Surface Chlorophyll Concentration Research Articles

Satellite-Observed Multi-Scale Variability of Sea Surface Chlorophyll-a Concentration along the South Coast of the Sumatra-Java Islands

The southern coast of Java is known as one of the most productive fishing grounds for tuna, feeding by nutrient-rich water along the coast caused by the subsurface water upwelling. This primary productivity can be evidenced by the high sea surface chlorophyll-a concentration (SSC). Based on satellite remote sensing products, we investigate the multi-scale variability in SSC along the Sumatra-Java coast. The results show that seasonal variability of SSCs is primarily due to monsoon-driven upwelling and rainfall in the Indian Ocean and Indonesian seas sides of the Sumatra and Java Islands, respectively. Local Ekman pumping plays a secondary role, while rainfall input to the ocean has little effect. Coastally trapped Kelvin waves and mesoscale eddies are responsible for the intraseasonal SSC anomalies in regions along the south coast of Java and off the Sunda and Lombok Straits, respectively. The interannual variability in SSC is caused by the anomalous upwelling related to the Indian Ocean Dipole. There was a weak increasing trend of ~0.1–0.2 mg/m3 per decade, above the global averaged trend, which may be related to enhanced local Ekman pumping. These analyses provide an overall description of SSC variations based on satellite observations; however, further investigations based on in situ observations are needed to achieve better quantification.

Model of Habitat Characteristics of Sardinella lemuru in the Bali Strait, Indonesia

This article describes a new approach to the study of the environmental conditions that relate to the Sardinella lemuru habitat in the Bali Strait, through remote sensing data and fish catch data using the generalized additive model. Data that are acquired daily and then compiled into monthly data for sea surface temperature, sea surface chlorophyll-a concentration, photosynthetically available radiation, and sea surface depth (SSD) were used for the years 2008–2010. The objectives of the study are to describe the variability of the environmental conditions in the Bali Strait, to analyze a combination model of environmental factors in estimating the Sardinella lemuru habitat, and to map potential Sardinella lemuru fishing areas. We illustrate the proposed method by constructing seven generalized additive models with catches of Sardinella lemuru as a variable response and use sea surface temperature, sea surface chlorophyll-a concentration, photosynthetically available radiation, and SSD as covariant models for assessing the environmental characteristics of the abundance of Sardinella lemuru. Predicted values were validated using a linear model. Based on the three model parameters, habitat selection for Sardinella lemuru was significantly (P < 0.0001) influenced by photosynthetically available radiation (50–55 Einstein m-2 d-1), sea surface chlorophyll-a concentration (0.2–2.0 mgm-3), sea surface temperature (28.95–29.64 °C), and SSD (60–150 m). Catch predictions show a consistent trend toward environmental conditions and water depth. Our method allows for improvement with the validation of catch predictions that were observed and collected monthly, and the result was significant (P < 0.001, r2 = 0.816). Photosynthetically available radiation explains the highest deviation in continued generalized additive models; therefore, it was considered to be the best predictor of habitat, followed by sea surface chlorophyll-a concentration, sea surface temperature, and then SSD. New research results supplement several previous studies that relate to the analysis of environmental parameters in estimating the fish habitat and can be used in mapping the distribution of potential Sardinella lemuru fishing areas in spatial and temporal scales.

Spatiotemporal BME characterization and mapping of sea surface chlorophyll in Chesapeake Bay (USA) using auxiliary sea surface temperature data

