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Trends of global coastal phytoplankton blooms between 2003 and 2020 a, Spatial patterns of the trends in bloom frequency at a 1° × 1° grid scale. The latitudinal profiles show the fractions of grids with significant and insignificant trends (positive or negative) along the east–west direction. b, Interannual variability and trends in annual median bloom frequency and total global bloom-affected area. The linear slopes and P-value (two-sided t-test) are indicated. The shading associated with the bloom frequency data represents an uncertainty level of 5% in bloom detection. Map created using Python 3.8. Source Data
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Phytoplankton blooms in coastal oceans can be beneficial to coastal fisheries production and ecosystem function, but can also cause major environmental problems1,2—yet detailed characterizations of bloom incidence and distribution are not available worldwide. Here we map daily marine coastal algal blooms between 2003 and 2020 using global satellite...
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... intensity. Validation with independent satellite samples selected via several visual inspection techniques showed an overall accuracy level of more than 95% for our method, and comparisons using discrete events in HAEDAT 6 indicated that we successfully identified bloom counts for 79.3% of the historical HAB events in that database (Extended Data Figs. 2-6). We examined phytoplankton blooms in the exclusive economic zones (EEZs) of 153 coastal countries and in 54 large marine ecosystems (LMEs) (Extended Data Fig. 7). Our study area encompasses global continental shelves and outer margins of coastal currents, which offer the majority of marine resources available for human use (see ...Context 2
... total global bloom-affected area has expanded by 3.97 million km 2 (13.2%) between 2003 and 2020, equivalent to 0.14 million km 2 yr −1 (P < 0.05; Fig. 2). Furthermore, the number of countries with significant bloom expansion was about 1.6 times those with a decreasing trend. The global median bloom frequency showed an increasing rate of 59.2% (+2.19% yr −1 , P < 0.05) over the observed period. Spatially, areas showing significant increasing trends (P < 0.05) in bloom frequency were ...Context 3
... with significant bloom expansion was about 1.6 times those with a decreasing trend. The global median bloom frequency showed an increasing rate of 59.2% (+2.19% yr −1 , P < 0.05) over the observed period. Spatially, areas showing significant increasing trends (P < 0.05) in bloom frequency were 77.6% larger than those with the opposite trends (Fig. 2). Globally, our analysis revealed overall consistent fluctuations between the bloom-affected area and bloom frequency between 2003 and 2020 (Fig. 2b). However, there was no significant relationship between bloom extent and frequency in 23 countries and 10 LMEs over the past two decades, underscoring the spatial and temporal variability ...Context 4
... of 59.2% (+2.19% yr −1 , P < 0.05) over the observed period. Spatially, areas showing significant increasing trends (P < 0.05) in bloom frequency were 77.6% larger than those with the opposite trends (Fig. 2). Globally, our analysis revealed overall consistent fluctuations between the bloom-affected area and bloom frequency between 2003 and 2020 (Fig. 2b). However, there was no significant relationship between bloom extent and frequency in 23 countries and 10 LMEs over the past two decades, underscoring the spatial and temporal variability of algal blooms and the importance of continuous satellite ...Context 5
... entire Southern Hemisphere was primarily characterized by increased bloom frequency, although weakened blooms were also sometimes found. In the Northern Hemisphere, the low latitude (<30° N) coasts were mainly featured with strong bloom weakening (Fig. 2a), primarily in the California Current System and the Arabian Sea. Bloom strengthening was found in the northern Gulf of Mexico and the East and South China Seas, albeit at smaller magnitudes. At higher latitudes, weakening blooms were detected mainly in the northeastern North Atlantic and the Okhotsk Sea in the northwestern North ...Context 6
... studies, in which the bloom-favourable seasons in these temperate seas have been extended under warmer temperatures [27][28][29] . However, this temperature-based mechanism did not apply to regions with inconsistent trends between SST and bloom frequency, particularly for the substantial bloom weakening in the tropical and subtropical areas (Figs. 2a and 3b). ...Context 7
... represented as the multivariate El Niño-Southern Oscillation index 36 (MEI), also showed connections with coastal bloom frequency. The minimum MEI in 2010 (a strong La Niña year) was followed by a low bloom frequency in the following year, and the largest MEI in 2015 (a strong El Niño year) was followed by the strongest bloom frequency in 2016 ( Fig. 2b and Extended Data Fig. ...Context 8
