scholarly journals Estimation of Size-Fractionated Primary Production from Satellite Ocean Colour in UK Shelf Seas

2018 ◽  
Vol 10 (9) ◽  
pp. 1389 ◽  
Author(s):  
Kieran Curran ◽  
Robert Brewin ◽  
Gavin Tilstone ◽  
Heather Bouman ◽  
Anna Hickman
Keyword(s):  
Primary Production ◽  
Ocean Model ◽  
Open Ocean ◽  
Photosynthetic Parameters ◽  
Ocean Colour ◽  
Chl A ◽  
In Situ Data ◽  
Shelf Seas ◽  
Shelf Sea

Satellite ocean-colour based models of size-fractionated primary production (PP) have been developed for the oceans on a global level. Uncertainties exist as to whether these models are accurate for temperate Shelf seas. In this paper, an existing ocean-colour based PP model is tuned using a large in situ database of size-fractionated measurements from the Celtic Sea and Western English Channel of chlorophyll-a (Chl a) and the photosynthetic parameters, the maximum photosynthetic rate ( P m B ) and light limited slope ( α B ). Estimates of size fractionated PP over an annual cycle in the UK shelf seas are compared with the original model that was parameterised using in situ data from the open ocean and a climatology of in situ PP from 2009 to 2015. The Shelf Sea model captured the seasonal patterns in size-fractionated PP for micro- and picophytoplankton, and generally performed better than the original open ocean model, except for nanophytoplankton PP which was over-estimated. The overestimation in PP is in part due to errors in the parameterisation of the biomass profile during summer, stratified conditions. Compared to the climatology of in situ data, the shelf sea model performed better when phytoplankton biomass was high, but overestimated PP at low Chl a.

scholarly journals Phytoplankton Phenology in the Coastal Zone of Cyprus, Based on Remote Sensing and In Situ Observations

2021 ◽  
Vol 14 (1) ◽  
pp. 12
Author(s):  
Monica Demetriou ◽  
Dionysios E. Raitsos ◽  
Antonia Kournopoulou ◽  
Manolis Mandalakis ◽  
Spyros Sfenthourakis ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Phytoplankton Biomass ◽  
Trophic Levels ◽  
Data Availability ◽  
Ocean Colour ◽  
Chl A ◽  
In Situ Data

Alterations in phytoplankton biomass, community structure and timing of their growth (phenology), are directly implicated in the carbon cycle and energy transfer to higher trophic levels of the marine food web. Due to the lack of long-term in situ datasets, there is very little information on phytoplankton seasonal succession in Cyprus (eastern Mediterranean Sea). On the other hand, satellite-derived measurements of ocean colour can only provide long-term time series of chlorophyll (an index of phytoplankton biomass) up to the first optical depth (surface waters). The coupling of both means of observations is essential for understanding phytoplankton dynamics and their response to environmental change. Here, we use 23 years of remotely sensed, regionally tuned ocean-colour observations, along with a unique time series of in situ phytoplankton pigment composition data, collected in coastal waters of Cyprus during 2016. The satellite observations show an initiation of phytoplankton growth period in November, a peak in February and termination in April, with an overall mean duration of ~4 months. An in-depth exploration of in situ total Chl-a concentration and phytoplankton pigments revealed that pico- and nano-plankton cells dominated the phytoplankton community. The growth peak in February was dominated by nanophytoplankton and potentially larger diatoms (pigments of 19’ hexanoyloxyfucoxanthin and fucoxanthin, respectively), in the 0–20 m layer. The highest total Chl-a concentration was recorded at a station off Akrotiri peninsula in the south, where strong coastal upwelling has been reported. Another station in the southern part, located next to a fish farm, showed a higher contribution of picophytoplankton during the most oligotrophic period (summer). Our results highlight the importance of using available in situ data coupled to ocean-colour remote sensing, for monitoring marine ecosystems in areas with limited in situ data availability.

scholarly journals VERTICAL DISTRIBUTION OF CHLOROPHYLL-A BASED ON NEURAL NETWORK

2010 ◽  
Vol 2 (-) ◽  
Author(s):  
TAKAHIRO OSAWA ◽  
CHAO FANG ZHAO ◽  
I WAYAN Nuarsa ◽  
I KETUT SWARDIKA ◽  
YASUHIRO SUGIMORI
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Vertical Distribution ◽  
Primary Production ◽  
Chlorophyll A ◽  
Ocean Color ◽  
Chl A ◽  
In Situ Data ◽  
Artificial Neural

