RT info:eu-repo/semantics/article
T1 Evaluation and validation of forest models: Insight from Mediterranean and scots pine models in Spain
A1 Vázquez Veloso, Aitor
A1 Pando Fernández, Valentín
A1 Ordoñez, C.
A1 Bravo Oviedo, Felipe
K1 Gestión forestal
K1 Bosques y silvicultura
K1 Survival
K1 Growth
K1 Modelling
K1 Supervivencia
K1 Crecimiento
K1 Modelado
K1 3106 Ciencia Forestal
AB 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.
PB Elsevier
SN 1574-9541
YR 2023
FD 2023
LK https://uvadoc.uva.es/handle/10324/61223
UL https://uvadoc.uva.es/handle/10324/61223
LA eng
NO Ecological Informatics, 2023, vol. 77, 102246
NO Producción Científica
DS UVaDOC
RD 23-dic-2024