... selected 53,820 bloom-containing pixels from the MODIS R rc data as training samples to determine the boundary of the CIE colour space. These sample points were selected from nearshore waters worldwide where frequent phytoplankton blooms have been reported (Extended Data Fig. 2); the algal species included various species of dinoflagellates and diatoms 20 . A total of 80 images was used, which were acquired from different seasons and across various bloom magnitudes, to ensure that the samples used could almost exhaustively represent the different bloom conditions in the coastal oceans. ...Context 9
... scale level-3 composites. The number of bloom counts within a year for each location can be easily enumerated, and the long-term annual mean values were then estimated (Fig. 1a). We further calculated the total global bloom-affected area (the areas where algal blooms were detected at least once) for each year and examined their changes over time (Fig. ...Context 10
... n represents the associated number of bloom-affected pixels in the same cell (the number of pixels with M i > 0), and N is the total number of 1-km MODIS pixels in this grid cell. We estimated the bloom frequency for each year between 2003 and 2020, and determined the long-term trend over global EEZs through a linear least-squares regression (see Fig. ...Context 11
... intensity. Validation with independent satellite samples selected via several visual inspection techniques showed an overall accuracy level of more than 95% for our method, and comparisons using discrete events in HAEDAT 6 indicated that we successfully identified bloom counts for 79.3% of the historical HAB events in that database (Extended Data Figs. 2-6). We examined phytoplankton blooms in the exclusive economic zones (EEZs) of 153 coastal countries and in 54 large marine ecosystems (LMEs) (Extended Data Fig. 7). Our study area encompasses global continental shelves and outer margins of coastal currents, which offer the majority of marine resources available for human use (see ...Context 12
... total global bloom-affected area has expanded by 3.97 million km 2 (13.2%) between 2003 and 2020, equivalent to 0.14 million km 2 yr −1 (P < 0.05; Fig. 2). Furthermore, the number of countries with significant bloom expansion was about 1.6 times those with a decreasing trend. The global median bloom frequency showed an increasing rate of 59.2% (+2.19% yr −1 , P < 0.05) over the observed period. Spatially, areas showing significant increasing trends (P < 0.05) in bloom frequency were ...Context 13
... with significant bloom expansion was about 1.6 times those with a decreasing trend. The global median bloom frequency showed an increasing rate of 59.2% (+2.19% yr −1 , P < 0.05) over the observed period. Spatially, areas showing significant increasing trends (P < 0.05) in bloom frequency were 77.6% larger than those with the opposite trends (Fig. 2). Globally, our analysis revealed overall consistent fluctuations between the bloom-affected area and bloom frequency between 2003 and 2020 (Fig. 2b). However, there was no significant relationship between bloom extent and frequency in 23 countries and 10 LMEs over the past two decades, underscoring the spatial and temporal variability ...Context 14
... of 59.2% (+2.19% yr −1 , P < 0.05) over the observed period. Spatially, areas showing significant increasing trends (P < 0.05) in bloom frequency were 77.6% larger than those with the opposite trends (Fig. 2). Globally, our analysis revealed overall consistent fluctuations between the bloom-affected area and bloom frequency between 2003 and 2020 (Fig. 2b). However, there was no significant relationship between bloom extent and frequency in 23 countries and 10 LMEs over the past two decades, underscoring the spatial and temporal variability of algal blooms and the importance of continuous satellite ...Context 15
... entire Southern Hemisphere was primarily characterized by increased bloom frequency, although weakened blooms were also sometimes found. In the Northern Hemisphere, the low latitude (<30° N) coasts were mainly featured with strong bloom weakening (Fig. 2a), primarily in the California Current System and the Arabian Sea. Bloom strengthening was found in the northern Gulf of Mexico and the East and South China Seas, albeit at smaller magnitudes. At higher latitudes, weakening blooms were detected mainly in the northeastern North Atlantic and the Okhotsk Sea in the northwestern North ...Context 16
... studies, in which the bloom-favourable seasons in these temperate seas have been extended under warmer temperatures [27][28][29] . However, this temperature-based mechanism did not apply to regions with inconsistent trends between SST and bloom frequency, particularly for the substantial bloom weakening in the tropical and subtropical areas (Figs. 2a and 3b). ...Context 17
