Simultaneous and accurate measurements of whole-plant instantaneous carbon-use efficiency (ICUE) and annual total carbon-use efficiency (TCUE) are difficult to make, especially for trees. One usually estimates ICUE based on the net photosynthetic rate or the assumed proportional relationship between growth efficiency and ICUE. However, thus far, protocols for easily estimating annual TCUE remain problematic. Here, we present a theoretical framework (based on the metabolic scaling theory) to predict whole-plant annual TCUE by directly measuring instantaneous net photosynthetic and respiratory rates. This framework makes four predictions, which were evaluated empirically using seedlings of nine Picea taxa: (i) the flux rates of CO(2) and energy will scale isometrically as a function of plant size, (ii) whole-plant net and gross photosynthetic rates and the net primary productivity will scale isometrically with respect to total leaf mass, (iii) these scaling relationships will be independent of ambient temperature and humidity fluctuations (as measured within an experimental chamber) regardless of the instantaneous net photosynthetic rate or dark respiratory rate, or overall growth rate and (iv) TCUE will scale isometrically with respect to instantaneous efficiency of carbon use (i.e., the latter can be used to predict the former) across diverse species. These predictions were experimentally verified. We also found that the ranking of the nine taxa based on net photosynthetic rates differed from ranking based on either ICUE or TCUE. In addition, the absolute values of ICUE and TCUE significantly differed among the nine taxa, with both ICUE and temperature-corrected ICUE being highest for Picea abies and lowest for Picea schrenkiana. Nevertheless, the data are consistent with the predictions of our general theoretical framework, which can be used to access annual carbon-use efficiency of different species at the level of an individual plant based on simple, direct measurements. Moreover, we believe that our approach provides a way to cope with the complexities of different ecosystems, provided that sufficient measurements are taken to calibrate our approach to that of the system being studied.
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http://dx.doi.org/10.1093/treephys/tpv030 | DOI Listing |
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School of Energy & Environmental Engineering, Hebei University of Technology, Tianjin, 300401, China. Electronic address:
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Department of Agriculture, Food, Environment and Forestry (DAGRI), University of Florence, Viale delle idee 30, 50019 Sesto Fiorentino, Florence, Italy.
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