Phytoplankton Absorption Coefficient Research Articles

Performance of two semi-analytical algorithms in deriving water inherent optical properties in the Southern Ocean

Remotely sensed inherent optical properties (IOPs) are key proxies for synoptic mapping of primary production and carbon export in the global ocean. However, the IOPs inversion algorithms are scarcely evaluated in the Southern Ocean (SO) because of limited field observations. In this study, the performance of two widely used semi-analytical algorithms (SAAs), i.e., the quasi-analytical algorithm (QAA) and the generalized IOP model (GIOP), were evaluated using a compiled in situ bio-optical dataset in SO, as well as measurements from the Visible Infrared Imaging Radiometer Suite (VIIRS). Evaluations with in situ data show that QAA and GIOP have comparable performance in retrieving the total absorption coefficient (a(λ)), absorption coefficients of phytoplankton (aph(λ)), and that of detritus and colored dissolved organic matter (adg(λ)). Overall, it was found that remotely sensed a(λ) and aph(λ) by both SAAs agreed well with field measurements, with the mean absolute percentage difference (MAPD) of derived a(λ) and aph(λ) in the blue-green bands being ∼20% and ∼40%, respectively. However, derived adg(λ) by both SAAs were higher than the measured values at the lower end (adg(443) < ∼0.01 m-1), but lower at the higher end (adg(443) > ∼0.02 m-1), with MAPD of ∼60%. Results of this effort suggest confident products of a(λ) and aph(λ) from VIIRS in SO, but more dedicated efforts on the measurements and evaluation of adg(λ) in SO would be desired.

Offshore high chlorophyll eddies: Separating upwelling from nearshore migration from ocean color remote sensing

Offshore eddies are often associated with high amounts of phytoplankton (represented by the chlorophyll-a concentration (Chla)), or, phytoplankton blooms, which can be detected from ocean color satellites. The phytoplankton “blooms” in these eddies are commonly explained as a result of enhanced nutrients - local growth - brought up from deeper waters by these eddies, although potentially they could simply be a migration of high Chla waters from nearshore regions. To better understand the interactions between physical forcing and phytoplankton dynamics, it is necessary to separate these “blooms” between local growth and migration. In this study, we first updated the multiple pigment inversion model using a synthetic dataset, for retrieving the absorption coefficient and absorption Gaussian peaks of phytoplankton from remote sensing reflectance in the broad aquatic environments. On this basis, a two-dimensional spatial model was developed to identify the sources of phytoplankton associated with offshore eddies. The model was based on the absorption coefficient of phytoplankton at 443 nm (aph(443)) and the ratio of two Gaussian peaks at 519 nm and 435 nm, where these two peaks represent different contributions of phytoplankton pigments to aph. This two-dimensional spatial model was applied to images collected by the Ocean and Land Color Instrument in the California offshore region to demonstrate that the scheme effectively separated offshore upwelling waters from those migrating from nearshore waters. Such separations provide independent sources for identifying offshore upwelling water that will be important for studying offshore circulation processes.

Evaluation of three contrasting models in estimating primary production from ocean color remote sensing using long-term time-series data at oceanic and coastal sites

Accurate estimates of depth-integrated Net Primary Production (NPP, mg C m−2 d−1) and the creation of a robust climate data record of NPP for the global oceans are essential goals of the ocean color remote sensing community. Here, we take advantage of in situ NPP measurements from three long-term time-series sites, the HOT (Hawaii Ocean Time-series), BATS (Bermuda Atlantic Time-series Study) and CARIACO (Ocean Time-Series Program from the Cariaco basin), spanning over 30 years to evaluate three contrasting models in estimating NPP from ocean color remote sensing. These models for NPP estimation include the Absorption-based Model (AbPM), which relies on phytoplankton absorption coefficient, the Vertically Generalized Production Model (VGPM), which centers on chlorophyll-a concentration, and the Carbon-based Productivity Model (CbPM) centering on phytoplankton carbon. In addition to the accuracy of NPP estimation from these models, we laid great emphasis on evaluating their skills in capturing the monthly to seasonal variations and interannual trends in NPP at the three sites. Comparison with in situ NPP at all three long-term sites (∼20 years) showed that AbPM yielded the highest coefficient of determination (R2 = 0.67) and the lowest uncertainties (Bias = 0.03 and unbiased root mean square difference = 0.17). Seasonal and interannual variations apparent in the in situ NPP time-series records were best captured by AbPM. These results showcase the robust capabilities of AbPM and its superiority for global carbon cycling and climate change studies, largely because it takes into account optical and photosynthetic parameters of local phytoplankton.

