Factors Affecting the Oxygen Isotope Ratio of Plant Organic Material

Margaret M. Barbour, Lucas A. Cernusak, Graham D.

Farguhar

Early work by Epstein et al. (1977) showed that cellulose from aquatic plants was 27 ± 4%o more enriched in lsO than the water in which it grew. They explained the observed 27%o fractionation by suggesting that CO2 had been shown to be 41 %o more enriched than water at equilibrium, and that fixation of CO2 by Rubisco required one CO2 molecule and one H2O molecule (2/3 of 41 %o is about 27%o). However, DeNiro and Epstein (1979) later ruled out the 2/3 CO2 hypothesis by pointing out that one of the oxygen atoms added by CO2 fixation is lost in the photosynthetic carbon reduction cycle (PCR cycle). An alternate hypothesis was proposed by Sternberg and DeNiro (1983), who suggested that the oxygen atoms in water and those in organic molecules exchanged isotopically, allowing organic material (including cellulose) to reflect variation in plant water. Using acetone as a model molecule, they demonstrated that at equilibrium the organic molecule is 28%o more enriched in lsO than the water with which it exchanged. Hence, the oxygen isotope composition of plant organic material (<518Op) should largely reflect the oxygen isotope composition of plant water.

¿180 of water in plants changes as a result of: (1) variations in <5lsO of water taken up by plants; (2) leaf water enrichment in lsO during transpiration, the extent to which is dependent on the atmospheric conditions (relative humidity, and <5180 of water vapor in the atmosphere) and the stomatal regulation of water loss; and (3) variation in <5lsO of water in cells forming organic material (e.g., cellulose), which may be a mixture of unenriched source water and enriched leaf water. Variation in 5180 of plant organic material may also occur as a result of variation in the extent of iso-topic exchange between water and organic molecules during biosynthesis.

This chapter will outline current understanding of the factors affecting á18Op, formalize this understanding in mathematical models, and then describe potential applications of the technique.

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