Improving the spatiotemporal coverage of remote sensing (RS) products, such as sea surface chlorophyll concentration (SSCC), can offer a better understanding of the spatiotemporal SSCC distribution for ocean management purposes. In the first part of this work, 834 in-situ SSCC measurements of the SeaBASS-NASA (National Aeronautics and Space Administration) during 2002–2016 served as the empirical dataset. A moving window with ±3 days and ±0.5° centered at each of the in-situ SSCC measurements established a search neighborhood for Moderate Resolution Imaging Spectroradiometer Level 2 (MODIS L2) SSCC and MODIS L2 sea surface temperature (SST) data, and the matched SSCC and SST data were used for building a linear SSCC-SST relationship. The unmatched SST was introduced to the linear model for generating soft SSCC data with uniform distributions. The inherent spatiotemporal dependency of the SSCC distribution was then represented by the Bayesian maximum entropy (BME) method, which incorporated the soft SSCC data as auxiliary variable for SSCC estimation and mapping purposes. The results showed that a 75.3% accuracy improvement of remote SSCC retrieval in terms of R2 can be achieved by BME-based method compared to the original MODIS L2 product. Subsequently, the BME-based method was applied to obtain daily SSCC dataset in Chesapeake Bay (USA) during the period 2010–2019. It was found that the SSCC distribution exhibited a decreasing spatial trend from the upper bay to the outer bay, whereas decreasing and increasing temporal trends were detected during the periods 2011–2014 and 2016–2019, respectively. The generalized Cauchy process was used to quantitatively describe the autocorrelation SSCC function in the Chesapeake Bay. The results showed that the outer bay exhibited the strongest long-range dependence among the four sub-regions, whereas the middle bay exhibited the weakest long-range dependence. Finally, one-point and two-point stochastic site indicators (SSIs) were employed to explore the spatiotemporal SSCC characteristics in Chesapeake Bay. The one-point SSI results showed that nearly 100% of the upper, middle and the lower bay areas experienced a high SSCC level (>5 mg/m3) during the entire study period. The area with SSCC >5 mg/m3 in the outer bay increased a lot during the winter season, but the area with SSCC >10 or 20 mg/m3 decreased significantly in the upper, middle and lower bay. Simultaneously, the SSCC dispersion in these areas was rather small during the winter season. On the other hand, the two-point SSI results showed that although the SSCC levels differ among the four sub-regions, but the SSCC connectivity structures between pairs of points also displayed some similarities in terms of their spatiotemporal dependency. In conclusion, the proposed BME-based method was shown to be a promising remote SSCC mapping technique that exhibited a powerful ability to improve both accuracy and coverage of RS products. The SSIs can be also used to explore the spatiotemporal characteristics of a variety of natural attributes in waters.

Evolution of satellite derived chlorophyll-a trends in the Bohai and Yellow Seas during 2002–2018: Comparison between linear and nonlinear trends

The trends of sea surface chlorophyll-a (Chl-a) concentrations in the Bohai and Yellow Seas of China (BYS) were analysed based on the satellite-derived Chl-a dataset from August 2002 to December 2018. The result of linear trend analysis based on the seasonal Mann-Kendall test indicates a significant positive Chl-a trend during this period, with an average trend of ~1.15% year−1 (Slope: ~0.011 mg year −1). However, the linear trends of Chl-a varied seasonally, with strong and significant increases in spring and summer (about 2% year−1), and weak and non-significant increases in winter (lower than 1% year−1). The results of the ensemble empirical mode decomposition (EEMD) analysis revealed highly nonlinear and time-varying trends of Chl-a in the BYS, with gradually increased Chl-a during 2002–2011 and decreased Chl-a from 2012 to 2018. The instantaneous rate of Chl-a change was continuously reduced from 2002 to 2018, from a positive value of ~2.0% year−1 around the beginning year (2002) to a negative value of approximately −2.0% year−1 around the recent year (2018). The temporal evolution of the Chl-a trend was well in accordance with the changes in nutrient enrichment, suggesting that the status of eutrophication might be the primary driver of the long-term trends in Chl-a. The increase (decrease) in nutrient levels could alleviate (aggravate) the nutrient limitation for phytoplankton growth in spring and summer, thus regulating the changes in Chl-a. In contrast, the Chl-a trend seems to be unrelated to the trend of light intensity in this area. This is the first study aimed to discern and compare the linear and evolutionary nonlinear Chl-a trends in the BYS and provides a baseline against which future changes can be monitored.