An algorithm of estimating Vertical distribution of Chlorophyll-a (Chl-a) was evaluated based on Artificial Neural Networks (ANN) method in Hokkaido field in the northwest of Pacific Ocean. The algorithm applied to the data of SeaWiFS on OrbView-2 and AVHRR on NOAA off Hokkaido, has been applied on September 24, 1998 and September 28, 2001. Ocean color sensor provides the information of the photosynthetic pigment concentration for the upper 22% of the euphotic zone. In order to model a primary production in the water column derived from satellite, it is important to obtain the vertical profile of Chl-a distribution, because the maximum value of Chl-a concentration used to lie in the subsurface region. A shifted Gaussian model has been proposed to describe the variation of the chlorophyll-a (Chl-a) profile which consists of four parameters, i.e. background biomass (B0), maximum depth of Chl-a (zm), total biomass in the peak (h), and a measurement of the thickness or vertical scale of the peak (cr). However, these parameters are not easy to be determined directly from satellite data. Therefore, in the present study, an ANN methodology is used. Using in-situ data from 1974 to 1994 around Japan Islands, the above four parameters are calculated to derive the Chl-a concentration, sea surface temperature, mixed layer depth, latitude, longitude, and Julian days. The total of 6983 profiles of Chl-a and temperature are used for ANN. The correlation coefficients of these parameters are 0.79 (B0), 0.73 (h), 0.76 (cr) and 0.79 (zm) respectively. A site called A-linc off Hokkaido is used to evaluate Chl-a concentration in each depth. After comparing with in-situ data and ANN model, the results show good agreement relatively. Therefore, the ANN method is applicable and available tool to estimate primary production and fish resources from the space. Keywords : Ocean color, Chlorophyll-a (Chl-a), Vertical structure, Artificial Neural Networks (ANN).

scholarly journals Bromocarbons in the tropical coastal and open ocean atmosphere during the 2009 Prime Expedition Scientific Cruise (PESC-09)

2014 ◽  
Vol 14 (15) ◽  
pp. 8137-8148 ◽  
Author(s):  
M. S. Mohd Nadzir ◽  
S. M. Phang ◽  
M. R. Abas ◽  
N. Abdul Rahman ◽  
A. Abu Samah ◽  
...  
Keyword(s):  
Chlorophyll A ◽  
Statistical Tests ◽  
Open Ocean ◽  
Common Source ◽  
Sampling Point ◽  
Coastal Regions ◽  
Chl A ◽  
June July ◽  
Strait Of Malacca

Abstract. Atmospheric concentrations of very short-lived species (VSLS) bromocarbons, including CHBr3, CH2Br2, CHCl2Br, CHClBr2, and CH2BrCl, were measured in the Strait of Malacca and the South China and Sulu–Sulawesi seas during a two-month research cruise in June–July 2009. The highest bromocarbon concentrations were found in the Strait of Malacca, with smaller enhancements in coastal regions of northern Borneo. CHBr3 was the most abundant bromocarbon, ranging from 5.2 pmol mol−1 in the Strait of Malacca to 0.94 pmol mol−1 over the open ocean. Other bromocarbons showed lower concentrations, in the range of 0.8–1.3 pmol mol−1 for CH2Br2, 0.1–0.5 pmol mol−1 for CHCl2Br, and 0.1–0.4 pmol mol−1 for CHClBr2. There was no significant correlation between bromocarbons and in situ chlorophyll a, but positive correlations with both MODIS and SeaWiFS satellite chlorophyll a. Together, the short-lived bromocarbons contribute an average of 8.9 pmol mol−1 (range 5.2–21.4 pmol mol−1) to tropospheric bromine loading, which is similar to that found in previous studies from global sampling networks (Montzka et al., 2011). Statistical tests showed strong Spearman correlations between brominated compounds, suggesting a common source. Log–log plots of CHBr3/CH2Br2 versus CHBr2Cl/CH2Br2 show that both chemical reactions and dilution into the background atmosphere contribute to the composition of these halocarbons at each sampling point. We have used the correlation to make a crude estimate of the regional emissions of CHBr3 and to derive a value of 32 Gg yr−1 for the Southeast (SE) Asian region (10° N–20° S, 90–150° E). Finally, we note that satellite-derived chlorophyll a (chl a) products do not always agree well with in situ measurements, particularly in coastal regions of high turbidity, meaning that satellite chl a may not always be a good proxy for marine productivity.

scholarly journals Bromocarbons in the tropical coastal and open ocean atmosphere during the Prime Expedition Scientific Cruise 2009 (PESC 09)

2014 ◽  
Vol 14 (1) ◽  
pp. 953-984 ◽  
Author(s):  
M. S. Mohd Nadzir ◽  
S. M. Phang ◽  
M. R. Abas ◽  
N. Abdul Rahman ◽  
A. Abu Samah ◽  
...  
Keyword(s):  
Chlorophyll A ◽  
Statistical Tests ◽  
Open Ocean ◽  
Common Source ◽  
Sampling Point ◽  
The South ◽  
Coastal Regions ◽  
Chl A ◽  
Strait Of Malacca