2016–2020年呼伦湖水体固有光学参数遥感产品

Hulun Lake, the largest steppe lake in the high latitude semi-arid region of inland China, holds great significance for grassland production and steppe-lake ecosystem. The absorption coefficient of water constitutes is indicative of the optically active components in water, thus conducive to estimating the optically active substances and other related bio-optical parameters of waters. In this study, we used the quasi-analytical algorithm (QAA), a QAA-750E absorption coefficient inversion algorithm suitable for inland waters. Based on Sentinel-3/OLCI remote sensing reflectance data, we produced a dataset of monthly mean phytoplankton absorption coefficient aph(675)and backscattering coefficient bbp(560) of Hulun Lake during 2016-2020. Validation analysis results show that the model-derived b_bp (560) has an R2 value of 0.59, RMSE of 0.55, and MRD of 0.54 (N = 15), indicating a high level of reliability of the dataset. The dataset is expected to offer data support for water quality monitoring and ecological environment protection of Hulun Lake.

Sensing profiles of the volume scattering function at 180° using a single-photon oceanic fluorescence lidar.

A novel oceanic fluorescence lidar technique has been proposed and demonstrated for remotely sensing the volume scattering function at 180° (βf), which can be used to further retrieve the profiles of the absorption coefficient of phytoplankton (aph) at 532 nm and chlorophyll concentration (Chl). This scheme has these features. 1) The single-photon detection technology is employed to enhance the detection sensitivity to the single-photon level, enabling the oceanic lidar to obtain fluorescence backscatter profiles. 2) In terms of algorithms, the Raman backscattered signals of the water are utilized to normalize the backscattered signals of chlorophyll fluorescence, effectively minimizing the depth-dependent variation of the differential lidar attenuation coefficient (Δ K l i d a r f r). To reduce the contamination of fluorescence signals in the Raman backscatter signals, a Raman filter with a bandwidth of 6 nm was chosen. Subsequently, a perturbation method is utilized to invert the βf of the fluorescence lidar. Finally, aph and Chl profiles can be inverted based on empirical models. 3) The value of Δ K l i d a r f r used in inversion is obtained through a semi-analytic Monte Carlo simulation. According to theoretical analysis, the maximum relative error of βf for Chl ranging from 0.01 mg/m3 to 10 mg/m3 is less than 13 %. To validate this approach, a field experiment was conducted aboard the R/V Tan Kah Kee in the South China Sea from September 4th to September 5th, 2022, resulting in continuous subsurface profiles of βf, aph, and Chl. These measurements confirm the robustness and reliability of the oceanic single-photon fluorescence lidar system and the inversion algorithm.

Estimation of primary production from the light absorption of phytoplankton and photosynthetically active radiation in the South China Sea

A model was constructed to estimate Primary production (PP) and examine the effect of the dominant phytoplankton group on PP, using a dataset collected in 2019 in the South China Sea (SCS) based on phytoplankton absorption coefficient at 443nm [aph(443)] and photosynthetically active radiation (PAR). There was a significant log-log linear correlation between PP and the product of aph(443) and PAR (aph(443)×PAR), with an adjusted R2 of 0.64. The model was validated using K-fold cross-validation and an in situ dataset collected in 2018 in the SCS basin. The results showed that the model had good generalisability and was suitable across marine environments, including basin, coastal, and offshore areas. The model was more sensitive to changes in PAR than changes in aph(443). Phytoplankton in the diatom-dominant and haptophyte-dominant clusters were in the light-limited stage, and their PP values increased with increasing aph(443)×PAR. However, Prochlorococcus-dominant samples exhibited photoinhibition, and the PP values decreased with increasing aph(443)×PAR, likely due to their bio-optical characteristics. The model’s predictive power was related to the photo-physiological state of dominant phytoplankton, which performs well in light-limited conditions but not in cases of massive photoinhibition. This study provides insight into the development of phytoplankton-specific aph-based PP models.

