Modeling dominant height growth of maritime pine in Portugal using GADA methodology with parameters depending on soil and climate variables
Modeling dominant height growth of maritime pine in Portugal using GADA methodology with parameters depending on soil and climate variables
复制标题
使用 GADA 方法对葡萄牙海松的主要高度生长进行建模，参数取决于土壤和气候变量
作者：
Luís Nunes;M. Patrício;J. Tomé;M. Tomé
海洋松（Pinus pinaster Ait.）是葡萄牙常见的针叶树种，对国民经济贡献巨大。基于地位指数和高生长动态的森林生产力的准确分类是该物种可持续森林管理的主要依据。目的本研究的主要目的是开发一个新的动态网站依赖的高度年龄模型的海洋松在葡萄牙，使用广义代数差分方法（GADA）的方法，并探讨可能的改进模型的性能，通过扩大其参数作为土壤和气候变量的子功能。方法对变形动力学方程、具有公共渐近线的多态动力学方程和具有多重渐近线的多态动力学方程进行了检验。将候选模型拟合到一个大型树干分析数据集，并在来自永久样地的独立数据上进行检验。·结果两个最好的模型与多个渐近线，一个变形和一个多态性，表现出类似的性能，但是，在扩大的气候和土壤变量的子功能的参数，多态性模型优于变形模型，以及其他模型以前用于该物种在葡萄牙的管理。本研究的结果还表明，海洋松模型，开发干分析数据，可以准确地预测优势高生长的永久样地数据测量。
Abstract• BackgroundMaritime pine (Pinus pinaster Ait.) is a common conifer species in Portugal that contributes significantly to the national economy. Accurate classification of forest productivity based on site index and height growth dynamics is the main basis for sustainable forest management of this species.• ObjectivesThe main objective of this study was to develop a new dynamic site-dependent height–age model for the maritime pine in Portugal, using the generalized algebraic difference approach (GADA) methodology, and to explore possible improvements of the model´s performance by expanding its parameters as sub-functions of soil and climate variables.• MethodsWe tested for this purpose several dynamic equations, including anamorphic, polymorphic with common asymptote, and polymorphic with multiple asymptotes equations. The candidate models were fitted to a large set of stem analysis data, and tested on independent data from permanent sample plots.• ResultsThe two best models with multiple asymptotes, one anamorphic and one polymorphic, showed similar performance; however, upon expanding the parameters as sub-functions of the climate and soil variables, the polymorphic model outperformed the anamorphic model, as well as other models previously used for the management of this species in Portugal. The results of this study also demonstrated that the maritime pine model, developed with stem analysis data, can accurately predict the dominant height growth measured on permanent sample plot data.
影响因子：
1.9
作者：
ZEGER, SL;LIANG, KY;ALBERT, PS
通讯作者：
ALBERT, PS