Temperature responses of leaf net photosynthesis: the role of component processes
Yan-Shih Lin1, Belinda E Medlyn, David S Ellsworth
1Hawkesbury Institute for the Environment, University of Western Sydney-Hawkesbury Campus, Locked Bag 1797, Penrith, NSW 2751, Australia. y.lin@uws.edu.au
Abstract:
The response of photosynthesis to temperature is a central facet of plant response to climate. Such responses have been found to be highly variable among species and among studies. Understanding this variability is key when trying to predict the effects of rising global temperatures on plant productivity. There are three major factors affecting the response of leaf net photosynthesis to temperature (A(n)-T): (i) photosynthetic biochemistry, (ii) respiration and (iii) vapour pressure deficit (D) and stomatal sensitivity to vapour pressure deficit during measurements. The overall goal of our study was to quantify the relative contribution of each of these factors in determining the response of A(n) to temperature. We first conducted a sensitivity analysis with a coupled photosynthesis-stomatal (A(n)-g(s)) model, using ranges for parameters of each factor taken from the literature, and quantified how these parameters affected the A(n)-T response. Second, we applied the A(n)-g(s) model to two example sets of field data, which had different optimum temperatures (T(opt)) of A(n), to analyse which factors were most important in causing the difference. We found that each of the three factors could have an equally large effect on T(opt) of A(n). In our comparison between two field datasets, the major cause for the difference in T(opt) was not the biochemical component, but rather the differences in respiratory components and in D conditions during measurements. We concluded that shifts in A(n)-T responses are not always driven by acclimation of photosynthetic biochemistry, but can result from other factors. The D conditions during measurements and stomatal responses to D also need to be quantified if we are to better understand and predict shifts in A(n)-T with climate.
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