Phytoplankton bloom detection and trends in satellite inherent optical properties over the last two decades in a heterogeneous Patagonian coastal system

ABSTRACT

To effectively address ecosystem health risks, it is crucial to use detection methods that efficiently cover vast areas with good spatial resolution. These methods should enhance understanding of how phytoplankton blooms might evolve due to climate change. Satellite Ocean Color sensors are advantageous for detecting and monitoring phytoplankton blooms over time. This study uses the Inherent Optical Properties (IOP) index, which considers light absorption by phytoplankton (Ab_phy) and by detritus plus colored dissolved organic matter (Ab_adg), to detect phytoplankton blooms in six subareas within the San Matías Gulf (SMG; Patagonia, Argentina). The findings reveal a significant increase in bloom alerts over the last 20 years in the northwestern and southwestern subareas. Temporal changes in chlorophyll a (Chla) and sea surface temperature (SST) were observed, both showing an increase over the studied period. Environmental features like the diffusive attenuation coefficient (Kd_490) and Ab_phy also showed positive trends in four of the six subareas. The positive trends in SST and Kd_490 suggest a potential reduction in the euphotic zone depth. Additionally, the presence of phytoplankton biomass, indicated by Chla and Ab_phy, is linked to reduced light penetration in the water column due to absorption by the cells and self-shading. A decrease in Ab_adg was observed, while photosynthetically active radiation (PAR) showed no significant trend over the last two decades. These patterns could significantly impact the frequency and timing of phytoplankton blooms, altering their community composition and phenology. Such changes have profound implications for the entire marine food web and the ecosystem services within the SMG. The results underscore the importance of incorporating optical data for monitoring phytoplankton blooms across multiple areas.

Acknowledgements

The authors thank the Ocean Biology Processing Group (Code 614.2) at the GSFC, Greenbelt, MD20 771, for the distribution of the ocean colour data. The work was supported by funding from the National Agency for Scientific and Technological Promotion (ANPCyT, Argentina) through projects PICT 2013 #0687 and 2019 # 00454 and partially funded by CONICET (Postdoctoral Grant to ACN).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The work was supported by the National Agency for Scientific and Technological Promotion (ANPCyT, Argentina) through project PICT 2019 # 00454 and partially funded by CONICET (postdoctoral Grant to ACN).