Vázquez-Lule, AlmaSeyfferth, Angelia L.Limmer, Matt A.Mey, PaulGuevara, MarioVargas, Rodrigo2023-01-052023-01-052022-11-04Vázquez-Lule, A., Seyfferth, A. L., Limmer, M. A., Mey, P., Guevara, M., & Vargas, R. (2022). Hyperspectral reflectance for measuring canopy-level nutrients and photosynthesis in a salt marsh. Journal of Geophysical Research: Biogeosciences, 127, e2022JG007088. https://doi.org/10.1029/2022JG0070882169-8961https://udspace.udel.edu/handle/19716/31986An edited version of this paper was published in Journal of Geophysical Research: Biogeosciences by AGU. Copyright 2022 American Geophysical Union. The version of record is available at: https://doi.org/10.1029/2022JG007088. This article will be embargoed until 05/04/2023.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 (FA) 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 FA in a temperate salt marsh. We found that FA 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. FA 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 FA. The red-edge electromagnetic region and ∼770 nm showed the highest contribution of variance in PLSR models for canopy-level nutrients and FA, 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 FA. 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. Plain Language Summary Canopy photosynthesis in salt marshes contributes to the carbon stored in these ecosystems; however, its relationship with canopy-level nutrients has been underrepresented in models. Reflectance from near surface remote sensing could be a cost-effective nondestructive tool to monitor canopy photosynthesis and associated nutrients in salt marshes. We combined canopy-level nutrient information with hyperspectral canopy reflectance to represent the spatial and temporal variability of canopy photosynthesis in a salt marsh in the Mid-Atlantic cost of the U.S. We found that local variability such as different salt marsh species have an influence on the relationship between canopy photosynthesis and associated nutrients, in consequence the most limiting nutrients for photosynthesis were phosphorus, potassium, and sodium. We propose that underlying sediment biogeochemistry can potentially obscure the expected relationships between plant nutrients and photosynthesis in remote sensing of coastal wetlands. These results open the possibility to use similar reflectance information from airborne or spaceborne platforms to explore these relationships at broader scales. Key Points - Local environmental variability influences the relationship of canopy nutrients with canopy photosynthesis in a salt marsh ecosystem - Sediment biogeochemistry can obscure expected relationships between plant nutrients and photosynthesis in remote sensing of coastal wetlands - Canopy surface hyperspectral remote sensing is a promising technique for studying vegetation dynamics of salt marshesen-USblue carbongross primary productivityproximal remote sensingcoastal vegetationgrassesplant nutrientsArticle