Predicting summer fin whale distribution in the Pelagos Sanctuary (north‐western Mediterranean Sea) to identify dynamic whale–vessel collision risk areas

Abstract Mediterranean fin whales aggregating in the Pelagos Sanctuary in summer to feed are exposed to vessel collision risk, particularly from high‐speed ferries. This study developed models to predict summer fin whale distribution using a generalized additive model (GAM) and MaxEnt, with the aim of providing a tool to identify potential high whale–ferry collision risk areas along ferry routes within the Pelagos Sanctuary during summertime. Models were trained using sightings data collected in the summer months of 2009–2018 on board ferries crossing the central area of the Pelagos Sanctuary. Environmental predictors were bathymetry and mean sea surface chlorophyll concentration of the annual spring bloom period. The predictive ability of GAM and MaxEnt was assessed using existing knowledge of summer fin whale distribution in the region. GAM (deviance explained = 20.2%) predictions matched documented distributions more closely than that of MaxEnt, with highest predicted fin whale occurrence in deep offshore waters (>2000 m) encompassing the central north‐western and western regions, and in the south‐eastern region, consistent with known fin whale habitats within the Pelagos Sanctuary. Inter‐annual variability was evident, influencing collision risk areas. Collision risk was estimated as a function of the overlap between the predicted probability of fin whale occurrence and ferry density estimated from Automated Identification System data. Ferry routes that cross the northern and eastern regions of the Pelagos Sanctuary presented relatively higher collision risk. Areas with changes in risk intensity between the years were temporally and spatially dynamic: some appeared intermittently throughout the study period while others persisted over consecutive years or recurred in different years. Due to the vastness of the Pelagos Sanctuary, vessel speed reduction maybe a more practical measure to manage collision risk than re‐routing shipping lanes. A combination of Seasonal Management Areas and Dynamic Management Areas approaches could be adopted for high‐risk areas.

Zonally asymmetric phytoplankton response to the Southern annular mode in the marginal sea of the Southern ocean

Antarctic marine biological variability modulates climate systems via the biological pump. However, the knowledge of biological response in the Southern Ocean to climate variability still has been lack of understanding owing to limited ocean color data in the high latitude region. We investigated the surface chlorophyll concentration responses to the Southern annular mode (SAM) in the marginal sea of the Southern ocean using satellite observation and reanalysis data focusing on the austral summer. The positive phase of SAM is associated with enhanced and poleward-shifted westerly winds, leading to physical and biogeochemical responses over the Southern ocean. Our result indicates that chlorophyll has strong zonally asymmetric responses to SAM owing to different limiting factors of phytoplankton growth per region. For the positive SAM phase, chlorophyll tends to increase in the western Amundsen–Ross Sea but decreases in the D’Urville Sea. It is suggested that the distinct limiting factors are associated with the seasonal variability of sea ice and upwelling per region.

Estimating Water Surface Chlorophyll-a Concentration by Big Remote Sensing Data in the Persian Gulf, Bushehr

Estimating Water Surface Chlorophyll-a Concentration by Big Remote Sensing Data in the Persian Gulf, Bushehr

Far-Field Impacts of a Super Typhoon on Upper Ocean Phytoplankton Dynamics

Super typhoon Rammasun (2014) traveled across the South China Sea on July 16–18. Its far-field impacts on phytoplankton dynamics in the upper ocean were documented by a Biogeochemical-Argo (BGC-Argo) float located 200 km to the left of its track. Both surface chlorophyll-a concentration (Chla) and particulate backscattering coefficient (bbp) were observed to increase substantially within two distinct stages. The initial increase occurred during the passage of the typhoon, and the subsequent increase happened 5 days after the typhoon. In contrast, depth-integrated Chla and bbp in the upper 150 m underwent negligible changes throughout the entire period. The key lies in the fact that surface phytoplankton increases in the far-field region resulted from the physically driven vertical redistribution of particles, rather than from biological alternations. The first increase was attributed to the typhoon-induced strong turbulence which deepened the surface mixed layer, and thus entrained subsurface particles to the surface; the second was due to the post-typhoon adiabatic quasi-geostrophic adjustment of the upper ocean that gradually raised the isopycnals (and thus subsurface particles). These results challenge the prevailing wisdom on typhoon impacts, and thus shed new lights on the nature of the upper ocean responses to typhoons from both physical and biological perspectives.

