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Essential Climate Variables (ECVs) like ocean colour provide crucial information on the Optically Active Constituents (OACs) of seawater, such as phytoplankton, non-algal particles, and coloured dissolved organic matter (CDOM). The challenge in estimating these constituents through remote sensing is in accurately distinguishing and quantifying optical and biogeochemical properties, e.g., absorption coefficients and the concentration of chlorophyll a (Chla), especially in complex waters. This study evaluated the temporal and spatial variability of bio-optical properties in the coastal waters of the Western Iberian Coast (WIC), contributing to the assessment of satellite retrievals. In situ data from three oceanographic cruises conducted in 2019–2020 across different seasons were analyzed. Field-measured biogenic light absorption coefficients were compared to satellite estimates from Ocean-Colour Climate Change Initiative (OC-CCI) reflectance data using semi-analytical approaches (QAA, GSM, GIOP). Key findings indicate substantial variability in bio-optical properties across different seasons and regions. New bio-optical coefficients improved satellite data retrieval, reducing uncertainties and providing more reliable phytoplankton absorption estimates. These results highlight the need for region-specific algorithms to accurately capture the unique optical characteristics of coastal waters. Improved comprehension of bio-optical variability and retrieval techniques offers valuable insights for future research and coastal environment monitoring using satellite ocean colour data. [ABSTRACT FROM AUTHOR]

Essential Climate Variables (ECVs) like ocean colour provide crucial information on the Optically Active Constituents (OACs) of seawater, such as phytoplankton, non-algal particles, and coloured dissolved organic matter (CDOM). The challenge in estimating these constituents through remote sensing is in accurately distinguishing and quantifying optical and biogeochemical properties, e.g., absorption coefficients and the concentration of chlorophyll a (Chla), especially in complex waters. This study evaluated the temporal and spatial variability of bio-optical properties in the coastal waters of the Western Iberian Coast (WIC), contributing to the assessment of satellite retrievals. In situ data from three oceanographic cruises conducted in 2019–2020 across different seasons were analyzed. Field-measured biogenic light absorption coefficients were compared to satellite estimates from Ocean-Colour Climate Change Initiative (OC-CCI) reflectance data using semi-analytical approaches (QAA, GSM, GIOP). Key findings indicate substantial variability in bio-optical properties across different seasons and regions. New bio-optical coefficients improved satellite data retrieval, reducing uncertainties and providing more reliable phytoplankton absorption estimates. These results highlight the need for region-specific algorithms to accurately capture the unique optical characteristics of coastal waters. Improved comprehension of bio-optical variability and retrieval techniques offers valuable insights for future research and coastal environment monitoring using satellite ocean colour data.

HJ-2 (Huanjing-2) was launched in September 2020. It has a charge-coupled device (CCD) that offers a spatial resolution of 16 m and a revisiting time of two days, making it an excellent option for environmental and disaster monitoring. However, more evaluation is needed for the ability of CCD to monitor water quality. As chlorophyll a concentration (CChla) is the main indicator for water quality evaluation, in this study, the performance of the CCD sensor to monitor CChla has been verified, with a particular focus on typical eutrophic lakes. The essential findings can be summarized as follows: (1) the CCD sensor has a signal-to-noise ratio (SNR) greater than 400 in all bands except the green band, indicating that it meets the requirements for water quality monitoring; (2) the semi-empirical estimation model of CChla derived from HJ-2 CCD has a mean absolute deviation (MAD) of 8.18 μg/L, root mean square deviation (RMSD) of 10.66 μg/L and mean absolute percentage deviation (MAPD) of 20.93 %; (3) the higher temporal and spatial resolution of the CCD data enables effective monitoring of water quality parameters characterized by high spatiotemporal variations; (4) HJ-2 CCD exhibits strong consistency with Sentinel-2 MSI and Sentinel-3 OLCI across various bands, with most bands showing correlation coefficients exceeding 0.8 and a MAPD below 30 %. This study reveals the significant potential and practical value of HJ-2 CCD data for monitoring and assessing water quality, providing important information for the design and development of next-generation satellites.

Multiple factors influence the spatial and temporal chlorophyll‐a concentration of marine systems. The Hudson Bay Complex has historically been seen as a large, low‐production inland sea situated in the north of Canada. However, recent field campaigns, for the BaySys project, have provided new data on primary production in the bay. Due to the Hudson Bay complex's positioning, it experiences seasonal sea‐ice cover and has many rivers draining into it, resulting in a unique estuarine‐like environment. We use the biogeochemical model BLINGv0 + DIC, coupled to the online regional physical oceanographic and sea‐ice models, NEMOv3.6 and LIM2, respectively, forced with two bias‐corrected Coupled Model Intercomparison Project 5 climate forcings (MIROC5 and MRI) to simulate the base of the ecosystem. The simulations were evaluated with chlorophyll‐a satellite imagery and observations collected in 2018 and analyzed with Empirical Orthogonal Functions to understand the underlying physical forcings and key areas of chlorophyll‐a concentration distribution. The evaluation showed that both simulations successfully reproduced the sea‐ice melt, from west to east and formation, from north to south and correlated well with spatial bloom patterns. The main drivers of phytoplankton growth are the seasonal light and nutrient levels (48% and 54%), the mixed layer depth dynamics (18% and 14%), nutrient supply from rivers (13% and 8%), and sea ice production (7%) for the MIROC5 and MRI simulations, respectively. The sea‐ice dynamics and river runoff played a significant role in the system's productivity. Therefore, with future climate change and increased river regulation projects, up to 20% of overall chlorophyll‐a may be negatively impacted. Plain Language Summary: The Hudson Bay Complex (HBC) is an inland sub‐Arctic sea that is covered by sea ice from December to June. Many rivers drain into the bay, making it a relatively fresh marine environment. Due to its size, difficulty to access, and seasonal ice cover, it is a challenging environment to sample. A recent Hudson Bay system study, BaySys, has allowed us to understand that the HBC is more productive than previously thought. Using regional numerical ocean, sea ice, and biological models, we can simulate the biological productivity in this area with two different climate forcings. Comparing the simulations with satellite and in situ observations from 2018, we can see that our models simulate sea‐ice production and the spatial and temporal pattern of chlorophyll a relatively well. Using a statistical method called Empirical Orthogonal Functions, we could identify that the physical components influencing this region's phytoplankton growth are the mixed layer depth, river runoff into the area and sea‐ice melt and freeze cycle. The HBC expects to experience significant climate change and changes in river runoff in the future. Any changes in these two physical forcings can negatively impact up to 20% of the overall chlorophyll a distribution patterns. Key Points: Physical and biogeochemical models can be used to understand the underlying drivers of primary productivityThe biogeochemical model, BLINGv0 + DIC, simulates the spatial and temporal distributions of chlorophyll a within the Hudson Bay ComplexMixed layer depth dynamics, river runoff, and sea‐ice production were observed to have the largest impact on simulated chlorophyll a [ABSTRACT FROM AUTHOR]

