Spatial Distribution Of Chlorophyll-a Research Articles

Composition and distribution of the near-shore waters bordering the coral reefs of Aruba, Bonaire, and Curaçao in the Southern Caribbean

This study aimed to identify ocean- and land-based sources of nutrients to the coral reef communities surrounding the Southern Caribbean islands Aruba, Bonaire, and Curaçao (ABC islands). The composition of water masses around these islands were assessed to depths up to 300 m and three distinct overlying water masses were identified, separated by mixing zones. A fluctuating pycnocline separating surface from deeper (>∼50 m) water indicated the presence of internal waves. Nutrient profiles were typical of tropical waters with oligotrophic waters occurring above the pycnocline and a deep chlorophyll-a maximum (DCM) just below it (∼65 m). Concentrations of dissolved nutrients differed among islands. Inorganic nitrogen (DIN) and phosphate concentrations were respectively lowest around Bonaire and Curaçao. The spatial distribution of chlorophyll-a (indicative of phytoplankton biomass), rather than nutrient concentrations, suggested the presence of higher-than-average nutrient concentrations in islands with higher population densities and near urbanized/industrial areas.

SPATIAL DISTRIBUTION OF CHLOROPHYLL-A AND NUTRIENTS IN THE TENGAH ISLAND, KARIMUNJAWA INDONESIA

Tengah Island is located between Sintok Island and Cilik Island in Karimunjawa, Jepara Regency, Central Java. Tengah Island is one of the zones for the use of marine tourism, which has the allure of attractive spots for snorkeling and diving for tourists. Coral reefs require chlorophyll-a, which is in this case produced by zooxanthellae, as a photosynthetic pigment. The chlorophyll-a concentration is influenced by many factors, including nutrients and environmental parameters. This study aims to see the spatial distribution of chlorophyll-a on Tengah Island and its relationship to nutrients, including ammonium, phosphate, and nitrate, as well as environmental parameters, namely Total Suspended Solid (TSS), salinity, pH, Dissolve Oxygen (DO), temperature, and brightness. Chlorophyll-a is analyzed using the APHA standard (2005), while nutrient analyses for ammonium, nitrate, and phosphate employ the UV-Vis spectrophotometer and Nessler reagent, the APHA 4500-No.3-B (2017), and the APHA 4500-P B, C (2017), respectively. TSS is obtained from Sentinel-2A data processing. The correlation between each dataset was carried out by a method of statistical analysis called Principal Component Analysis (PCA). The results showed that chlorophyll-a had a close relationship with ammonium (r=0.826), brightness (r=0.492), and TSS (r=-0.979). The highest chlorophyll-a concentration of 1,063 μg/L was obtained at Station 1, which is the jetty area and the closest to the mainland. This finding is supported by maximum ammonium, sourced from domestic waste and microbial activity, and good brightness, required by chlorophyll-a for photosynthesis processes.

Methane migration, sea ice melting and spatial distribution of chlorophyll-a in the Barents Sea

The paper considers the theoretical and practical aspects of the relationship between the processes of sea ice melting and methane migration, and their influence on the distribution of chlorophyll-a concentration as an indicator of productivity and the level of quantitative development of the phytoplankton community at the spring stage of the succession cycle. In the spring of 2018 and 2019 the thermohaline characteristics of waters and the content of chlorophyll-a in the Barents Sea were studied. The area of work covered both areas with the most probable release of methane from near-bottom gas hydrates, as well as background areas, where the presence of methane hydrates is unlikely. In 2018, the phytoplankton community of the study area was in the spring flowering stage. In the area of the most probable influence of methane, the average concentrations of chlorophyll-a were approximately 2 times higher than in the background area. High concentrations of the pigment were associated with the thawed layer, which may indicate the release of methane from the ice. In 2019, low concentrations of chlorophyll-a in the edge zone excluded the stage of spring flowering of the phytoplankton community, which did not allow us to trace the possible effect of the release of methane hydrates on the concentration of chlorophyll-a.

Distribution of Chlorophil-A and Sea Surface Temperature (SST) on Operation of Payang Catching Equipment in Gorontalo Bay Waters

This research was carried out in January - August 2020 with the aim of looking at the temporal and spatial distribution of Chlorophyll-a (CHL-a) and Sea Surface Temperature (SST) in the waters of Gorontalo Bay, their effect on payang catches. The data used in the form of field data and image data were analyzed by descriptive analysis and analysis of Geographic Information Systems (GIS). Based on the results of the study, it was found that the existence of payang fishing gear in Gorontalo Bay is in an area that has a high chlorophyll content between the West Season, West-East Transition Season and East Season. The highest average payang catch was found in the West-East transition season compared to other seasons. The West-East transition season has sea surface temperatures between 30.64°C-30.99°C while the density of chlorophyll-a is 0.1701 mg/m3-0.1925 mg/m3.

