Decomposition analysis on soybean productivity increase under elevated CO2 using 3-D canopy model reveals synergestic effects of CO2 and light in photosynthesis.

BACKGROUND AND AIMS: Understanding how climate change influences crop productivity helps in identifying new options to increase crop productivity. Soybean is the most important dicotyledonous seed crop in terms of planting area. Although the impacts of elevated atmospheric [CO2] on soybean physiology, growth and biomass accumulation have been studied extensively, the contribution of different factors to changes in season-long whole crop photosynthetic CO2 uptake [gross primary productivity (GPP)] under elevated [CO2] have not been fully quantified. METHODS: A 3-D canopy model combining canopy 3-D architecture, ray tracing and leaf photosynthesis was built to: (1) study the impacts of elevated [CO2] on soybean GPP across a whole growing season; (2) dissect the contribution of different factors to changes in GPP; and (3) determine the extent, if any, of synergism between [CO2] and light on changes in GPP. The model was parameterized from measurements of leaf physiology and canopy architectural parameters at the soybean Free Air CO2 Enrichment (SoyFACE) facility in Champaign, Illinois. KEY RESULTS: Using this model, we showed that both a CO2 fertilization effect and changes in canopy architecture contributed to the large increase in GPP while acclimation in photosynthetic physiological parameters to elevated [CO2] and altered leaf temperature played only a minor role in the changes in GPP. Furthermore, at early developmental stages, elevated [CO2] increased leaf area index which led to increased canopy light absorption and canopy photosynthesis. At later developmental stages, on days with high ambient light levels, the proportion of leaves in a canopy limited by Rubisco carboxylation increased from 12.2 % to 35.6 %, which led to a greater enhancement of elevated [CO2] to GPP. CONCLUSIONS: This study develops a new method to dissect the contribution of different factors to responses of crops under climate change. We showed that there is a synergestic effect of CO2 and light on crop growth under elevated CO2 conditions.

MORE EFFICIENT PLANTS: A Consequence of Rising Atmospheric CO2?

The primary effect of the response of plants to rising atmospheric CO2 (Ca) is to increase resource use efficiency. Elevated Ca reduces stomatal conductance and transpiration and improves water use efficiency, and at the same time it stimulates higher rates of photosynthesis and increases light-use efficiency. Acclimation of photosynthesis during long-term exposure to elevated Ca reduces key enzymes of the photosynthetic carbon reduction cycle, and this increases nutrient use efficiency. Improved soil-water balance, increased carbon uptake in the shade, greater carbon to nitrogen ratio, and reduced nutrient quality for insect and animal grazers are all possibilities that have been observed in field studies of the effects of elevated Ca. These effects have major consequences for agriculture and native ecosystems in a world of rising atmospheric Ca and climate change.

Primary Production in Grasslands and Coniferous Forests with Climate Change: An Overview.

In energy terms primary production is the driving step of the global carbon cycle. To predict the interaction of ecosystems with the "greenhoude" effect, it is necessary to understand how primary production, consumption, and decomposition will respond to climate change. Most estimates of primary production have been made by extrapolation from measured standing crops. For grasslands we show this approach to be seriously in error. Even where detailed studies of turnover and belowground production have been undertaken, errors are invariably high, severely limiting the value of models based on correlation of climate with measured production. Detailed information is available on the responses of individual plant processes to individual climatic variables at the leaf, plant, and stand level, giving potential for a more mechanistic approach in modelling. This approach is limited by lack of information on multivariate interactions and on some key physiological processes, and by uncertainties in scaling up to populations and communities. Despite this, some important insights to possible community responses, particularly those of C3 and C4 types, may be gained from knowledge of responses at the plant level and below. This review outlines the expected character of climate change in grasslands and coniferous forests. Knowledge of the responses of different physiological processes underlying production to individual aspects of climate change is considered, and its implications for higher levels of organization are discussed. Although feasible, mechanistic models of production compound the errors associated with individual process responses with uncertainties surrounding interaction and scaling up, and result in very large errors in any prediction of response to climate change. We conclude that there is insufficient information to predict accurately the response of primary production to climate change. The key processes for which information is inadequate and the parameters that have meaning at different scales need to be identified. Of particular promise is the approach of predicting production from light interception and conversion efficiency.