Using observational data from multiple satellites, we studied seasonal variations of the shape and location of the Luzon cold eddy (LCE) northwest of Luzon Island. The shape and location of the LCE have obvious seasonal variations. The LCE occurs, develops, and disappears from December to April of the next year. During this period, the shape of the LCE changed from a flat ellipse to a circular ellipse, and the change in shape can be reflected by the increase of the ellipticity of the LCE from 0.16 to 0.82. The latitude of center location of the LCE changes from 17.4°N to 19°N, and the change in latitude can reach 1.6°. Further study showed that seasonal variation of the northeast monsoon intensity leads to the change in the shape and location of the LCE. The seasonal variation of the LCE shape can significantly alter the spatial distribution of the thermal front and chlorophyll a northwest of the Luzon Island by geostrophic advection. [ABSTRACT FROM AUTHOR]

Low- and medium-resolution satellites have been a relatively mature platform for inland eutrophic water classification and chlorophyll a concentration (Chl-a) retrieval algorithms. However, for oligotrophic and mesotrophic waters in small- and medium-sized reservoirs, problems of low satellite resolution, insufficient water sampling, and higher uncertainty in retrieval accuracy exist. In this paper, a hybrid Chl-a estimation method based on spectral characteristics (i.e., remote sensing reflectance (Rrs)) classification was developed for oligotrophic and mesotrophic waters using high-resolution satellite Sentinel-2 (A and B) data. First, 99 samples and quasi-synchronous Sentinel-2 satellite data were collected from four small- and medium-sized reservoirs in central China, and the usability of the Sentinel-2 Rrs data in inland oligotrophic and mesotrophic waters was verified by accurate atmospheric correction. Second, a new optical classification method was constructed based on different water characteristics to classify waters into clear water, phytoplankton-dominated water, and water dominated by phytoplankton and suspended matter together using the thresholds of Rrs490/Rrs560 and Rrs665/Rrs560. The proposed method has a higher classification accuracy compared to other classification methods, and the band-ratio algorithm is simpler and more effective for satellite sensors without NIR bands. Third, given the sensitivity of the empirical method to water variability and the ease of development and implementation, a nonlinear least squares fitted one-dimensional nonlinear function was established based on the selection of the best-fitting spectral indices for different optical water types (OWTs) and compared with other Chl-a estimation algorithms. The validation results showed that the hybrid two-band method had the highest accuracy with squared correlation coefficient, root mean squared difference, mean absolute percentage error, and bias of 0.85, 2.93, 32.42%, and −0.75 mg/m3, respectively, and the results of the residual values further validated the applicability and reliability of the model. Finally, the performance of the classification and estimation algorithms on the four reservoirs was evaluated to obtain images mapping the Chl-a in the reservoirs. In conclusion, this study improves the accuracy of Chl-a estimation for oligotrophic and mesotrophic waters by combining a new classification algorithm with a two-band hybrid model, which is an important contribution to solving the problem of low resolution and high uncertainty in the retrieval of Chl-a in oligotrophic and mesotrophic waters in small- and medium-sized reservoirs and has the potential to be applied to other optically similar oligotrophic and mesotrophic lakes and reservoirs using similar spectrally satellite sensors. [ABSTRACT FROM AUTHOR]

Chlorophyll a concentration (CHL) is an important proxy of the marine ecological environment and phytoplankton production. Long-term trends in CHL of the South China Sea (SCS) reflect the changes in the ecosystem's productivity and functionality in the regional carbon cycle. In this study, we applied a previously reconstructed 15-a (2005–2019) CHL product, which has a complete coverage at 4 km and daily resolutions, to analyze the long-term trends of CHL in the SCS. Quantile regression was used to elaborate on the long-term trends of high, median, and low CHL values, as an extended method of conventional linear regression. The results showed downward trends of the SCS CHL for the 75th, 50th, and 25th quantile in the past 15 a, which were −0.004 0 mg/(m3·a) (−1.62% per year), −0.002 3 mg/(m3·a) (−1.10% per year), and −0.001 9 mg/(m3·a) (−1.01% per year). The negative trends in winter (November to March) were more prominent than those in summer (May to September). In terms of spatial distribution, the downward trend was more significant in regions with higher CHL. These led to a reduced standard deviation of CHL over time and space. We further explored the influence of various dynamic factors on CHL trends for the entire SCS and two typical systems (winter Luzon Strait (LZ) and summer Vietnam Upwelling System (SV)) with single-variate linear regression and multivariate Random Forest analysis. The multivariate analysis suggested the CHL trend pattern can be best explained by the trends of wind speed and mixed-layer depth. The divergent importance of controlling factors for LZ and SV can explain the different CHL trends for the two systems. This study expanded our understanding of the long-term changes of CHL in the SCS and provided a reference for investigating changes in the marine ecosystem. [ABSTRACT FROM AUTHOR]

The 3-year-long (2019–2021) dynamics of the qualitative and quantitative composition of plankton communities in the lower reaches of the Northern Dvina River is analyzed. The results of the analysis of the species richness and the taxonomic composition of zooplankton, as well as of the spacetime distribution of the abundance and biomass of phyto- and zooplankton, are presented. The mean annual phytoplankton biomass and the chlorophyll a concentration varied from 0.42 g/m3 and 1.04 mg/L in the preestuary coastal areas in 2021 to 2.16 g/m3 and 5.41 mg/L, respectively, in the Kuznechikha channel in 2020. The species list of zooplankton for the study period included 79 species, the number of which in samples varied from 33 in 2020–2021 to 75 in 2019. In the temporal aspect, the highest quantitative parameters of zooplankton were revealed in 2021; in the spatial aspect, their highest values were recorded in the Kuznechikha and Maimaksa channels in all years of research. The main contribution to zooplankton abundance and biomass was made by species of the genera Bosmina and Eurytemora. [ABSTRACT FROM AUTHOR]

