Distribution Of Chlorophyll Research Articles

Ephemeral Surface Chlorophyll Enhancement at the New England Shelf Break Driven by Ekman Restratification

AbstractThe Mid‐Atlantic Bight (MAB) hosts a large and productive marine ecosystem supported by high phytoplankton concentrations. Enhanced surface chlorophyll concentrations at the MAB shelf‐break front have been detected in synoptic measurements, yet this feature is not present in seasonal means. To understand why, we assess the conditions associated with enhanced surface chlorophyll at the shelf break. We employ in‐situ and remote sensing data, and a 2‐dimensional model to show that Ekman restratification driven by upfront winds drives ephemerally enhanced chlorophyll concentrations at the shelf‐break front in spring. Using 8‐day composite satellite‐measured surface chlorophyll concentration data from 2003–2020, we constructed a daily running mean (DRM) climatology of the cross‐shelf chlorophyll distribution for the northern MAB region. While the frontal enhancement of chlorophyll is apparent in the DRM climatology, it is not captured in the seasonal climatology due to its short duration of less than a week. In‐situ measurements of the frontal chlorophyll enhancement reveal that chlorophyll is highest in spring when the shelf‐break front slumps offshore from its steep wintertime position causing restratification in the upper part of the water column. Several restratification mechanisms are possible, but the first day of enhanced chlorophyll at the shelf break corresponds to increasing upfront winds, suggesting that the frontal restratification is driven by offshore Ekman transport of the shelf water over the denser slope water. The 2‐dimensional model shows that upfront winds can indeed drive Ekman restratification and alleviate light limitation of phytoplankton growth at the shelf‐break front.

Study on the Optimization of Hyperspectral Characteristic Bands Combined with Monitoring and Visualization of Pepper Leaf SPAD Value.

Chlorophyll content is an important indicator of plant photosynthesis, which directly affects the growth and yield of crops. Using hyperspectral imaging technology to quickly and non-destructively estimate the soil plant analysis development (SPAD) value of pepper leaf and its distribution inversion is of great significance for agricultural monitoring and precise fertilization during pepper growth. In this study, 150 samples of pepper leaves with different leaf positions were selected, and the hyperspectral image data and SPAD value were collected for the sampled leaves. The correlation coefficient, stability competitive adaptive reweighted sampling (sCARS), and iteratively retaining informative variables (IRIV) methods were used to screen characteristic bands. These were combined with partial least-squares regression (PLSR), extreme gradient boosting (XGBoost), random forest regression (RFR), and gradient boosting decision tree (GBDT) to build regression models. The developed model was then used to build the inversion map of pepper leaf chlorophyll distribution. The research results show that: (1) The IRIV-XGBoost model demonstrates the most comprehensive performance in the modeling and inversion stages, and its , , and are 0.81, 2.76, and 2.30, respectively; (2) The IRIV-XGBoost model was used to calculate the SPAD value of each pixel of pepper leaves, and to subsequently invert the chlorophyll distribution map of pepper leaves at different leaf positions, which can provide support for the intuitive monitoring of crop growth and lay the foundation for the development of hyperspectral field dynamic monitoring sensors.

How Are Under Ice Phytoplankton Related to Sea Ice in the Southern Ocean?

AbstractLittle is known about Southern Ocean under‐ice phytoplankton, despite their suspected potential—ice and stratification conditions permitting—to produce blooms. We use a distributional approach to ask how Southern Ocean sea ice and under‐ice phytoplankton characteristics are related, circumventing the dearth of co‐located ice and phytoplankton data. We leverage all available Argo float profiles, together with freeboard (height of sea ice above sea level) and lead (ice fractures yielding open water) data from ICESat‐2, to describe co‐variations over time. We calculate moments of the probability distributions of maximum chlorophyll, particulate backscatter, the depths of these maxima, freeboard, and ice thickness. Argo moments correlate significantly with freeboard variance, lead fraction, and mixed layer depth, implying that sea ice dynamics drive plankton by modulating how much light they receive. We discuss ecological implications in the context of data limitations and advocate for diagnostic models and field studies to test additional processes influencing under‐ice phytoplankton.