Light Absorption by Optically Active Components in the Arctic Region (August 2020) and the Possibility of Application to Satellite Products for Water Quality Assessment

In August 2020, during the 80th cruise of the R/V “Akademik Mstislav Keldysh”, the chlorophyll a concentration (Chl-a) and spectral coefficients of light absorption by phytoplankton pigments, non-algal particles (NAP) and colored dissolved organic matter (CDOM) were measured in the Norwegian Sea, the Barents Sea and the adjacent area of the Arctic Ocean. It was shown that the spatial distribution of the three light-absorbing components in the explored Arctic region was non-homogenous. It was revealed that CDOM contributed largely to the total non-water light absorption (atot(λ) = aph(λ) + aNAP(λ) + aCDOM(λ)) in the blue spectral range in the Arctic Ocean and the Barents Sea. The fraction of NAP in the total non-water absorption was low (less than 20%). The depth of the euphotic zone depended on atot(λ) in the surface water layer, which was described by a power equation. The Arctic Ocean, the Norwegian Sea and the Barents Sea did not differ in the Chl-a-specific light absorption coefficients of phytoplankton. In the blue maximum of phytoplankton absorption spectra, Chl-a-specific light absorption coefficients of phytoplankton in the upper mixed layer (UML) were higher than those below the UML. Relationships between phytoplankton absorption coefficients and Chl-a were derived by least squares fitting to power functions for the whole visible domain with a 1 nm interval. The OCI, OC3 and GIOP algorithms were validated using a database of co-located results (day-to-day) of in situ measurements (n = 63) and the ocean color scanner data: the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra (EOS AM) and Aqua (EOS PM) satellites, the Visible and Infrared Imager/Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (S-NPP) and JPSS-1 satellites (also known as NOAA-20), and the Ocean and the Land Color Imager (OLCI) onboard the Sentinel-3A and Sentinel-3B satellites. The comparison showed that despite the technological progress in optical scanners and the algorithms refinement, the considered standard products (chlor_a, chl_ocx, aph_443, adg_443) carried little information about inherent optical properties in Arctic waters. Based on the statistic metrics (Bias, MdAD, MAE and RMSE), it was concluded that refinement of the algorithm for retrieval of water bio-optical properties based on remote sensing data was required for the Arctic region.

An operational model for separating the absorption of optically active constituents from SeaWiFS measurements

ABSTRACT To analytically or semi-analytically convert satellite-measured remote sensing reflectance (R rs) to widely used biogeochemical variables from the global oceans, it is common to first determine the total absorption coefficient from satellite R rs data and then separate the total absorption coefficient into the absorption coefficients of phytoplankton (a ph ) and non-phytoplankton (a dg ) pigments. While still considering the spectral characteristics of a ph and a dg , we developed an operational model to improve the accuracy of estimating a ph and a dg products from satellite R rs data. Our results show that our model effectively separates a ph and a dg from the total absorption coefficient spectrum, which decreases the uncertainty by 6.81% to 17.52% compared to a widely used quasi-analytical algorithm. Moreover, after applying the new model to SeaWiFS satellite images, we present the spatial and temporal variations of a ph (443) and a dg (443) for the global oceans from 1997 to 2010, further confirming that coastal zones exhibited higher a ph (443) and a dg (443) than the open oceans during that time. In addition, a ph (443) and a dg (443) declined in the tropical Indian Ocean Gyre over those 13 years. Our results improve our knowledge of the spatiotemporal variations of optical properties of the global oceans, and also demonstrate the potential of our model in separating the total absorption.

Semi-analytical inversion modelling of Chlorophyll a variability in the U.S. Virgin Islands

Coral reef health in the U.S. Virgin Islands (USVI) is in decline due to land-based sources of pollution associated with watershed development and global climate change. Water quality is a good indicator of stress in these nearshore environments as it plays a key role in determining the health and distribution of coral reef communities. Conventional water quality assessment methods based on in situ measurements are both time consuming and costly, and they lack the spatial coverage and temporal resolution that can be achieved using satellite remote sensing techniques. Water quality parameters (WQPs) such as Chlorophyll a (Chl-a), can be studied remotely using models that account for the inherent optical properties (IOPs) of the water. In this study, empirical based standard ocean color algorithm (OC4) and two semi-analytical algorithms, the Garver–Siegel–Maritorena (GSM) and the Generalized Inherent Optical Properties (GIOP) model, were evaluated in retrieving Chl-a in the nearshore waters of the USVI. GSM and GIOP were also evaluated for modeling inherent optical properties such as absorption coefficient of phytoplankton (aph (443)). Analysis of the results from each model using a field database from six cruises during May/June and December between 2016 and 2018, showed that the OC4 performed poorly with R2 of 0.14 and RMSE = 0.15. Effects of suspended particulates and benthic reflectance most likely contributed to the poor performance of the algorithm. GSM is a slightly better estimator for aph (443) and Chl-a (R2 = 0.55, RMSE = 0.04; R2 = 0.60, RMSE = 0.09) than GIOP (R2 = 0.52, RMSE = 0.05; R2 = 0.17, RMSE = 0.15). Performance of the semi-analytical models are limited in estimating particulate back scattering (bbp (443)) also due to the benthic albedo effects in the shallow waters. The calibrated GSM model was applied to Landsat 8 OLI satellite imagery spanning 2016–2018 to develop a time series of the spatial changes in Chl-a concentrations in the coastal waters of the USVI. The Landsat GSM Chl-a model produced promising results of R2 = 0.45, RMSE = 0.07, in an environment where signal-to-noise ratio is significantly low.

