dc.contributor.author | Dellar, M. | |
dc.contributor.author | Topp, C. | |
dc.contributor.author | Pardo, G. | |
dc.contributor.author | del Prado, A. | |
dc.contributor.author | Fitton, N. | |
dc.contributor.author | Holmes, D. | |
dc.contributor.author | Banos, G. | |
dc.contributor.author | Wall, E. | |
dc.date.accessioned | 2020-06-23T09:44:43Z | |
dc.date.available | 2020-06-23T09:44:43Z | |
dc.date.issued | 2019 | |
dc.identifier.citation | Environmental Modelling and Software 122 : 104562 (2019) | |
dc.identifier.issn | 1364-8152 | |
dc.identifier.uri | http://hdl.handle.net/10810/44147 | |
dc.description.abstract | We 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.sponsorship | This 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.iso | eng | |
dc.publisher | Elsevier | |
dc.relation | info:eu-repo/grantAgreement/EC/H2020/679302 | |
dc.relation | info:eu-repo/grantAgreement/MINECO/RYC-2017-22143 | |
dc.relation | ES/1PE/RYC-2017-22143 | |
dc.relation | EUS/BERC/BERC.2018-2021 | |
dc.relation | ES/1PE/MDM-2017-0714 | |
dc.relation | info:eu-repo/grantAgreement/MINECO/MDM-2017-0714 | |
dc.relation.uri | https://dx.doi.org/10.1016/j.envsoft.2019.104562 | |
dc.rights | info:eu-repo/semantics/openAccess | |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/3.0/es/ | |
dc.title | Empirical and dynamic approaches for modelling the yield and N content of European grasslands | |
dc.type | info: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.doi | 10.1016/j.envsoft.2019.104562 | |
dc.contributor.funder | European Commission | |