An in-depth analysis of the impact of environmental drivers on the variability of phytoplankton community in Arabian Sea in 2010–2021

• Published in: Environmental science--processes & impacts 2025
• Main Authors: Ali, Syed Moosa, Kuttippurath, Jayanarayanan, Krishna, Aswathy Vijaya, Gupta, Anurag, Anjaneyan, P, Mini, Raman, Babu, K.N.
• Format: Article
• Language: English
• ISSN: 2050-7887; 2050-7895
• DOI: 10.1039/D4EM00385C

This study investigates long-term changes in phytoplankton size classes (PSC) in the Arabian Sea (AS) using 12 years (2010–2021) of remote sensing reflectance (Rrs) data from the Moderate Resolution Imaging Spectroradiometer (MODIS). The Rrs spectra were inverted to derive Chlorophyll-a (Chl-a) concentrations through a non-linear optimization method, which were then utilized to estimate PSC using a region-specific three-component model. The analyses are conducted for the four seasons: winter (December to February), pre-monsoon (March to May), monsoon (June to September), and post-monsoon (October to November). A machine learning random forest (RF) model is employed to predict both seasonal and long-term variability in PSC and to quantify the influence of environmental drivers. The seasonal climatology reveals that micro-phytoplankton predominantly occupy the northern AS during winter and pre-monsoon seasons, contributing over 50% to total Chl-a. During the monsoon, a significant increase in micro-phytoplankton contribution (60–80%) is observed off the coasts of Somalia, Oman, and Kerala due to strong upwelling. In contrast, contributions from nano-phytoplankton are minimal during the pre-monsoon but remained relatively stable in other seasons, while pico-phytoplankton dominate the oligotrophic waters of central and southern AS during pre- and post-monsoon. Analysis from 2010 to 2021 reveals a strong decreasing trend in micro-phytoplankton concentration (-0.13 ± 0.19 mg m⁻³ yr⁻¹), accompanied by steady increases in pico- (0.0009 ± 0.0005 mg m⁻³ yr⁻¹) and nano-phytoplankton (0.001 ± 0.0009 mg m⁻³ yr⁻¹). The random forest model identifies key environmental drivers, with sea surface temperature (SST) emerging as the most influential factor affecting pico- and micro-phytoplankton. The highest importance scores for SST occurr during winter and pre-monsoon, highlighting the sensitivity of these classes to temperature changes. Additionally, the model emphasizes the roles of mixed layer depth (MLD) and wind speed (WS) in driving seasonal shifts in PSC, particularly during the monsoon and post-monsoon periods. These findings suggest that rising SST, along with changes in vertical mixing and stratification, drives the shift toward smaller cells, primarily pico-phytoplankton. This trend indicates a potential decline in marine food chain efficiency, reduced carbon export rates, and diminishing primary productivity, raising concerns for food security in the AS region.