Estimation of chromophoric dissolved organic matter and non-algal particulate absorption coefficients of seawater in the ultraviolet by extrapolation from the visible spectral region.

Extending the capabilities of optical remote sensing and inverse optical algorithms, which have been commonly focused on the visible (VIS) range of the electromagnetic spectrum, to derive the optical properties of seawater in the ultraviolet (UV) range is important to advancing the understanding of various optical, biological, and photochemical processes in the ocean. In particular, existing remote-sensing reflectance models that derive the total spectral absorption coefficient of seawater, a(λ), and absorption partitioning models that partition a(λ) into the component absorption coefficients of phytoplankton, aph(λ), non-algal (depigmented) particles, ad(λ), and chromophoric dissolved organic matter (CDOM), ag(λ), are restricted to the VIS range. We assembled a quality-controlled development dataset of hyperspectral measurements of ag(λ) (N = 1294) and ad(λ) (N = 409) spanning a wide range of values across various ocean basins, and evaluated several extrapolation methods to extend ag(λ), ad(λ), and adg(λ) ≡ ag(λ) + ad(λ) into the near-UV spectral region by examining different sections of the VIS as a basis for extrapolation, different extrapolation functions, and different spectral sampling intervals of input data in the VIS. Our analysis determined the optimal method to estimate ag(λ) and adg(λ) at near-UV wavelengths (350 to 400 nm) which relies on an exponential extrapolation of data from the 400-450 nm range. The initial ad(λ) is obtained as a difference between the extrapolated estimates of adg(λ) and ag(λ). Additional correction functions based on the analysis of differences between the extrapolated and measured values in the near-UV were defined to obtain improved final estimates of ag(λ) and ad(λ) and then the final estimates of adg(λ) as a sum of final ag(λ) and ad(λ). The extrapolation model provides very good agreement between the extrapolated and measured data in the near-UV when the input data in the blue spectral region are available at 1 or 5 nm spectral sampling intervals. There is negligible bias between the modeled and measured values of all three absorption coefficients and the median absolute percent difference (MdAPD) is small, e.g., < 5.2% for ag(λ) and < 10.5% for ad(λ) at all near-UV wavelengths when evaluated with the development dataset. Assessment of the model on an independent dataset of concurrent ag(λ) and ad(λ) measurements (N = 149) yielded similar findings with only slight reduction of performance and MdAPD remaining below 6.7% for ag(λ) and 11% for ad(λ). These results are promising for integration of the extrapolation method with absorption partitioning models operating in the VIS.

Chlorophyll-Specific Absorption Coefficient of Phytoplankton in World Oceans: Seasonal and Regional Variability

This study investigates the seasonal and regional variability in the chlorophyll-specific absorption coefficient of phytoplankton at 443 nm (aph*(443); unit: m2 mg−1) in surface oceans. It is focused on the time series data derived from the satellite products of chlorophyll-a (Chl-a) concentration and the phytoplankton absorption coefficient. Global estimates of aph*(443) reveal a decreasing gradient from the open ocean toward the coastal environment, with considerable spatial variance. Seasonal variations are prominent over most oceans, resulting in substantial deviations from the climatological means. A sinusoidal model was fitted to the monthly time series data to characterize the annual and semiannual features. The amplitudes and the phases of the monthly data were latitudinally dependent. The occurrence times of the maximum aph*(443) values were six months out of phase between the northern and southern hemispheres. Satellite observations present a global mean relationship between aph*(443) and Chl-a comparable with those obtained via in situ measurements. However, the seasonal/regional aph*(443) and Chl-a relationships can significantly depart from the global mean relationship. We propose a hypothesis that aph*(443) can be predicted as a function of geolocation and time. Preliminary validations with in situ matchup data confirm that the proposed model is a promising alternative to the traditional approaches requiring Chl-a as the input. The present exploration helps understand the phytoplankton biogeography and facilitates future efforts to improve bio-optical modeling, including estimating the primary production.