Priority Marine Regions (PMR) are important areas for biodiversity conservation in the Northwest Pacific Ocean in Mexico. The oceanographic dynamics of these regions are very important to understand their variability, generate analyses, and predict climate change trends by generating an adequate management of marine resources and their ecological characterization. Chlorophyll a (Chl a) is important to quantify phytoplankton biomass, consider the main basis of the trophic web in marine ecosystems, and determine the primary productivity levels and trends of change. The objective of this research is to analyze the oceanographic variability of 24 PMR through monthly 1-km satellite image resolution Chl a data from September 1997 to October 2018. A cluster analysis of Chl a data yielded 18 regions with clear seasonal variability in the Chl a concentration in the South-Californian Pacific (maximum values in spring-summer and minimum ones in autumn-winter) and Gulf of California (maximum values in winter-spring and minimum ones in summer-autumn). Significant differences (p < 0.05) were observed in Chl a concentration analyses for each one of the regions when climate patterns—El Niño/La Niña Southern Oscillation (ENSO) and normal events—were compared for all the seasons of the year (spring, summer, autumn, and winter). [ABSTRACT FROM AUTHOR]

Chlorophyll a concentration is an important indicator to characterize phytoplankton biomass, which further reflects the water quality of lakes. Based on the data of chlorophyll a concentration and environmental factors extracted from the ChlaData, HydroLAKES, and HELLAKES databases for Chinese lakes for three years (2000, 2005, and 2010), we used the random forest model and the generalized linear model to analyze the relationship between chlorophyll a concentration and environmental factors in Chinese lakes and predict the chlorophyll a concentration. The results showed that the relative importance of environmental factors for chlorophyll a was as follows: nutrient salt concentration > longitude and latitude > monthly mean precipitation > altitude > annual average temperature. The coefficient of determination of the random forest model was 0.9997 (R2 = 0.9997), and the root-mean-square error was 0.0010 (RMSE = 0.0010), with high prediction accuracy. The random forest model and the generalized linear model both showed that TP was the main influencing factor of chlorophyll a concentration. The validation results based on the measured data show that the models are reliable. By making more accurate predictions of chlorophyll a concentrations, we can facilitate the prevention, control, and treatment of lake blooms. [ABSTRACT FROM AUTHOR]

Lake eutrophication is a global water environmental problem and has become a research focus nowadays. Chlorophyll a concentration is an important index in terms of evaluating lake eutrophication. The aim of this study was to build an effective and universal empirical model for simulation of chlorophyll a concentration in Donghu Lake. On the basis of the relationship between chlorophyll a concentration and dissolved oxygen (DO), water temperature (T), total nitrogen (TN), and total phosphorus (TP), models for simulating chlorophyll a concentration were built by using simulated annealing (SA), genetic algorithm (GA), artificial bee colony (ABC), and particle swarm optimization (PSO) to optimize parameters of support vector machine (SVM). Moreover, a collaborative mode (Col-SVM model) was built by introducing data assimilation, and meanwhile, accuracy and universality of the model were studied. Modeling results showed that the application of optimization algorithms and data assimilation improved the performance of modeling based on SVM. Model simulation results demonstrated that the Col-SVM model has high accuracy, decent stability, and good simulation effect; the root mean square error (RMSE), mean absolute percentage error (MAPE), Nash–Sutcliffe efficiency coefficient (NSE), bias, and mean relative error (MRE) between simulated values and observed values were 10.07 μg/L, 0.31, 0.96, −0.050, and 0.15, respectively. In addition, model universality analysis results revealed that the Col-SVM model has good universality and can be used to simulate the chlorophyll a concentration of Donghu Lake at different times. Overall, we have built an effective and universal simulation model of chlorophyll a concentration that provides a new idea and method for chlorophyll a concentration modeling. [ABSTRACT FROM AUTHOR]

The study assesses dynamics of phytoplankton biomass in the surface layer, the depth of the upper mixed layer, and the photic zone based on satellite data in the deep sea and coastal regions of the Black Sea for 1998–2015. The annual biomass dynamics had the same character in all regions and was described by a U-shaped curve with some deviation in the spring. Average seasonal values were at the maximum in winter and minimum in summer, differing by 2–2.5-fold. Phytoplankton blooms with an average duration 1–2.5 months were present in all seasons, but with different frequencies. The highest numbers were recorded in spring, minimal numbers in summer and fall; during the bloom, biomass was twice as much as the background values. Phytoplankton biomass grew with decrease in water temperature and increase in mixed layer depth during fall. There was no such dependence during the other seasons. The dynamics of the annual average biomass showed negative trend in the deep sea from 1998 to 2015, the latter was not observed in the coastal zone. The strongest decrease in biomass was recorded in spring and summer; it was not observed in winter and fall. [ABSTRACT FROM AUTHOR]

Chlorophyll a concentration (Chl-a), wind, and water temperature were measured at a buoy moored near Dok-Do in the Japan/East Sea (JES). Short-term (1–3 day) enhancements of Chl-a associated with the surface layer cooling observed in spring (May–June) and autumn (Oct-Nov) were found to be correlated with the Ekman pumping induced by the interaction of the eddy current and wind, separable into components due to the wind stress and the lateral gradient in vertical vorticity. In the spring, surface Chl-a increases in conjunction with upwelling due to the lateral gradient in vorticity and the curl of the wind stress. However, in fall, positive Chl-a anomalies are only correlated with upwelling due to the curl of relative wind stress, which arises from the difference between the wind and the ocean surface current. The observed response time of the upwelling induced by wind-current interaction was very short (less than a day) compared to most theoretical studies which are driven by steady winds of more than 3 days. Our analysis suggests that as the mixed layer deepens, Chl-a at the surface is enhanced by the turbulent mixing of the underlying mixed layer water with high Chl-a and nutrients. However, the upwelling is a necessary condition for it to occur. [ABSTRACT FROM AUTHOR]

Low- and medium-resolution satellites have been a relatively mature platform for inland eutrophic water classification and chlorophyll a concentration (Chl-a) retrieval algorithms. However, for oligotrophic and mesotrophic waters in small- and medium-sized reservoirs, problems of low satellite resolution, insufficient water sampling, and higher uncertainty in retrieval accuracy exist. In this paper, a hybrid Chl-a estimation method based on spectral characteristics (i.e., remote sensing reflectance (Rrs)) classification was developed for oligotrophic and mesotrophic waters using high-resolution satellite Sentinel-2 (A and B) data. First, 99 samples and quasi-synchronous Sentinel-2 satellite data were collected from four small- and medium-sized reservoirs in central China, and the usability of the Sentinel-2 Rrs data in inland oligotrophic and mesotrophic waters was verified by accurate atmospheric correction. Second, a new optical classification method was constructed based on different water characteristics to classify waters into clear water, phytoplankton-dominated water, and water dominated by phytoplankton and suspended matter together using the thresholds of Rrs490/Rrs560 and Rrs665/Rrs560. The proposed method has a higher classification accuracy compared to other classification methods, and the band-ratio algorithm is simpler and more effective for satellite sensors without NIR bands. Third, given the sensitivity of the empirical method to water variability and the ease of development and implementation, a nonlinear least squares fitted one-dimensional nonlinear function was established based on the selection of the best-fitting spectral indices for different optical water types (OWTs) and compared with other Chl-a estimation algorithms. The validation results showed that the hybrid two-band method had the highest accuracy with squared correlation coefficient, root mean squared difference, mean absolute percentage error, and bias of 0.85, 2.93, 32.42%, and −0.75 mg/m3, respectively, and the results of the residual values further validated the applicability and reliability of the model. Finally, the performance of the classification and estimation algorithms on the four reservoirs was evaluated to obtain images mapping the Chl-a in the reservoirs. In conclusion, this study improves the accuracy of Chl-a estimation for oligotrophic and mesotrophic waters by combining a new classification algorithm with a two-band hybrid model, which is an important contribution to solving the problem of low resolution and high uncertainty in the retrieval of Chl-a in oligotrophic and mesotrophic waters in small- and medium-sized reservoirs and has the potential to be applied to other optically similar oligotrophic and mesotrophic lakes and reservoirs using similar spectrally satellite sensors.