Hubungan Klorofil-a dan Suhu Permukaan Laut (SPL) Terhadap Hasil Tangkapan Ikan Lemuru Sardinella lemuru di Selat Bali Menggunakan Citra Aqua MODIS Tahun 2009-2018

Oceanographic parameters such as sea surface temperature (SST) and chlorophyll-a in the water can influence the productivity of pelagic fish such as Lemuru. Many studies have been conducted on the relationship between SST and chlorophyll-a and the fluctuations in the catch of Lemuru fish, especially using satellite databased sensing technology. Most of the research using satellite data is done in a short-term period (not climatology), so there are still a lot of unanswered questions. One of them is: how the correlation between the fluctuation in the number of Lemuru fish catches is related to SST and chlorophyll-a in the ENSO and IOD periods. The purpose of this study is to determine the distribution of SST and chlorophyll-a concentrations and their relationship with the yield of Lemuru fish catches in the Bali Strait from 2009 to 2018. Aqua Moderate Imaging Spectroradiometer (MODIS) satellite data level 2 from Oceancolor and data on the number of fish caught in the Bali Strait from the National Fisheries Port (PPN) Pengambengan and UPT PPP Muncar. The method is used with correlation analysis between SST and chlorophyll-a to the number of Lemuru fish caught. The monthly average SST in Bali Strait waters from 2009 to 2018 was approximately 24,76 0C-30, 11 0C, with an estimated monthly chlorophyll-a concentration of 0,10 mg/m3-3,68 mg/m3. The spatial distribution of SST tends to be low in the southern Bali Strait and tends to be high in the northern Bali Strait. The spatial distribution of chlorophyll-a appears to have a high value in the near land area. The cross-correlation test between chlorophyll-a and the number of Lemuru catches showed a positive correlation yield at the 4th month lag. While the correlation of SST to the number of Lemuru fish catches shows a positive correlation at lag (-1).

Influence of river water expansion on the spatial distribution of chlorophyll-a in the Kara Sea

In August-September 2013, the thermohaline characteristics of water masses and the concentration of chlorophyll-a were studied in the Kara Sea. Expansion of surface desalinated water to the north, according to the central type, influenced the spatial distribution of chlorophyll. Beyond the boundary of the Stock Front, the average pigment concentration in the surface layer was 0.45±0.16 mg/m3. In the area affected by the surface desalinated layer, most of the chlorophyll (0 m – 1.04±0.27 mg/m3, 5 m – 0.97±0.27 mg/m3, 10 m – 0.69±0.36 mg/m3) was localized within this layer (10-17 m). High concentrations were observed in the bays of the Kara Sea. The maximum concentration of chlorophyll-a in the surface layer of the Ob Bay was 4.22 mg/m3, in the Yenisei Bay – 3.22 mg/m3.

Exploiting high frequency monitoring and satellite imagery for assessing chlorophyll-a dynamics in a shallow eutrophic lake

Freshwater ecosystems are challenged by cultural eutrophication across the globe, and it is a priority for water managers to implement water quality monitoring at different spatio-temporal scales to control and mitigate the eutrophication process. Phytoplankton abundance is a key indicator of the trophic and water quality status of lakes. Phytoplankton dynamics are characterized by high spatio-temporal variation, driven by physical, chemical and biological factors, that challenge the capacity of routine monitoring with conventional sampling techniques (i.e., boat based sampling) to characterise these complex relationships. In this study, high frequency in situ measurements and multispectral satellite data were used in a synergistic way to explore temporal (diurnal and seasonal) dynamics and spatial distribution of Chlorophyll-a (Chl-a) concentration, a proxy of phytoplankton abundance, together with physico-chemical water parameters in a shallow fluvial-lake system (Mantua Lakes). A good agreement was found between Chl-a retrieved by remote sensing data and Chl-a fluorescence data recorded by multi-parameters probes (R2 = 0.94). The Chl-a maps allowed a seasonal classification of the Mantua Lakes system as eutrophic or hypertrophic. Along the Mantua lakes system an increasing gradient in Chl-a concentration was recorded following the transition from a fluvial to lacustrine system. There was significant seasonal heterogeneity among the sub-basins, probably due to different hydrodynamics, influenced also by macrophyte stands. High-frequency data revealed the importance of rainfall events in the timing and growth dynamics of phytoplankton, particularly for spring and late summer blooms. Combining temporal and spatial data at high resolution improves the understanding of complex fluvial-lake systems. This technique can allow managers to target blooms in near-real time as they move through a system and guide them to localized hot spots enabling timely management action in ecosystems of high conservation and recreational value.

