Validation of a Primary Production Algorithm of Vertically Generalized Production Model Derived from Multi-Satellite Data around the Waters of Taiwan

Basin-scale sampling for high frequency oceanic primary production (PP) is available from satellites and must achieve a strong match-up with in situ observations. This study evaluated a regionally high-resolution satellite-derived PP using a vertically generalized production model (VGPM) with in situ PP. The aim was to compare the root mean square difference (RMSD) and relative percent bias (Bias) in different water masses around Taiwan. Determined using light–dark bottle methods, the spatial distribution of VGPM derived from different Chl-a data of MODIS Aqua (PPA), MODIS Terra (PPT), and averaged MODIS Aqua and Terra (PPA&T) exhibited similar seasonal patterns with in situ PP. The three types of satellite-derived PPs were linearly correlated with in situ PPs, the coefficients of which were higher throughout the year in PPA&T (r2 = 0.61) than in PPA (r2 = 0.42) and PPT (r2 = 0.38), respectively. The seasonal RMSR and bias for the satellite-derived PPs were in the range of 0.03 to 0.09 and −0.14 to −0.39, respectively, which suggests the PPA&T produces slightly more accurate PP measurements than PPA and PPT. On the basis of environmental conditions, the subareas were further divided into China Coast water, Taiwan Strait water, Northeastern upwelling water, and Kuroshio water. The VPGM PP in the four subareas displayed similar features to Chl-a variations, with the highest PP in the China Coast water and lowest PP in the Kuroshio water. The RMSD was higher in the Kuroshio water with an almost negative bias. The PPA exhibited significant correlations with in situ PP in the subareas; however, the sampling locations were insufficient to yield significant results in the China Coast water.

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Photosynthesis-irradiance parameters of marine phytoplankton: synthesis of a global data set

10.5194/essd-2017-40 ◽

2017 ◽

Author(s):

Heather A. Bouman ◽

Trevor Platt ◽

Martina Doblin ◽

Francisco G. Figueiras ◽

Kristinn Gudmudsson ◽

...

Keyword(s):

Primary Production ◽

Broad Band ◽

Marine Phytoplankton ◽

Production Model ◽

Initial Slope ◽

Model Parameters ◽

Data Set ◽

Spatial Coverage ◽

Basin Scale ◽

Marine Primary Production

Abstract. The photosynthetic performance of marine phytoplankton varies in response to a variety of factors, environmental and taxonomic. One of the aims of the MArine primary Production: model Parameters from Space (MAPPS) project of the European Space Agency is to assemble a global database of photosynthesis-irradiance (P-E) parameters from a range of oceanographic regimes as an aid to examining the basin-scale variability in the photophysiological response of marine phytoplankton and to use this information to improve the assignment of P-E parameters in the estimation of global marine primary production using satellite data. The MAPPS P-E Database, which consists of over 5000 P-E experiments, provides information on the spatio-temporal variability in the two P-E parameters (the assimilation number, PmB, and the initial slope, αB, where the superscripts B indicate normalisation to concentration of chlorophyll) that are fundamental inputs for models (satellite-based and otherwise) of marine primary production that use chlorophyll as the state variable. Quality-control measures consisted of removing samples with abnormally-high parameter values and flags were added to denote whether the spectral quality of the incubator lamp was used to calculate a broad-band value of αB. The MAPPS database provides a photophysiological dataset that is unprecedented in number of observations and in spatial coverage. The database would be useful to a variety of research communities, including marine ecologists, biogeochemical modellers, remote-sensing scientists and algal physiologists. The compiled data are available at https://doi.org/10.1594/PANGAEA.874087 (Bouman et al., 2017).

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

Remote Sensing ◽

10.3390/rs14010158 ◽

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.

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

Remote Sensing ◽

10.3390/rs10091389 ◽

2018 ◽

Vol 10 (9) ◽

pp. 1389 ◽

Cited By ~ 1

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.