Cross frontal variability in bio-optical characteristics in the Indian sector of the Southern Ocean during an austral summer

Bio-optical properties, which play a crucial role in the understanding of the radiation budget of optical active substances (OAS), phytoplankton community, biological pump, and detection of algal blooms have been sparsely studied in the Southern Ocean (SO). We assessed how bio-optical characteristics change across the frontal regions and during phytoplankton bloom and non-bloom domains in the Indian sector of the SO (ISSO) during the austral summer of 2011. In both the meridional transect (47 oE and 57.5 oE), the surface Chlorophyll-a, and phytoplankton absorption coefficient (aph(443)) increased with latitude. Whereas Chlorophyll-a specific phytoplankton absorption (a*ph(443)), an index for the “pigment package effect”, decreased with latitude, implying that the size of phytoplankton increases with latitude. The 57.5 oE transect showed higher quantities of OAS than 47 oE, except for Polar Front 2 (PF-2). Moreover, the vertical profiles of Chlorophyll-a in PF-2 at 47 oE showed a massive phytoplankton bloom with a thickness of 60 m, which could be confirmed in the surface Chlorophyll-a images from the MODIS Aqua satellite. The massive bloom occurred due to distinct physical processes (nutrients supplied by pack ice), causing high productivity. The vertical profiles of Chlorophyll-a, aph(443), and a*ph(443) identified subsurface chlorophyll maxima (SCM) and different phytoplankton communities across the fronts. The interrelationships between bio-optical properties exhibited distinct features in bloom and non-bloom domains. The aCDOM(443) and its spectral slope (S300−500) increased and decreased with latitude, respectively. Using the vertical distribution of CDOM and its relationships with slope and Chlorophyll-a, multiple sources of CDOM could be identified. The percentage-contribution of OAS in the Polar Front-1 (PF-1) exhibited lower aph, lower detrital absorption (ad), and higher aCDOM indicating its low productivity compared to other fronts. This study facilitates the understanding of the phytoplankton size-class (pico, nano and micro) and productivity using the bio-optical properties in this lesser-studied polar region.

Spatio-Temporal Study of Phytoplankton Groups from Inherent Optical Properties (Iops) in The Ivorian Marine Coastline from 2010 To 2020

Today global warming affects all environments including coastal marine environments. Climate change also affects the development and proliferation of phytoplankton groups often leading to the massive production of phytoplankton groups in marine waters. Itis with this in mind that the study on the determination of phytoplankton groups from optical properties in Ivorian marine waters was initiated.This study showed a great diversity of phytoplankton in the Ivorian marine domain during the years 2010 and 2020. The data used in these studies are geospatial data (remote sensing) of the optical properties of theoceans, in particular the IOPs (inherent optical properties). These are the fusion data from the various SeaWiFS, MODIS, MERIS, VIIRS sensors from 2010 to 2020 from the various OrbView 2, NOAA, ENVISAT and AQUA satellites, in particular the absorption coefficient data for dissolved and detrital matter at 443 nm (adg ), phytoplankton absorption coefficient data at 443 nm (aph), and dissolved and detrital particulate backscatter coefficient data at 443 nm (bbp).For the processing of these data the pixel-oriented classification method was used for the identification of phytoplankton groups. The SeaDAS v 7.4 software, allowed to process and analyze the data and the Envi 5.3 software allowed to perform the data classification. Thevalues of inherent optical properties (IOPs) were obtained as well as the spatial distribution of phytoplankton groups, thus allowing the production of maps of IOPs and the production of spatio-temporal distribution maps of cyanobacteria and diatoms.

