Evaluation of forest inventory processes in a forest under concession in the southwestern Brazilian Amazon

Felipe Kauai,Carlos Roberto Sanquetta,Ana Paula Dalla Corte,Vinicius Cysneiros,Allan Libanio Pelissari

doi:10.1590/1809-4392201801331

Felipe Kauai, Carlos Roberto Sanquetta + Show 3 more

Open Access

https://doi.org/10.1590/1809-4392201801331

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Journal: Acta Amazonica	Publication Date: Apr 1, 2019
Citations: 5	License type: CC BY 4.0

Affiliation: Federal University of Paraná

Abstract

ABSTRACT Forest inventory procedures are of utmost importance to studies of wood volume stocks, and forest structure and diversity, which provide relevant information to public policies, management plans and ecological research. The present work focused on the performance of inventory techniques in the Amazon region to evaluate wood volume stocks with higher levels of accuracy while maintaining sampling intensity fixed. Two sampling processes were assessed: simple random sampling and two-stage cluster sampling. The processes were evaluated through the allocation of sampling units with different dimensions, and the effectiveness of the generated estimators was analyzed as a function of stand density and basal area. Simple random sampling resulted in the smallest errors, reaching 9% when all species were sampled together. The method depicted forest phytosociological parameters with greater sensitivity, whereas two-stage cluster sampling produced the least accurate estimators and presented slower responses to variation in phytosociological parameters.

Highlights

The rich composition of plant species in Amazonian forests is not completely elucidated and much remains unknown (Steege et al 2013)
The relative sampling error ranged from 9% for Simple random sampling (SRS) using 2,000 m2 to 21.7% for IFN using 8,000 m2 (Table 3)
The relative sampling error was significantly correlated with stand density in all cases (R2 > 0.85, p < 0.05)

Summary

Introduction

The rich composition of plant species in Amazonian forests is not completely elucidated and much remains unknown (Steege et al 2013). As far as the evaluation of forest structure is concerned, forest survey processes are of the utmost importance for data acquisition, since a true inventory, i.e. the enumeration of all trees in the target area, is not always feasible due to operational limitations (Scolforo and Mello 1993). Such survey processes involve a number of statistical techniques and methods used to estimate important forest parameters with well-delimited errors (Scolforo and Mello 1993; Sanquetta et al 2014; Péllico Netto et al 2017).

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Conclusion