Distribution of Chlorophyll in Coastal Borneo Island Using Modis Terra Satellite Data

Clorophyll is the colour pigment most common found in phytoplankton. Its concentration is one of the indicator of the high of productivity of aquatic area, especially in coastal area. Information of chlorophyll concentration and distribution is very important to determine the suitable location of marine aquaculture and prediction of fishing ground. The aims of this research were to: 1) find out and analyze the concentration of chlorophyll and its distribution in Borneo Island Indonesia and 2) the pattern of chlorophyll distribution for each provinces using modis terra data for five years (from January 2016 to December 2020) in monthly and annually data series. In addition, it used Seadas 7.5.3 for data visualization. The result of this research showed that the chlorophyll concentration ranged 0,045 – 20 mg/m3 and clorophyll distribution affected by the location that seen in all variation data series. In annually time series data, the highest value of concentration shown by west borneo province and central borneo province with the distribution area were larger as well. The distribution of chlorophyll in monthly data showed almost same with annually data time series. The difference was just in large area distribution. The pattern of chlorophyll distribution also showed that in the west Kalimantan and central Kalimantan area had the highest values.

Variation in the Accumulation of Phytochemicals and Their Bioactive Properties among the Aerial Parts of Cauliflower.

Vegetables from the Brassicaceae family are excellent sources of bioactive phytochemicals and may reduce the risk of chronic diseases. Variation of phytochemicals in the edible part of cauliflower is known. However, information about the distribution of bioactive and nutritive compounds as well as antioxidant activity among aerial organs of cauliflower is unavailable. Therefore, this study aimed to evaluate the distribution of glucosinolates (GLS), phenolics, flavonoids, chlorophylls, nutritive compounds and antioxidant capacity between the aerial parts of the common variety of cauliflower and to evaluate whether these changes contribute to the differences in the antioxidant capacity between the plant organs. Our study showed that all the aerial organs of cauliflower are a rich source of health-promoting bioactive compounds, including GLS, phenolics and flavonoids, exhibiting antioxidant capacity. The highest contents of phytochemicals and the highest antioxidant capacity were found in leaves. Cauliflower organs were also found to be rich in nutritive compounds, including minerals, proteins and amino acids. Our study showed that the non-edible organs, such as stems and leaves, being neglected parts of cauliflower, if not consumed as the main ingredient, can be used as additives for developing new, functional foodstuff.

Development of the UKESM-TOPAZ Earth System Model (Version 1.0) and Preliminary Evaluation of its Biogeochemical Simulations

Earth system models (ESMs) comprise various Earth system components and simulate the interactions between these components. ESMs can be used to understand climate feedbacks between physical, chemical, and biological processes and predict future climate. We developed a new ESM, UKESM-TOPAZ, by coupling the UK ESM (UKESM1) and the Tracers of Phytoplankton with Allometric Zooplankton (TOPAZ) biogeochemical module. We then compared the preliminary simulated biogeochemical variables, which were conducted over a period of 70 years, using observational and existing UKESM1 model data. Similar to UKESM1, the newly developed UKESM-TOPAZ closely simulated the relationship between the El Niño-Southern Oscillation and chlorophyll concentration anomalies during the boreal winter. However, there were differences in the chlorophyll distributions in the eastern equatorial Pacific between the two models, which were due to dissolved iron, as this value was higher in UKESM-TOPAZ than in UKESM1. In a mean field analysis, the distributions of the major marine biogeochemical variables in UKESM-TOPAZ (i.e., nitrate, silicate, dissolved oxygen, dissolved inorganic carbon, and alkalinity) were not significantly different from those of UKESM1, likely because the models share the same initial conditions. Our results indicate that TOPAZ has a simulation performance that does not lag behind UKESM1’s basic biogeochemical model (Model of Ecosystem Dynamics, nutrient Utilisation, Sequestration, and Acidification; MEDUSA). The UKESM-TOPAZ model can simulate the variability of the observed Niño 3.4 and 4 indices more closely than UKESM1. Thus, the UKESM-TOPAZ model can be used to deepen our understanding of the Earth system and to estimate ESM uncertainty.

