Estratégias de projeção da estrutura diamétrica em Floresta Ombrófila Mista.

da Silveira Gomes, Marina; Nogueira Dias, Andrea; Figueiredo Filho, Afonso; de Souza Retslaff, Fabiane Aparecida; Rodrigo Lanssanova, Luciano

In order for forest to be used in a sustainable way, it is important to know the forests' structure in the future, which can be estimated through the prognosis of the diametric distribution. Projections such as these can assist in the decision-making process for management and preservation, and it is necessary to develop strategies seeking improvement of these estimates. Thus, this study aimed to evaluate the effect of forest stratification on the prediction of the diametric structure in a Mixed Ombrophilous Forest. Data from 26 permanent plots (1 ha) were analyzed in Três Barras National Forest, in the state of Santa Catarina. Each primary unit was divided into 20 secondary units of 0.05 ha, measured in 2004, 2009 and 2016. Within multivariate statistics of cluster analysis, the stratification of secondary units was performed using as attributes the average annual increment in diameter, basal area, and the number of stems of each secondary unit. Using the Movement Ratio, the forest's diametric distribution for the year 2016 was projected. Using as its basis the data from the 2004 and 2009 inventories, the projection was carried out for the forest as a whole. However, the projection for the stratified forest was conducted based only on the inventory for the year 2009. The projection's consistency was evaluated by the Komolgorov-Smirnov test and the Reynolds Index. The cluster analysis resulted in three strata and the prediction formulated for the stratified forest had the best performance, both in total number of stems and in the first diametric classes, where the greatest variations between observed and estimated frequency normally occur. The stratification of the forest improves the estimate and provides more accurate results in the prediction of the diametric structure, being an important tool to be used in extensive heterogeneous forest areas.

SANTA Catarina (Brazil : State); CLUSTER analysis (Statistics); MIXED forests; FOREST reserves; FOREST management; DECISION making; INVENTORIES

Ciência Florestal (01039954), 2022, Vol 32, Issue 2, p902

0103-9954

Academic Journal

10.5902/1980509863311