... represented as the multivariate El Niño-Southern Oscillation index 36 (MEI), also showed connections with coastal bloom frequency. The minimum MEI in 2010 (a strong La Niña year) was followed by a low bloom frequency in the following year, and the largest MEI in 2015 (a strong El Niño year) was followed by the strongest bloom frequency in 2016 ( Fig. 2b and Extended Data Fig. ...Context 18
... selected 53,820 bloom-containing pixels from the MODIS R rc data as training samples to determine the boundary of the CIE colour space. These sample points were selected from nearshore waters worldwide where frequent phytoplankton blooms have been reported (Extended Data Fig. 2); the algal species included various species of dinoflagellates and diatoms 20 . A total of 80 images was used, which were acquired from different seasons and across various bloom magnitudes, to ensure that the samples used could almost exhaustively represent the different bloom conditions in the coastal oceans. ...Context 19
... scale level-3 composites. The number of bloom counts within a year for each location can be easily enumerated, and the long-term annual mean values were then estimated (Fig. 1a). We further calculated the total global bloom-affected area (the areas where algal blooms were detected at least once) for each year and examined their changes over time (Fig. ...Context 20
... n represents the associated number of bloom-affected pixels in the same cell (the number of pixels with M i > 0), and N is the total number of 1-km MODIS pixels in this grid cell. We estimated the bloom frequency for each year between 2003 and 2020, and determined the long-term trend over global EEZs through a linear least-squares regression (see Fig. ...Similar publications
Studying correlations between phytoplankton communities and environmental factors is critical for understanding how aquatic ecosystems function. The high sensitivity of phytoplankton to changes in these factors makes it possible to control the state of the ecosystem of water bodies. Artificial lakes often demonstrate increased trophic status, induc...
Citations
... In recent years, global climate change and intensified anthropogenic activities have contributed to increasing HAB frequency worldwide. Between 2003 and 2020, algal bloom events were documented in over 80% of coastal nations worldwide, with their geographical coverage expanding by 13.2% alongside a 59.1% increase in occurrence frequency [21]. While the coexistence of algae and seagrass is natural in healthy marine ecosystems, excessive algal growth disrupts the ecological balance of seagrass habitats, resulting in cascading negative impacts [19] (Fig. 1). ...
... Elevated surface temperatures intensify water column stratification, creating favorable conditions for algal proliferation by reducing vertical mixing and maintaining algal populations within the photic zone; this thermally induced stratification leads to earlier bloom initiation and extended bloom duration [104]. Furthermore, temperaturedriven alterations in oceanic circulation patterns enhance upwelling intensity, particularly along eastern boundary currents, thereby elevating nutrient flux to surface waters and optimizing stoichiometric conditions (N:P > 16) for algal biomass accumulation [21]. ...
... Concurrently, temperature elevation within the 5-25 °C range enhances enzymatic catalytic efficiency in algal cells, accelerating photosynthetic processes and shortening cellular division cycles [21]. For instance, diatom proliferation rates increase by 33% when temperatures rise from 15 °C to 20 °C, significantly compressing their reproductive timelines [21]. ...
Purpose of Review
Harmful algal blooms (HABs) present a growing threat to seagrass ecosystems, significantly impacting their ecological functions and blue carbon potential. Understanding the complex interactions between HABs and seagrasses is crucial for developing adaptive management strategies to protect seagrass ecosystems.
Recent Findings
Recent studies reveal that global HAB events have significantly expanded both geographically and in frequency over the past two decades. The geomorphological processes and depositional environments of seagrass meadows, along with the effects of climate change, act as contemporary drivers that influence algal invasion, presence, and retention within seagrass ecosystems. Emerging research demonstrates that macroalgal blooms can significantly accelerate seagrass carbon loss by enhancing decomposition rates and increasing greenhouse gas emissions from blue carbon stocks. Seagrass allelopathy and associated algicidal bacteria play crucial roles in natural HAB control. Advanced monitoring techniques combining artificial intelligence with remote sensing have achieved significant improvements in detecting and tracking HAB events and seagrass ecosystems.
