Ecophysiology and multivariate analysis for production of Tachigali vulgaris in Brazil: Influence of rainfall seasonality and fertilization
Studies on fertilization management of species native to the Amazon for energy plantations contribute to the diversity of species use and reduce biological risk due to the excessive use of clones or hybrids of Eucalyptus. This study evaluates the effect of precipitation seasonality and phosphorus an...
Saved in:
Published in | Journal of forestry research Vol. 34; no. 5; pp. 1289 - 1305 |
---|---|
Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
Singapore
Springer Nature Singapore
01.10.2023
Springer Nature B.V Universidade Federal de Mato Grosso,Campus Universitário de Sinop,Sinop 78550728,Mato Grosso,Brazil%Universidade Federal Rural da Amaz?nia,Campus Belém,Belém 66077830,Pará,Brazil%Universidade do Estado do Pará,Centro de Ciências Naturais e Tecnologia,Belém 66095015,Pará,Brazil%Universidade Federal Rural da Amaz?nia,Campus Capit?o-Po?o,Capit?o Po?o 68650000,Pará,Brazil |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | Studies on fertilization management of species native to the Amazon for energy plantations contribute to the diversity of species use and reduce biological risk due to the excessive use of clones or hybrids of
Eucalyptus.
This study evaluates the effect of precipitation seasonality and phosphorus and potassium fertilization on gas exchange in a
Tachigali vulgaris
plantation. Three levels of P (zero, 65.2, 130.4 kg ha
−1
) and three of K (zero, 100.0, 200.0 kg ha
−1
) were applied in a 3 × 3 factorial randomized block design. Gas exchange measurements were conducted in April and November 2018. In low rainfall, high irradiance period, photosynthetic rates were up to four times higher than in the high rainfall period, reaching 20.3 μmol m
−2
s
−1
in the treatment with 130.4 g kg
−1
of P and 100.0 g kg
−1
of K. Factor analysis and principal component analysis reduced the initial eight gas exchange variables to two and three principal components in periods of high and low rainfall, respectively. The multivariate method used in this study readily identified variations in the variables as a function of rainfall, with high reliability in explaining the data set. |
---|---|
ISSN: | 1007-662X 1993-0607 |
DOI: | 10.1007/s11676-023-01611-8 |