RESUMO A modelagem da distribuição diamétrica em florestas naturais é uma ferramenta importante para compreender a dinâmica de espécies nativas lenhosas, auxiliando na tomada de decisão para o manejo e a recuperação de áreas degradadas. Dessa forma, o objetivo deste trabalho foi ajustar funções de densidade probabilística para avaliar a estrutura diamétrica de três espécies arbóreas de interesse econômico, como Campomansesia xanthocarpa Marl. Ex. O. Berg, Piptadenia gonoacantha (Mart.) J.F. Macbr. e Zeyheria tuberculosa (Vell.) Bureau ex Verl., em um fragmento de Floresta Estacional Semidecidual no estado de São Paulo, Brasil. Os dados foram provenientes de 83 parcelas temporárias de 10 m x 20 m distribuídas sistematicamente ao longo de 164 ha. As funções Log-normal, Gamma e Weibull foram ajustadas para as três espécies por meio do pacote fitdistrplus no programa R. O teste de aderência de Kolmogorov-Smirnov foi aplicado a 5% de probabilidade para avaliar os ajustes. As funções foram .selecionadas por meio do Critério de Informação Akaike (AIC) e do Critério de Informação Bayesiano de Schwaarz (BIC), além da análise gráfica das funções ajustadas. Os resultados indicaram que a estrutura diamétrica das três espécies é assimétrica positiva, as quais apresentam o padrão exponencial, sugerindo uma regeneração natural contínua. As estatísticas de AIC e BIC indicaram a função Log-normal para descrever a distribuição diamétrica de C. xanthocarpa e Z. tuberculosa, enquanto a função Gamma foi a mais adequada para P. gonoacantha. Para as três espécies, a análise gráfica mostrou que a função Gamma resultou no melhor ajuste, não apresentando tendências nas estimativas da densidade de frequências por classe de diâmetro. lenhosas degradadas forma econômico Marl Ex Berg Mart. Mart (Mart. JF J F J.F Macbr Vell. Vell (Vell. Verl Verl. Paulo Brasil 8 1 2 16 ha Lognormal, Lognormal Log normal, normal R KolmogorovSmirnov Kolmogorov Smirnov 5 ajustes selecionadas (AIC BIC, , (BIC) positiva exponencial contínua C Z P ajuste diâmetro (Mart (Vell (BIC

ABSTRACT Modeling diameter distribution in natural forests is an important tool for understanding the native woody species dynamics, supporting decision-making for degraded lands management and restoration. Therefore, this work aimed to fit probabilistic density functions to evaluate the diameter structure of three tree species with economic interest, such as Campomansesia xanthocarpa Marl. Ex. O. Berg, Piptadenia gonoacantha (Mart.) J.F. Macbr. and Zeyheria tuberculosa (Vell.) Bureau ex Verl., in a Semideciduous Seasonal Forest fragment at São Paulo State, Brazil. The data came from 83 temporary plots of 10 m x 20 m systematically distributed along 164 ha. Log-normal, Gamma, and Weibull functions were fitted to the three species using the fitdistrplus-package in the R program. Kolmogorov-Smirnov's adherence test was used to evaluate the fits at a 5% probability level. The functions were selected employing Akaike's Information Criterion (AIC) and Schwarz's Bayesian Information Criterion (BIC), in addition to a graphical analysis of the fitted functions. The results indicated that the three species diameter structure is positively asymmetric, representing the exponential pattern, representing continuous natural regeneration. AIC and BIC statistics indicated the Log-normal function to describe the diameter distribution of C. xanthocarpa and Z. tuberculosa, while the Gamma function was the most appropriate for P. gonoacantha. For the three species, the graphical analysis showed the Gamma function results in the best fit without tendency for estimating frequency density per diameter class. dynamics decisionmaking decision making restoration Therefore interest Marl Ex O Berg Mart. Mart (Mart. JF J F J.F Macbr Vell. Vell (Vell. Verl Verl. State Brazil 8 1 2 16 ha Lognormal, Lognormal Log normal, normal fitdistrpluspackage fitdistrplus package program KolmogorovSmirnovs Kolmogorov Smirnov s 5 level Akaikes Akaike (AIC Schwarzs Schwarz BIC, , (BIC) asymmetric pattern regeneration C Z P class (Mart (Vell (BIC

Abstract Floristic surveys and diversity indices are often applied to measure tree species diversity in mixed tropical forest remnants. However, these analyses are frequently limited to the overall results and do not allow to evaluate the spatial variability distributions of tree diversity, leading to develop additional tools. This study aimed to estimate the spatial variability of tree diversity and map their spatial patterns in a Brazilian mixed tropical forest conservation area. We used indices to measure the tree species diversity (dbh ≥ 10 cm) in 400 sampling units (25 m x 25 m) from a continuous forest inventory. Semivariograms were fitted to estimate spatial dependences and punctual kriging was applied to compose maps. Mean diversity values were constant in the continuous inventories, indicating a forest remnant in an advanced stage of ecological succession. On the other hand, tree diversity presented spatial patterns identified by geostatistics, in which the dynamics were composed of heterogeneous mosaics spatially influenced by tree species with different ecological features and densities, gap dynamics, advancement of forest succession, mortality, and Araucaria angustilofia’s cohorts.

ABSTRACT The spatial distribution of tropical tree species can affect the consistency of the estimators in commercial forest inventories, therefore, appropriate sampling procedures are required to survey species with different spatial patterns in the Amazon Forest. For this, the present study aims to evaluate the conventional sampling procedures and introduce the adaptive cluster sampling for volumetric inventories of Amazonian tree species, considering the hypotheses that the density, the spatial distribution and the zero-plots affect the consistency of the estimators, and that the adaptive cluster sampling allows to obtain more accurate volumetric estimation. We use data from a census carried out in Jamari National Forest, Brazil, where trees with diameters equal to or higher than 40 cm were measured in 1,355 plots. Species with different spatial patterns were selected and sampled with simple random sampling, systematic sampling, linear cluster sampling and adaptive cluster sampling, whereby the accuracy of the volumetric estimation and presence of zero-plots were evaluated. The sampling procedures applied to species were affected by the low density of trees and the large number of zero-plots, wherein the adaptive clusters allowed concentrating the sampling effort in plots with trees and, thus, agglutinating more representative samples to estimate the commercial volume.