One of the main concerns of environmental and ecological managers for rivers, lakes, reservoirs, and marine ecosystems is developing a reliable and efficient predictive model for chlorophyll a concentration. In this study, the online sequential extreme learning machine, M5 Prime tree, multilayer perceptron artificial neural network, response surface methodology, and multivariate adaptive regression spline models were investigated for daily chlorophyll a concentration prediction by assessing the relations between Chl-a and several water quality parameters, including water temperature, pH, specific conductance, and turbidity. Different scenarios based on TE, pH, SC, and TU were defined. Also, this study evaluated the influence of periodicity input as the last scenario to obtain more accurate predictions of Chl-a values. Daily data measured for 2009–2019 from USGS no. 14207200 and USGS no. 14211720 stations were used. For assessing the prediction performance of the proposed techniques, three different objective indicators were employed, namely RMSE, R2, and NSE. Moreover, the Taylor diagram was employed for evaluating the accuracy and generalization capability of the applied models for the prediction of Chl-a. Results indicated that OS-ELM with input parameters of TE, pH, SC, TU, Y (year), M (month), and D (day) showed higher accuracy in predicting Chl-a with RMSE of 3.151, NSE of 0.798, and R of 0.894 for USGS no. 14207200 and with RMSE of 0.907, NSE of 0.820, and R of 0.912 for USGS no. 14211720 than the other models, respectively. Additionally, MLPNN ranked as the second best method for the estimation of Chl-a values at both stations. As an interesting point, it was quite evident that adding periodicity as an input parameter could significantly enhance the performance of all models in predicting the daily Chl-a concentration at both stations. Results proved that OS-ELM models can be a reliable tool for the prediction of the Chl-a values in aquatic environments, benefiting ecological and environmental management, and algal bloom control. [ABSTRACT FROM AUTHOR]

The Indo-Pacific humpback dolphin (Sousa chinensis) has been reported to prefer estuary habitats. This study explored the environmental factors affecting a critically endangered population off the coast of Yunlin, Taiwan. We measured dolphin sighting rates and estuary characteristics affected by the watershed, including seven physical factors (watershed rainfall, watershed runoff, estuarine turbidity, pH, salinity, temperature, and dissolved oxygen) and two biological factors (estuarine net primary production and chlorophyll a concentration), at the Hsinhuwei River estuary in Taiwan. Dolphin activity was measured by sighting rate and behavioral indices for feeding and traveling between 2017 and 2018. We observed that when the maximum net production increased alongside rising temperatures in spring, both the dolphin sighting rate and foraging activity increased. This trend was maintained until heavy rainfall or increased river runoff occurred during late summer, which resulted in high turbidity in autumn and winter. Turbidity was significantly negatively correlated with dolphin activity (sighting rate and foraging). Furthermore, we found that dolphin traveling positively correlated with the chlorophyll a concentration and maximum net production factors, which could attract dolphins expecting more abundant prey fish in the estuary supported by the high primary production. This study provides empirical evidence on how estuary characteristics affected by the watershed can affect the sighting rate and behavioral activities of Indo-Pacific humpback dolphins.

Based on the measurement data obtained during the 121th cruise of the RV Professor Vodyanitsky , regularities were established between spatial distribution of quantitative characteristics and phytoplankton species composition, chlorophyll a concentration, and hydrometeorological parameters of the environment on the southern Crimean coast in the spring 2022. Chlorophyll a concentration was compared with satellite observation data of high spatial resolution. In selected areas with different shelf depths, the features of the distribution of phytoplankton indicators under conditions of changing hydrometeorological parameters were studied. The mechanisms of vertical water exchange were described. In coastal waters of the Crimea (Foros–Novy Svet), with intense western wind contributing to Ekman upwelling and low water temperature is a consequence of the upwelling, rather high values of phytoplankton biomass and abundance and chlorophyll a concentration were recorded, which were accompanied by the highest values of oxygen content. In the area of Sudak–Feodosiya, with intense northeastern wind and waves and with quite high water temperature, low dissolved oxygen, low values of phytoplankton biomass and abundance and chlorophyll a concentration were registered. Apparently, in Sevastopol area, Ekman upwelling arises under the effect of northern and northwestern winds. In three regions, dinoflagellate microalgae prevailed in spring 2022 in phytoplankton biomass. Those accounted for 52, 66, 81 % of the total number of species identified in the regions: Foros–Novy Svet, Sudak–Feodosiya, near Sevastopol, respectively. Thus, the main mechanisms were analyzed, which drive spatial distribution of quantitative characteristics and species composition of the phytoplankton community in the Crimean coastal water area with different shelf depths in spring. • The mechanisms of vertical mixing are studied.. • Particular attention is paid to the effect of wind–wave characteristics on phytoplankton distribution in the shelf areas on the southern Crimean coast (Black Sea) in spring. • Western and southwestern winds positively affect the phytoplankton on the Foros–Yalta area. Northeastern winds and waves adversely affect phytoplankton abundance in the Sudak–Feodosiya area. • The prevalence of dinoflagellates in phytoplankton biomass is determined. [ABSTRACT FROM AUTHOR]

Priority Marine Regions (PMR) are important areas for biodiversity conservation in the Northwest Pacific Ocean in Mexico. The oceanographic dynamics of these regions are very important to understand their variability, generate analyses, and predict climate change trends by generating an adequate management of marine resources and their ecological characterization. Chlorophyll a (Chl a) is important to quantify phytoplankton biomass, consider the main basis of the trophic web in marine ecosystems, and determine the primary productivity levels and trends of change. The objective of this research is to analyze the oceanographic variability of 24 PMR through monthly 1-km satellite image resolution Chl a data from September 1997 to October 2018. A cluster analysis of Chl a data yielded 18 regions with clear seasonal variability in the Chl a concentration in the South-Californian Pacific (maximum values in spring-summer and minimum ones in autumn-winter) and Gulf of California (maximum values in winter-spring and minimum ones in summer-autumn). Significant differences (p < 0.05) were observed in Chl a concentration analyses for each one of the regions when climate patterns—El Niño/La Niña Southern Oscillation (ENSO) and normal events—were compared for all the seasons of the year (spring, summer, autumn, and winter).