Phytoplankton Light Absorption Impacted by Photoprotective Carotenoids in a Global Ocean Spectrally‐Resolved Biogeochemistry Model

AbstractThe chlorophyll‐specific absorption spectrum of phytoplankton multiplied with phytoplankton chlorophyll provides the total absorption coefficient of phytoplankton [], a fundamental quantity with significance in many marine biogeochemical (BGC) and environmental processes. Representing accurately the sources of variability of in BGC ocean models is a crucial task. The two main sources of variability in are changes in the pigment composition of the phytoplankton community and the size‐dependent constraints to pigment packaging. Therefore, changes in community structure and physiological state impact and consequently . The objective of this work is to improve estimates of in a BGC model of the global ocean by portraying the variability of driven by the variable content in photoprotective carotenoids (PPCs) in the phytoplankton community. We used a three‐dimensional spectrally‐resolved BGC model to simulate the inherent and apparent optical properties of the global ocean based on its content on optically active constituents. The for each phytoplankton type represented in the model were made variable as a function of the type‐specific content in PPCs. By comparing model‐derived to satellite retrievals and an extensive field data set of optical and BGC observations, we concluded that photoprotective pigments content impacted significantly the contribution of the to the total non‐water absorption in the ocean. Pigment‐impacted contributed to reproduce the global variability of as well as the observed bio‐optical relationship between and chlorophyll. The improved representation of the of the phytoplankton community influenced model simulations in terms of water‐leaving radiances.

Bio-optical properties of the Brazilian Abrolhos Bank’s shallow coral-reef waters

The Abrolhos Bank harbors the richest coral reef ecosystem in the South Atlantic Ocean. It exhibits unique geomorphologic structures, is localized in shallow depths, and is divided into two reef regions with an inner arc close to the coast (3–20 m depth) and an outer deeper arc (5–30 m depth). This study aims to describe some bio-optical properties of the Abrolhos Bank waters and to evaluate the performance of the inversion Hyperspectral Optimization Processing Exemplar (HOPE) model, developed to retrieve optical properties in shallow waters, in the region. To this end, measurements at 75 stations during two field campaigns conducted during the 2013 and 2016 wet seasons were analyzed, and the HOPE model was applied to both in situ remote sensing reflectance (Rrs) spectra and PRecursore IperSpettrale della Missione Applicativa (PRISMA) imagery. Significant differences in optical and biological properties were found between the two arcs. The empirical relationships between chlorophyll-a concentration (Chl-a) and absorption coefficient of phytoplankton at 440 nm (aphy(440)) diverged from Bricaud’s models, suggesting differences in phytoplankton diversity and cell size. In both arcs, total non-water absorption coefficient at 440 nm (aT-w(440)) was dominated by colored dissolved organic matter (CDOM) by ∼60%. Absorption coefficient by CDOM (acdom) presented a higher variability within the outer arc, with the lowest contribution from non-algal particles (NAPs), and the spectral slopes of aCDOM resembled those of the inner arc. The spectral slopes of the NAP absorption coefficient suggested a dominance by organic rather than mineral particles that probably originated from biological production. The HOPE model applied to in situ Rrs performed satisfactorily for depth in the Abrolhos Bank waters, although retrievals of aphy(440), CDOM plus NAP (adg(440)) and aT-w(440) were underestimated with a relative bias of −27.9%, −32.1% and −45.8%, respectively. The HOPE model retrievals from the PRISMA image exhibited low aphy(440) values over the whole scene and the highest adg(440) values in the Caravelas river plume. Very shallow depths (≤3 m), bottom substrate reflectance used as input in the HOPE model, model parametrization associated with the water complexity in the study site, and uncertainties associated to Rrs measurements used as input might be responsible for differences found when comparing HOPE retrievals with in situ measurements.

Spatiotemporal variability in bio-optical characteristics of the southwestern tropical Indian Ocean during boreal summer: Biophysical influences

