Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.5/7411
Título: Analysis of the performance of the 3-PG model for Scots pine in Turkey
Autor: Çolak, Deniz
Orientador: Tomé, Margarida
Carvalho, Ana Paula Soares
Palavras-chave: Scots pine
Pinus sylvestris
forest models
3-PG model
process-based models
Turkey
Data de Defesa: 2014
Editora: ISA/UL
Citação: Çolak, D. - Analysis of the performance of the 3-PG model for Scots pine in Turkey. Lisboa: ISA, 2014, 70 p.
Resumo: The 3-PG (Physiological Principles in Predicting Growth) is a dynamic, process-based model of forest growth developed in order to bridge the gap between empirical models and very detailed physiological models. The aim of this thesis is to analyse the performance of the model 3-PG for Scots pine (Pinus sylvestris L.) with data from Turkey. A first step was to identify and organise data for this purpose. Two important data sets were found in Turkey, the first containing 68 trees that were destructively sampled for biomass assessment, the second from 135 temporary plots. The absence of data from permanent plots lead to the use of existing yield tables, that were complemented in order to provide foliage and stem biomass, as growth data. The first runs of 3-PG were based on parameters available from the literature, followed by the calibration of as many parameters as possible with the data available, namely the age-related and the allometric and partitioning parameters. The model showed quite reasonable results in predicting the above-ground biomass and stand density, but some problems with the prediction of leaves biomass whose estimations in the yield table were also questionable. The results are promising and point out for research lines that must be pursued in order to improve the performance of 3-PG for Scots pine in Turkey.
Descrição: Mestrado - Mediterranean Forestry and Natural Resources Management - Instituto Superior de Agronomia
URI: http://hdl.handle.net/10400.5/7411
Aparece nas colecções:BISA - Dissertações de Mestrado / Master Thesis

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