Seasonal Monitoring Of Chlorophyll-A With Landsat 8 Oli In The Madura Strait, Pasuruan, East Java, Indonesia

Chlorophyll-a (Chl-a) is a type of pigment is most common and predominant in all oxygen-evolving photosynthetic organisms such as higher plants, red and green algae. The concentrations of high chlorophyll-a (Chl-a) in coastal waters tend to be lower offshore due to land through river water runoff. The Madura Strait is one of the Indonesian basins that is widely used for fisheries activity, which directly impacts and puts quite high pressure on the aquatic resources. In addition, the development of urban areas and changes of land use in the hinterland areas of East Java Province due to increasing population are also intensive. The objectives of this research were: (1) to map the distribution of chlorophyll-a, its concentration and dynamics in the Madura Strait near the Pasuruan coastal area using remote sensing for both dry and rainy seasons, (2) figure out the influence of rivers or other oceanographic factors that may occur, and (3) calculate the accuracy of the estimation compared to the field data. The Landsat 8 OLI imagery was used to determine the concentration of Chl-a and analyze its seasonal spatial distribution pattern. The results show that (1) spatial distribution of chlorophyll-a (Chl-a), its concentration and dynamics in the Madura Strait waters near the Pasuruan coastal area varies between dry and rainy months or seasons, (2) input from rivers, waves, tidal level, and eddy circulation constitute the oceanographic parameters that influence the spatial distribution pattern of chlorophyll-a (Chl-a) in the Madura Strait waters near the Pasuruan coastal area, and (3) validation of the estimated Chl-a concentrations from Landsat 8 OLI using field data has shown RMSE value of 0.49.

A Deep Learning Model Using Satellite Ocean Color and Hydrodynamic Model to Estimate Chlorophyll-a Concentration

In this study, we used convolutional neural networks (CNNs)—which are well-known deep learning models suitable for image data processing—to estimate the temporal and spatial distribution of chlorophyll-a in a bay. The training data required the construction of a deep learning model acquired from the satellite ocean color and hydrodynamic model. Chlorophyll-a, total suspended sediment (TSS), visibility, and colored dissolved organic matter (CDOM) were extracted from the satellite ocean color data, and water level, currents, temperature, and salinity were generated from the hydrodynamic model. We developed CNN Model I—which estimates the concentration of chlorophyll-a using a 48 × 27 sized overall image—and CNN Model II—which uses a 7 × 7 segmented image. Because the CNN Model II conducts estimation using only data around the points of interest, the quantity of training data is more than 300 times larger than that of CNN Model I. Consequently, it was possible to extract and analyze the inherent patterns in the training data, improving the predictive ability of the deep learning model. The average root mean square error (RMSE), calculated by applying CNN Model II, was 0.191, and when the prediction was good, the coefficient of determination (R2) exceeded 0.91. Finally, we performed a sensitivity analysis, which revealed that CDOM is the most influential variable in estimating the spatiotemporal distribution of chlorophyll-a.

Temporal and Spatial Distribution of Chlorophyll-a in Caotang River of Three Gorges Reservoir

To study the formation of algae blooms in Caotang River, a tributary of the Three Gorges Reservoir, the authors set up six monitoring sites in Caotang River and Yangtze River to continuously monitor the concentration of chlorophyll-a for one year from July 2017 to June 2018 and analyzed the distribution of algae blooms. It is found that in the vertical direction, chlorophyll-a had a maximum concentration at 2.41 mg/m3 at the surface and a minimum concentration of 0.69 mg/m3 at the bottom. The algae blooms broke out in Caotang River from July to September 2017, and there was no significant difference in the concentration of chlorophyll-a during other periods. During algae blooms, the concentration of chlorophyll-a increased from downstream to upstream except for the source section. There was no significant difference in the concentration of chlorophyll in the middle and bottom water bodies. The Yangtze River has a lower concentration of algal toxin than that in the Caotang River. Excluding the source where algal toxin was not observed, this study found that the concentrations of algal toxin in the other three sections (CT01, CT02 and CT03) were at 0.42 ug/L, 0.56 ug/L and 0.83 ug/L, respectively.

