Abstract
An approach that improves the spectral-based PHYSAT method for identifying phytoplankton functional types (PFT) in satellite ocean-color imagery is developed and applied to one study case. This new approach, called PHYSTWO, relies on the assumption that the dominant effect of chlorophyll-a (Chl-a) in the normalized water-leaving radiance (nLw) spectrum can be effectively isolated from the signal of accessory pigment biomarkers of different PFT by using Empirical Orthogonal Function (EOF) decomposition. PHYSTWO operates in the dimensionless plane composed by the first two EOF modes generated through the decomposition of a space–nLw matrix at seven wavelengths (412, 443, 469, 488, 531, 547, and 555 nm). PFT determination is performed using orthogonal models derived from the acceptable ranges of anomalies proposed by PHYSAT but adjusted with the available regional and global data. In applying PHYSTWO to study phytoplankton community structures in the coastal upwelling system off central Chile, we find that this method increases the accuracy of PFT identification, extends the application of this tool to waters with high Chl-a concentration, and significantly decreases (~60%) the undetermined retrievals when compared with PHYSAT. The improved accuracy of PHYSTWO and its applicability for the identification of new PFT are discussed.
Highlights
Phytoplankton Functional Types (PFTs) represent an operational division that combines highly diverse taxa into groups which share traits associated with ecological and/or biogeochemical functions [1]
PHYSAT is a pioneering method in the identification of PFTs using remote sensing retrievals of radiance reflectance spectra
Since the signal of Chl-a and non-chlorophyll pigments conform to different modes of the spectral variability retrieved by satellites, PHYSTWO separates these signal by employing an orthogonal decomposition of space–normalized water-leaving radiance (nLw) matrices constructed with satellite nLw information
Summary
Phytoplankton Functional Types (PFTs) represent an operational division that combines highly diverse taxa (species level) into groups which share traits (morphological, physiological, behavioral, and/or life-history) associated with ecological and/or biogeochemical functions (resource acquisition, predator avoidance, and metabolite production) [1]. The purpose of this division is to simplify community analyses and aid in the model building associated with climate change impacts on the biogeochemical and ecological components of oceans [2,3,4]. The development and validation of PFT methods rely on HPLC (High-Performance Liquid Chromatography) pigment-based proxies of taxonomic composition or size structure and there is a clear need to complement these validations with supplemental datasets, including flow-cytometry, microscopy, and size-fractionated estimates [10,18,19]
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