Polycyclic Aromatic Hydrocarbons Have Adverse Effects on Benthic Communities in the Baltic Sea: Implications for Environmental Status Assessment

Changes in benthic macrofaunal communities are indicative of environmental stressors, including eutrophication and hypoxia. However, some species are sensitive not only to hypoxia but also to various environmental contaminants. We tested which of the environmental predictors (sediment organic carbon, sediment concentrations of metals and polyaromatic hydrocarbons [PAHs], bottom water oxygen, salinity, temperature, and surface chlorophyll-a concentration) that best explained the following response variables: (1) macrofauna community composition, (2) abundance of a benthic sentinel species, the amphipod Monoporeia affinis; and (3) the Benthic Quality Index (BQI). All data originated from 29 reference monitoring stations in the Baltic Sea and the statistical tests included both uni- and multivariate analyses. The community composition and BQI were best explained by the same combination of salinity, depth, temperature and PAH concentrations. The abundance of M. affinis, which is sensitive to hypoxia and chemical exposure, was best explained by PAHs as a single predictor. Our findings suggest that benthic communities in the Baltic Sea are influenced by anthropogenic contaminants, which should be taken into account when benthos is used for eutrophication status assessment.

Influence of multi-scale dynamics on the vertical nitrate distribution around the Kuroshio Extension: An investigation based on BGC-Argo and satellite data

The vertical delivery of nutrients from deep water into the euphotic zone is one of the major limitations for the ocean primary productivity. In this study, the influence of multi-scale dynamics on the nitrate distribution observed by two BGC-Argo floats around the Kuroshio Extension is investigated. Vertical fluctuations of iso-nitrate surfaces and isopycnals were found to be correlated to the variation of absolute dynamic topography. In the subtropical Northwestern Pacific Ocean, subsurface nitrate concentration was found to be elevated inside a cyclonic mesoscale eddy during summer, while little nitrate was supplied into the surface layer, which was possibly due to the inhibition of seasonal thermocline. On the northern edge of the Kuroshio Extension, elevated euphotic-layer nitrate and surface chlorophyll concentrations were observed along the periphery of an anti-cyclonic eddy. In addition to horizontal advection, upwelling induced by the submesoscale dynamics is suggested to likely play an important role in the enhancements of nitrate and chlorophyll concentrations. The enhanced vertical delivery of nutrients from depth due to submesoscale dynamics has been hypothesized as a significant source for some satellite-observed events of high surface chlorophyll concentration, but direct evidence from in-situ observations is lacking. In this study, the synchronous occurrence of elevated nitrate and chlorophyll concentrations along the periphery of an anti-cyclonic eddy provides an evidence to support this hypothesis to some extent.

Observed variability of monsoon blooms in the north-central Arabian Sea and its implication on oxygen concentration: A bio-argo study

The central Arabian Sea (CAS) is productive during both the summer and winter monsoons owing to different physical processes. We analysed four years (2013–2016) record of chlorophyll and dissolved oxygen (DO) concentration from a Bio-Argo float deployed in this region. Though the surface blooms were observed during both the monsoons and sub-surface chlorophyll was also persistently observed, the intensity and duration of the bloom have been decreasing over the past few years. Also, the winter blooms were more prominent compared to the summer bloom in the study region. Our analysis shows that the observed inter-annual variability in the summer bloom can be attributed to the variability in wind speed, oceanic stratification and advection of nutrient rich water from the western Arabian Sea. During both the monsoons, stratification played an important role in reducing the productivity in recent years. We also found that during the winter monsoon, the upwelling Rossby wave propagating from the west coast of India influenced productivity as north as 15°N. The chlorophyll data from Bio-Argo float shows that the total surface chlorophyll concentration and backscattering (a proxy for particulate flux) in the OMZ region have been decreasing during the study period. Consequently, the DO concentration in the deeper waters has also been increasing. We believe that the decrease in surface productivity, lateral advection from the west and their manifestation on the export flux has reduced the oxygen demand in the deeper layer.