Abstract. Atmospheric concentrations of very short-lived species (VSLS) bromocarbons, including CHBr3, CH2Br2, CHCl2Br, CHClBr2, CH2BrCl, were measured in the Strait of Malacca and the South China and Sulu-Sulawesi Seas during a two month research cruise in June/July 2009. The highest bromocarbon concentrations were found in the Strait of Malacca, with smaller enhancements in coastal regions of Northern Borneo. CHBr3 was the most abundant bromocarbon, ranging from 5.2 pmol mol−1 in the Strait of Malacca to 0.94 pmol mol−1 over the open ocean. Other bromocarbons showed lower concentrations, in the range of 0.8–1.3 pmol mol−1 for CH2Br2, 0.1–0.5 pmol mol−1 (CHCl2Br) and 0.1–0.4 pmol mol−1 (CHClBr2). There was no significant correlation between bromocarbons and in situ chlorophyll a. Together the short-lived bromocarbons contribute an average of 8.9 pmol mol−1 (range 5.2–21.4 pmol mol−1) to tropospheric bromine load, which is similar to that found in previous studies (Montzka et al., 2011). Statistical tests showed strong Spearman correlations amongst brominated compounds suggesting a common source. Log-log plots of CHBr3/CH2Br2 vs. CHBr2Cl/CH2Br2 show that both chemical reactions and dilution into the background atmosphere contribute to the composition of these halocarbons at each sampling point. We have used the correlation to make a crude estimate of the regional emissions of CHBr3 and derive a value of 63 Gg yr−1 for the South East (S.E.) Asian region (10° N–20° S, 90–150° E). Finally, we note that satellite-derived chlorophyll a (chl a) products do not always agree well with in situ measurements, particularly in coastal regions of high turbidity, meaning that satellite chl a may not always be a good proxy for marine productivity.

scholarly journals A Model-Based Assessment of Canopy-Scale Primary Productivity for the Baltic Sea Benthic Vegetation Using Environmental Variables and Spectral Indices

2021 ◽  
Vol 14 (1) ◽  
pp. 158
Author(s):  
Ele Vahtmäe ◽  
Jonne Kotta ◽  
Laura Argus ◽  
Mihkel Kotta ◽  
Ilmar Kotta ◽  
...  
Keyword(s):  
Primary Production ◽  
Aquatic Vegetation ◽  
Meteorological Data ◽  
Boosted Regression Trees ◽  
Model Description ◽  
Spectral Indices ◽  
Blue Band ◽  
Chl A ◽  
The Baltic

This study investigated the potential to predict primary production in benthic ecosystems using meteorological variables and spectral indices. In situ production experiments were carried out during the vegetation season of 2020, wherein the primary production and spectral reflectance of different communities of submerged aquatic vegetation (SAV) were measured and chlorophyll (Chl a+b) concentration was quantified in the laboratory. The reflectance of SAV was measured both in air and underwater. First, in situ reflectance spectra of each SAV class were used to calculate different spectral indices, and then the indices were correlated with Chl a+b. Indices using red and blue band combinations such as 650/450 and 650/480 nm explained the largest part of variability in Chl a+b for datasets measured in air and underwater. Subsequently, the best-performing indices were used in boosted regression trees (BRT) models, together with meteorological data to predict the community photosynthesis of different SAV classes. The predictive power (R2) of production models were very high, estimated at the range of 0.82-0.87. The variable contributing the most to the model description was SAV class, followed in most cases by the water temperature. Nevertheless, the inclusion of spectral indices significantly improved BRT models, often by over 20%, and surprisingly their contribution mostly exceeded that of photosynthetically active radiation.

Circulation patterns and eutrophication phenomena in the Thermaikos Gulf

2020 ◽  
Author(s):  
Yannis N. Krestenitis ◽  
Vasilis Kolovoyiannis ◽  
Yannis Androulidakis ◽  
Christos Makris ◽  
Vasilis Baltikas
Keyword(s):  
Water Column ◽  
Marine Ecosystem ◽  
Simulated Data ◽  
Aegean Sea ◽  
Ocean Model ◽  
Biological Parameters ◽  
Chl A ◽  
Physical Chemical ◽  
Circulation Patterns