Spatial Distribution of Chlorophyll-a and Its Relationship with Dissolved Inorganic Phosphate Influenced by Rivers in the North Coast of Java

Spatial Distribution of Chlorophyll-a and Its Relationship with Dissolved Inorganic Phosphate Influenced by Rivers in the North Coast of Java

Impact of Water-Sediment Regulation Scheme on seasonal and spatial variations of biogeochemical factors in the Yellow River estuary

Seasonal and spatial distributions of nutrients and chlorophyll-a (Chl-a), together with temperature, salinity and total suspended matter (TSM), were investigated in the Yellow River estuary (China) to examine the biogeochemical influence of the “Water and Sediment Regulation Scheme (WSRS)” that is used to manage outflows from the river. Four cruises in April, June (early phase of WSRS), July (late phase of WSRS) and September were conducted in 2013 (WSRS from 19th June to 12th July). The results showed that nutrient species could be divided into two major groups according to their seasonal and spatial distributions. One group included NO3−, dissolved organic nitrogen (DON) and Si(OH)4, primarily from freshwater discharge. NO3− and DON related to anthropogenic sources were also separated from Si(OH)4, which was related to weather. The other group included dissolved inorganic phosphorus (DIP), dissolved organic phosphorus (DOP), NO2−, and NH4+. Along with freshwater inputs, sediment absorption/desorption showed impacts on DIP and DOP concentration and distribution. Nitrification was a dominant factor controlling NO2− concentrations. NH4+ was influenced by both sediment absorption/desorption and nitrification. The WSRS not only shifted the seasonal patterns of nutrients in the estuary, with high concentrations moved from autumn to June and July, but also promoted the nutrient spread to the south central part of the Bohai Sea. Spatial distribution of Chlorophyll-a (Chl-a) was influenced by the WSRS, with high concentrations being found in the river mouth in June and September, flanking the river mouth in July, and in the south central part of the Bohai Sea in September. Although Chl-a concentrations increased in June and July, the seasonal patterns did not change. The highest concentrations were found in September. Nutrient loadings during the WSRS relieved DIP and Si(OH)4 limitation in the estuary and south central Bohai Sea, causing an excess of DIN and disrupting the balance of DIN/DIP in the estuary and Bohai Sea. High turbidity and freshwater flushing depressed the growth of phytoplankton during the WSRS. The growth of phytoplankton was nutrient limited in June (DIP) when the WSRS started and in September after DIP and Si(OH)4 had been consumed by phytoplankton.

Bathymetrical influences on spatial and temporal characteristics of chlorophyll-a concentrations in the Southern Ocean from 2002 to 2012 (October to March) using MODIS

Phytoplankton blooms, particularly in the Southern Ocean, can have significant impact on global biogeochemistry cycling. To investigate the accuracy of chlorophyll-a distribution, and to better understand the spatial and temporal dynamics of phytoplankton biomass, we examine chlorophyll-a estimates (October–March from 2002 to 2012) derived from Moderate Resolution Imaging Spectrometer (MODIS) data following the ocean chlorophyll-a 3 model (OC3M) algorithm. Noticeable seasonality occurs in the temporal distribution of chlorophyll-a concentrations, which shows the highest value in December and January and an increasing tendency during the 2002–2012 period. The spatial distribution of chlorophyll-a varies greatly with latitude, as higher latitudes experience more phytoplankton blooms (chlorophyll-a concentration larger than 1 mg/m3) and marginal seas (Ross Sea and Amundsen Sea) show different bloom anomalies caused by two dominant algae species. Areas at higher latitudes and shallow water (<500 m) experience the shorter ice-free periods with greater seasonality. A noticeable bathymetry gradient exists at 2500-m isobaths, while water at the 500–2500-m depth experiences quite long ice-free periods with a stable water environment. Blooms generally occur near topographic features where currents have strong interactions when the water depth is more than 2500 m. Based on these findings, we can classify the Southern Ocean into two bloom subregions, 0–500 m as an enhanced bloom zone (EBZ), and 500–2500 m as a moderate bloom zone (MBZ). The EBZ has a quite high-bloom probability of about 30%, while the MBZ has only 10%.

