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dc.contributor.authorVázquez Veloso, Aitor
dc.contributor.authorPando Fernández, Valentín 
dc.contributor.authorOrdoñez, C.
dc.contributor.authorBravo Oviedo, Felipe 
dc.date.accessioned2023-08-30T08:51:58Z
dc.date.available2023-08-30T08:51:58Z
dc.date.issued2023
dc.identifier.citationEcological Informatics, 2023, vol. 77, 102246es
dc.identifier.issn1574-9541es
dc.identifier.urihttps://uvadoc.uva.es/handle/10324/61223
dc.descriptionProducción Científicaes
dc.description.abstractForest models predict tree and stand evolution under different scenarios, thereby supporting decision-making in forest management. Models are complex structures composed of sub-models that estimate forest variables at tree and stand levels. Prediction accuracy has generally been evaluated independently of the model. Integrated sub-models make forest models easier to use and provide predictions for growth, survival, ingrowth and many other tree and stand variables with reduced effort. However, while individual submodel validation is widely practiced and normally done by each author individually, joint model validation remains less explored. This study deploys a useful methodology for evaluating and validating models. After comparing observed and predicted data, several case studies were then proposed to improve the accuracy of the joint model. We used the IBERO model, data from the Spanish National Forest Inventory and the SIMANFOR simulator platform. The accuracy of growth submodels was improved by calibrating their equations, though accuracy was not improved in survival and ingrowth submodels.es
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.publisherElsevieres
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectGestión forestales
dc.subjectBosques y silviculturaes
dc.subject.classificationSurvivales
dc.subject.classificationGrowthes
dc.subject.classificationModellinges
dc.subject.classificationSupervivenciaes
dc.subject.classificationCrecimientoes
dc.subject.classificationModeladoes
dc.titleEvaluation and validation of forest models: Insight from Mediterranean and scots pine models in Spaines
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.holder© 2023 The Authorses
dc.identifier.doi10.1016/j.ecoinf.2023.102246es
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S1574954123002753?via%3Dihubes
dc.identifier.publicationfirstpage102246es
dc.identifier.publicationtitleEcological Informaticses
dc.identifier.publicationvolume77es
dc.peerreviewedSIes
dc.description.projectFEDER - Junta de Castilla y León (CLU-2019-01 y CL-EI-2021-05)es
dc.description.projectProject COMFOR-SUDOE: Integrated and intelligent management of complex forests and mixed-species plantations in Southwest Europe (SOE4/PA/E1012)es
dc.description.projectProject SMART: Bosques mixtos : selvicultura, mitigación, adaptación, resiliencia y trade-offs (VA183P20)es
dc.description.projectProject Integrated Forest Management along complexity gradients (IMFLEX) (PID2021-1262750B-C229)es
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones
dc.subject.unesco3106 Ciencia Forestales


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