Radiometric approach for the detection of picophytoplankton assemblages across oceanic fronts.

Area of Science:

• Oceanography
• Marine Ecology
• Remote Sensing

Background:

• Phytoplankton, including Prochlorococcus, Synechococcus, and picoeukaryotes, are crucial to marine ecosystems.
• Estimating the abundance and distribution of these microorganisms is vital for understanding ocean dynamics.
• Previous methods often lack the spatial or spectral resolution to accurately map these small but significant organisms.

Purpose of the Study:

• To develop and validate models for estimating cell abundances of key phytoplankton groups in surface waters.
• To utilize principal component analysis (PCA) with remote-sensing reflectance data for abundance estimation.
• To assess the performance of hyperspectral versus multispectral data for this application.

Main Methods:

• Developed models correlating cell abundances with PCA scores and sea surface temperature.
• Employed multilinear regression using hyperspectral and multispectral remote-sensing reflectance data.
• Validated satellite-derived estimates against extensive in-situ data from Atlantic Meridional Transect cruises.

Main Results:

• Successfully mapped Prochlorococcus abundances in the Equatorial Convergence Zone and oceanic gyres.
• Identified shifts in phytoplankton dominance, with Synechococcus thriving in temperate waters and picoeukaryotes emerging.
• Demonstrated good model performance (R2 > 0.50) using satellite data, especially with hyperspectral information.
• Detected fine-scale Synechococcus patches using in-situ sampling for model training.

Conclusions:

• Remote sensing, particularly with hyperspectral capabilities, can effectively estimate phytoplankton abundances.
• Future missions like NASA's PACE will enhance spatiotemporal knowledge of phytoplankton assemblages.
• Understanding phytoplankton distribution is key to comprehending marine ecosystem functioning and biogeochemical cycles.