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Vegetation biomass and carbon stocks in the Parnaíba River Delta, NE Brazil.

Authors :
Portela, Mirya Grazielle Torres
de Espindola, Giovana Mira
Valladares, Gustavo Souza
Amorim, João Victor Alves
Frota, Jéssica Cristina Oliveira
Source :
Wetlands Ecology & Management; Aug2020, Vol. 28 Issue 4, p607-622, 16p
Publication Year :
2020

Abstract

Coastal ecosystems are considered environments with great potential for carbon storage. Given the difficulties in quantifying biomass, allometric equations and remote sensing have become fundamental tools in the studies of quantification of vegetation biomass and carbon stocks. Thus, the objective of this study is to quantify and estimate the spatial distribution of vegetation biomass and to quantify the carbon stock of the Parnaíba River Delta vegetation. The study was carried out in part of the Parnaíba River Delta Environmental Protection Area and in the Parnaíba River Delta Marine Extractive Reserve, in NE Brazil, in five spots within distinct vegetation types: psammophile pioneer vegetation, dune subevergreen vegetation, mangrove evergreen vegetation, floodplain vegetation and vegetation associated with carnaubals. At 26 collection points, 10 × 20 m plots were marked, in which the diameter at breast height and height of all individuals were measured. The collected data were used in allometric equations for vegetation biomass estimates and these values were converted into carbon stocks. The spatial distribution of aboveground vegetation biomass (AGB) was also estimated by remote sensing, where we extracted and selected spectral variables obtained from Landsat-8 OLI sensor images, on three different dates. Prediction models were calculated by multiple linear regression analysis. It was observed that the mangrove evergreen vegetation obtained higher vegetation biomass and carbon stock than the others. The models obtained through remote sensing that provided the best estimates of AGB were those of November 12th, 2016 (EAM = 6.84; RMSE = 47.89 Mg ha<superscript>−1</superscript>; R<superscript>2</superscript> = 0.72) and November 28th, 2016 (EAM = 9.63; RMSE = 34.67 Mg ha<superscript>−1</superscript>; R<superscript>2</superscript> = 0.58). [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09234861
Volume :
28
Issue :
4
Database :
Complementary Index
Journal :
Wetlands Ecology & Management
Publication Type :
Academic Journal
Accession number :
145047337
Full Text :
https://doi.org/10.1007/s11273-020-09735-y