Observations of land surface reflectance in visible and near-infrared wavelengths provide a key strategy to monitor photosynthetic processes across wide temporal and spatial scales, though most approaches remain largely empirical. An approach that incorporates current understanding of land-radiation interactions and plant function across a range of ecological conditions is lacking, which slows our transition toward a more mechanistic understanding of the reflectance-photosynthesis relationship. We used coupled models describing leaf and canopy radiation transfer and canopy photosynthesis to identify vegetation traits that link reflectance to ecosystem photosynthesis. Multi-year eddy covariance and in situ remote sensing data for sites over a large ecological gradient in California were used to explore the patterns of reflectance vs photosynthesis among ecosystem types. Our ultimate goal is to understand the reflectance vs photosynthesis relationship over the natural variation of traits across ecosystem types.
Results/Conclusions
In addition to the widely recognized importance of chlorophyll content and leaf area index, our analysis identified leaf mass per area (LMA) as key trait that strongly drives surface reflectance, especially on the near infrared wavelengths. Variation in LMA across ecosystem types modified the relationships between reflectance and ecosystem photosynthesis, a pattern that was broadly supported by field observations from eddy covariance and in situ remote sensing. We discuss the possibility that LMA, especially in coordination with related traits across the leaf economic spectrum, is central to the reflectance vs photosynthesis relationship and represents a key link between plant-radiation interactions and plant investment in resource acquisition.