Hyperspectral Reflectance for Measuring Canopy-Level Nutrients and Photosynthesis in a Salt Marsh

Salt marsh ecosystems are underrepresented in process-based models due to their unique location across the terrestrial-aquatic interface. Particularly, the role of leaf nutrients on canopy photosynthesis (F-A) remains unclear, despite their relevance for regulating vegetation growth. We combined multiyear information of canopy-level nutrients and eddy covariance measurements with canopy surface hyperspectral remote sensing (CSHRS) to quantify the spatial and temporal variability of F-A in a temperate salt marsh. We found that F-A showed a positive relationship with canopy-level N at the ecosystem scale and for areas dominated by Spartina cynosuroides, but not for areas dominated by short S. alterniflora. F-A showed a positive relationship with canopy-level P, K, and Na, but a negative relationship with Fe, for areas associated with S. cynosuroides, S. alterniflora, and at the ecosystem scale. We used partial least squares regression (PLSR) with CSHRS and found statistically significant data-model agreements to predict canopy-level nutrients and F-A. The red-edge electromagnetic region and similar to 770 nm showed the highest contribution of variance in PLSR models for canopy-level nutrients and F-A, but we propose that underlying sediment biogeochemistry can complicate interpretation of reflectance measurements. Our findings highlight the relevance of spatial variability in salt marshes vegetation and the promising application of CSHRS for linking information of canopy-level nutrients with F-A. We call for further development of canopy surface hyperspectral methods and analyses across salt marshes to improve our understanding of how these ecosystems will respond to global environmental change.