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dc.contributor.authorDellar, M.
dc.contributor.authorTopp, C.
dc.contributor.authorPardo, G.
dc.contributor.authordel Prado, A.
dc.contributor.authorFitton, N.
dc.contributor.authorHolmes, D.
dc.contributor.authorBanos, G.
dc.contributor.authorWall, E.
dc.date.accessioned2020-06-23T09:44:43Z
dc.date.available2020-06-23T09:44:43Z
dc.date.issued2019
dc.identifier.citationEnvironmental Modelling and Software 122 : 104562 (2019)
dc.identifier.issn1364-8152
dc.identifier.urihttp://hdl.handle.net/10810/44147
dc.description.abstractWe applied two approaches to model grassland yield and nitrogen (N) content. The first was a series of regression equations; the second was the Century dynamic model. The regression model was generated from data from eighty-nine experimental sites across Europe, distinguishing between five climatic regions. The Century model was applied to six sites across these regions. Both approaches estimated mean grassland yields and N content reasonably well, though the root mean squared error tended to be lower for the dynamic model. The regression model achieved better correlations between observed and predicted values. Both models were more sensitive to uncertainties in weather than in soil properties, with precipitation often accounting for the majority of model uncertainty. The regression approach is applicable over large spatial scales but lacks precision, making it suitable for considering general trends. Century is better applied at a local level where more detailed and specific analysis is required. © 2019 The Authors
dc.description.sponsorshipThis work was supported by the Horizon 2020 SFS-01c-2015 project entitled “Innovation of sustainable sheep and goat production in Europe (iSAGE)” [grant number 679302 ]; and the Rural & Environment Science & Analytical Services Division of the Scottish Government . BC3 is supported by the Basque Government through the BERC 2018–2021 program and by Spanish Ministry of Economy and Competitiveness MINECO through BC3 María de Maeztu excellence accreditation MDM-2017-0714 . Agustin del Prado is supported by the Ramon y Cajal Programme .
dc.language.isoeng
dc.publisherElsevier
dc.relationinfo:eu-repo/grantAgreement/EC/H2020/679302
dc.relationinfo:eu-repo/grantAgreement/MINECO/RYC-2017-22143
dc.relationES/1PE/RYC-2017-22143
dc.relationEUS/BERC/BERC.2018-2021
dc.relationES/1PE/MDM-2017-0714
dc.relationinfo:eu-repo/grantAgreement/MINECO/MDM-2017-0714
dc.relation.urihttps://dx.doi.org/10.1016/j.envsoft.2019.104562
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/es/
dc.titleEmpirical and dynamic approaches for modelling the yield and N content of European grasslands
dc.typeinfo:eu-repo/semantics/article
dc.rights.holder(c) 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
dc.identifier.doi10.1016/j.envsoft.2019.104562
dc.contributor.funderEuropean Commission


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(c) 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's license is described as (c) 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).