The bio-optical characteristics of the surface ocean play a pivotal role in radiative transfer and photosynthetic carbon fixation. To examine spatiotemporal variability of bio-optical properties in the tropical Indian Ocean, a 10-day time-series comparative study was made at one fixed and 3 variable stations in the southwestern tropical Indian Ocean (SWTIO), and 4-stations in the Equatorial Indian Ocean (EIO) during June 2014. A total of 24 hyperspectral radiometer profiles were collected along with physicochemical parameters and phytoplankton pigments analysis. A negative sea level anomaly (SLA), higher precipitation, a more stable mixed layer, and higher buoyancy frequency (N2) were observed in SWTIO compared to EIO. The deep chlorophyll maxima (DCM) in SWTIO were characterised by deep biomass maxima (DBM) whereas in the EIO it was due to deep photoacclimation maxima (DAM). The photosynthetically available radiation (PAR) profiles were obtained by integrating downwelling irradiance from 400 to 700 nm suggesting that the SWTIO had a greater abundance of optically active substances (OAS) than the EIO. Surface chlorophyll a (Chl-a) was found to have significant relationships with phytoplankton absorption coefficient (aph(443)). Chl-a-specific phytoplankton absorption coefficients (a*ph(443)), total absorption coefficient (at(443)), and particulate backscattering (bbp(555)) were also related to Chl-a implying that the phytoplankton was in growth/active phase. The time-series variability of the phytoplankton and changes in the photosynthetic pigments (PSP) to photoprotective pigments (PPP) ratio at SWTIO suggested phytoplankton community shift during 5th to 7th days. Microplankton percent-abundances showed distinct linear relationships with Chl-a and bbp(555) implying that carbon fixation per unit Chl-a was higher in microplankton than in nano and picoplankton at SWTIO. The in situ Chl-a, aph(443), adg(443), Kd(490) and C¯pd were used to validate the various empirical algorithms available as well as the satellite-retrieved data. The MODIS and VIIRS data correlated moderately. This study would help towards improving regional optimized algorithms for OAS and provide a baseline understanding of the scale of variability of primary production and carbon flux from space. In addition, this would contribute valuable bio-optical data from an under-sampled geographical area.

Influence of the phytoplankton community composition on the in situ fluorescence signal: Implication for an improved estimation of the chlorophyll-a concentration from BioGeoChemical-Argo profiling floats

In-situ fluorescence is a widely used method to estimate the chlorophyll-a (Chla) concentration, a proxy of the phytoplankton biomass. With the emergence of autonomous platforms such as BioGeoChemical-Argo (BGC-Argo) profiling floats, its use has expanded to global scale observations. However, the relationship between in-situ fluorescence and Chla may vary significantly, leading to major discrepancies between oceanic regions. This study aims to investigate the main sources of the natural variability in the in-situ fluorescence signal in the global open ocean, specifically the influence of the phytoplankton community composition. In this view, we analyzed a combination of three datasets comprising concomitant measurements of in-situ fluorescence, pigment concentrations and phytoplankton absorption spectra. Two datasets cover several contrasted bioregions of the global ocean whereas the third one consists of a regional time series in the northwestern Mediterranean Sea, which allows to examine the effect of phytoplankton community composition on the fluorescence signal on the global, seasonal and vertical scales. We studied the variability of the two major drivers of the natural variability of the fluorescence process, i.e. the light absorption and the fluorescence quantum yield of phytoplankton, in regards of the variability of the pigment composition of the communities. The community composition correlates substantially with the Chla-to-fluorescence ratio, with high fluorescence values associated with phytoplankton communities dominated by large cells. This trend may be explained by the combined effects of the community composition on the phytoplankton absorption coefficient and the fluorescence quantum yield, and is consistently observed globally, seasonally and vertically. Non-photosynthetic pigments also appear to play a critical role in oligotrophic surface waters, leading to a reduction of the quantum yield of fluorescence. The results indicate that the phytoplankton community composition plays a key role in the relationship between the in-situ fluorescence signal and Chla concentration. Therefore, we suggest that taking into account the composition of phytoplankton communities in the retrieval of the Chla concentration from current in-situ fluorometers, those mounted on BGC-Argo floats in particular, would lead to a better estimation of the phytoplankton biomass on a wide range of spatial and temporal scales.

Seasonal and decadal variations in absorption properties of phytoplankton and non-algal particulate matter in three oceanic regimes of the Northwest Atlantic