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Modelled estimates of spatial variability of iron stress in the Atlantic sector of the Southern Ocean

10.5194/bg-2017-74 ◽

2017 ◽

Author(s):

Thomas J. Ryan-Keogh ◽

Sandy J. Thomalla ◽

Thato N. Mtshali ◽

Hazel Little

Keyword(s):

Southern Ocean ◽

Primary Production ◽

Production Model ◽

Photosynthetic Parameters ◽

Atlantic Sector ◽

Mean Values ◽

Chl A ◽

Biogeochemical Models ◽

The Absolute ◽

Iron Addition

Abstract. The Atlantic sector of the Southern Ocean is characterized by markedly different frontal zones with specific seasonal and sub-seasonal dynamics. Demonstrated here is the effect of iron on the potential maximum productivity rates of the phytoplankton community. A series of iron addition productivity versus irradiance (PE) experiments utilising a unique experimental design that allowed for 24 hour incubations were performed within the austral summer of 2015/16. The addition of iron can result in the doubling of the photosynthetic parameters αB and PBmax, with subsequent changes in Ek. Mean values for each parameter under iron replete conditions were 1.46 ± 0.55 (μg (μg Chl a)−1 h−1 (μM photons m−2 s−1)−1), 72.55 ± 27.97 (μg (μg Chl a)−1 h−1) and 50.84 ± 11.89 (μM photons m−2 s−1); whereas mean values under the control conditions were 1.25 ± 0.92 (μg (μg Chl a)−1 h−1 (μM photons m−2 s−1)−1), 62.44 ± 36.96 (μg (μg Chl a)−1 h−1) and 55.81 ± 19.60 (μM photons m−2 s−1). There were no clear spatial patterns in either the absolute values or the absolute differences between the treatments at the experimental locations. When these parameters are integrated into a standard depth-integrated primary production model across a latitudinal transect, the effect of iron addition shows higher levels of primary production south of 50° S, with very little difference observed in the sub-Antarctic and Polar Frontal zone. These results emphasize the need for better parameterisation of photosynthetic parameters in biogeochemical models around sensitivities in their response to iron supply. Future biogeochemical models will need to consider the combined and individual effects of iron and light to better resolve the natural background in primary production and predict its response under a changing climate.

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Comparison of Primary Production Using in situ and Satellite-Derived Values at the SEATS Station in the South China Sea

Frontiers in Marine Science ◽

10.3389/fmars.2021.747763 ◽

2021 ◽

Vol 8 ◽

Author(s):

Yung-Yen Shih ◽

Fuh-Kwo Shiah ◽

Chao-Chen Lai ◽

Wen-Chen Chou ◽

Jen-Hua Tai ◽

...

Keyword(s):

Primary Production ◽

Carbon Fixation ◽

Negative Relationship ◽

Euphotic Zone ◽

Production Model ◽

Global Ocean ◽

The South ◽

Fixation Rate ◽

Zone Depth

Satellite-based observations of primary production (PP) are broadly used to assess carbon fixation rate of phytoplankton in the global ocean with small spatiotemporal limitations. However, the remote sensing can only reach the ocean surface, the assumption of a PP vertically exponential decrease with increasing depth from the surface to the bottom of euphotic zone may cause a substantial and potential discrepancy between in situ measurements and satellite-based observations of PP. This study compared euphotic zone integrated PP derived from measurements based on ship-based in situ incubation (i.e., PPin situ) and those derived from the satellite-based vertically generalized production model (VGPM; PPVGPM) for the period 2003∼2016 at the South East Asian Time-series Study (SEATS) station. PP values obtained during the NE-monsoon (NEM: Nov∼Mar; PPin situ = 323 ± 134; PPVGPM = 443 ± 142 mg-C m–2 d–1) were ∼2-fold higher than those recorded during the SW-monsoon (SWM: Apr∼Oct; PPin situ = 159 ± 58; PPVGPM = 250 ± 36 mg-C m–2 d–1), regardless of the method used for derivation. The main reason for the higher PP values during the NEM appears to have been a greater abundance of inorganic nutrients were made available by vertical advection. Note that on average, PPin situ estimates were ∼50% lower than PPVGPM estimates, regardless of the monsoon. These discrepancies can be mainly attributed to differences from the euphotic zone depth between satellite-based and in situ measurements. The significantly negative relationship between PP measurements obtained in situ and sea surface temperatures observed throughout this study demonstrates that both methods are effective indicators in estimating PP. Overall, our PPin situ analysis indicates that a warming climate is unfavorable for primary production in low-latitude open ocean ecosystems.

