Scaling poses a fundamental challenge in studies that target the role of physiological processes across levels of biological organization—from individual organisms to populations and ecosystems. Plant physiological studies are often limited in sample size, and thus spatial and temporal coverage. Satellite remote sensing observations have traditionally been limited by resolution, and unable to distinguish leaves and other plant organs. Near-surface remote sensing of sun-induced chlorophyll fluorescence (SIF) promises estimation of gross photosynthesis from the sub-leaf scale to ecosystem scale — bridging the gap between traditional tools. However, most leaf- level studies demonstrating the link between chlorophyll fluorescence and photosynthesis have studied leaves in their prime: leaves that recently expanded and have yet to senesce. By contrast, remote sensing of ecosystems involves observing leaves of different ages. For example, broadleaf deciduous forests in temperate regions have leaves that develop and then senesce over the course of a growing season. How could changing leaf age demographics within canopies impact chlorophyll fluoresence alone and in the combination with stress?
In a greenhouse experiment, we explored how leaf age and moisture availability affect steady-state fluoresence (Fs) at the leaf level. We simultaneously measured net photosynthesis (Anet) and Fs for leaves of known ages on greenhouse-grown dwarf Helianthus annuus from two watering treatments.
Results/Conclusions
We found that fully expanded or near-fully expanded leaves (~8 to ~23 days old) had significantly higher Anet at saturating light than young, expanding leaves (less than 8 days old) or old leaves nearing senescence (>23 days old). We found a positive relationship between Fs and Anet (preliminary R2=0.25, P<0.05), suggesting that the link between fluorescence emission and photosynthesis is robust across leaves of different ages. However, leaf age also affected the response of nonphotochemical quenching to light. These results suggest that leaf age distribution, and changes in leaf age distribution due to phenology, should be considered when interpreting SIF at the landscape level. More generally, this case study highlights how the interpretation of SIF from proximal remote sensing of canopies requires accounting for multiples sources of leaf-level and plant-level variation.