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Semideciduous Seasonal Forest Production of Leaves and Deciduousness in Function of the Water Balance, LAI, and NDVI
Author(s) -
T. C. e C. da Costa,
J. H. M. Viana,
Juliana Leite Ribeiro
Publication year - 2014
Publication title -
international journal of ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.373
H-Index - 20
eISSN - 1687-9716
pISSN - 1687-9708
DOI - 10.1155/2014/923027
Subject(s) - deciduous , normalized difference vegetation index , plant litter , water balance , atmospheric sciences , environmental science , litter , leaf area index , mathematics , vegetation (pathology) , ecosystem , ecology , biology , physics , geology , medicine , geotechnical engineering , pathology
This study investigated the relationship between leaf production, litterfall, water balance, Leaf Area Index (LAI), and Normalized Difference Vegetation Index (NDVI) in semideciduous forests. The goal was to model this phenomenon to obtain the estimates of this component as an additional compartment of the ecosystem carbon sink. The tests were conducted in eight semideciduous forest fragments. Twenty-four permanent plots were monitored monthly and LAI measurements and weighing of litterfall deposited in nets were conducted for a period of thirteen months. In this period, Landsat 5 and IRS satellite images were obtained and processed for generation of NDVI. The water balance was calculated for each day. The relationship among the variables “leaf dry weight,” “LAI,” “NDVI,” and “water balance” was verified and a regression model was built and evaluated. The deciduous phenomenon can be explained by hydric balance, and LAI and NDVI are ancillary variables. The tendency of the variables in the period of 13 months was explained by quadratic functions. The varied behavior among the monitoring sites helped to know differences in the deposition of leaves. This study showed that only the leaf component of the litterfall of a semideciduous forest in tropical climate can capture 4 to 8 Mg·ha−1·yr−1 of CO2 and this amount can be estimated using climate, biophysics, and vegetation index variables

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