Path Analysis Applied to Evaluation of Biomass Estimates in Subtropical Forests at Brazil

Abstract

________________________________________________________________________________________ ResumoAnálise de trilha aplicada à avaliação de estimativas de biomassa em florestas subtropicais no Brasil. A análise de correlação entre diferentes variáveis nem sempre expressa totalmente o efeito direto real de uma variável sobre outra, especialmente em experimentos florestais. O objetivo do presente estudo foi avaliar as correlações e seus desdobramentos em efeitos diretos e indiretos do diâmetro das árvores, altura e componentes da biomassa na biomassa total acima do solo, utilizando a análise de trilha. Também objetiva definir quais variáveis devem ser incluídas na modelagem de biomassa. Os dados das árvores foram coletados em oito locais localizados no Paraná e no Rio Grande do Sul, onde o diâmetro a 1,30 m acima do solo (dbh); altura total (h); biomassa de fuste, galhos, folhas e biomassa total acima do solo foram medidas. A correlação de Spearman mostrou que dbh (0,93), fuste (0,94) e galhos (0,90) tiveram a maior associação com a biomassa total acima do solo quando os efeitos diretos e indiretos das variáveis foram desdobrados por análise de trilha. Os componentes fuste (0,44) e galhos (0,35) propiciaram maiores efeitos diretos quando comparados com o dbh (0,17). Para o componente fuste, galhos e folhas a biomassa total acima do solo apresentou os maiores efeitos diretos de 0,59, 0,74 e 0,36, respectivamente. Assim, esses resultados indicam a conveniência em se incluir pelo menos um componente de biomassa no modelo de regressão de biomassa, juntamente com dbh e h. Palavras-chave: correlação de Spearman, componente de biomassa, efeitos diretos e indiretos, florestas nativas. AbstractCorrelation analysis among different variables do not always fully express the real direct effect of one variable on another, especially in forest experiments. The objective of the present study was to evaluate the correlations among direct/indirect effects of tree diameter, height, and biomass components on tree total aboveground biomass and consequences when using path analysis. We also aimed to define which of the variables should be included in biomass modeling. The tree data were collected from eight sites located in Paraná and Rio Grande do Sul, where the diameter at 1.30 m aboveground (dbh), total height (h), biomass of stems, branches, leaves and tree total aboveground biomass were measured. Spearman's correlation showed that dbh (0.93), stems (0.94), and branches (0.90) had the highest association with total aboveground biomass when the direct and indirect effects of these variables were deconstructed by path analysis. The stem (0.44) and branch (0.35) components provided greater direct effects when compared with dbh (0.17). For the component stem, branches, and leaves the total aboveground biomass presented the greatest direct effects of 0.59, 0.74, and 0.36, respectively. Thus, these results indicate the convenience of including at least one biomass component in the biomass regression model, along with dbh and height.

Heteroblastic Foliage Affects the Accumulation of Non-Structural Carbohydrates and Biomass in Pinus massoniana (Lamb.) Seedlings

“…In addition, Pearson's correlation coefficient (Tables 3 and 4) and path analysis (Figures 7 and 8) revealed close relationships among the various indicators, showing that different factors were involved in the regulation of biomass accumulation in PNS and SNS. Although correlation analysis reflects the degree of correlation between various factors to some extent, biomass is a comprehensive character, and simple correlation analysis cannot truly reflect the correlation between each character and the biomass [57]. Path analysis can effectively express the direct effect of related variables on dependent variables and estimate the indirect effect of derived variables on dependent variables, which makes the statistical analysis of multivariable data more reasonable [58,59].…”

Correlations between dendrometric and allometric variables of Eucalyptus benthamii under agroforestry systems in the subtropic of Brazil

“…For studies with modeling of allometric variables, it is essential to study correlations (Zianis et al 2016;Trautenmüller et al 2019). However, simple correlations can result in mistakes in the choice of variables to be used in modeling allometric variables, as their estimate and magnitude may not reflect the true associations between the variables under study (Trautenmüller et al 2019).…”

“…For studies with modeling of allometric variables, it is essential to study correlations (Zianis et al 2016;Trautenmüller et al 2019). However, simple correlations can result in mistakes in the choice of variables to be used in modeling allometric variables, as their estimate and magnitude may not reflect the true associations between the variables under study (Trautenmüller et al 2019). To better understand the cause-and-effect relationships between variables Wright (1921) proposed a method called Path Analysis, which breaks down simple correlations into direct and indirect effects.…”

Determination of the biomass stock in a mixed plantation of Pinus taeda L. and Pinus elliottii Engelm.

“…Measuring the biomass of all trees in a plantation is impractical given the constraints of time and resources (Watzlawick et al 2013;Trautenmüller et al 2019). In general, forest biomass is evaluated using four techniques, namely the medium tree (Trautenmüller et al 2019), stratified tree (by diameter class), area unit (Balbinot et al 2017;Trautenmüller et al 2019), and regression (Balbinot et al 2019) techniques; these techniques are further divided into direct (destructive) and indirect (non-destructive) methods. For any of the above biomass assessment techniques, a forest inventory must initially be performed.…”

“…In the direct method, the selected trees are felled and then biomass is measured. However, despite its accuracy, the direct method is timeconsuming and costly, since forest biomass is determined through quantification and weighing (wet and dry) of different tree components (Qureshi et al 2012;Balbinot et al 2017;Trautenmüller et al 2019).…”