Temporal and plant-structural constraints for eco-evolutionary optimality models

Quantifying leaf transpiration and photosynthesis is crucial for modeling global vegetation in a changing climate, but deriving general relationships and responses to environmental drivers across time scales remains challenging. A promising new approach to predict general leaf trait responses is the P-model (Prentice et al., 2014), which is based on eco-evolutionary optimality (EEO) theory. Leaf-level optimality is defined as the optimal ratio of leaf internal CO2 partial pressure to ambient CO2 partial pressure, resulting in maximum assimilation while minimizing respiration and transpiration costs. This process is coordinated via changes in both stomatal conductance and photosynthetic biochemistry, and results in a fundamental model with a strong dependency on climatic variables including temperature, relative humidity, CO2 levels, and light quantity. The P-model currently predicts instantaneous changes in leaf-level traits of photosynthesis and gas exchange without explicitly considering timescales of adaptation and acclimation, and the associated ranges of phenotypic plasticity of individual plants. It is also limited/confined to leaf-level traits, without considering whole-plant processes, like resource allocation. Thus, it is uncertain how leaf-level optimality and their related costs translate to organ level carbon and nitrogen allocation.

Our work focuses on further developing and evaluating the P-model by incorporating time scales of acclimation and adaptation, as well as upscaling leaf-level traits to whole-plant traits. To achieve these aims, we first developed a theoretical framework which allows the distinction of different timescales. Using a literature review, we identified and highlighted the tight relationship between leaf traits across timescales, and we also identified constraints on key leaf-level EEO optimality traits, and the timescales at which these constraints occur. We then propose a new framework to separate these responses at physiological, developmental, and evolutionary timescales. Second, we performed experimental work in order to evaluate the link between leaf-level optimality and whole-plant acclimation. Our experiments showed a strong response in whole-plant resource allocation to nutrient availability while leaf-level optimality was unresponsive to the nutrient treatments. This indicates that while leaf-level optimality is regulated mainly by climatic variables, whole-plant performance is strongly influenced by below-ground resource availability.

This research is a way forward in bridging plant ecophysiology and vegetation modeling, while acknowledging timescales and plasticity ranging from meteorology to deep time climate research. This work can be used to further develop EEO-modeling, and specifically the P-model.