Excessive productivity and heat content in tropical Pacific analyses: Disentangling the effects of in situ and altimetry assimilation

Monitoring and predicting global ocean biogeochemistry and marine ecosystems is one of the biggest challenges for the coming decade. In operational systems, biogeochemical (BGC) models are forced – or coupled – with physical ocean models fields that are generally constrained by data assimilation of temperature, salinity and sea level anomalies. Yet, while physical data assimilation substantially improves simulated physical fields, BGC models forced by such analyses are commonly degraded, and more especially in equatorial regions. Here impacts of physical data assimilation on surface chlorophyll and nitrate concentrations are investigated in the tropical Pacific, based on three ocean reanalysis runs using the same physical–BGC model configuration but differing in their level of physical data assimilation. It is shown that, in the Mercator Ocean operational system, the assimilation of satellite altimetry and sea surface temperature in addition to temperature and salinity in situ profiles leads to spurious vertical velocities in the western equatorial Pacific. Our analysis suggests that these unrealistic vertical velocities are explained by the use of an inaccurate mean dynamic topography for the assimilation of altimetry that modifies the pressure-driven horizontal circulation in the upper ocean layer. Moreover, the biases found in this key region modify the subtle dynamical and BGC balances in the whole tropical Pacific and result in unrealistic trends of ocean heat content and nitrate concentration. This study demonstrates that looking into details of the physics is indispensable to improve physical data assimilation systems and to ensure that they make the best use of observations. This is also a key point to refine the strategy of the BGC models forcing and further improve ocean predictions.

A limited effect of sub-tropical typhoons on phytoplankton dynamics

Abstract. Typhoons are assumed to stimulate primary ocean production through the upward mixing of nutrients into the ocean surface. This assumption is based largely on observations of increased surface chlorophyll concentrations following the passage of typhoons. This surface chlorophyll enhancement, occasionally detected by satellites, is often undetected due to intense cloud coverage. Daily data from a BGC-Argo profiling float revealed the upper-ocean response to Typhoon Trami in the northwest Pacific Ocean. Temperature and chlorophyll changed rapidly, with a significant drop in sea surface temperature and a surge in surface chlorophyll associated with strong vertical mixing, which was only partially captured by satellite observations. However, no net increase in vertically integrated chlorophyll was observed during Typhoon Trami or in its wake. In contrast to the prevailing dogma, the result shows that typhoons likely have a limited effect on net primary ocean production. Observed surface chlorophyll enhancements during and immediately following typhoons in tropical and subtropical waters are more likely to be associated with surface entrainment of deep chlorophyll maxima. Moreover, the findings demonstrate that remote sensing data alone can overestimate the impact of storms on primary production in all oceans. Full understanding of the impact of storms on upper-ocean productivity can only be achieved with ocean-observing robots dedicated to high-resolution temporal sampling in the path of storms.

On the robustness of an eastern boundary upwelling ecosystem exposed to multiple stressors

The resistance of an east border upwelling system was investigated using relative index of marine pelagic biomass estimates under a changing environment spanning 20-years in the strongly exploited southern Canary Current Large marine Ecosystem (sCCLME). We divided the sCCLME in two parts (north and south of Cap Blanc), based on oceanographic regimes. We delineated two size-based groups (“plankton” and “pelagic fish”) corresponding to lower and higher trophic levels, respectively. Over the 20-year period, all spatial remote sensing environmental variables increased significantly, except in the area south of Cap Blanc where sea surface Chlorophyll-a concentrations declined and the upwelling favorable wind was stable. Relative index of marine pelagic abundance was higher in the south area compared to the north area of Cap Blanc. No significant latitudinal shift to the mass center was detected, regardless of trophic level. Relative pelagic abundance did not change, suggesting sCCLME pelagic organisms were able to adapt to changing environmental conditions. Despite strong annual variability and the presence of major stressors (overfishing, climate change), the marine pelagic ressources, mainly fish and plankton remained relatively stable over the two decades, advancing our understanding on the resistance of this east border upwelling system.