Distributions of environmental parameters and Plankton’s volume backscattering strength at Yos Sudarso Bay, Jayapura, Indonesia

The present study combined the data of environmental parameters and plankton distribution using hydroacoustic technology with the purpose to map the horizontal and vertical distribution of plankton in Yos Sudarso Bay, Jayapura, Indonesia. Hydroacoustic data were processed using a threshold in the range of −90 dB to −70 dB which was used for plankton detection at a depth range of 5–100 m. The results of the current study showed that the surface temperature changed from 30 °C on the outside to 18 °C on the inside of the bay. Similarly, the salinity of the surface outside the bay was 36‰ while it was 18‰ inside the bay. The distribution of chlorophyll had also decreased, where the value outside the bay was 0.32 mg/m3 and inside the bay was 0.02 mg/m3. The horizontal distribution of the values of plankton's volume backscattering strength (Sv) had a range of −82 dB to −75 dB with an average of −76.63 dB. When the distribution of plankton's Sv was detected vertically, it showed that the value of plankton’s Sv decreased with increasing the water depth.

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.

Chlorophyll content estimation based on cascade spectral optimizations of interval and wavelength characteristics

Spectroscopy is an efficient way to estimate the chlorophyll content of crop canopy in the visible and near-infrared region to indicate the photosynthesis capacity and growth status. Although hyperspectral data of crop canopy provide a lot of information, a critical issue is that the subsequent redundant and interference wavelengths could reduce the accuracy and robustness of the estimated results in the field. Therefore, a cascade method of interval-wavelength screening was proposed to reduce the data dimension and improve the crop estimation accuracy and robustness for the chlorophyll content diagnosis of maize crops. In the experiments, spectral reflectance data of maize canopy within 325–1075 nm were obtained, and chlorophyll contents were measured under the conditions of six nitrogen application rates and three growth periods following the early flaring, flaring, and tasseling stages. First, the backward interval partial least squares (BiPLS) method was used to optimize the spectrum interval. Then, competitive adaptive reweighted sampling (CARS) and genetic algorithm (GA) were used for secondary wavelength screening, and the partial least squares regression (Bi-CARS-PLSR and Bi-GA-PLSR) model was established with the chlorophyll content. Compared with the full-spectrum modeling (Full-PLSR) results and the GA and CARS screening wavelength modeling (Full-CARS-PLSR and Full-GA-PLSR) results in the full-spectrum range, the number of wavelengths in the Full-PLSR model was 751. The accuracy of the Full-PLSR model with the coefficient of determination was 0.88 for the calibration set (Rc2) and 0.66 for the verification set (Rv2). The root mean square error (RMSE) was 2.05 mg/L. The wavelength numbers of Full-CARS-PLSR and Full-GA-PLSR were 125 and 99, and their Rc2 and Rv2 were 0.88 and 0.67, respectively. The RMSE values of Full-CARS-PLSR and Full-GA-PLSR were 2.04 and 1.89 mg/L, respectively. By using the proposed cascade method, the wavelength numbers of the Bi-CARS-PLSR model and Bi-GA-PLSR model after interval optimization were 60 and 49, respectively. Their accuracy values for the calibration set (Rc2) were both 0.87, while those for the verification set (Rv2) were 0.7 and 0.78, respectively. The RMSE values of both models were 1.97 and 1.86 mg/L, respectively. The results showed that the proposed cascaded interval-wavelength screening method could eliminate redundant and collinearity variables and improve model performances. At the same time, the Bi-GA-PLSR modeling result was used for field prediction to establish a chlorophyll distribution map, which had a high consistency with the real chlorophyll distribution, and showed the potential to detect chlorophyll content of maize in the field.

