Predicting of biomass in Brazilian tropical dry forest: a statistical evaluation of generic equations

LIMA, ROBSON B DE; ALVES JÚNIOR, FRANCISCO T; OLIVEIRA, CINTHIA P DE; SILVA, JOSÉ A A DA; FERREIRA, RINALDO L C

LIMA, ROBSON B DE; ALVES JÚNIOR, FRANCISCO T; OLIVEIRA, CINTHIA P DE; SILVA, JOSÉ A A DA; FERREIRA, RINALDO L C.

Afiliação

LIMA, ROBSON B DE; Universidade do Estado do Amapá. Laboratório de Manejo Florestal. Macapá. BR
ALVES JÚNIOR, FRANCISCO T; Universidade do Estado do Amapá. Laboratório de Manejo Florestal. Macapá. BR
OLIVEIRA, CINTHIA P DE; Universidade do Estado do Amapá. Laboratório de Manejo Florestal. Macapá. BR
SILVA, JOSÉ A A DA; Universidade do Estado do Amapá. Laboratório de Manejo Florestal. Macapá. BR
FERREIRA, RINALDO L C; Universidade do Estado do Amapá. Laboratório de Manejo Florestal. Macapá. BR

An. acad. bras. ciênc ; 89(3): 1815-1828, July-Sept. 2017. tab, graf

Article em En | LILACS | ID: biblio-886723

Biblioteca responsável: BR1.1

ABSTRACT

ABSTRACT

ABSTRACT Dry tropical forests are a key component in the global carbon cycle and their biomass estimates depend almost exclusively of fitted equations for multi-species or individual species data. Therefore, a systematic evaluation of statistical models through validation of estimates of aboveground biomass stocks is justifiable. In this study was analyzed the capacity of generic and specific equations obtained from different locations in Mexico and Brazil, to estimate aboveground biomass at multi-species levels and for four different species. Generic equations developed in Mexico and Brazil performed better in estimating tree biomass for multi-species data. For Poincianella bracteosa and Mimosa ophthalmocentra, only the Sampaio and Silva (2005) generic equation was the most recommended. These equations indicate lower tendency and lower bias, and biomass estimates for these equations are similar. For the species Mimosa tenuiflora, Aspidosperma pyrifolium and for the genus Croton the specific regional equations are more recommended, although the generic equation of Sampaio and Silva (2005) is not discarded for biomass estimates. Models considering gender, families, successional groups, climatic variables and wood specific gravity should be adjusted, tested and the resulting equations should be validated at both local and regional levels as well as on the scales of tropics with dry forest dominance.

Assuntos

Florestas; Biomassa; Clima Tropical; Brasil; Monitoramento Ambiental; Modelos Estatísticos; México

Palavras-chave

Above-ground biomass; Allometric models; Caatinga; Forest management; Statistical validation

Texto completo

Adicionar na Minha BVS

Imprimir

XML

Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: LILACS Assunto principal: Florestas / Biomassa Tipo de estudo: Prognostic_studies / Risk_factors_studies País/Região como assunto: America do sul / Brasil / Mexico Idioma: En Revista: An. acad. bras. ciênc Assunto da revista: CIENCIA Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Brasil País de publicação: Brasil

Texto completo

Adicionar na Minha BVS

Imprimir

XML

Buscar no Google