Prostar

The software tool Prostar estimates terrestrial gross primary productivity (GPP), a crucial aspect of the global carbon cycle. Prostar uses chlorophyll fluorescence (ChlF), particularly with remote sensing data, to explore the seasonal relationships between ChlF and photosynthesis at different spatial scales. The study, conducted in a temperate deciduous forest at Harvard Forest, Massachusetts, establishes significant linear relationships between ChlF and photosynthesis at leaf, canopy, and satellite scales (R² = 0.73, 0.77, and 0.86, respectively; P < 0.0001). Prostar develops a model that estimates GPP from tower-based measurements of solar-induced chlorophyll fluorescence (SIF) and leaf-level ChlF parameters, demonstrating its potential for modeling GPP. Prostar identifies leaf Fq'/Fm' at the leaf scale as the best fluorescence parameter correlating with canopy SIF yield (R² = 0.79; P < 0.0001). Moreover, canopy SIF and SIF-derived GPP strongly correlate with leaf-level biochemistry and canopy structure, emphasizing the power of ChlF to track photosynthetic rates at various scales.