Can assimilation of satellite observations improve subsurface biological properties in a numerical model? A case study for the Gulf of Mexico

Abstract. Given current threats to ocean ecosystem health, there is a growing demand for accurate biogeochemical hindcasts, nowcasts, and predictions. Provision of such products requires data assimilation, i.e., a comprehensive strategy for incorporating observations into biogeochemical models, but current data streams of biogeochemical observations are generally considered insufficient for the operational provision of such products. This study investigates to what degree the assimilation of satellite observations in combination with a priori model calibration by sparse BGC-Argo profiles can improve subsurface biogeochemical properties. The multivariate deterministic ensemble Kalman filter (DEnKF) has been implemented to assimilate physical and biological observations into a three-dimensional coupled physical–biogeochemical model, the biogeochemical component of which has been calibrated by BGC-Argo float data for the Gulf of Mexico. Specifically, observations of sea surface height, sea surface temperature, and surface chlorophyll were assimilated, and profiles of both physical and biological variables were updated based on the surface information. We assessed whether this leads to improved subsurface distributions, especially of biological properties, using observations from five BGC-Argo floats that were not assimilated. An alternative light parameterization that was tuned a priori using BGC-Argo observations was also applied to test the sensitivity of data assimilation impact on subsurface biological properties. Results show that assimilation of the satellite data improves model representation of major circulation features, which translate into improved three-dimensional distributions of temperature and salinity. The multivariate assimilation also improves the agreement of subsurface nitrate through its tight correlation with temperature, but the improvements in subsurface chlorophyll were modest initially due to suboptimal choices of the model's optical module. Repeating the assimilation run by using the alternative light parameterization greatly improved the subsurface distribution of chlorophyll. Therefore, even sparse BGC-Argo observations can provide substantial benefits for biogeochemical prediction by enabling a priori model tuning. Given that, so far, the abundance of BGC-Argo profiles in the Gulf of Mexico and elsewhere has been insufficient for sequential assimilation, updating 3D biological properties in a model that has been well calibrated is an intermediate step toward full assimilation of the new data types.

Spatial covariation between solar-induced fluorescence and vegetation indices from Arctic-Boreal landscapes

The Arctic-Boreal Zone (ABZ) is characterized by spatially heterogeneous vegetation composition and structure, leading to challenges for inferring patterns in vegetation productivity. A mechanistic understanding of the patterns and processes underlying spectral remote sensing observations is necessary to overcome these challenges. Solar-induced chlorophyll fluorescence (SIF), near-infrared reflectance of vegetation (NIRv), and chlorophyll/carotenoid index (CCI) show promise for tracking productivity and disentangling links to the activity and distribution of chlorophyll at coarse spatial scales (e.g. 0.5°), but their effectiveness for studying mixed landscapes characteristic of the ABZ remains unclear. Here, we use airborne observations collected during NASA’s Arctic-Boreal Vulnerability Experiment to examine the spatial covariation between SIF, NIRv, and CCI at a scale (30 m) commensurate with the best available landcover products across interior Alaska. Additionally, we compare relationships among SIF and vegetation indices from spaceborne observations (TROPOMI and MODIS) resampled to a 0.01° (∼1000 m) scale. We find that the strength of the SIF-NIRv linear relationship degrades when compared from the spaceborne to the airborne scale (R 2 = 0.50 vs. 0.26) as does the strength of the SIF-CCI linear relationship (R 2 = 0.30 vs. 0.18), though the degradation of SIF-CCI is less severe than that of SIF-NIRv. The relationship of SIF with either vegetation index is strongly dependent on landcover class at both airborne and spaceborne scales. We provide context for how further work could leverage SIF with reflectance indices measurable from a variety of platforms to improve mapping of vegetation dynamics in this ecoregion.