<p>Thermaikos Gulf, located in the Northwestern Aegean Sea (Greece), is a marine ecosystem of major importance, not only environmentally (as an area of the deep water formation with contribution to the renewal of the North Aegean deep waters), but also due to the various socioeconomic activities associated with the area. Observational and simulated data are used to investigate the evolution of eutrophication events during the last two years in order to evaluate the current (2017-2019) quality state of the seawater in the Gulf. The quality of the marine environment of Thermaikos Gulf was appraised by measuring physical, chemical and biological parameters. Specific physical-chemical characteristics (temperature, salinity, density along with pH and dissolved oxygen) and biological parameters (chl-a and phytoplankton biomass) throughout the water column were evaluated by conducting in situ measurements during the sampling campaigns. Current fields, derived from a high-resolution 3-D ocean model, together with ADCP measurements, are used to describe the major circulation patterns, the river plume dynamics and the renewal pathways of the Gulf. The obtained results are discussed with regards to seasonal and spatial variability, and the water column stratification. Satellite ocean color data were also used to discuss the in-situ findings and confirm “Dirty” Sea and Red Tide phenomena, that were detected and analyzed based on the physical dynamics and especially the renewal patterns of the Gulf. Moreover, we compare these recent findings to respective observations from a previous period (1997 to 2007) to evaluate potential changes in the quality state of the Gulf with respect to meteorological and river discharge conditions.     </p>

scholarly journals A Prediction Model of Water In Situ Data Change under the Influence of Environmental Variables in Remote Sensing Validation

2020 ◽  
Vol 13 (1) ◽  
pp. 70
Author(s):  
Futai Xie ◽  
Zui Tao ◽  
Xiang Zhou ◽  
Tingting Lv ◽  
Jin Wang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Prediction Model ◽  
Environmental Variables ◽  
Time Window ◽  
Generalized Regression Neural Network ◽  
Chl A ◽  
Data Matching ◽  
In Situ Data ◽  
Relative Errors

Validation is an essential process to evaluate the quality of waterbody remote sensing products, and the reliability and effective application of the in situ data of waterbody parameters are an important part of validation. Based on the in situ data of chlorophyll-a (Chl-a), total suspended solids (TSS) and other environmental variables (EVs) measured at the fixed station in Taihu Lake, we attempt to develop a prediction model to determine whether the in situ measurement has enough representativeness for validating waterbody remote sensing products. Key EVs that affect the changes of Chl-a and TSS are firstly identified by using correlation analysis, which participate in modeling as variables. In addition, three multi-parameter modeling approaches are selected to simulate the daily changes of Chl-a and TSS under different EVs configurations. The results indicate that the highest prediction accuracy can be achieved through the generalized regression neural network (GRNN) based model. In the all-valid dataset, the testing absolute average relative errors (AEs) of GRNN-based Chl-a and TSS prediction model are 11.4% and 11.3%, respectively, and in the sunny-day dataset, the testing AEs are 8.6% and 8.2%, respectively. Meanwhile, the application example proves that the prediction model in this paper can be effectively used to screen the in situ data and determine the time window for satellite-ground data matching.

scholarly journals Bio-optical evidence for increasing Phaeocystis dominance in the Barents Sea

2020 ◽  
Vol 378 (2181) ◽  
pp. 20190357 ◽  
Author(s):  
A. Orkney ◽  
T. Platt ◽  
B. E. Narayanaswamy ◽  
I. Kostakis ◽  
H. A. Bouman
Keyword(s):  
Community Composition ◽  
Phytoplankton Community ◽  
Barents Sea ◽  
Community Change ◽  
Phytoplankton Production ◽  
Ocean Colour ◽  
Chl A ◽  
Phytoplankton Community Composition ◽  
Functional Types

Increasing contributions of prymnesiophytes such as Phaeocystis pouchetii and Emiliania huxleyi to Barents Sea (BS) phytoplankton production have been suggested based on in situ observations of phytoplankton community composition, but the scattered and discontinuous nature of these records confounds simple inference of community change or its relationship to salient environmental variables. However, provided that meaningful assessments of phytoplankton community composition can be inferred based on their optical characteristics, ocean-colour records offer a potential means to develop a synthesis between sporadic in situ observations. Existing remote-sensing algorithms to retrieve phytoplankton functional types based on chlorophyll-a ( chl-a ) concentration or indices of pigment packaging may, however, fail to distinguish Phaeocystis from other blooms of phytoplankton with high pigment packaging, such as diatoms. We develop a novel algorithm to distinguish major phytoplankton functional types in the BS and apply it to the MODIS-Aqua ocean-colour record, to study changes in the composition of BS phytoplankton blooms in July, between 2002 and 2018, creating time series of the spatial distribution and intensity of coccolithophore, diatom and Phaeocystis blooms. We confirm a north-eastward expansion in coccolithophore bloom distribution, identified in previous studies, and suggest an inferred increase in chl-a concentrations, reported by previous researchers, may be partly explained by increasing frequencies of Phaeocystis blooms. This article is part of the theme issue ‘The changing Arctic Ocean: consequences for biological communities, biogeochemical processes and ecosystem functioning’.

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