2026-05-05T11:40:59Zhttps://uvadoc.uva.es/oai/request

oai:uvadoc.uva.es:10324/612232025-02-21T10:32:36Zcom_10324_7492com_10324_952com_10324_894col_10324_7493

Vázquez Veloso, Aitor Pando Fernández, Valentín Ordoñez Alonso, Ángel Cristobal Bravo Oviedo, Felipe 2023 Producción Científica Forest 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. application/pdf https://uvadoc.uva.es/handle/10324/61223 eng Elsevier Gestión forestal Bosques y silvicultura 3106 Ciencia Forestal Evaluation and validation of forest models: Insight from Mediterranean and scots pine models in Spain info:eu-repo/semantics/article TEXT UVaDOC. Repositorio Documental de la Universidad de Valladolid Hispana