A novel method to simulate the 3D chlorophyll distribution in marine oligotrophic waters

A 3D advection-diffusion-reaction model is proposed to investigate the abundance of phytoplankton in a difficult-to-access ecosystem such as the Gulf of Sirte (southern Mediterranean Sea) characterized by oligotrophic waters. The model exploits experimentally measured environmental variables to reproduce the dynamics of four populations that dominate phytoplankton community in the studied area: Synechococcus, Prochlorococcus HL, Prochlorococcus LL and picoeukaryotes. The theoretical results obtained for phytoplankton abundances are converted into chl-a and Dvchl-a concentrations, and the simulated vertical chlorophyll profiles are compared to the corresponding experimentally acquired data during the MedSudMed-08 oceanographic survey. Non parametric tests showed that the 3D model successfully simulates the spatial distribution of chlorophyll in most of the Gulf of Sirte. Statistical analysis indicates that about 80% of the simulated chlorophyll vertical profiles are not significantly different from the experimental data. This model is also a useful tool to predict chlorophyll distributions in hard-to-access areas, where experimental data cannot be collected. Moreover, the model could be used to predict the effects of global warming on phytoplankton dynamics and primary production in marine ecosystems.

Fine-scale leaf chlorophyll distribution across a deciduous forest through two-step model inversion from Sentinel-2 data

Leaf chlorophyll content (LCC) is a key physiological trait and is crucial for monitoring plant health and accurately modeling the terrestrial carbon cycle. However, spatially-continuous information on LCC variability at fine time-steps, and at fine spatial resolutions across regional spatial extents, is sparse. In this study, we improved a physically-based, two-step inversion approach by using an advanced canopy-to-leaf reflectance conversion model to estimate LCC at fine spatial resolution (20 m) from Sentinel-2 Multi-Spectral Instrument (MSI) data. The first step is to convert MSI canopy reflectance to leaf reflectance using look-up tables constructed from a geometric optical model (4-Scale). The second step is to estimate LCC from the modeled leaf reflectance using the PROSPECT-5 leaf optical model. Both leaf reflectance and LCC derived from MSI were validated against field measurements at a mixed temperate forest site in Canada to examine the accuracy of leaf area index (LAI) and LCC retrievals. The results demonstrate robust canopy-level inversions with strong relationships between measured and MSI-derived leaf reflectance (R2 = 0.995, p < 0.001, RMSE = 0.0143). The modeled LCC results were also strong when compared to measured LCC samples: R2 = 0.849, p < 0.001, and RMSE = 0.304 μg/cm2, respectively. The most important Sentinel-2 MSI band for LAI and LCC derivation was centered at 705 nm (Band 5). Importantly, this two-step radiative transfer inversion approach substantially improved upon the current LAI and LCC algorithms adopted by the Sentinel-2 Application Platform, which underestimated LAI by 52.93% and overestimated LCC by 44.45%. This work highlights the potential of the physically-based two-step inversion method for deriving leaf and canopy traits from Sentinel-2 at very fine spatial and temporal resolutions, for a wide range of terrestrial ecological applications.

Opposing shifts in distributions of chlorophyll concentration and composition in grassland under warming

Global warming has significantly altered the distribution and productivity of vegetation owing to shifts in plant functional traits. However, chlorophyll adaptations—good representative of plant production—in grasslands have not been investigated on a large scale, hindering ecological predictions of climate change. Three grassland transects with a natural temperature gradient were designed in the Tibetan, Mongolian, and Loess Plateau to describe the changes in chlorophyll under different warming scenarios for 475 species. In the three plateaus, variations and distributions of species chlorophyll concentration and composition were compared. The results showed that the means of chlorophyll concentration and composition (chlorophyll a/b) increased with the mean annual temperature. Still, their distributions shifted in opposite manners: chlorophyll concentration was distributed in a broader but more differential manner, while chlorophyll composition was distributed in a narrower but more uniform manner. Compared to chlorophyll concentration, chlorophyll composition was more conservative, with a slight shift in distribution. At the regional level, the chlorophyll concentration and composition depend on the limitations of the local climate or resources. The results implied that warming might drive shifts in grassland chlorophyll distribution mainly by alternations in species composition. Large-scale chlorophyll investigations will be useful for developing prediction techniques.

