2008
DOI: 10.1007/s00468-008-0252-5
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Morphogenetic trends in the morphological, optical and biochemical features of phyllodes in Acacia mangium Willd (Mimosaceae)

Abstract: International audienceEndogenous variations in the annual growth of trees suggest that similar trends would occur in phyllodes. In comparison to leaves, the characteristics of phyllodes are less well known, hence this study examines the effects of architectural position and age of tree on the phyllodes of Acacia mangium. Phyllodes were investigated on 1-, 2-, and 3-year-old trees from three axis positions within the crown. We focused on the morphological, optical and biochemical traits of the phyllodes. The in… Show more

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Cited by 9 publications
(6 citation statements)
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“…For our study, the leaf mass area of the main stem (average of 0.019 g/cm 2 with a standard deviation of 0.002 g/cm 2 ) was higher than that of the branches (average of 0.014 g/cm 2 with a standard deviation of 0.003 g/cm 2 ). Our results back the results on the variability in leaf mass area linked to the architectural position and the axis category of the parent shoots (Leroy et al 2008).…”
Section: Estimation Of Leaf Dry Mass Based On the Product Of Leaf Lensupporting
confidence: 82%
“…For our study, the leaf mass area of the main stem (average of 0.019 g/cm 2 with a standard deviation of 0.002 g/cm 2 ) was higher than that of the branches (average of 0.014 g/cm 2 with a standard deviation of 0.003 g/cm 2 ). Our results back the results on the variability in leaf mass area linked to the architectural position and the axis category of the parent shoots (Leroy et al 2008).…”
Section: Estimation Of Leaf Dry Mass Based On the Product Of Leaf Lensupporting
confidence: 82%
“…The occurrence probabilities of each species were visualized on the SOM map in grey scale, and allowed us to analyse the effect of each species on the patterning input dataset (sites). The SOM was clustered using Ward's algorithm (Leroy et al, 2009). In order to bring out relationships between biological and environmental variables, we introduced the environmental variables into the SOM previously trained with bird occurrences (see Park et al, 2003).…”
Section: Methodsmentioning
confidence: 99%
“…The occurrence probabilities of each species were visualized on the SOM map in grey scale, and allowed us to analyse the effect of each species on the patterning input dataset (sites). The SOM was clustered using Ward's algorithm (Leroy et al, 2009). In arder to bring out relationships between biological and environmental variables, we introduced the environmental variables into the SOM previously trained with bird occurrences + + The 39 species recorded in our 11 gravel pits (Toulouse suburbs) appear in bold, + = presence.…”
Section: Methodsmentioning
confidence: 99%