SEASONAL DIFFERENCES IN SPATIAL SCALES OF CHLOROPHYLL-A CONCENTRATION IN LAKE TAIHU，CHINA

Abstract. Spatial distribution of chlorophyll-a (chla) concentration in Lake Taihu is non-uniform and seasonal variability. Chla concentration retrieval algorithms were separately established using measured data and remote sensing images (HJ-1 CCD and MODIS data) in October 2010, March 2011, and September 2011. Then parameters of semi- variance were calculated on the scale of 30m, 250m and 500m for analyzing spatial heterogeneity in different seasons. Finally, based on the definitions of Lumped chla (chlaL) and Distributed chla (chlaD), seasonal model of chla concentration scale error was built. The results indicated that: spatial distribution of chla concentration in spring was more uniform. In summer and autumn, chla concentration in the north of the lake such as Meiliang Bay and Zhushan Bay was higher than that in the south of Lake Taihu. Chla concentration on different scales showed the similar structure in the same season, while it had different structure in different seasons. And inversion chla concentration from MODIS 500m had a greater scale error. The spatial scale error changed with seasons. It was higher in summer and autumn than that in spring. The maximum relative error can achieve 23%.

Spatial distribution of chlorophyll-a and its relationships with environmental factors in Qinhuai River, Nanjing

In recent years,algae bloom is common in the flowing waters,which has been one of the top scientific problems after the algae bloom in lakes.Due to the water pollution,phytoplankton blooms arose in Qinhuai River between August and September,2010.Based on the conventional monitoring data in August 15 and September 8,2010,this paper studied the spatial distribution characteristic of chlorophyll-a and its relationships with environmental factors.Results showed that chlorophyll-a concentration appeared obvious spatial difference from upstream to downstream,with a mean value of 73.7μg/L and the maximum value occurred in Mamuqiao(184.52μg/L).The ratio of TN/TP was 26.86,and the logarithmic correlation between chlorophyll-a and TP was positive,but the logarithmic correlation between chlorophyll-a and the TN/TP ratio was negative.It suggested that phosphorous might be the main impact factor for blue-green algae.Significantly positive correlation was found between chlorophyll-a and pH and DO,and significantly positive correlation was found between chlorophyll-a and NO-2-N,but no significant correlation between chlorophyll-a and NH+4-N,NO-3-N and TN.

Mapping Potential Fishing Grounds in Lake Malawi Using AVHRR and MODIS Satellite Imagery

This paper discusses a procedure that was developed to delineate potential fishing grounds in Lake Malawi using data on chlorophyll-a concentration derived from Moderate-resolution Imaging Spectroradiometer (MODIS/AQUA) in combination with lake surface temperature (LST) data obtained from Advanced Very High Resolution Radiometer (AVHRR) and MODIS/Terra satellite sensors. The paper draws from findings of studies [1,2] on development of algorithms for estimating chlorophyll-a and lake surface temperature in Lake Malawi from satellite imagery, respectively. To estimate chlorophyll concentration (a proxy for phytoplankton) in Lake Malawi using data from MODIS satellite imagery, in situ measurements of chlorophyll concentration were conducted at three selected sampling stations over the southeastern arm of Lake Malawi concurrent with satellite image acquisitions. These were regressed on chlorophyll-a concentration values obtained from Ocean Color (MODIS/AQUA) Data using SeaWIFS Data Analysis System (SeaDAS) software. From this, an equation for estimating chlorophyll-a concentration in Lake Malawi from MODIS satellite imagery was developed and used for mapping the spatial distribution of chlorophyll-a concentration in the lake. Since Lake Malawi is an oligotrophic lake, with an average value of chlorophyll concentration of 1 μg/L, areas in the lake with relatively high chlorophyll-a concentration were identified as potential locations for the development of the fishery industry. Estimation of lake surface temperature using satellite imagery involved two main activities. Firstly, in situ measurements of lake surface temperature were conducted at the three selected sampling stations over Lake Malawi concurrent with satellite image acquisitions. The second activity involved downloading and processing AVHRR and MODIS/Terra satellite imagery. AVHRR data covered the period September 1997 to February 1998 whereas MODIS/Terra data covered the period May to November, 2006. Both MODIS Land Surface Temperature (MOD11A1) and Ocean Color Sea Surface Temperature (SST) were downloaded from EOS Gateway website and processed into lake surface temperature. Two glass thermometers were used to measure temperature directly from the lake surface at a depth of 0 - 7.0 cm (i.e., skin temperature) and the average of the two readings was recorded as the lake surface temperature at a particular sampling station. Observed temperatures were regressed on remotely sensed data. ER Mapper was employed in drawing maps showing the distribution of lake surface temperature using the regression equation that was developed. Upwelling and downwelling zones were demarcated from lake surface temperature maps. Upwelling zones were identified as areas with a high potential for the development of the fishery industry because of their association with primary productivity. Using a simple overlay technique, data from both the spatial and temporal distribution of chlorophyll-a and lake surface temperature were used to delineate potential fishing grounds in Lake Malawi. The zone extending from Salima up to the northern part of Nkhotakota and the area on the northeastern tip of Lake Malawi were identified as areas of high primary productivity and therefore potential fishing grounds. These areas generally exhibit persistent cool surface waters, indicative of upwelling; and have relatively abundant phytoplankton.

