doi10.1016/j.scitotenv.2024.172855
dc.relation.funderEuropean Commissionen
dc.relation.funderEuroopan komissiofi
jyx.fundingprogramERC European Research Council, H2020en
jyx.fundingprogramERC European Research Council, H2020fi
jyx.fundinginformationThis work was funded by the Strategic Research Council of Academy of Finland (Contract No. 312650 BlueAdapt). OO was supported by the Academy of Finland grant 309581 and the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program; grant agreement No 856506; ERC -synergy project LIFEPLAN.
dc.type.okmA2


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