000906182 001__ 906182
000906182 005__ 20230522125349.0
000906182 0247_ $$2doi$$a10.1016/j.eja.2022.126464
000906182 0247_ $$2ISSN$$a1161-0301
000906182 0247_ $$2ISSN$$a1873-7331
000906182 0247_ $$2Handle$$a2128/30684
000906182 0247_ $$2altmetric$$aaltmetric:122161285
000906182 0247_ $$2WOS$$aWOS:000784446200004
000906182 037__ $$aFZJ-2022-01281
000906182 082__ $$a640
000906182 1001_ $$0P:(DE-HGF)0$$aKamali, Bahareh$$b0$$eCorresponding author
000906182 245__ $$aImproving the simulation of permanent grasslands across Germany by using multi-objective uncertainty-based calibration of plant-water dynamics
000906182 260__ $$aAmsterdam [u.a.]$$bElsevier Science$$c2022
000906182 3367_ $$2DRIVER$$aarticle
000906182 3367_ $$2DataCite$$aOutput Types/Journal article
000906182 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1644592452_7250
000906182 3367_ $$2BibTeX$$aARTICLE
000906182 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000906182 3367_ $$00$$2EndNote$$aJournal Article
000906182 520__ $$aThe dynamics of grassland ecosystems are highly complex due to multifaceted interactions among their soil, water, and vegetation components. Precise simulations of grassland productivity therefore rely on accurately estimating a variety of parameters that characterize different processes of these systems. This study applied three calibration schemes – a Single-Objective (SO-SUFI2), a Multi-Objective Pareto (MO-Pareto), and, a novel Uncertainty-Based Multi-Objective (MO-SUFI2) – to estimate the parameters of MONICA (Model for Nitrogen and Carbon Simulation) agro-ecosystem model in grassland ecosystems across Germany. The MO-Pareto model is based on a traditional Pareto optimality concept, while the MO-SUFI2 optimizes multiple target variables considering their level of prediction uncertainty. We used measurements of leaf area index, aboveground biomass, and soil moisture from experimental data at five sites with different intensities of cutting regimes (from two to five cutting events per season) to evaluate model performance. Both MO-Pareto and MO-SUFI2 outperformed SO-SUFI2 during calibration and validation. The comparison of the two MO approaches shows that they do not necessarily conflict with each other, but MO-SUFI2 provides complementary information for better estimations of model parameter uncertainty. We used the obtained parameter ranges to simulate grassland productivity across Germany under different cutting regimes and quantified the uncertainty associated with estimated productivity across regions. The results showed higher uncertainty in intensively managed grasslands compared to extensively managed grasslands, partially due to a lack of high-resolution input information concerning cutting dates. Furthermore, the additional information on the quantified uncertainty provided by our proposed MO-SUFI2 method adds deeper insights on confidence levels of estimated productivity. Benefiting from additional management data collected at high resolution and ground measurements on the composition of grassland species mixtures appear to be promising solutions to reduce uncertainty and increase model reliability.
000906182 536__ $$0G:(DE-HGF)POF4-2173$$a2173 - Agro-biogeosystems: controls, feedbacks and impact (POF4-217)$$cPOF4-217$$fPOF IV$$x0
000906182 588__ $$aDataset connected to CrossRef, Journals: juser.fz-juelich.de
000906182 7001_ $$0P:(DE-HGF)0$$aStella, Tommaso$$b1
000906182 7001_ $$0P:(DE-HGF)0$$aBerg-Mohnicke, Michael$$b2
000906182 7001_ $$0P:(DE-HGF)0$$aPickert, Jürgen$$b3
000906182 7001_ $$0P:(DE-Juel1)158034$$aGroh, Jannis$$b4$$ufzj
000906182 7001_ $$0P:(DE-HGF)0$$aNendel, Claas$$b5
000906182 773__ $$0PERI:(DE-600)2016158-X$$a10.1016/j.eja.2022.126464$$gVol. 134, p. 126464 -$$p126464$$tEuropean journal of agronomy$$v134$$x1161-0301$$y2022
000906182 8564_ $$uhttps://juser.fz-juelich.de/record/906182/files/EURAGR9929_R3g.pdf$$yOpenAccess
000906182 909CO $$ooai:juser.fz-juelich.de:906182$$pdnbdelivery$$pdriver$$pVDB$$popen_access$$popenaire
000906182 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)158034$$aForschungszentrum Jülich$$b4$$kFZJ
000906182 9131_ $$0G:(DE-HGF)POF4-217$$1G:(DE-HGF)POF4-210$$2G:(DE-HGF)POF4-200$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-2173$$aDE-HGF$$bForschungsbereich Erde und Umwelt$$lErde im Wandel – Unsere Zukunft nachhaltig gestalten$$vFür eine nachhaltige Bio-Ökonomie – von Ressourcen zu Produkten$$x0
000906182 9141_ $$y2022
000906182 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2021-02-04
000906182 915__ $$0StatID:(DE-HGF)1190$$2StatID$$aDBCoverage$$bBiological Abstracts$$d2021-02-04
000906182 915__ $$0LIC:(DE-HGF)CCBYNCND4$$2HGFVOC$$aCreative Commons Attribution-NonCommercial-NoDerivs CC BY-NC-ND 4.0
000906182 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2021-02-04
000906182 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
000906182 915__ $$0StatID:(DE-HGF)0420$$2StatID$$aNationallizenz$$d2022-11-16$$wger
000906182 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2022-11-16
000906182 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2022-11-16
000906182 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2022-11-16
000906182 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews$$d2022-11-16
000906182 915__ $$0StatID:(DE-HGF)1060$$2StatID$$aDBCoverage$$bCurrent Contents - Agriculture, Biology and Environmental Sciences$$d2022-11-16
000906182 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bEUR J AGRON : 2021$$d2022-11-16
000906182 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2022-11-16
000906182 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2022-11-16
000906182 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2022-11-16
000906182 915__ $$0StatID:(DE-HGF)9905$$2StatID$$aIF >= 5$$bEUR J AGRON : 2021$$d2022-11-16
000906182 920__ $$lyes
000906182 9201_ $$0I:(DE-Juel1)IBG-3-20101118$$kIBG-3$$lAgrosphäre$$x0
000906182 980__ $$ajournal
000906182 980__ $$aVDB
000906182 980__ $$aUNRESTRICTED
000906182 980__ $$aI:(DE-Juel1)IBG-3-20101118
000906182 9801_ $$aFullTexts