Use este identificador para citar ou linkar para este item: http://repositorio.inpa.gov.br/handle/123/2713
Título: UNCERTAINTY IN THE BIOMASS OF AMAZONIAN FORESTS - AN EXEMPLE FROM RONDÔNIA, BRASIL
Autor(es): BROWN I FMARTINELLI L A THOMAS W WMOREIRA M Z FERREIRA CAC V
Carlos Alberto Cid Ferreira
Assunto: BIOMASS, UNCERTAINTY, AMAZONIAN FOREST
ISSN: 0378-1127
Revista: Forest Ecology and Management
Volume: 1-3
Resumo: A critical factor in estimating the contribution of tropical deforestation to nutrient mobilization and to CO2 build-up in the atmosphere is the amount of biomass available to burn. The biomass data for Brazil, a major site for deforestation, are few and of uncertain accuracy. Recent international agreements, however, require national inventories of sources and sinks for atmospheric greenhouse gases; such inventories will need better estimates of biomass and their uncertainties. To provide additional information on biomass uncertainty and on forest structure in southwestern Amazonia, a region of active deforestation, we measured in 1988 the diameter, bole and canopy heights of 474 trees covering a total of 1 ha (10 000 m2) in the Ecological Station of the Samuel Hydroelectric Reservoir in Rondônia (845′S, 63°23′W). Using allometric equations based on destructively sampled trees, we estimated the largest biomass component, standing alive aboveground biomass (SAAB), as 285 Mg (dry weight) ha−1. Fallen trunks and litter were 30 Mg and 10 Mg ha−1, respectively. The sum of these components, 325 Mg ha−1, is an underestimate of the total biomass because the biomass of roots, vines, shrubs, and small trees was not measured. Measurement error of SAAB is ± 20%, ± 57 Mg ha−1 about the mean (95% confidence interval), as derived by a Monte Carlo simulation. The SAAB distribution among trees is highly skewed: 3% of the trees contain 50% of the SAAB. For forests of similar distributions, sampling units typically used for biomass estimates (less than 2000 m2) will usually produce biomass estimates significantly different from those of larger units. Based on subsamples of our data, sampling units of 1000 m2 or smaller had at least a 75% chance of being outside the confidence interval of the global mean (228–342 Mg ha−1) derived from Monte Carlo simulation. To improve estimates of SAAB in similar forests a sampling program should focus on emergent and large canopy trees, the dominant contributors to biomass.
URI: http://repositorio.inpa.gov.br/handle/123/2713
ISSN: 0378-1127
DOI: http://dx.doi.org/10.1016/0378-1127(94)03512-U
Local de publicação: Holanda
Aparece nas coleções:Coordenação de Biodiversidade (CBIO)

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