Proximal remote sensing and gross primary productivity in a temperate salt marsh

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cg.contributor.affiliationCenter for International Forestry Researchen_US
cg.contributor.affiliationUniversity of Delawareen_US
cg.coverage.countryUnited Statesen_US
cg.coverage.iso3166-alpha2USen_US
cg.identifier.doihttps://doi.org/10.1016/j.agrformet.2023.109639en_US
cg.isijournalISI Journalen_US
cg.issn0168-1923en_US
cg.journalAgricultural and Forest Meteorologyen_US
cg.reviewStatusPeer Reviewen_US
cg.subject.sdgSDG 13 - Climate actionen_US
cg.volume341en_US
dc.contributor.authorVázquez-Lule, A.en_US
dc.contributor.authorVargas, R.en_US
dc.date.accessioned2024-06-13T05:02:09Zen_US
dc.date.available2024-06-13T05:02:09Zen_US
dc.identifier.urihttps://hdl.handle.net/10568/145216en_US
dc.titleProximal remote sensing and gross primary productivity in a temperate salt marshen_US
dcterms.abstractSalt marshes are highly productive ecosystems relevant for Blue Carbon assessments, but information for estimating gross primary productivity (GPP) from proximal remote sensing (PRS) is limited. Temperate salt marshes have seasonal canopy structure and metabolism changes, defining different canopy phenological phases, GPP rates, and spectral reflectance. We combined multi-annual PRS data (i.e., PhenoCam, discrete hyperspectral measurements, and automated spectral reflectance sensors) with GPP derived from eddy covariance. We tested the performance of empirical models to predict GPP from 12 common vegetation indices (VIs; e.g., NDVI, EVI, PSRI, GCC), Sun-Induced Fluorescence (SIF), and reflectance from different areas of the electromagnetic spectrum (i.e., VIS-IR, RedEdge, IR, and SIF) across the annual cycle and canopy phenological phases (i.e., Greenup, Maturity, Senescence, and Dormancy). Plant Senescence Reflectance Index (PSRI) from hyperspectral data and the Greenness Index (GCC) from PhenoCam, showed the strongest relationship with daily GPP across the annual cycle and within phenological phases (r2=0.30–0.92). Information from the visible-infrared electromagnetic region (VIS-IR) coupled with a partial least square approach (PLSR) showed the highest data-model agreement with GPP, mainly because of its relevance to respond to physiological and structural changes in the canopy, compared with indices (e.g., GCC) that particularly react to changes in the greenness of the canopy. The most relevant electromagnetic regions to model GPP were ∼550 nm and ∼710 nm. Canopy phenological phases impose challenges for modeling GPP with VIs and the PLSR approach, particularly during Maturity, Senescence, and Dormancy. As more eddy covariance sites are established in salt marshes, the application of PRS can be widely tested. Our results highlight the potential to use canopy reflectance from the visible spectrum region for modeling annual GPP in salt marshes as an example of advances within the AmeriFlux network.en_US
dcterms.accessRightsLimited Accessen_US
dcterms.bibliographicCitationVázquez-Lule, A. and Vargas, R., 2023. Proximal remote sensing and gross primary productivity in a temperate salt marsh. Agricultural and Forest Meteorology, 341, 109639. https://doi.org/10.1016/j.agrformet.2023.109639en_US
dcterms.extent109639en_US
dcterms.issued2023-10en_US
dcterms.languageenen_US
dcterms.licenseCopyrighted; all rights reserveden_US
dcterms.publisherElsevieren_US
dcterms.subjectremote sensingen_US
dcterms.subjectcarbon sequestrationen_US
dcterms.typeJournal Articleen_US

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