Spatial and Temporal Vertical Distribution of Chlorophyll in Relation to Submarine Wastewater Effluent Discharges

The vertical distribution of chlorophyll in coastal waters is influenced by a combination of the hydrodynamic environment and different biotic and abiotic processes. The spatial and temporal occurrences of chlorophyll profiles provide a good representation of the changes in the marine environment. The majority of studies in the Adriatic Sea have so far been conducted in areas unaffected by anthropogenic pressure. Our study site is located near two marine outfalls, which are part of the public sewage system. This study aims to characterize the chlorophyll vertical distribution and describe its variability based on the stratification conditions and the presence of a wastewater effluent plume. Based on these conditions, we identified three characteristic scenarios/types of chlorophyll profiles. The first one occurs when the vertical mixing of the water column creates the upwelling of chlorophyll and nutrients to the upper part of the water column. The second and third scenarios occur during stratified conditions and differ by the extent of the effluent plume intrusion. Using modern fluorescence techniques, we identified and described three different vertical chlorophyll profiles, characterizing them according to their physical and biological parameters and processes. For cases with a visible effluent intrusion, we confirmed the importance of the pycnocline formation in keeping the effluent below and maintaining the higher water quality status at the top of the water column.

Do Loop Current eddies stimulate productivity in the Gulf of Mexico?

Abstract. Surface chlorophyll concentrations inferred from satellite images suggest a strong influence of the mesoscale activity on biogeochemical variability within the oligotrophic regions of the Gulf of Mexico (GoM). More specifically, long-living anticyclonic Loop Current eddies (LCEs) are shed episodically from the Loop Current and propagate westward. This study addresses the biogeochemical response of the LCEs to seasonal forcing and show their role in driving phytoplankton biomass distribution in the GoM. Using an eddy resolving (1/12∘) interannual regional simulation, it is shown that the LCEs foster a large biomass increase in winter in the upper ocean. It is based on the coupled physical–biogeochemical model NEMO-PISCES (Nucleus for European Modeling of the Ocean and Pelagic Interaction Scheme for Carbon and Ecosystem Studies) that yields a realistic representation of the surface chlorophyll distribution. The primary production in the LCEs is larger than the average rate in the surrounding open waters of the GoM. This behavior cannot be directly identified from surface chlorophyll distribution alone since LCEs are associated with a negative surface chlorophyll anomaly all year long. This anomalous biomass increase in the LCEs is explained by the mixed-layer response to winter convective mixing that reaches deeper and nutrient-richer waters.

Photoacclimation by phytoplankton determines the distribution of global subsurface chlorophyll maxima in the ocean

Subsurface chlorophyll maxima are widely observed in the ocean, and they often occur at greater depths than maximum phytoplankton biomass. However, a consistent mechanistic explanation for their distribution in the global ocean remains lacking. One possible mechanism is photoacclimation, whereby phytoplankton adjust their cellular chlorophyll content in response to environmental conditions. Here, we incorporate optimality-based photoacclimation theory based on resource allocation trade-off between nutrient uptake and light harvesting capacity into a 3D biogeochemical ocean circulation model to determine the influence of resource allocation strategy on phytoplankton chlorophyll to carbon ratio distributions. We find that photoacclimation is a common driving mechanism that consistently explains observed global scale patterns in the depth and intensity of subsurface chlorophyll maxima across ocean regions. This mechanistic link between cellular-scale physiological responses and the global scale chlorophyll distribution can inform interpretation of ocean observations and projections of phytoplankton responses to climate change.

Statistical tools for studying the temporal variations in chlorophyll-a concentration along the Southwest Bay of Bengal waters