Summary
This review provides a comprehensive analysis of HAB-seagrass interactions, documenting diverse types of HABs affecting seagrass beds, including macroalgal and microalgal blooms. We examine key environmental factors contributing to HABs in seagrass ecosystems, particularly eutrophication, global warming, and ocean acidification, and analyze their complex impact mechanisms, including light limitation, resource competition, biogeochemical alterations, and toxin effects. Natural defense mechanisms of seagrasses, particularly allelopathy and algicidal bacteria, offer potential solutions for HAB control. Effective protection of these valuable blue carbon resources requires integrated adaptive management strategies, combining advanced monitoring technologies, water quality improvement measures, and community-based conservation approaches.
... Hue angle is widely used in color analysis and serves as an intermediate variable for estimating the Forel-Ule index (a traditional index of water color assessment), enabling the assessment of hue variations (23,24). The CIE system provides a standard for digitally expressing water color changes of satellite images and is now used to conduct related studies (22,(24)(25)(26). ...
... The fluctuation amplitude of α* anomaly ( a * a ) exhibits more pronounced fluctuations in coastal (SD > 10°) and highlatitude waters (SD, ~5°), whereas mid-low latitude oceans have relatively lower variability (SD < 3°) (Fig. 2C). Coastal waters, influenced by terrestrial inputs, algal blooms, and human activity (26,31,32), experience pronounced seasonal fluctuations, with a * a variations > 20° in certain regions (e.g., coast of the Bering Sea, the Argentine coast, and the marginal seas of China). ...
... The reported distribution of algal blooms through satellite analyses is similar to identified coastal areas with high hue fluctuations (25), underscoring the potential impact of phytoplankton blooms on water color anomalies. Natural triggers, aquaculture, and fertilizer use in coastal regions seem to contribute to algal blooms (25,26,(68)(69)(70). ...
Ocean change leaves a potentially important imprint on ocean colorimetry. Here, we present an overview and current evaluation of the global ocean color variability from 1998 to 2022, and satellites observe that 36% of oceans (~122 million square kilometers, derived from valid observations) have experienced changes ( P < 0.1). In this context, 25% of the area (formerly blue hue) is turning light blue or green, while the remaining 11% becomes bluer, mainly concentrating in the low-latitude oceans. This study further identifies a “direct” notable impact of both sea surface temperature (SST) and climate on ocean colorimetry tendency and anomaly, especially in the low-latitude oceans. Extreme SST events cause “distinct” ocean colorimetry anomalies, although 94% of cases involve relatively small SST fluctuations. Causal analysis reveals important impacts of climate change on equatorial ocean dynamics, particularly ENSO events. Our findings prove the low-latitude oceans as one of the core changing regions that respond to climate change in the early 21st century.
... Phytoplankton blooms are expanding and intensifying due to climate change, which likely add complexity to the metal trophic transfer in aquatic ecosystems 5 . On one hand, phytoplankton excrete dissolved organic matter (DOM) that chelates metal ions, potentially reducing their bioavailability 6,7 . ...
... These properties affect biological activity directly as physiological drivers and stressors, and indirectly by controlling the spatial distribution of nutrients, dissolved oxygen and prey (Lee and Gentemann, 2017;Thakur et al., 2018). Understanding and monitoring water temperature and salinity is crucial, especially in the coastal ocean, where climate change is increasing the frequency and intensity of marine extreme events including marine heat waves (Li et al., 2022;Dai et al., 2023), leading to increased thermal and freshwater stratification (Li et al., 2020), eutrophication (Breitburg et al., 2018), and hypoxic events (Altieri and Gedan, 2015). ...