Seasonal and inter-annual absorption properties of phytoplankton and non-algal particulate matter were studied in relation to phytoplankton biomass, as indexed by chlorophyll-a concentration, and presence of diatoms, as indexed by fucoxanthin concentration, using a 20-year time series of in situ data collected in the Northwest Atlantic. We found significant differences in the spatiotemporal variations of the bio-optical properties for three oceanic regimes: mesotrophic (Scotian Shelf), oligotrophic (Northwest Atlantic Basin, NAB), and subartic (Labrador Sea). The Scotian Shelf and NAB exhibited similar phenology with the spring and autumn blooms associated with low phytoplankton specific absorption, while only relatively high fucoxanthin concentration occurred in spring. The NAB showed a smaller seasonal variation than the Scotian Shelf in agreement with its oceanic conditions. The Labrador Sea showed a single phytoplankton bloom in spring followed by a continuous decrease in biomass the rest of the year. The relationship between phytoplankton absorption coefficient at 443 nm and chlorophyll-a concentration was consistent with other studies with coefficients that were region-dependent. Absorption by non-algal particulate matter remained between 5% and 60% of phytoplankton absorption with a mean of 15%. The slope of the non-algal particulate absorption varied with seasons and regions and appeared to depend on the trophic status with high values (i.e., up to 0.04) occurring during bloom conditions. We also introduced a new index, the phytoplankton apparent absorption wavelength (PAAW), a wavelength-weighted sum of absorption expressed in nanometers that provides information on the phytoplankton biomass and assemblage in a simple manner. Time series analysis of the PAAW revealed a decrease of this property in spring on the Scotian Shelf, NAB, and Labrador Sea and an increase in autumn on the Scotian Shelf and NAB, suggesting a shift in these ecosystems.

A novel semianalytical remote sensing retrieval strategy and algorithm for particulate organic carbon in inland waters based on biogeochemical-optical mechanisms

The estimation of particulate organic carbon (POC) concentrations from satellite images can provide crucial spatiotemporal continuous observation data for the carbon cycle and ecological environmental governance. Here, we developed a novel inversion algorithm for deriving POC in inland water based on remote sensing and geochemical isotopes, which is summarized as follows. First, we developed empirical relationships between the phytoplankton absorption coefficient and endogenous POC concentration (CendPOC) and between the nonalgal particulate absorption coefficient and terrestrial POC concentration (CterPOC). Second, based on the valid relationships, semianalytical retrieval models were established to estimate CendPOC and CterPOC. Third, the proportions of endogenous POC (RendPOC) and terrestrial POC (RterPOC) to the total POC concentration (CPOC) were derived using a three-band empirical model. Finally, CPOC was obtained by dividing CendPOC by RendPOC (RendPOC ≥ 0.5) or dividing CterPOC by RterPOC (RendPOC < 0.5). Validation with field data shows that our proposed algorithm can accurately derive CPOC (0–20 mg/L), with a root mean square deviation (RMSD), median bias (MB), median absolute percent difference (MAPD), and median ratio (MR) of 1.15 mg/L, −0.05 mg/L, 24%, and 0.98, respectively. Synchronous validation based on Sentinel-3/OLCI images confirmed the accuracy, with RMSD, MB, MAPD, and MR values of 0.41 mg/L, −0.16 mg/L, 28%, and 0.91, respectively. The algorithm was applied to ocean and land color sensor (OLCI) images to reveal the temporal and spatial variations in POC in Lake Taihu.

How do El Niño Southern Oscillation (ENSO) Events Impact Fish Catch in Sarawak Water?

The response of chlorophyll to climate variability plays an important role in regulating the regional marine ecological environment and carbon cycle. This study focuses on the impact of changes in chlorophyll on the catches of deep-water fish and offshore fish. The chlorophyll factors from satellite image MODIS were analysed during La Niña in 2008/2011 and El Niño in 2015/2016. Remote sensing reflectance’s 443 nanometres and 555 nanometres were utilized to examine the bias of the chlorophyll concentration, Thus the higher phytoplankton absorption coefficient at 443, and backscattering coefficient for dissolved and detrital material stated the more phytoplankton biomass and higher suspended sediment concentration. The results found that the fish catch during El Niño is higher at 295572 metric tons compared to during La Niña which is 255783 metric tons. The El Niño event was found to have experienced an increase in catch of 29789 metric tons. This is due to the influence of the change in the mean value of the concentration in the study area of 0.31 mg-3 during La Niña compared to during El Niño 0.4 m mg-3. A decrease in the average value concentration of -0.09 mg-3 resulted in a decrease in the number of catches. In addition, the maximum value of chlorophyll concentration was also found to be high during El Niño which is 22 m mg-3 compared to during La Niña which is 18 m mg-3. The high distribution of chlorophyll-a is in the coastal areas of Sarawak, which explains why the coastal fish catches are higher than in the deep sea. It is concluded that the distribution of chlorophyll concentration is different during the occurrence of ENSO. This may result in different fishing rates in the study area. Remote sensing technology successfully explains why fish catches during El Niño are higher than during La Niña based on different chlorophyll dispersions. The provision of information in this space is very important to fishermen to reduce operating costs.