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1.
PLoS One ; 16(12): e0255197, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34914697

RESUMO

Height measurements are essential to manage and monitor forest biomass and carbon stocks. However, accurate estimation of this variable in tropical ecosystems is still difficult due to species heterogeneity and environmental variability. In this article, we compare and discuss six nonlinear allometric models parameterized at different scales (local, regional and pantropical). We also evaluate the height measurements obtained in the field by the hypsometer when compared with the true tree height. We used a dataset composed of 180 harvested trees in two distinct areas located in the Amapá State. The functional form of the Weibull model was the best local model, showing similar performance to the pantropical model. The inaccuracy detected in the hypsometer estimates reinforces the importance of incorporating new technologies in measuring individual tree heights. Establishing accurate allometric models requires knowledge of ecophysiological and environmental processes that govern vegetation dynamics and tree height growth. It is essential to investigate the influence of different species and ecological gradients on the diameter/height ratio.


Assuntos
Biomassa , Florestas , Modelos Biológicos , Árvores/crescimento & desenvolvimento , Clima Tropical , Brasil
2.
Ciênc. rural (Online) ; 51(4): e20200312, 2021. tab, graf
Artigo em Inglês | LILACS-Express | LILACS | ID: biblio-1153869

RESUMO

ABSTRACT: The aim of this study was to determine the diversity. composition. forest structure of a stretch of dense ombrophilous forest in the state of Amapá. The area is located in the east of the state of Amapá. in the Eastern Amazon. at the following coordinates: 2º 0'0.00 '' N. 14º 0'0.00''O. The sampling process used was systematic. where nine plots of 1 ha (100 m x 100 m) were allocated. 0.5 km apart. within a 13 km long and 0.03 km wide transect. The horizontal structure of the forest was evaluated using phytosociological parameters. One thousand seven hundred and ninety trees were sampled in this study. they were distributed in 131 species. 69 genera and 48 families. The species that presented more individuals were Pouteria guianensis Aubl. (136). Eschweilera coriacea (DC.) S.A.Mori (78). Inga paraensis Ducke (45). Licania paraensis Prance (38). The area is highly diverse and dissimilar with great variability and complexity in vegetable formation.


RESUMO: O objetivo deste estudo foi determinar a diversidade, composição e estrutura florestal de um trecho de floresta ombrófila densa do estado do Amapá. A área está localizada a leste do Estado do Amapá, Amazônia Oriental. Nas seguintes coordenadas: 2º 0'0,00'' N. 14º 0'0.00''O. O processo de amostragem utilizado foi o sistemático em que foram alocadas nove parcelas de 1 ha (100 m x 100 m), distanciadas em 0.5 km entre si, dentro de um transecto de 13 km de comprimento por 0.03 km de largura. A estrutura horizontal da floresta foi avaliada por meio de parâmetros fitossociológicos. 1790 árvores foram amostradas neste estudo. Elas estão distribuídas em 131 espécies, 69 gêneros e 48 famílias. As espécies que apresentaram mais indivíduos foram Pouteria guianensis Aubl. (136), Eschweilera coriacea (DC.) S.A.Mori (78), Inga paraensis Ducke (45), Licania paraensis Prance (38). A área é altamente diversa e dissimilar com grande variabilidade e complexidade na formação vegetal.

3.
Sci Data ; 6(1): 198, 2019 10 10.
Artigo em Inglês | MEDLINE | ID: mdl-31601817

RESUMO

Forest biomass is an essential indicator for monitoring the Earth's ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (AGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. AGB and canopy height estimates with their associated uncertainties are derived at a 0.25 ha scale from field measurements made in permanent research plots across the world's forests. All plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RS-based biomass products while developing new synergies between the RS and ground-based ecosystem research communities.


Assuntos
Biomassa , Florestas , Tecnologia de Sensoriamento Remoto , Conservação dos Recursos Naturais , Monitoramento Ambiental/métodos
4.
Curr Biol ; 25(18): R787-8, 2015 Sep 21.
Artigo em Inglês | MEDLINE | ID: mdl-26394096

RESUMO

While around 20% of the Amazonian forest has been cleared for pastures and agriculture, one fourth of the remaining forest is dedicated to wood production. Most of these production forests have been or will be selectively harvested for commercial timber, but recent studies show that even soon after logging, harvested stands retain much of their tree-biomass carbon and biodiversity. Comparing species richness of various animal taxa among logged and unlogged forests across the tropics, Burivalova et al. found that despite some variability among taxa, biodiversity loss was generally explained by logging intensity (the number of trees extracted). Here, we use a network of 79 permanent sample plots (376 ha total) located at 10 sites across the Amazon Basin to assess the main drivers of time-to-recovery of post-logging tree carbon (Table S1). Recovery time is of direct relevance to policies governing management practices (i.e., allowable volumes cut and cutting cycle lengths), and indirectly to forest-based climate change mitigation interventions.


Assuntos
Biomassa , Carbono/metabolismo , Conservação dos Recursos Naturais , Agricultura Florestal , Florestas , Bolívia , Brasil , Suriname
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