Influence of Deposition of Atmospheric Nitrogen Compounds to the Surface Chlorophyll-a Concentration over Japan Sea

Influence of Deposition of Atmospheric Nitrogen Compounds to the Surface Chlorophyll-a Concentration over Japan Sea

The Effect of Medium Inhomogeneity in Modeling Underwater Optical Wireless Communication

This paper introduces a stratified approach to modeling underwater optical wireless communication (UOWC). The influence of medium inhomogeneity, which many researchers ignore, was considered in modeling the UOWC channel to achieve an accurate model. The Monte Carlo technique to simulate the photon propagation was adapted to include medium inhomogeneity to estimate the received power, channel bandwidth, and delay spread of the proposed model. We use the depth-dependent chlorophyll profile that was established in Kameda empirical model to constitute the medium inhomogeneity. The empirical model used 0.5 mg m-3 and 2 mg m-3 of surface chlorophyll concentration to represent clear and coastal water. Besides, the comparison between collimated and diffused links was also studied to highlight the effect of the medium inhomogeneity on both links. Our findings indicate that the homogeneous model produces an underestimation result compared to the stratified model. The stratified model estimated significant increases in received power, lower delay spread, and higher bandwidth, which indicates the medium inhomogeneity is important for a realistic channel model.

Neural Network Approaches to Reconstruct Phytoplankton Time-Series in the Global Ocean

Phytoplankton plays a key role in the carbon cycle and supports the oceanic food web. While its seasonal and interannual cycles are rather well characterized owing to the modern satellite ocean color era, its longer time variability remains largely unknown due to the short time-period covered by observations on a global scale. With the aim of reconstructing this longer-term phytoplankton variability, a support vector regression (SVR) approach was recently considered to derive surface Chlorophyll-a concentration (Chl, a proxy of phytoplankton biomass) from physical oceanic model outputs and atmospheric reanalysis. However, those early efforts relied on one particular algorithm, putting aside the question of whether different algorithms may have specific behaviors. Here, we show that this approach can also be applied on satellite observations and can even be further improved by testing performances of different machine learning algorithms, the SVR and a neural network with dense layers (a multi-layer perceptron, MLP). The MLP, thanks to its ability to capture complex non-linear relationships, outperforms the SVR to capture satellite Chl spatial patterns (correlation of 0.75 vs. 0.65 on a global scale, respectively) along with its interannual variability and trend, despite an underestimated amplitude. Among deep learning algorithms, neural network such as MLP models appear to be promising tools to investigate phytoplankton long-term time-series.

Temporal patterns of iron limitation in the Ross Sea as determined from chlorophyll fluorescence

The Ross Sea is one of the most productive regions in the Southern Ocean, with a significant role in carbon cycling as well as the massive abundance of higher trophic levels. The seasonal cycle is well established with an early summer Phaeocystis antarctica bloom that declines followed by a diatom bloom in late summer. This seasonal progression of the phytoplankton has been linked to the availability of iron in the mixed layer. Investigating the temporal progression of iron limitation is often limited by both the decreased sampling resolution from traditional platforms, such as ships, and the lack of regular deployments of specific sensors that can measure phytoplankton physiology. Through the use of a novel technique that uses the degree of quenching (NPQGlider), determined from a standard fluorometer deployed on a buoyancy glider, a proxy for iron limitation, αNPQ, was calculated for a glider time series in the Ross Sea from December 2011 to February 2012. Surface chlorophyll concentrations indicated that there were four stages: the first being a pre-bloom phase, the second in which phytoplankton growth was rapid, resulting in the accumulation of biomass; the third in which biomass in the surface layer decreased, and the fourth in which chlorophyll concentrations remained low but the POC:Chl ratio increased. The levels of NPQGlider in this region were much higher compared to other Southern Ocean regions, with the highest levels in the third phase. Similarly, αNPQ remained low throughout most of the time series except for the transition from the second to third phase when the surface biomass decreases. The increase in POC:Chl ratios in the final phase combined with the low values of αNPQ suggest the switch from a Phaeocystis antarctica bloom to a potentially non-iron limited diatom bloom. These results confirm that the application of novel methodologies to proven and reliable sensors will provide a greater understanding of biogeochemical cycles and their controls throughout the ocean.

