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The spatiotemporal variability of chlorophyll-a (Chl-a) in the Arabian Sea (AS) and Persian Gulf (PG) has been widely studied, but long-term trends and influencing factors remain less understood due to data gaps. This study investigates Chl-a variability and trends from 2001 to 2019 using reconstructed MODIS-Terra monthly Chl-a and sea surface temperature (SST) data, employing the Data Interpolating Empirical Orthogonal Functions (DINEOF) method for high-accuracy reconstruction. Results reveal pronounced seasonal variability, with Chl-a peaks exceeding 3 mg m-3 during southwestern monsoons and ranging between 1–3 mg m-3 during northeastern monsoons, with the lowest levels in transitional months. Spatially, the highest Chl-a concentrations were observed in the western and northeastern AS, influenced by summer southwestern (SW) and winter northeastern (NE) monsoons. Trend analysis using Sen’s slope and the Mann-Kendall test indicates significant Chl-a declines (-0.002 to 0) along ASPG coasts, with slight increases (~0.005) in the southeastern AS and southern PG. Rising SST anomalies (SST_A) correlated with reduced Chl-a anomalies (Chl-a_A) in the western AS, while increased wind anomalies (Wind_A) enhanced Chl-a_A in the western AS but decreased it in the southern PG. These findings enhance our understanding of the complex environmental dynamics shaping the ASPG ecosystems.

In recent decades, red tides of non-toxic harmful algal blooms have frequently occurred in monsoon-influenced tropical areas, particularly the green form of Noctiluca scintillans (hereafter green Noctiluca). However, our understanding of the mechanism of red tide formation is hindered by spatial and temporal constraints of field data. In this study, we used moderate resolution imaging spectroradiometer (MODIS) ocean color data along with a locally developed algal-bloom classification algorithm to investigate the seasonal variability of dominant red tides across the upper Gulf of Thailand (uGoT). During our July 2018 observation, a super green Noctiluca bloom with extraordinarily high chl-a (>1,469 mg m-3) displayed a distinct spectral reflectance characteristic among red tides in blue-to-green and red-to-near infrared wavelengths. According to the distinctive in situ hyperspectral characteristics of uGoT algal blooms, we developed a classification algorithm for MODIS normalized at 488, 531, and 667 nm, which successfully discriminated green Noctiluca in three levels of blooms, namely, super (100%), strong (>80%), and weak (>40%), from other algal blooms (i.e., dinoflagellates, diatoms, cyanobacteria, and mixed red tide species) as well as non-bloom oceanic and coastal waters using MODIS data, as confirmed by uGoT red tide reports. Monthly MODIS-based discrimination composites from 2003 to 2021 revealed seasonal variability in the surface distribution and bloom frequency of green Noctiluca and other red tides according to the Asian monsoon seasons: the southwest monsoon (May–September) and the northeast monsoon (October–January of the following year). Green Noctiluca blooms occurred farther from the shore and estuaries than other red tides (dinoflagellates and cyanobacteria), and were much more frequent than other red tides between the Tha Chin and Chao Phraya River mouths during the non-monsoon period (February to April). The frequency and distribution of green Noctiluca blooms, as well as other algal blooms, varied with the monsoon season. By comparing MODIS-derived algal blooms to monsoon-induced factors (i.e., sea surface winds, precipitation, and river discharge), we present an unprecedented overview of the spatial and temporal dynamics of red tides throughout the uGoT under Asian monsoon conditions. This research contributes to our understanding of the impact of climate change on phytoplankton dynamics.

This study investigated the seasonal variability of surface chlorophyll-a (chl-a) and the influence of the El Niño Southern Oscillation (ENSO) related to environmental parameters in the Gulf of Thailand (GoT). Monthly chl-a data from MODIS from 2002 to 2020 as well as sea surface temperature (SST), wind, precipitation, and river discharge were used in this analysis. Results from seasonal climatology and Empirical Orthogonal Function (EOF) described high chl-a concentration areas along the western to the southern coasts and near Ca Mau Cape during the northeast monsoon (NEM), and the upper GoT (UGoT), eastern coast, and the GoT mouth during the southwest monsoon (SWM), while low chl-a took place during the non-monsoon (NON). The GoT was divided into six areas based on the EOFs of chl-a, and then the correlation between chl-a variability and environmental parameters was also examined. The results suggested that chl-a in coastal and offshore areas were controlled by different mechanisms. Chl-a in coastal areas responded to precipitation and river discharge as well as the shoreward wind; meanwhile, chl-a in offshore areas correlated with SST and wind magnitude indicating the importance of water mixing and upwelling. The fluctuation of chl-a in each season related to ENSO was captured by EOF based on the seasonal anomaly. The influence of ENSO was strong during NEM and NON but minimal during SWM. El Niño/La Niña generally caused low/high precipitation and high/low SST. Moreover, El Niño/La Niña caused anomalously weak/strong wind during NEM contrary to during NON. Anomalous high/low chl-a were observed in shallow regions during El Niño/La Niña corresponding to strong/weak wind in NON. Abnormal wind under ENSO also created the shifting in the high chl-a area near Ca Mau Cape. These results have improved our understanding of monsoons and ENSO variabilities as the crucial drivers of changes in the tropical marine ecosystem in both seasonal and interannual time scales.

