Lara Souza1, Abhijit Karve2, David J. Weston2, Gregory M. Crutsinger3, Nathan J. Sanders1, and Aimee Classen4. (1) University of Tennessee, (2) Oak Ridge National Laboratory, (3) University of California Berkeley, (4) University of Tennessee, Knoxville
Background/Question/Methods Understanding plant physiological constraints to heat stress may help to predict the responses of plants to climate change. Using growth chamber experiments and a common garden experiment we asked two fundamental questions about within-species variation in constraints to heat stress in tall goldenrod, Solidago atlissima: (1), Is it possible to predict carbon gain at different levels of biological organization (from the cell to the whole plant)? under warming scenarios and (2) Does variation in cell-level carbon gain scale whole ecosystem carbon gain across populations? We collected Solidago genotypes from northern and southern latitude populations and exposed individual genotypes to a gradient in temperatures ranging from 14 °C to 42 °C. We measured cell-level production of reactive oxygen species, and total antioxidant capacity), leaf-level (carbon gain), and plant-level responses (net ecosystem carbon exchange).
Results/Conclusions We found intraspecific variation in temperature response at the cell level where both reactive oxygen species and total antioxidant capacity were 35% and 30% greater in southern than northern genotypes. In addition, leaf-level carbon gain in southern genotypes was 25% lower than in northern genotypes at higher temperatures. This is due, in part, to reduced maximal Rubisco activity, a photosynthetic enzyme that catalyzes CO2. These cell – and leaf-level patterns do not scale to the field -- perhaps because of increased total leaf area in the southern genotypes. These data indicate that intraspecific variation in physiological constraints to heat stress at lower-levels of biological organization are not predictive at the ecosystem-scale. They also suggest that when investigating plant responses to climate change one needs to measure across scales to better predict future constraints.