Sea surface salinity and temperature are essential climate variables in monitoring and modeling ocean health. Multispectral ocean color satellites allow the estimation of these properties at a resolution of 10 to 300 m, which is required to correctly represent their spatial variability in coastal waters. This paper investigates the effect of pre-applying an unsupervised classification in the performance of both temperature and salinity inversion. Two methodologies were explored: clustering based solely on spectral radiances, and clustering applied directly to satellite images. The former improved model generalization by identifying similar water clusters across different locations, reducing location dependency. It also demonstrated results correlating cluster type with salinity and temperature distributions thereby enhancing regression model performance and improving a global ocean color sea surface temperature regression model RMSE error by 10%. The latter approach, applying clustering directly to satellite images, incorporated spatial information into the models and enabled the identification of front boundaries and gradient information, improving global sea surface temperature models RMSE by 20% and sea surface salinity models by 30%, compared to the initial ocean color model. Beyond improving algorithm performance, optical water classification can be used to monitor and interpret changes to water optics, including algal blooms, sediment disturbance or other climate change or antropogenic disturbances. For example, the clusters have been used to show the impact of a category 4 hurricane landfall on the Mississippi estuarine region.
... Harmful algal blooms (HABs) are a growing global concern due to their detrimental impacts on water quality, aquatic ecosystems, and human health [1][2][3]. These events, driven by excessive algal growth, can deplete dissolved oxygen (DO) levels and disrupt ecological balance, posing significant challenges for environmental protection and sustainable water resource management. ...
... Equation (1) describes the observed change in oxygen concentration over time. The physical component of oxygen variation, O phy , is computed using equation (2), where gas transfer velocity k is derived from equation (3). Finally, the biologicallydriven component, O bio , is estimated as shown in equation (4). ...
Harmful algal blooms (HABs) threaten aquatic ecosystems and water quality, necessitating timely monitoring. Traditional satellite observations, including high-frequency sensors like Geostationary Ocean Color Imager II (GOCI-II), are often hindered by cloud cover and low-light conditions, limiting their temporal resolution and coverage. We propose a real-time approach using diel variations in dissolved oxygen (DO) measured by buoys to detect HAB initiation and dynamics. By isolating biologically driven oxygen variation ( Obio) from physical processes, we identify increases in Obio, elevated temperature, and maximum DO as key HAB indicators. This method captures bloom activity under cloudy or low-light conditions when satellites fail. To enhance spatial coverage, we integrate buoy-based DO data with high-frequency GOCI-II satellite observations, providing hourly, all-weather bloom detection. While satellite or buoy observations alone face limitations, their integration overcomes traditional barriers. Our results demonstrate a robust tool for real-time HAB monitoring and early warning, supporting sustainable water resource management.
... Macias et al. (2018) showed that removing river inputs in simulations led to the complete suppression of algal blooms in both the Adriatic and Aegean Sea, thereby demonstrating the local dominance of this factor in controlling primary productivity. Similarly, the reduction in riverine phosphorus and nitrogen loads due to recent regulations has resulted in a decrease in bloom occurrences in the region (Mélin et al., 2011;Mozetič et al., 2010), as observed in other areas worldwide (Dai et al., 2023). ...
In the open ocean, marine heatwaves (MHWs) have been associated to a decline of Chlorophyll-a (Chl-a) concentration in tropical and temperate areas while, at higher latitudes, they seem to enhance phytoplankton productivity. Currently, uncertainties remain on the outcomes of MHWs on primary production in coastal and heterogenous marine regions. We analyzed long-term modelled satellite-derived data on sea surface temperature and Chl-a concentration in the Adriatic Sea (Mediterranean Sea), a semi-enclosed basin where coastal and open-sea environmental conditions co-occur, to explore Chl-a responses to MHWs.
We found that both low and high Chl-a anomalies were strictly dependent on MHWs, although following direct or inverse relationships in different areas, as a consequence of regional-scale heterogeneities in nutrient availability, riverine inputs, circulation and geomorphology. Along the west coast and shallow areas of the North and Central Adriatic, high MHWs frequency, duration and intensity corresponded to high frequency of Chl-a peaks and/or increased intensity and duration of low Chl-a anomalies, suggesting pronounced fluctuations with intense phytoplankton blooms alternating to extremely low production events. Conversely, in offshore and deeper areas, especially in the South Adriatic, MHWs frequency, duration and intensity inversely correlated with Chl-a anomalies, indicating a possible reduction of phytoplankton biomass and a decline of organic matter flow towards the sea floor. Prolonged MHWs may therefore drive shifts in primary production with possible ecosystem-wide effects in both coastal and pelagic areas. These multifaceted MHW-Chl-a interactions observed in the Adriatic Sea emphasize the need for context-specific assessments in environmentally complex marine regions to develop management strategies addressing ecological and socioeconomic issues arising from the unrelenting increase of temperature anomalies.
