Phytoplankton blooms, while beneficial to fisheries and ecosystems, can also cause significant environmental problems, including harmful algal blooms (HABs) that produce toxins and create anoxic dead zones. The frequency and distribution of these blooms are projected to increase with climate change, yet global-scale characterizations are lacking. While databases like HAEDAT exist, inconsistent sampling efforts hinder trend analysis. Satellite data offer continuous monitoring, but technical challenges have limited global application. This study addresses these limitations by developing a method to map global coastal algal blooms using MODIS satellite imagery from 2003 to 2020, examining bloom frequency, spatial extent, and potential drivers.

Existing research highlights the increasing global concern over harmful algal blooms (HABs) and their association with eutrophication and climate change. Studies have indicated a potential link between increased aquaculture and HAB occurrences. However, comprehensive global-scale analyses of bloom trends have been hampered by limitations in data consistency and the technical difficulties of processing satellite imagery across diverse coastal waters. The literature points to the need for a large-scale, spatially and temporally consistent dataset to understand the global patterns and drivers of phytoplankton bloom changes.

This study utilized daily, 1-km resolution MODIS satellite data from 2003 to 2020 to create a global dataset of phytoplankton bloom occurrences. An automated method was developed to detect blooms based on satellite-detectable fluorescence signals. Bloom-affected areas were delineated, and bloom counts and frequencies were calculated for 1° × 1° grid cells. The methodology included validation against independent satellite data and HAEDAT, showing high accuracy. The study examined blooms within the exclusive economic zones (EEZs) of 153 coastal countries and 54 large marine ecosystems (LMEs). Analysis included assessing trends in bloom-affected area and frequency, examining relationships with sea surface temperature (SST), SST gradients (as a proxy for mesoscale currents), and the multivariate El Niño-Southern Oscillation index (MEI), and investigating correlations with fertilizer use and aquaculture production.

The study found that phytoplankton blooms occurred in 126 out of 153 coastal countries examined. The total bloom-affected area was 31.47 million km². Globally, the total bloom-affected area expanded by 13.2% (3.97 million km²) and the global median bloom frequency increased by 59.2% between 2003 and 2020. Europe and North America contributed the largest bloom areas, while Africa and South America experienced the most frequent blooms. Significant increasing trends in bloom frequency were observed in 77.6% more areas than those with decreasing trends. Positive correlations were found between bloom frequency and SST in several high-latitude regions, suggesting a temperature-driven mechanism. However, bloom weakening in tropical and subtropical areas indicates other factors are at play. Significant positive correlations were also found between bloom frequency and SST gradients (indicative of mesoscale currents) in various coastal current systems. The study also identified relationships between bloom frequency and the MEI, fertilizer use, and aquaculture production in certain regions. However, the relationship between fertilizer use and bloom frequency was not consistent across all regions.

The findings show a global increase in coastal phytoplankton blooms over the past two decades, indicating a significant shift in coastal ocean ecology. The non-uniform regional trends highlight the complex interplay between climate change (SST, SST gradients, and climate extremes), anthropogenic nutrient inputs (fertilizer use), and aquaculture development. The positive correlation between bloom frequency and SST in high-latitude regions supports the hypothesis of temperature-driven bloom expansion. The relationship with SST gradients suggests that changes in ocean circulation and nutrient transport play a substantial role. The influence of the MEI underscores the importance of large-scale climate events. The inconsistent correlation between fertilizer use and bloom frequency suggests that climate change may be overriding the impact of nutrient management efforts in some areas. The positive link between aquaculture production and bloom incidence requires further investigation.

This study provides a spatially and temporally consistent characterization of global coastal algal blooms, revealing a global increase in both bloom area and frequency. Regional variations emphasize the combined effects of climate change, eutrophication, and aquaculture. The data presented offers valuable baseline information for developing forecasting models and informing policies to mitigate the negative consequences of harmful blooms while sustaining the benefits of beneficial blooms. Future research should focus on improving bloom detection, refining ecosystem models incorporating natural and anthropogenic factors, and investigating region-specific drivers of bloom changes.

The study's definition of a detectable bloom event is influenced by sensor sensitivities and algorithm thresholds, potentially underestimating bloom incidence, especially low-cell-concentration HABs. The bloom count metric, averaged across 1-km pixels, may differ from discrete sampling in databases like HAEDAT. While these underestimates are likely uniform across regions, they should be considered when comparing the results with other studies. The study relies on correlations, and further research using ecosystem models is needed to fully quantify the contributions of various factors to bloom trends.