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Combining δ 13 C and δ 18 O analyses to unravel competition, CO 2 and O 3 effects on the physiological performance of different‐aged trees
Author(s) -
GRAMS THORSTEN E. E.,
KOZOVITS ALESSANDRA R.,
HÄBERLE KARLHEINZ,
MATYSSEK RAINER,
DAWSON TODD E.
Publication year - 2007
Publication title -
plant, cell and environment
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.646
H-Index - 200
eISSN - 1365-3040
pISSN - 0140-7791
DOI - 10.1111/j.1365-3040.2007.01696.x
Subject(s) - beech , photosynthesis , delta , fagus sylvatica , stomatal conductance , carbon dioxide , chemistry , botany , carbon 13 , horticulture , biology , ecology , physics , quantum mechanics , astronomy
Combined δ 13 C and δ 18 O analyses of leaf material were used to infer changes in photosynthetic capacity ( A max ) and stomatal conductance ( g l ) in Fagus sylvatica and Picea abies trees growing under natural and controlled conditions. Correlation between g l and δ 18 O in leaf cellulose ( δ 18 O cel ) allowed us to apply a semi‐quantitative model to infer g l from δ 18 O cel and also interpret variation in δ 13 C as reflecting variation in A max . Extraction of leaf cellulose was necessary, because δ 18 O from leaf organic matter ( δ 18 O LOM ) and δ 18 O cel was not reliably correlated. In juvenile trees, the model predicted elevated carbon dioxide (CO 2 ) to reduce A max in both species, whereas ozone (O 3 ) only affected beech by reducing CO 2 uptake via lowered g l . In adult trees, A max declined with decreasing light level as g l was unchanged. O 3 did not significantly affect isotopic signatures in leaves of adult trees, reflecting the higher O 3 susceptibility of juvenile trees under controlled conditions. The isotopic analysis compared favourably to the performance of leaf gas exchange, underlining that the semi‐quantitative model approach provides a robust way to gather time‐integrated information on photosynthetic performance of trees under multi‐faced ecological scenarios, in particular when information needed for quantitative modelling is only scarcely available.