... Ocean color remote sensing (OCRS), a noninvasive observational technique, has emerged as an indispensable tool for monitoring the marine environment. This technology has been instrumental in advancing our understanding of various oceanographic processes, including the detection and analysis of phytoplankton blooms [1,2], assessments of ocean primary production [3,4], evaluations of particulate carbon standing stock [5][6][7], and investigations into the impacts of climate change [8,9]. ...
Ocean color remote sensing technology has proven to be an indispensable tool for monitoring ocean conditions, as it has consistently provided critical data on global ocean optical properties, color, and biogeochemical parameters over several decades. With the rapid advancement of artificial intelligence, the integration of machine learning (ML) models into ocean color remote sensing has become a significant focus within the scientific community. This article provides a comprehensive review of the current status and challenges associated with ML models in ocean color remote sensing, assessing their applications in atmospheric correction, color inversion, carbon cycle analysis, and data reconstruction. This review highlights the advancements made in applying ML techniques, such as neural networks and deep learning, to improve data accuracy, enhance resolution, and enable more precise predictions of oceanic phenomena. Despite challenges such as model generalization and computational complexity, ML has significant potential for enhancing our understanding of marine ecosystems, facilitating real-time monitoring, and supporting global climate models.
... As a result, this also leads to changes in the composition of phytoplankton species and dominant populations [71]. This phenomenon exhibits variations across different aquatic systems; for example, in saline-alkaline lakes in Northeast China, an increase in WT results in a shift in the dominant population from Bacillariophyta to Cyanophyta; whereas, in the coastal waters of the Antarctic Peninsula, the dominant population shifts from diatoms to cryptophytes [72]. In saline-alkaline lakes in Alar, Xinjiang, an increase in WT leads to an increase in the number of phytoplankton, primarily due to more favorable growth conditions and additional nutrients provided by rising groundwater levels or supplementary water sources from the surrounding area [73]. ...
To evaluate the change trends of plankton in inland saline–alkaline water bodies, this study investigated the ecological restoration and rational development of saline–alkaline lakes in northwest China. From June to October 2023, phytoplankton communities in a high-salinity lake in Alar City, Xinjiang, were analyzed using standard survey methods for inland natural waters. Biodiversity indices were calculated, and redundancy analysis (RDA), Spearman’s correlation analysis, and Mantel test were carried out to assess the functional community structure of phytoplankton and its environmental drivers. In total, 115 phytoplankton taxa belonging to seven phyla were identified. The densities ranged from 23.76 × 10⁵ to 53.54 × 10⁷ cells/L. Bacillariophyta and Cyanophyta were the dominant phyla, accounting for 41.7% and 27.8% of the total taxa, respectively. The dominant species included Microcystis spp., Merismopedia sp., Cyclotella meneghiniana, and other algae. Spearman correlation analysis revealed that salinity, water temperature (WT), Na⁺, TDS, HCO3⁻, Cl⁻, and K⁺ were key environmental factors significantly influencing phytoplankton community structure. Mantel tests confirmed that salinity (SAL), TDS, DO, and major ions (K⁺, Na⁺, CO3²⁻) served as key determinants of spatiotemporal phytoplankton community distribution (p < 0.05). RDA results indicated that WT, TDS, alkalinity (ALK), pH, salinity, and Na⁺ were the key factors driving seasonal variations in phytoplankton communities. Notably, decreasing salinity and ion concentrations stabilized the phytoplankton community structure, maintaining high-diversity indices. This highlights the positive impact of ecological restoration measures, such as fisheries-based alkalinity control and systematic environmental management, on the health of saline–alkaline lake ecosystems. These findings provide important insights for the sustainable development of saline–alkaline fisheries and the conservation of aquatic biodiversity in arid regions.