In this study we evaluated the applicability of a space-borne hyperspectral sensor, Hyperion, to resolve for chlorophyll a (Chl a) concentration in Lake Atitlan, a tropical mountain lake in Guatemala. In situ water quality samples of Chl a concentration were collected and correlated with water surface reflectance derived from Hyperion images, to develop a semi-empirical algorithm. Existing operational algorithms were tested and the continuous bands of Hyperion were evaluated in an iterative manner. A third order polynomial regression provided a good fit to model Chl a. The final algorithm uses a blue (467 nm) to green (559 nm) band ratio to successfully model Chl a concentrations in Lake Atitlán during the dry season, with a relative error of 33%. This analysis confirmed the suitability of hyperspetral-imagers like Hyperion, to model Chl a concentrations in Lake Atitlán. This study also highlights the need to test and update this algorithm with operational multispectral sensors such as Landsat and Sentinel-2.

To study the water dynamics in the western Bering Sea, the time series of geostrophic velocities derived from satellite altimetry, Global total current (Copernicus Globcurrent) velocities, Argo buoys, and ship, borne data are analyzed. We demonstrate that the surface currents in the study area are characterized by a significant seasonal and interannual variability. In January, the southwestern currents are prevailing in the western Bering Sea, the geostrophic currents are connected to the continental slope, and mesoscale anticyclonic movement of waters is observed on the shelf. In July, the surface flow is oriented to the northeast along the continental slope, and cyclonic water movement prevails on the shelf. The formation of mesoscale anticyclones in late winter – early spring – is related to the supply of low-temperature and low-salinity Bering Sea shelf water. The temporal variability of the direction and current velocity in the western part of the Bering Sea during the summer period is associated with the wind and coastal upwelling. The presence of coastal upwelling and eddies should be considered as one of the factors leading to the high concentration of chlorophyll a on a shelf and continental slope in the summer. [ABSTRACT FROM AUTHOR]

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In order to solve the regional and seasonal limitations of the algorithm, the database is introduced into the chlorophyll a concentration inversion. Usually, the inherent optical quantity of different water bodies in different seasons is obtained through a large number of field experiments and laboratory analysis, and stored in the database, and the index is established according to water body, season and inherent optical quantity. The main content of this paper is to quantitatively monitor the concentration, distribution and evolution of chlorophyll a in turbid and eutrophic water bodies such as Taihu Lake by remote sensing. The research of inversion method and strategy based on measured spectrum of water surface provides theoretical and methodological support for its application in remote sensing images. The data obtained in this paper mainly include: water quality parameters, apparent optical quantity and inherent optical quantity of Taihu Lake. The results show that the correlation coefficient R2=0.936, which is linear and sensitive to high-value areas. This result not only reflects the feasibility of the ratio index model for chlorophyll content inversion, but also shows that the absolute error is basically below 23 mg/m3, and the inversion result is relatively stable.

A regional model is proposed for the estimation of the specific growth rate of phytoplankton in the sea surface layer using satellite data. The model is based on phytoplankton photosynthesis rate and biomass in organic carbon units. The phytoplankton photosynthesis rate was calculated based on ecological and physiological characteristics that were previously obtained for the Black Sea. The input parameters of the model are the chlorophyll concentration in the surface layer, water temperature, the intensity of the photosynthetic active radiation falling on the sea surface, the depth of the mixed layer, and the diffuse light attenuation coefficient. Seasonal variations in specific growth rate of phytoplankton were estimated for deep-water and near-Danube areas. The maximum values were found in the coastal area in May–June, the minimum values were observed in deep waters before the spring maximum of phytoplankton. The maximum and minimum values differed by a factor 5. The measured and calculated values of phytoplankton specific growth rate at individual stations and in selected extensive areas of the sea were fairly close. The model can be used for rapid estimation of the specific growth rate of phytoplankton in the sea surface layer using satellite data. [ABSTRACT FROM AUTHOR]

The vertical distribution of the concentration of chlorophyll a (Chl) and colored dissolved organic matter (CDOM), temperature (T), and salinity (S) were studied at two diel stations located at close coordinates and performed at a weekly interval and seven stations spaced 1 mi apart on hydrological section in the shelf zone of Possjet Bay (Sea of Japan) in the autumn of 2014. The Chl concentration was estimated from fluorescence intensity (FChl). In the surface layer of the diel stations, the Chl concentration varied within ± 10% of the mean value. In the water column, a negative correlation of FChl with T and a positive relationship of S with CDOM were established at both stations. At all stations, the maximum Chl concentration occurred under the seasonal pycnocline layer. [ABSTRACT FROM AUTHOR]

Large canyons incise the shelf break of the eastern Bering Sea to be preferred sites of the cross-shelf exchange. The mesoscale eddy activity is particularly strong near the shelf-break canyons. To study the mesoscale dynamics in the Navarin Canyon area of the Bering Sea, the time series of velocities derived from AVISO satellite altimetry between 1993 and 2015, drifters, Argo buoys, and ship-borne data are analyzed. We demonstrate that the strength of anticyclonic eddies along the shelf edge in spring and summer is determined by the wind stress in March-April. The increased southward wind stress in the central Bering Sea forced a supply of low-temperature and low-salinity outer shelf water to the deep basin and formation of the anticyclonic mesoscale circulation seaward of the Navarin Canyon. Enhanced northwestward advection of the Bering Slope Current water leads to increase in an ice-free area in March and April and increased bottom-layer temperature at the outer shelf. The strong (weak) northwestward advection of the eastern Bering Sea waters, determined by eastern winds in spring, creates favorable (unfavorable) conditions for the pollock abundance in the western Navarin Canyon area in summer. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • EFDC was applied to simulate the chl- a distribution in the Yangtze River and Xiangxi Bay. • Using water age to quantify the effects of upstream inflows and intrusion flow on chl- a in Xiangxi Bay. • Water age and temperature are key factors influencing algal blooms in study area. • Algal blooms occurred mostly in the tributaries but not in the Yangtze River due to distinct water age features. Abstract After the impoundment of Three Gorges Reservoir, algal blooms frequently occurred in the tributaries of the reservoir, which has posed a great challenge for the local aquatic environment and ecology. To investigate the main causes and key factors of the algal blooms, the Environmental Fluid Dynamics Code (EFDC) model is applied to the simulation of the three-dimensional hydrodynamics and water quality in the Yangtze River and Xiangxi Bay, and the concept of water age is adopted to quantitatively analyze the effects of hydrodynamics on the water quality by linking water age and phytoplankton levels, which has seldom been explored in previous studies. The model results show good agreement with the field data, and the simulation reproduces the thermal stratification and density current in Xiangxi Bay. The results show that Xiangxi Bay exhibits quite complicated hydrodynamic characteristics, and could be divided into different zones according to the transport process. In the upper reach, the water quality is mainly affected by the upstream inflows, while it is mainly affected by the intrusion flow from the mainstream near the river mouth. Water age and water temperature are found to be the key factors influencing the algal blooms in Xiangxi Bay. Besides, a significant positive correlation has been found between the chlorophyll a (chl- a) concentration in the surface layer and the water age of the dominant water source. This conclusion can be adopted to interpret the longitudinal distribution of chl- a concentration and to explain why Xiangxi Bay is susceptible to algal blooms. The correlation between water age and chl- a concentration is further used to evaluate the effectiveness of water level fluctuation in preventing algal blooms. The analyses and findings in this study could help to better understand the complicated hydrodynamic and water quality processes in Xiangxi Bay following the impoundment, and provide insights into ecological and environmental management of Three Gorges Reservoir. [ABSTRACT FROM AUTHOR]