Multivariate statistical analysis such as Multiple Linear Regression (MLR) and Principal Component Analysis (PCA) are used to study the effect of physico-chemical parameters on chlorophyll distribution along the southwest Bay of Bengal from January 2012 to June 2014. Physical properties recorded showed clear seasonal patterns in sea surface temperature (26.2 – 32.8 °C), salinity (24 – 36 PSU), pH (7.808 to 8.428), photosynthetic photon flux (522 – 1220.4 µM m-2s-1) with the minimum and maximum values during monsoon and summer seasons, respectively. In contrast, the chemical variables such as nitrite (0.15 to 2.35 µM), nitrate (1.02 to 6.58 µM), ammonia (0.11 – 5.22 µM), total nitrogen (1.04 to 11.58 µM), inorganic phosphate (0.16 – 2.97 µM), total phosphorus (0.55 – 8.60 µM) and reactive silicate (2.00 to 23.95 µM) showed the minimum and maximum concentration during summer and monsoon seasons, respectively. The high and low chlorophyll (0.10 to 6.92 µg l-1) and dissolved oxygen (4.07 and 7.884 mg l-1) concentrations are observed during summer and pre-monsoon seasons, respectively. PCA found that nitrogenous nutrients and chlorophyll are positively loaded and Sea Surface Temperature (SST) was negatively loaded in all the seasons except during summer season. Inter-comparison of modeled and in-situ chlorophyll-a (chl-a) concentration showed a significant correlation during monsoon season by 93 % of matchup with a R2 = 0.930, N = 60 and SEE = ±0.369 compared to other seasons. Regression analysis also predicted the positive influence of nitrate and ammonia and negative influence of SST with chl-a.

The Vertical Profile of Chlorophyll-a in the Waters of Submarine Volcano of Kawio Barat, Indonesia

The submarine volcano can release various materials into the waters and affect the distribution of chlorophyll. Nevertheless, studies in such kinds of exciting areas are rarely done. This study aims to determine the vertical profile of chlorophyll-a around the submarine volcano waters. A field survey was conducted in October 2018 in the photic zone (200 m) around the Kawio Barat submarine volcano waters, North Sulawesi Province, Indonesia. Chlorophyll fluorescence was measured using a sensor of WET Labs ECO-AFL/FL as a proxy of chlorophyll-a. The temperature, salinity, and depth were measured using a CTD. The nutrients, including nitrate, orthophosphate, and silicate, were measured using autoanalyzer Skalar SAN++. The average of chlorophyll-a values ranged between 0.098 - 0.175 mg/m3. The highest average chlorophyll-a was found around the waters of Kawio Barat submarine-volcano. The vertical profile of chlorophyll-a indicated a forming of Deep Chlorophyll Maxima (DCM), located at a depth of 69 - 90 meters. In the Kawio Barat submarine volcano waters, the DCM is found in a depth of 90 m. It has chlorophyll-a concentration four times higher than the surface (5 m). The Principal of Component Analysis (PCA) shows that the temperature and salinity have a more substantial influence on the value of chlorophyll-a. Meanwhile, the nutrients are more influence firmly on the depth of DCM. This current study may conclude that the Kawio Barat submarine volcano waters are more productive than the other stations.

Deep Chlorophyll Maxima in the Global Ocean: Occurrences, Drivers and Characteristics.

Stratified oceanic systems are characterized by the presence of a so‐called Deep Chlorophyll a Maximum (DCM) not detectable by ocean color satellites. A DCM can either be a phytoplankton (carbon) biomass maximum (Deep Biomass Maximum, DBM), or the consequence of photoacclimation processes (Deep photoAcclimation Maximum, DAM) resulting in the increase of chlorophyll a per phytoplankton carbon. Even though these DCM (further qualified as either DBMs or DAMs) have long been studied, no global‐scale assessment has yet been undertaken and large knowledge gaps still remain in relation to the environmental drivers responsible for their formation and maintenance. In order to investigate their spatial and temporal variability in the open ocean, we use a global data set acquired by more than 500 Biogeochemical‐Argo floats given that DCMs can be detected from the comparative vertical distribution of chlorophyll a concentrations and particulate backscattering coefficients. Our findings show that the seasonal dynamics of the DCMs are clearly region‐dependent. High‐latitude environments are characterized by a low occurrence of intense DBMs, restricted to summer. Meanwhile, oligotrophic regions host permanent DAMs, occasionally replaced by DBMs in summer, while subequatorial waters are characterized by permanent DBMs benefiting from favorable conditions in terms of both light and nutrients. Overall, the appearance and depth of DCMs are primarily driven by light attenuation in the upper layer. Our present assessment of DCM occurrence and of environmental conditions prevailing in their development lay the basis for a better understanding and quantification of their role in carbon budgets (primary production and export).