Comparação dos valores estimados por amostragem na caracterização da estrutura de uma área de floresta na Amazônia com as informações registradas no censo florestal

Cavalcanti, Francisco José de Barros; Machado, Sebastião do Amaral; Osokawa, Roberto Tuyuoshy; Cunha, Ulisses Silva da

doi:10.1590/s0100-67622011000600012

Cited by 13 publications

(11 citation statements)

References 9 publications

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“…Considering all the tree species of the area under management in the Jamari National Forest, the values of density (trees ha -1 ) and baseline area (m² ha -1 ) were low when compared to the sampling studies performed in Acre (Cavalcanti et al, 2011) and in Mato Grosso (Ubialli et al, 2009). However, when analyzing only the commercial species, these values are compatible with the results of Cavalcanti et al (2009).…”

Section: Discussionsupporting

confidence: 59%

Timber stock inventory in Amazon: simulations of cross-malt conglomerates sampling intensities

Cysneiros

Perego

Corte

et al. 2018

Agraria

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A high diversity of tree species and a fact that only a few they have commercial value makes it difficult to establish appropriate sampling to characterize the timber stocks of tropical forests. In contrast, large inventories are needed to subsidize the identification, description, and bidding of public forests for concession. The aim of this study was to evaluate the effectiveness of the cross-malt conglomerate in different sampling intensities to estimate the commercial volume of tree species and their susceptible to exploitation in an Amazon forest under concession. For this, a sampling process in cross-malt conglomerates was simulated with intensities of 20 (0.5%), 40 (1%), 60 (1.5%), 80 (2%), and 100 (2,5%) sampling units from a forest census. The intensity of 100 sampling units was adequate to sampling the timber stock in natural forests, since it generated sampling errors close to or less than 10% established by law. The detection of species susceptible for exploration and the characterization of floristic composition of the tree stratum were other advantages observed. Thus, sampling by cross-malt conglomerates with first random stage is recommended for inventories of production forests in Amazon.

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Section: Discussionsupporting

confidence: 59%

Timber stock inventory in Amazon: simulations of cross-malt conglomerates sampling intensities

Cysneiros

Perego

Corte

et al. 2018

Agraria

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“…In tropical forests, the wide heterogeneity of species, complex spatial distributions of species and large number of rare species are factors that can cause high sampling errors (Ubialli et al 2009). Comparatively, for timber management, the sampling error allowed, according to IBAMA, is 10 % (Cavalcanti et al 2011), and the maximum error allowed in diagnostic inventory of Clusia spp. and Heteropsis spp., in accordance with Resolution COEMA no.…”

Section: Statistical Analysis Of the Datamentioning

confidence: 99%

“…Studies sampling approaches for inventory are typically focused on analysis and ecological processes in the form of phenological or regeneration evaluations (D'Eça-Neves and Morellato 2004;Gama et al 2001) and/or the stock of wood in natural forests (Cavalcanti et al 2011;Piqué et al 2011) and plantations (Druszcz et al 2010;Fick 2011).…”

Section: Introductionmentioning

confidence: 99%

Sampling methods for titica vine (Heteropsis spp.) inventory in a tropical forest

Klauberg

Vidal

Silva

et al. 2016

Annals of Forest Science

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“…The X coordinate of each individual was obtained by means of the number of the mark and the distance of each tree in relation to it. Then, the next mark was attended to, executing the same work routine, and so on, until the last WU-16 mark was completed (Cavalcanti et al, 2011).…”

Section: Data Collectionmentioning

confidence: 99%

SAMPLING PROCESSES FOR Carapa guianensis AUBL. IN THE AMAZON

Vieira

Oliveira

Gama

et al. 2018

CERNE

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HIGHLIGHTSThe process of adaptive cluster sampling (ACS) is not legally viable.The processes of systematic sampling and simple random are legally viable.The use of larger parcels in the ACS overestimates the variable of interest.The higher the share in the ACS, the greater the sampling intensity. ABSTRACTThe objective of this study was to analyze the adaptive cluster sampling (ACS), simple random sampling (SRS) and systematic sampling (SS) processes to obtain the number of ha-1 trees of Carapa guianensis Aubl. in the Amazon. The data were obtained through 100% inventory and sampling simulations, considering a DBH ≥ 25 cm, a sampling intensity of 4%, a maximum error of 10% and plots of 0.09, 0.16 and 0.25 ha. The last two sizes were only used to analyze their effect on the ACS estimators. The processes were evaluated for accuracy, precision (E % ) and confi dence interval (CI), while the mean ha -1 of the processes were compared with that of the 100% inventory by the Z test. The ACS process showed no signifi cant difference between its average ha -1 trees and the 100% inventory, and it was also the most accurate and the only one whose CI was true. However, it presented a fi nal sample intensity 3.6 times greater than the simple and systematic random samplings, in addition to E % above 10%, which makes it unacceptable, legally, and economically unfeasible. The other processes had densities signifi cantly higher than the 100% inventory, with sample intensities lower than ACS and E % lower than 10%, making them legally viable. The use of larger plots in the ACS implies larger clusters and a greater tendency to underestimate the number of trees, resulting in larger sample errors and less accuracy. v.24 n.3 2018 SAMPLING PROCESSES FOR Carapa guianensis AUBL. IN THE AMAZON FOREST 170 CERNE VIEIRA et al.

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Comparação dos valores estimados por amostragem na caracterização da estrutura de uma área de floresta na Amazônia com as informações registradas no censo florestal

Cited by 13 publications

References 9 publications

Timber stock inventory in Amazon: simulations of cross-malt conglomerates sampling intensities

Timber stock inventory in Amazon: simulations of cross-malt conglomerates sampling intensities

Sampling methods for titica vine (Heteropsis spp.) inventory in a tropical forest

SAMPLING PROCESSES FOR Carapa guianensis AUBL. IN THE AMAZON

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