... Phytoplankton blooms are large accumulations of microscopic algae on fresh and marine open waters (Dai et al., 2023). Although many blooms may occur naturally, human-induced eutrophication (e.g., municipal and industrial effluent, and agricultural runoff from fertilized topsoil) increases their occurrence globally (Beman et al., 2005;Heisler et al., 2008;Srisuksomwong and Pekkoh, 2020) and these blooms have become a serious environmental hazard worldwide (Smith, 2003;Anderson et al., 2012;Hallegreaf et al., 2021). ...
... Once the bloom occurs, it increases the population and growth of the phytoplankton, resulting in a multifold increase in biomass. The decomposition of dense algal blooms can deplete oxygen from bottom waters, resulting in hypoxic/anoxic "dead zones" that can cause the death of fish and invertebrates, while restructuring ecosystems, causing serious consequences and affecting the coastal community and stakeholders (Diaz and Resenberg, 2008;Van Dolahet al., 2016;Breitburg et al., 2018;Dai et al., 2023). ...
Phytoplankton blooms represent a sudden increase in microalgae biomass, generally last for a week or so. Typically, they consist of one particular species dominating the plankton in the surface water, characterized by colorations of water due to high concentrations of photosynthetic pigments in the microalgae. Hence, the present study explores the variability of nutrient ratios t hat alters the phytoplankton community structure, competition, and succession between algal species for the coastal water of the western Bay of Ben-gal. An intense bloom of four phytoplankton species, i.e., the diatom (Asterionellopsis glacialis), followed by the green alga (Chlorella salina), the cyanobacteria (Trichodesmium thiebautii), and the diatom (Chaetoceros diadema), was encountered within the surf zone of Chennai coast on the 13 th ,15 th and 19 th of January 2015, and the 17 th of February 2016, respectively. Chlorophyll-a (Chl-a) concentration was increased by 10-fold during the bloom period compared to the non-bloom period. A higher Si:P ratio favored the bloom of A. glacialis and C. diadema and during lower ratio resulted in the bloom of C. salina. T. thiebautii bloom forms at a higher concentration of N:P ratio and a lower ratio resulted in C. salina bloom. Along with the nutrient ratio, the concentration of dissolved inorganic nitrogen (DIN) and surface water temperature also favored the bloom conditions within the surf zones. Multivariate analysis showed that SiO4 and Si:P ratio were important environmental factors that induced the growth of A. glacialis, and C. diadema. The favorable temperature and nutrient ratios (Si:P and N:P) along this coast during the post-northeast monsoon period trigger the proliferation of algal blooms. The present study reported the first of its kind on phytoplankton succession along the east coast of India.
... Amongst mountainous watersheds in North America, the Olympic Mountains, the Sierra Nevada, and the Appalachian uplands are the most vulnerable to increased frequency of ROS events. The anticipated impacts on coastal erosion (Nielsen et al., 2022), sediment dynamics (Moragoda & Cohen, 2020), streamflow hydrograph (Tohver et al., 2014), nutrient loads (Pihlainen et al., 2020), and phytoplankton blooms (Dai et al., 2023) underscore the need for future foundational studies that integrate the interconnected physical, chemical, and biological processes. ...
Extreme floods and landslides in high‐latitude watersheds have been associated with rain‐on‐snow (ROS) events. Yet, the risks of changing precipitation phases on a declining snowpack under a warming climate remain unclear. Normalizing the total annual duration of ROS with that of the seasonal snowpack, the ERA5 data (1941–2023) show that the frequency of high‐runoff ROS events is a characteristic feature of high‐latitude coastal zones, particularly over the coasts of south‐central Alaska and southern Newfoundland. Total rainfall accumulation per seasonal snowpack duration has increased across western mountain ranges, with the Olympic Mountains experiencing more than 40 mm of additional rainfall over the snowpack in the past eight decades, followed by the Sierra Nevada. These trends could drive an 8% increase in rainfall extremes (e.g., more than 10 mm for 6 hr storm with a 15‐year return period), highlighting the need for resilient flood control systems in high‐latitude coastal cities.