Using the data of long-term observations of the Secchi disk visibility depth and water salinity (1947-2000) and satellite monitoring of chlorophyll a concentration (1978-1986), their seasonal spatial distributions and intraannual variability in the coastal waters of the western Black Sea are considered. The estimates of seasonal variations are obtained for the coastal zone of the sea. A good agreement is demonstrated between intraannual variations in the salinity of transformed river water, chlorophyll a concentration, and transparency in the areas where these waters propagate. We studied the effects of the Danube River runoff and transformed river water on the phytoplankton development and chlorophyll a concentration which largely define water transparency. [ABSTRACT FROM AUTHOR]

Variability in the vertical distribution of the hydrobiont bioluminescence intensity and chlorophyll a concentration in autumn along the coast of Crimea and its causes are analyzed based on expedition data and satellite information. It is shown that minimum bioluminescence intensities of marine organisms and chlorophyll a concentration were observed in the abyssal sea of the water area under study in the region of a cyclonic mesoscale eddy, where the upwelling was detected, and the thickness of the upper mixed layer did not exceed 20 m. The maximum values of the chlorophyll a concentration and bioluminescence intensity were observed at stations positioned in the shallow-water littoral sea which is rich in biogenic elements. [ABSTRACT FROM AUTHOR]

The typhoon Wind-Pump induced upwelling and cold eddy often promote the significant growth of phytoplankton after the typhoon. However, the importance of eddy-pumping and wind-driven upwelling on the sea surface chlorophyll a concentration (Chl-a) during the typhoon are still not clearly distinguished. In addition, the air−sea heat flux exchange is closely related to the upper ocean processes, but few studies have discussed its role in the sea surface Chl-a variations under typhoon conditions. Based on the cruise data, remote sensing data, and model data, this paper analyzes the contribution of the vertical motion caused by the eddy-pumping upwelling and Ekman pumping upwelling on the surface Chl-a, and quantitatively analyzes the influence of air−sea heat exchange on the surface Chl-a after the typhoon Linfa over the northeastern South China Sea (NSCS) in 2009. The results reveal the Wind Pump impacts on upper ocean processes: (1) The euphotic layer-integrated Chl-a increased after the typhoon, and the increasing of the surface Chl-a was not only the uplift of the deeper waters with high Chl-a but also the growth of the phytoplankton; (2) The Net Heat Flux (air−sea heat exchange) played a major role in controlling the upper ocean physical processes through cooling the SST and indirectly increased the surface Chl-a until two weeks after the typhoon; (3) the typhoon-induced cyclonic eddy was the most important physical process in increasing the surface Chl-a rather than the Ekman pumping and wind-stirring mixing after typhoon; (4) the spatial shift between the surface Chl-a blooms and the typhoon-induced cyclonic eddy could be due to the Ekman transport; (5) nutrients uplifting and adequate light were two major biochemical elements supplying for the growth of surface phytoplankton.

Since the impoundment of the Three Gorges Reservoir in 2003, algal blooms have frequently been observed in it. The chlorophyll a concentration is an important parameter for evaluating algal blooms. In this study, the chlorophyll a concentration in Xiangxi Bay, in the Three Gorges Reservoir, was predicted using HJ-1 satellite imagery. Several models were established based on a correlation analysis between in situ measurements of the chlorophyll a concentration and the values obtained from satellite images of the study area from January 2010 to December 2011. Chlorophyll a concentrations in Xiangxi Bay were predicted based on the established models. The results show that the maximum correlation is between the reflectance of the band combination of B4/(B2+B3) and in situ measurements of chlorophyll a concentration. The root mean square errors of the predicted values using the linear and quadratic models are 18.49 mg/m3 and 18.52 mg/m3, respectively, and the average relative errors are 37.79% and 36.79%, respectively. The results provide a reference for water bloom prediction in typical tributaries of the Three Gorges Reservoir and contribute to large-scale remote sensing monitoring and water quality management.

We have been developing a wireless sensor network system to monitor the quality of lake water in real time. It consists of a sensor module and a system module, which includes communication and power modules. We have focused on pH, turbidity and chlorophyll a concentration as the criteria for qualifying lake water quality. These parameters will be detected by a microfluidic device based sensor module embedded in the wireless sensor network system. In order to detect the turbidity and the chlorophyll a concentration simultaneously, we propose a simple optical measurement method using LED and photodiode in this paper. Before integrating a turbidity and chlorophyll a concentration sensor into the microfluidic device based pH sensor, we performed feasibility studies such as confirmation of the working principle and experiments using environmental water samples. As a result, we successfully verified our simultaneous sensing method by using a simple optical setup of the turbidity and the chlorophyll a concentration. [ABSTRACT FROM AUTHOR]

Graphene oxide (GO), a recently discovered material, has been investigated for many applications in various fields. Thus, an immense awareness should be paid on the potential effects of the material on the environment as huge quantities of GO may get to the environment. Aquatic organisms, marine algae as an example, are exposed to such material when disposed to the environment. Accordingly, it is significant to assess the probable interactions of GO with algae in evaluating its possible environmental risks. In this study, we have examined the effect of different concentrations of GO on Picochlorum sp. during the different growth phases. The results showed that the toxicity of GO increases with increasing its concentration. The lowest concentration (0.5 mg L) was found to improve the algae growth and pigment content of Picochlorum sp. In contrast, higher GO concentrations had a negative consequence on the growth of algae and photosynthetic pigment concentration. [ABSTRACT FROM AUTHOR]