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Preliminary Investigation on Phytoplankton Dynamics and Primary Production Models in an Oligotrophic Lake from Remote Sensing Measurements

Sensors ◽

10.3390/s21155072 ◽

2021 ◽

Vol 21 (15) ◽

pp. 5072

Author(s):

Ilaria Cesana ◽

Mariano Bresciani ◽

Sergio Cogliati ◽

Claudia Giardino ◽

Remika Gupana ◽

...

Keyword(s):

Remote Sensing ◽

Primary Production ◽

Preliminary Investigation ◽

Fluorescence Emission ◽

Phytoplankton Primary Production ◽

Chl A ◽

Production Models ◽

Solar Noon ◽

Lake Waters

The aim of this study is to test a series of methods relying on hyperspectral measurements to characterize phytoplankton in clear lake waters. The phytoplankton temporal evolutions were analyzed exploiting remote sensed indices and metrics linked to the amount of light reaching the target (EPAR), the chlorophyll-a concentration ([Chl-a]OC4) and the fluorescence emission proxy. The latter one evaluated by an adapted version of the Fluorescence Line Height algorithm (FFLH). A peculiar trend was observed around the solar noon during the clear sky days. It is characterized by a drop of the FFLH metric and the [Chl-a]OC4 index. In addition to remote sensed parameters, water samples were also collected and analyzed to characterize the water body and to evaluate the in-situ fluorescence (FF) and absorbed light (FA). The relations between the remote sensed quantities and the in-situ values were employed to develop and test several phytoplankton primary production (PP) models. Promising results were achieved replacing the FA by the EPAR or FFLH in the equation evaluating a PP proxy (R2 > 0.65). This study represents a preliminary outcome supporting the PP monitoring in inland waters by means of remote sensing-based indices and fluorescence metrics.

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CMEMS Primary production from satellite remote sensing: spatial and temporal evolution and comparison with other products

10.5194/egusphere-egu2020-21903 ◽

2020 ◽

Author(s):

Marine Bretagnon ◽

Philippe Garnesson ◽

Antoine Mangin

Keyword(s):

Primary Production ◽

Carbon Sink ◽

Global Scale ◽

Trophic Levels ◽

Economic Resources ◽

In Situ Data ◽

Basin Scale ◽

Carbon Pump ◽

Satellite Estimate

Half of the global primary production is produced in the ocean by phytoplankton and the reaction of photosynthesis. For the marine environment, primary production is at the basis for the food web, by the supply of energy for higher trophic levels. Monitor primary production appears therefore to be a guideline to reach sustainable fisheries. In addition to its role on the trophic web, primary production is also important for its role on CO2 fluxes. Indeed, while phytoplankton creates matter from nutrients and CO2. The produced matter can be grazed by higher trophic levels or sink towards sediment. Amount of carbon sequestrated and exported out of the productive layer give some clues efficiencies of the oceanic biological carbon pump. Primary production is therefore important not only for economic resources, but also for climatic studies, to investigate if the ocean is a carbon sink or sources.A strategy of algorithm validation / inter-comparison was used as part as the CMEMS project to identify most accurate primary production algorithm among the most used in the literature.Primary production validation is based on the commonly used comparison with in situ data, as well as the frequency and the intensity of the annual bloom in different basin. Inter-comparison with model were performed at the basin scale of the Mediterranean Sea to assess the robustness and the consistency of different type of estimates.Satellite estimate of primary production, as proposed by CMEMS, give now access to an archive of 21 years for user community, to investigate evolution of primary production at the global scale or in specific basin.&#160;

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VERTICAL DISTRIBUTION OF CHLOROPHYLL-A BASED ON NEURAL NETWORK

International Journal of Remote Sensing and Earth Sciences (IJReSES) ◽

10.30536/j.ijreses.2005.v2.a1353 ◽

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).

