Using a multi-scale approach to synthesize measurements and models of C4 photosynthesis Active

Plants convert carbon dioxide into sugars for food during photosynthesis, and this provides food for all animal life. However, photosynthesis is inhibited when a plant’s enzymes use oxygen instead of carbon dioxide. To avoid this use of oxygen, some plants developed a photosynthetic adaptation – called C4 photosynthesis – to concentrate carbon dioxide around the enzymes. While less than 5% of plants use the C4 photosynthetic pathway, they make up ~20% of global terrestrial gross primary productivity. Due to their high productivity, C4 plants have a profound impact on ecosystems, economies, the carbon cycle, and our climate. Corn and sugarcane are both C4 plants, as are foundational western livestock and wildlife forage, making C4 grasses economically important. Several C4 plants, like buffelgrass, are noxious and/or invasive. Despite their importance, there is currently only a limited ability to predict the productivity, ecological resilience, and distribution of C4 plants in the face of environmental change. How will C4 plants respond to future temperatures, precipitation, and land use? What is the impact of their responses on regional-to-global productivity and the composition of terrestrial communities? The answers to these questions are imperative for creating forecasts that can inform effective adaptation and mitigation strategies that agronomists and land managers can implement to manage ecosystems for food, forage, and invasion by exotic species.  

We will conduct the first comprehensive analysis to evaluate and improve predictions of C4 photosynthesis in regional and global scale models, synthesizing data to advance our basic understanding of C4 ecology and our ability to improve the representation of C4 photosynthesis in models. To accomplish this, we will use two complementary activities: 1) Synthesize existing C4 photosynthetic data, including measurements under ambient and manipulated environmental conditions to evaluate current C4 models; and 2) Compare the current representation of C4 photosynthesis across models and evaluate them against the synthesized observational data. These activities will produce actionable information, datasets, and tools that land managers and policy makers can use to manage C4 plants under changing environmental conditions.