The remote sensing reflectance Rrs, concentrations of chlorophyll a and other pigments Ci, suspended particulate matter concentrations CSPM and coloured dissolved organic matter absorption coefficient aCDOM(λ) were measured in the euphotic zones of 15 Pomeranian lakes in 2007-2010. On the basis of 235 sets of data points obtained from simultaneous estimates of these quantities, we classified the lake waters into three types. The first one, with the lowest aCDOM(440 nm) (usually between 0.1 and 1.3 m-1 and chlorophyll a concentrations 1.3 < Ca < 33 mg m-3), displays a broad peak on the reflectance spectrum at 560-580 nm and resembles the shape of the remote sensing reflectance spectra usually observed in the Baltic Proper. A set of Rrs spectra from the Baltic Proper is given for comparison. The second lake water type has a very high CDOM absorption coefficient (usually aCDOM(440 nm) > 10 m-1, up to 17.4 m-1 in Lake Pyszne; it has a relatively low reflectance (Rrs < 0.001 sr-1) over the entire spectral range, and two visible reflectance spectra peaks at ca 650 and 690-710 nm. The third type of lake water represents waters with a lower CDOM absorption coefficient (usually aCDOM(440 nm) < 5 m-1) and a high chlorophyll a concentration (usually Ca > 4 mg m-3, up to 336 mg m-3 in Lake Gardno). The remote sensing reflectance spectra in these waters always exhibit three peaks (Rrs > 0.005 sr-1): a broad one at 560-580 nm, a smaller one at ca 650 nm and a well-pronounced one at 690-720 nm. These Rrs(λ) peaks correspond to the relatively low absorption of light by the various optically active components of the lake water and the considerable scattering (over the entire spectral range investigated) due to the high SPM concentrations there. The remote sensing maximum at λ ≈ 690-720 nm is higher still as a result of the natural fluorescence of chlorophyll a. Empirical relationships between the spectral reflectance band ratios at selected wavelengths and the various optically active components for these lake waters are also established: for example, the chlorophyll a concentration in surface water layer Ca = 6.432 e4.556X, where X = [max Rrs (695 ≤ λ ≤ 720) - Rrs(λ = 670)] / max Rrs (695 ≤ λ ≤ 720), and the coefficient of determination R2 = 0.95.

This article is the first in a series of three describing the modelling of the vertical different photosynthetic and photoprotecting phytoplankton pigments concentration distributions in the Baltic and their interrelationsdescribed by the so-called non-photosynthetic pigment factor.The model formulas yielded by this research are an integral part of the algorithms used in the remote sensingof the Baltic ecosystem. Algorithms of this kind have already been developed by our team from data relating mainly to oceanic Case 1 waters (WC1) and have produced good results for these waters. But their application to Baltic waters, i.e.,Case 2 waters, was not so successful. On the basis of empirical data for the Baltic Sea, we therefore derived new mathematical expressions for the spatial distribution of Baltic phytoplankton pigments. They are discussed in this series of articles. This first article presents a statistical model for determining the total concentration ofchlorophyll, a (i.e., the sum of chlorophylls a+pheo derived spectrophotometrically) at different depths in the Baltic Sea Ca(z) on the basis of its surface concentration Ca(0),which can be determined by remote sensing. This model accounts for the principal features of the vertical distributions of chlorophyll concentrations characteristic of the Baltic Sea. The model's precision was verified empirically: it was found suitable for application in the efficient monitoring of the Baltic Sea. The modified mathematical descriptions of the concentrations of accessory pigments (photosynthetic and photoprotecting) in Baltic phytoplankton and selected relationships between them are given in the other two articles in this series (Majchrowski et al. 2007, Woźniak et al. 2007b, both in this volume).

The aim of the study was to measure the transparent exopolymerparticles (TEP) concentration in cultures of Anabaena flos-aquae OL-K10and to determine the relationship between the quantity of particlesproduced and the light intensity, the age of the culture andthe presence of nitrogen in the culture medium. This is the firsttime TEP production has been investigated in the Nostocales,an order of nitrogen-fixing phytoplankton species. The resultsshowed that TEP production depends on the presence of nitrogenin the culture medium. The longer the culture is grown, the higherthe correlation between its TEP content and its chlorophyll aconcentration.

Multiple data sets were combined to investigate five dust storm events over East Asia in spring 2010 and their impacts on chlorophyll in the East China Sea (ECS) and the North Pacific Subtropical Gyre (NPSG). Satellite-observed column aerosol images were able to show the spatial distribution of the transport of dust from the source regions to the two seas for some of the dust storm events. The CALIPSO satellite showed the vertical structure of dust aerosol for a greater number of dust storm events, including some weak events. This was confirmed by simulations of dust deposition and backward trajectories traced to dust source regions. The simulated dust deposition flux for five dust storms ranged from 13.0 to 145.6 mg.m-2.d-1 in the ECS and from 0.6 to 5.5 mg.m-2.d-1 in the NPSG, suggesting that the highest deposition was about one order of magnitude higher than the lowest. The estimated nutrients from dust showed that dust containing iron had the greatest effect on phytoplankton growth in both seas; the iron deposited by one dust storm event accounted for at least 5% of growth and satisfied the increase in demand required for chlorophyll a concentration. [ABSTRACT FROM AUTHOR]

Ocean remote sensing is the only technique capable of quantitatively detecting long-term and global variability of marine primary production. However, because the spectral curves of light derived from satellite sensors have a limited capability to identify the physiological state of phytoplankton, the direct estimation of photoadaptive variables, such as daily maximum carbon fixation in a water column (P{opt^{b}}), from the spectra of satellite sensors is difficult. This difficulty results in most of the errors in ocean color-based primary productivity models. In this paper, algorithms were developed to estimate $P_{{{\rm opt}}}^{{\rm b}}$ using statistical models known as support vector machines (SVM). The algorithms were run using three different inputs: sea surface temperature (SST); both SST and sea surface chlorophyll a concentration; and SST, sea surface chlorophyll a concentration and photosynthetically active radiation (PAR) together. The results indicate that the algorithm using the three inputs (SST, sea surface chlorophyll a concentration, and PAR) had the best performance. The algorithms based on the SVM had better results than the general statistical regression method. Using the new $P_{{{\rm opt}}}^{{\rm b}}$ algorithm, the performances of the previous primary production models, including the vertically generalized production model and the statistical model developed in our earlier research, were improved. In contrast to the previous algorithm, the global primary productivity estimated using the new $P_{{{\rm opt}}}^{{\rm b}}$ algorithm showed regional changes, with higher primary productivity in most open ocean areas and lower primary productivity in coastal waters. [ABSTRACT FROM PUBLISHER]