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Photosynthesis–irradiance parameters of marine phytoplankton: synthesis of a global data set

Earth System Science Data ◽

10.5194/essd-10-251-2018 ◽

2018 ◽

Vol 10 (1) ◽

pp. 251-266 ◽

Cited By ~ 24

Author(s):

Heather A. Bouman ◽

Trevor Platt ◽

Martina Doblin ◽

Francisco G. Figueiras ◽

Kristinn Gudmundsson ◽

...

Keyword(s):

Primary Production ◽

Broad Band ◽

Marine Phytoplankton ◽

Production Model ◽

Initial Slope ◽

Model Parameters ◽

Data Set ◽

Spatial Coverage ◽

Basin Scale ◽

Marine Primary Production

Abstract. The photosynthetic performance of marine phytoplankton varies in response to a variety of factors, environmental and taxonomic. One of the aims of the MArine primary Production: model Parameters from Space (MAPPS) project of the European Space Agency is to assemble a global database of photosynthesis–irradiance (P-E) parameters from a range of oceanographic regimes as an aid to examining the basin-scale variability in the photophysiological response of marine phytoplankton and to use this information to improve the assignment of P-E parameters in the estimation of global marine primary production using satellite data. The MAPPS P-E database, which consists of over 5000 P-E experiments, provides information on the spatio-temporal variability in the two P-E parameters (the assimilation number, PmB, and the initial slope, αB, where the superscripts B indicate normalisation to concentration of chlorophyll) that are fundamental inputs for models (satellite-based and otherwise) of marine primary production that use chlorophyll as the state variable. Quality-control measures consisted of removing samples with abnormally high parameter values and flags were added to denote whether the spectral quality of the incubator lamp was used to calculate a broad-band value of αB. The MAPPS database provides a photophysiological data set that is unprecedented in number of observations and in spatial coverage. The database will be useful to a variety of research communities, including marine ecologists, biogeochemical modellers, remote-sensing scientists and algal physiologists. The compiled data are available at https://doi.org/10.1594/PANGAEA.874087 (Bouman et al., 2017).

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Dynamics of Lake Michigan Phytoplankton: Primary Production and Growth

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/f87-062 ◽

1987 ◽

Vol 44 (3) ◽

pp. 499-508 ◽

Cited By ~ 72

Author(s):

Gary L Fahnenstiel ◽

Donald Scavia

Keyword(s):

Primary Production ◽

Thermal Stratification ◽

Lake Michigan ◽

Production Model ◽

Daily Production ◽

Model Estimate ◽

Phytoplankton Primary Production ◽

Net Production ◽

Assimilation Number

Primary production was measured with the 14C technique during May through July–August 1982–84. 14C experiments varied from short-term incubations (1–2 h) in a photosynthesis–irradiance (P–I) chamber to 24-h in situ incubations. The maximum assimilation number from six P–I experiments during thermal stratification averaged 2.1 mg C∙mg Chl−1∙h−1 which agreed well with estimates from the 1970s. Chlorophyll-corrected P–I curves were combined with incident irradiation, chlorophyll concentrations, and extinction coefficients to estimate daily production (model estimate). Summer average integral production estimates in 1983 and 1984 were 615–630 mg C∙m−2∙d−1. Approximately 50% of summer primary production occurred below the epilimnion. Daily model production estimates were higher than 24-h in situ estimates at light intensities above Ik, the light saturation parameter, and similar at intensities below Ik. Comparisons of production estimates converted to growth rates suggest that 24-h in situ estimates provide a measure close to net production whereas model estimates provide a measure greater than net production. Summer epilimnetic growth rate estimates were low (range 0.06–0.60∙d−1), reflecting the limited availability of phosphorus.

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