Vertical distribution of phytoplankton composition in the East China Sea (ECS) and Tsushima Strait (TS) was highly variable in the region where the Changjiang River diluted water (CDW), Kuroshio water (KW), and Tsushima water (TW) intersected. An in-situ multiple excitation fluorometer was used to obtain the high-resolution phytoplankton groups data from every meter of the water column. Sharp differences were noted in the distribution of phytoplankton groups in the CDW, KW, and TW. In the CDW, brown algae were generally present ~60% of all depths with exception of subsurface chlorophyll-a maximum (SCM), whereas cyanobacteria (>40%) and green algae plus cryptophytes (>40%) were found above and below the SCM, respectively. In TW, where chlorophyll a (CHL) was lower than in the CDW, brown algae predominated the water column (>60%) and SCM (>80%), except the surface layer where cyanobacteria dominated. In KW, a high fraction of cyanobacteria (>40%) extended up to 40 m, while brown and green algae dominated (>60%) the deeper waters below 40 m at western and eastern stations, respectively. These results can be further related to water property and nutrient concentration of the water masses in each region. This new data show that the in-situ multiple excitation fluorometer can be a powerful tool to estimate high-resolution vertical profiles of phytoplankton groups on a large scale in marine environments.

Predicting conversion of photosynthetic electron transport to inorganic carbon uptake rates (the so-called electron requirement for carbon fixation, KC) is central to the broad scale deployment of Fast Repetition Rate fluorometry (FRRf) for primary productivity studies. However, reconciling variability of KC over space and time to produce robust algorithms remains challenging, given the large number of factors that influence KC. We have previously shown that light appears to be a proximal driver of Kc in several ocean regions and we therefore examined whether and how light similarly regulated KC variability in the Arctic Ocean, during a summer cruise in 2016. Sampling transited ice-free and ice-covered waters, with temperature, salinity and Chl-a concentrations all higher for the ice-free than ice covered surface waters. Micro- and pico-phytoplankton generally dominated the ice-free and ice-covered waters, respectively. Values of KC, determined from parallel measures of daily integrated electron transport rates and 14C-uptake, were overall lower for the ice-covered vs. ice-free stations. As in our previous studies, KC was strongly linearly correlated to daily PAR (r = 0.68, n = 46, p < 0.001) and this relationship could be further improved (r = 0.84, n = 46, p < 0.001) by separating samples into ice-free (micro-phytoplankton dominated) vs. ice-covered (Nano- and Pico-phytoplankton dominated water. We subsequently contrasted the PAR-KC relationship form the Arctic waters with the previous relationships from the Ariake Bay and East China Sea and revealed that these various PAR-KC relationships can be systematically explained across regions by phytoplankton community size structures. Specifically, the value of the linear slope describing PAR-KC decreases as water bodies have an increasing fraction of larger phytoplankton. We propose that this synoptic trend reflects how phytoplankton community structure integrates past and immediate environmental histories and hence may be a better broad-scale predictor of KC than specific environmental factors such as temperature and nutrients. We provide a novel algorithm that may enable broad-scale retrieval of CO2 uptake from FRRf with knowledge of light and phytoplankton community size information.

Riverine nutrients act in concert with local hydrographic conditions to create distinct ecological niches for phytoplankton communities across river-ocean continuums. Here we compare two of the world’s largest river-ocean systems, the Amazon River Plume (ARP) which outflows into the Western Tropical North Atlantic and the Changjiang Diluted Water (CDW) which empties into the East China Sea to show how distinctly different N: P supply ratios of their source waters, shape phytoplankton communities along the river-ocean continuum. Sampling in the relatively unpolluted surface waters of the ARP during peak river discharge revealed that phytoplankton communities along the river-ocean continuum were strongly limited by Dissolved Inorganic Nitrogen (DIN, nitrate plus nitrite) which was low or beyond detectable, while Dissolved Inorganic Phosphorous (DIP, phosphate) and Silica were not limiting. The resulting low N:P supply ratio allowed diazotrophs to co-exist with non-diazotrophs. Diatom-Diazotroph Associations (DDAs) such as Hemiaulus hauckii-Richelia proliferated, while in the oligotrophic oceanic waters, Trichodesmium spp. thrived. In contrast, in the CDW, anthropogenic nitrogen inputs from human pressures in the Changjiang River system has led to a system where the changing supply rate of the single nutrient (DIP) is responsible for the interannual variability seen in the phytoplankton community structure of the CDW. During years of low discharge, DIP limitation can be ameliorated by on-shelf upwelling of DIP rich Kuroshio Intermediate Waters leading to domination of diatoms and dinoflagellates. Conversely, during years of heavy discharge, the westward flowing CDW plume was severely DIP limited, probably because water column stratification dampened upwelling of subsurface waters. The consequent DIP limitation led to the proliferation of small phytoplankton such as Chlorophytes and Cyanobacteria. The absence of diazotrophs in the CDW, leads us to hypothesize that river-ocean continuums, whose source waters are heavily impacted by anthropogenic activities and with high nitrate concentrations often substantially in excess of Redfield ratios, may not support diatoms offshore on account of DIP limitation nor diazotrophy because of excess DIN.