Fan, R.; Wei, H., and Zhao, L., 2016. Linking suspended particulate material characteristics to the plankton distribution in summer in the Yellow Sea and East China Sea. Identifying particle characteristics through in situ observations can be beneficial for understanding local sediment dynamics. This study analyzed the suspended particulate material (SPM) characteristics in the Yellow Sea and East China Sea, as well as the hydrological structure and chlorophyll a (Chl a) concentration in summer during a cruise conducted from 16 August 2013 to 31 August 2013. This study identifies two significant particle size (PS) peaks ranging between approximately 12 < diameter ( d) < 63 and 280 < d < 390 μm, defined as small and large particles, respectively, by using the SPM PS spectrum. In the surface layer, the main part of small SPMs is composed of phytoplankton, whereas large SPMs are primarily dominated by mesozooplankton. High concentrations of SPM in the surface layer located on Subei Shoal and off the Changjiang River estuary overlap with the high Chl a concentration. High total SPM concentrations, maximum levels of Chl a, and large particle concentrations were observed in the pycnocline in the central Yellow Sea and at the middle shelf of the East China Sea. The high SPM subsurface concentration is primarily influenced by plankton, particularly mesozooplankton. Small particles are dominant in the bottom layer and consist mainly of inorganic particulate matter. [ABSTRACT FROM AUTHOR]

Bu araşt ı rmada Sakaryaba şı 'n ı oluşturan iki kaynaktan biri olan Do ğ u Göleti'nin baz ı su kalite parametreleri mevsimsel olarak belirlenmi ştir. Araşt ı rma gölette seçilen iki istasyonda ve 1999 y ı l ı n ı n ocak, nisan, temmuz, ekim ayları nda su örnekleri al ı narak yap ı lm ışt ı r. Gölet suyunda fosfor ve azot fraksiyonlar ı , klorofil a konsantrasyonları ile baz ı fıziko-kimyasal özellikler tespit edilmi ştir. Gölet suyunun s ı cakl ı k, çözünmüş oksijen ve pH değ erlerinin, göletin rekreaktif kullan ı m ı için kabul edilebilir standart s ı n ı rlar içerisinde oldu ğ u belirlenmiştir.

The spatio-temporal distribution of four coexistingAcartia(Copepoda: Calanoida: Acartiidae) species,A. hudsonica, A. omorii, A. ohtsukaiandA. forticrusawas examined along a salinity gradient in the Seomjin River estuary, during the spring tide of each month for one year from January to December 2000. Most of theAcartiaspecies were found in mesohaline (5–18 psu) and polyhaline regions (>18 psu), but their densities varied seasonally both along the salinity gradient and with chlorophyllaconcentration.Acartia hudsonicashowed a high density in mesohaline and polyhaline regions in March and April when chlorophyllaconcentration was >20 µg l–1, butA. omoriishowed high density only in the polyhaline region in April.Acartia ohtsukaioccurred both in mesohaline and polyhaline regions after June, but its peak density occurred in the polyhaline region in October when there was an autumn diatom bloom in the mesohaline.Acartia forticrusashowed peak density in the mesohaline in June when the water temperature was >20°C. These results indicate that food can be an important factor in controlling spatio-temporal distributions in the Seomjin River estuary, in addition to other environmental factors. [ABSTRACT FROM AUTHOR]

Periphyton was sampled from an artificial substrate in situ at 8-day intervals in the littoral zone of four shallow lakes with different trophic status. Phosphorus and chlorophyll a were determined including different phosphorus fractions. There was a strong correlation between periphyton chl a levels and the amount of total phosphorus in the lakes, indicating that the phosphorus retention ability of periphyton increased with periphyton mass. The amounts of total phosphorus and chemically extractable phosphorus in periphyton were greater in two of the lakes, Nanhu and Donghu, than in the other two lakes, Niuchaohu and Liangzihu. The greatest chl a and total phosphorus concentrations in periphyton were 103 and 129 μg cm −2 , respectively, in Nanhu. The amount of total phosphorus was significantly associated ( r > 0.881) with the chl a concentration and amounts of Fe/Al-bound phosphorus and Ca-bound phosphorus in the periphyton. Most of the total phosphorus in the periphyton was inorganic phosphorus, which mainly consisted of Fe/Al-bound phosphorus and Ca-bound phosphorus; the organic phosphorus fraction only made up 20%, on average, of total phosphorus. Fe/Al-bound phosphorus was the dominant fraction and its relative contribution to total phosphorus in the lakes was 59% (Nanhu), 46% (Donghu), 44% (Niuchaohu), and 38% (Liangzihu). These data demonstrated that periphyton in eutrophic lakes could retain considerable amounts of phosphorus and that high levels of Fe/Al-bound phosphorus are an important early warning symptom of eutrophication. [ABSTRACT FROM AUTHOR]

Variability in primary productivity and fishing pressure can shape the abundance, species composition, and diversity of marine life. Though parasites comprise nearly half of marine species, their responses to these important forces remain little explored. We quantified parasite assemblages at two spatial scales, across a gradient in productivity and fishing pressure that spans six coral islands of the Line Islands archipelago and within the largest Line Island, Kiritimati, which experiences a west-to-east gradient in fishing pressure and upwelling-driven productivity. In the across-islands data set, we found that increasing productivity was correlated with increased parasite abundance overall, but that the effects of productivity differed among parasite groups. Trophically transmitted parasites increased in abundance with increasing productivity, but directly transmitted parasites did not exhibit significant changes. This probably arises because productivity has stronger effects on the abundance of the planktonic crustaceans and herbivorous snails that serve as the intermediate hosts of trophically transmitted parasites than on the higher-trophic level fishes that are the sole hosts of directly transmitted parasites. We also found that specialist parasites increased in response to increasing productivity, while generalists did not, possibly because specialist parasites tend to be more strongly limited by host availability than are generalist parasites. After the effect of productivity was controlled for, fishing was correlated with decreases in the abundance of trophically transmitted parasites, while directly transmitted parasites appeared to track host density; we observed increases in the abundance of parasites using hosts that experienced fishing-driven compensatory increases in abundance. The within-island data set confirmed these patterns for the combined effects of productivity and fishing on parasite abundance, suggesting that our conclusions are robust across a span of spatial scales. Overall, these results indicate that there are strong and variable effects of anthropogenic and natural drivers on parasite abundance and taxonomic richness. These effects are likely to be mediated by parasite traits, particularly by parasite transmission strategies. [ABSTRACT FROM AUTHOR]