Publication Date:
2015-01-15
Description:
There is an increasing necessity to understand how climate change factors, particularly increasing atmospheric concentrations of CO 2 ([CO 2 ]) and rising temperature, will influence photosynthetic carbon assimilation ( A ). Based on theory, an increased [CO 2 ] concomitant with a rise in temperature will increase A in C3 plants beyond that of an increase in [CO 2 ] alone. However, uncertainty surrounding the acclimation response of key photosynthetic parameters to these changes can influence this response. In this work, the acclimation responses of C3 photosynthesis for soybean measured at the SoyFACE Temperature by Free Air CO 2 Enrichment (T-FACE) experiment is incorporated in a leaf biochemical and canopy photosynthesis model. The two key parameters used as model inputs, the maximum velocity for carboxylation ( V c,max ) and maximum rate of electron transport ( J max ), were measured in a full factorial [CO 2 ] by temperature experiment over two growing seasons and applied in leaf- and canopy-scale models to (1) reassess the theory of combined increases in [CO 2 ] and temperature on A , (2) determine the role of photosynthetic acclimation to increased growth [CO 2 ] and/or temperature in leaf and canopy predictions of A for these treatments, and (3) assess the diurnal and seasonal differences in leaf- and canopy-scale A associated with the imposed treatments. The results demonstrate that the theory behind combined increases in [CO 2 ] and temperature are sound, however, incorporating more recent parameterizations into the photosynthesis model predicts greater increases in A when [CO 2 ] and temperature are increased together. Photosynthetic acclimation is shown to decrease leaf-level A for all treatments, however, in elevated [CO 2 ] the impact of acclimation does not result in any appreciable loss in photosynthetic potential at the canopy scale. In this analysis, neglecting photosynthetic acclimation in heated treatments, with or without concomitant rise in [CO 2 ], leads to modeled over-estimates of carbon gain for soybean under future predicted conditions.
Print ISSN:
0886-6236
Electronic ISSN:
1944-9224
Topics:
Biology
,
Chemistry and Pharmacology
,
Geography
,
Geosciences
,
Physics