Interannual-decadal variation in satellite-derived surface chlorophyll-a concentration in the Bohai Sea over the past 16 years

Chlorophyll-a (Chl-a) concentration is an important indicator of the state of marine ecosystems. In the current study, the interannual-decadal variation in the Bohai Sea's surface Chl-a concentration and the underlying dynamics are investigated based on 16 years (August 2002–February 2019) of satellite ocean colour observations. The Chl-a concentration shows a spatially coherent increasing trend from 2003 to 2011 and a decreasing trend from 2012 to 2018 in both the Bohai and North Yellow Seas. Both decadal trends are clearer in the Bohai Sea than in the Yellow Sea and in coastal waters than in offshore waters. The decreasing trend is more obvious than the increasing trend. The low-frequency variations are mainly controlled by sea surface temperature (SST) and rainfall variations and eventually related to the Pacific Decadal Oscillation (PDO). During positive PDO phases, warm SST anomalies exist in the Bohai and Yellow Seas and negative rainfall anomalies exist over the sea and surrounding lands. These anomalies would decrease the surface layer dissolved inorganic nitrogen concentration through suppressing the upward turbulent nutrient diffusion and reducing land-sourced nutrient fluxes into the ocean, leading to negative Chl-a concentration anomalies. During negative PDO phases, the opposite situation occurs. Human activities may make a secondary contribution through enhancing/reducing the anthropogenic nitrogen emission before/after 2011. This study emphasizes the natural climate variability in modulating low-frequency variations in surface Chl-a concentrations in the Bohai and Yellow Seas in recent decades and is useful for marine resource planning and marine ecological management in the Bohai Sea in the future. • Surface chlorophyll-a concentration in the Bohai Sea has interannual-decadal variation. • Spatially coherent upward trend over 2003–2011 and downward trend over 2012–2018. • Downward trends are more obvious than upward trends. • Chlorophyll-a concentration variation is related to the Pacific Decadal Oscillation.

Seasonal variability of gelatinous zooplankton during an anomalously warm year at Cabo Pulmo National Park, Mexico

The seasonal variability of gelatinous zooplankton (siphonophores, medusae, and thaliaceans) abundance was investigated at Cabo Pulmo National Park (CPNP) from weekly zooplankton samples collected throughout 2014. The Gulf of California had prolonged warming during 2009-2019, with 2014 as the anomalously warm year preceding El Niño 2015-2016 compared to the 2003-2020 SST time series. Gelatinous zooplankton accounted <1% of the entire zooplankton community abundance at CPNP during 2014, suggesting a low influence of predation pressure upon their zooplanktonic and micronekton preys. Siphonophores (57%), thaliaceans (42%), and medusae (1%) were present throughout the year. The abundance of gelatinous zooplankton had a significant negative association with sea surface temperature and a positive association with sea surface chlorophyll-a concentration and velocity and direction of the wind, increasing their abundance during October after the hurricane season. The gelatinous zooplankton species assemblage at the coastal CPNP was similar but less abundant than the gelatinous zooplankton species assemblage observed in the oceanic region of the southern Gulf of California during summer 2014. Tropical species Diphyes dispar, Abylopsis tetragona, Chelophyes contorta, and Thalia spp. numerically dominated the gelatinous zooplankton community associated with a regional heatwave period recorded during 2014. A high proportion of tropical zooplankton indicates that mesotrophic conditions sustain the current high biomass and diversity of nektonic and benthonic planktophagous fauna inhabiting CPNP. However, prolonged warming events might decrease zooplankton biomass in the southern region of the Gulf of California in the future.