Optical characterization of marine phytoplankton assemblages within surface waters of the western Arctic Ocean

Abstract

An extensive data set of measurements within the Chukchi and Beaufort Seas is used to characterize the optical properties of seawater associated with different phytoplankton communities. Hierarchical cluster analysis of diagnostic pigment concentrations partitioned stations into four distinct surface phytoplankton communities based on taxonomic composition and average cell size. Concurrent optical measurements of spectral absorption and backscattering coefficients and remote‐sensing reflectance were used to characterize the magnitudes and spectral shapes of seawater optical properties associated with each phytoplankton assemblage. The results demonstrate measurable differences among communities in the average spectral shapes of the phytoplankton absorption coefficient. Similar or smaller differences were also observed in the spectral shapes of nonphytoplankton absorption coefficients and the particulate backscattering coefficient. Phytoplankton on average, however, contributed only 25% or less to the total absorption coefficient of seawater. Our analyses indicate that the interplay between the magnitudes and relative contributions of all optically significant constituents generally dampens any influence of varying phytoplankton absorption spectral shapes on the total absorption coefficient, yet there is still a marked discrimination observed in the spectral shape of the ratio of the total backscattering to total absorption coefficient and remote‐sensing reflectance among the phytoplankton assemblages. These spectral variations arise mainly from differences in the bio‐optical environment in which specific communities were found, as opposed to differences in the spectral shapes of phytoplankton optical properties per se. These results suggest potential approaches for the development of algorithms to assess phytoplankton community composition from measurements of seawater optical properties in western Arctic waters.

Dynamic Satellite Seascapes as a Biogeographic Framework for Understanding Phytoplankton Assemblages in the Florida Keys National Marine Sanctuary, United States

“…Inverse correlations were observed between fucoxanthin and a phy ( 673)" (r = 0.46; p < 0.001), likely driven by dominance of large taxa with increasing seascape class (Figure 5); fucoxanthin is a diagnostic pigment of large phytoplankton groups such as diatoms. Several other studies have found a consistent effects of diatom concentrations on a phy spectra at this wavelength or in its close vicinity across different ocean regions (Werdell et al, 2014;Lorenzoni et al, 2015;Catlett and Siegel, 2018;Reynolds and Stramski, 2019).…”

Aquatic particulate absorption coefficient combining extraction and bleaching optimized for inland waters

“…For upcoming hyperspectral remote sensing platforms, maintaining all the spectral signatures as unbiased as possible is key for developing algorithms that can exploit the small nm‐level variations in the spectra (Giardino et al 2014), potentially allowing even the determination of phytoplankton community composition (Xi et al 2015; Zheng and DiGiacomo 2018; Reynolds and Stramski 2019). In this work, we describe a new approach of sequential methanol extraction and NaOCl bleaching that retrieves the NAP and algal fractions which, after appropriate fitting procedures, avoids most of the biases introduced by these methods separately.…”

Analysis and Classification of Stormwater and Wastewater Runoff From the Tijuana River Using Remote Sensing Imagery

“…Clusters that are considered more similar (i.e., shortest distance) are then used to generate larger clusters. Previous work has demonstrated the utility of HCA on water quality classifications and aquatic properties (Brezonik et al, 2005;Kamble and Vijay, 2011;Reynolds and Stramski, 2019).…”