1 research outputs found
Site Index Model For Natural Stands Of Rebollo Oak ( Quercus pyrenaica Willd.) In Galicia, NW Iberian Peninsula
Dados da an\ue1lise de tronco de 56 \ue1rvores dominantes de
Quercus pyrenaica Willd. de florestas naturais da Galicia (NW
Pen\uednsula Ib\ue9rica) foram utilizados para avaliar quatro
equa\ue7\uf5es dinamicas de \uedndice de sitio obtidas com a
Abordagem Generalizada de Diferen\ue7a Alg\ue9brica (GADA). Todas
as equa\ue7\uf5es s\ue3o baseadas na idade invariante e
diretamente estimam a altura e o \uedndice de sitio. Os ajustes foram
feitos utilizando uma estrutura de dados que incluiam todos os
poss\uedveis intervalos de crescimento. A formula\ue7\ue3o GADA
teve base no modelo Bertalanffy- Richards, considerando a
ass\uedntota e do padr\ue3o inicial como par\ue2metros
relacionados \ue0 produtividade do sitio. Assim, recomenda-se o
modelo na previs\ue3o do crescimento em altura e
classifica\ue7\ue3o de sitios para povoamentos naturais de carvalho
negro na Galicia. A autocorrela\ue7\ue3o foi analisada com um teste
de res\uedduos utilizando Durbin's t-teste, sem chegar a um resultado
significativo de autocorrela\ue7\ue3o entre os dados.Data from stem analysis of 56 dominant trees of Quercus pyrenaica
Willd., in natural stands in Galicia (NW Iberian Peninsula), were used
to evaluate four dynamic site equations derived with the Generalized
Algebraic Difference Approach (GADA). All the equations are base-age
invariant and directly estimate height and site index from any height
and age. The fittings were made using a data structure involving all
possible growth intervals. The GADA formulation derived on the basis of
the Bertalanffy- Richards model by considering the asymptote and the
initial pattern parameters as related to site productivity. It is
therefore recommended for height growth prediction and site
classification for natural stands of rebollo oak in Galicia. The
autocorrelation was analyzed with a test of residuals using
Durbin\u2019s ttest without reaching a manifest result of
autocorrelation between managed data