Response of sea surface temperature to chlorophyll-a concentration in the tropical Pacific: Annual mean, seasonal cycle, and interannual variability

The response of the upper-ocean temperatures and currents in the tropical Pacific to the spatial distribution of chlorophyll-a and its seasonal cycle is investigated using a coupled atmosphere-ocean model and a stand-alone oceanic general circulation model. The spatial distribution of chlorophyll-a significantly influences the mean state of models in the tropical Pacific. The annual mean SST in the eastern equatorial Pacific decreases accompanied by a shallow thermocline and stronger currents because of shallow penetration depth of solar radiation. Equatorial upwelling dominates the heat budget in that region. Atmosphere-ocean interaction processes can further amplify such changes. The seasonal cycle of chlorophyll-a can dramatically change ENSO period in the coupled model. After introducing the seasonal cycle of chlorophyll-a concentration, the peak of the power spectrum becomes broad, and longer periods (>3 years) are found. These changes led to ENSO irregularities in the model. The increasing period is mainly due to the slow speed of Rossby waves, which are caused by the shallow mean thermocline in the northeastern Pacific.

Numerical simulation for impacts of hydrodynamic conditions on algae growth in Chongqing Section of Jialing River, China

Hydrodynamic conditions are important factors for planktonic algae growth, through introducing two parameters which express the optimal velocity and the velocity range for planktonic algae growth, a new velocity factor was put forward for the formula of growth rate. Therefore, the two-dimensional unsteady ecological dynamic model for algae growth was established to analyze the effects of hydrodynamic conditions on algae growth in Chongqing Reach of Jialing River in China. The temporal and spatial distribution of Chlorophyll-a (Chl-a) concentration was simulated numerically for various water levels, under climate conditions in period of high frequency for algae blooms of Three Gorges Reservoir and nutrition status at present in the research reach. The corresponding locations and areas of likely algae blooms were analyzed and forecasted. The results showed that about 0.04 m s −1 was the optimal velocity for algae growth, and the occurrence of algae blooms in large scale is almost impossible because of relatively high water flow velocity for Jialing River.

The satellite-derived distribution of chlorophyll-a and its relation to ice cover, radiation and sea surface temperature in the Barents Sea

The response of oceanic phytoplankton to climate forcing in the Arctic Ocean has attracted increasing attention due to its special geographical position and potential susceptibility to global warming. Here, we examine the relationship between satellite-derived (sea-viewing wide field-of-view sensor, SeaWiFS) surface chlorophyll-a (CHL) distribution and climatic conditions in the Barents Sea (30–35°E, 70–80°N) for the period 1998–2002. We separately examined the regions north and south of the Polar Front (∼76°N). Although field data are rather limited, the satellite CHL distribution was generally consistent with cruise observations. The temporal and spatial distribution of CHL was strongly influenced by the light regime, mixed layer depth, wind speed and ice cover. Maximum CHL values were found in the marginal sea-ice zone (72–73°N) and not in the ice-free region further south (70–71°N). This indicates that melt-water is an important contributor to higher CHL production. The vernal phytoplankton bloom generally started in late March, reaching its peak in late April. A second, smaller CHL peak occurred regularly in late summer (September). Of the 5 years, 2002 had the highest CHL production in the southern region, likely due to earlier ice melting and stronger solar irradiance in spring and summer.

Temporal and spatial distribution of chlorophyll-a in surface waters of the Scotia Sea as determined by both shipboard measurements and satellite data

Temporal and spatial distribution of chlorophyll-a in surface waters of the Scotia Sea as determined by both shipboard measurements and satellite data