Ocean primary production calculated by spectral and broad-band models

Kyewalyanga, Margareth S.; Piatt, T.; Sathyendrath, S.

doi:10.3354/meps085171

Cited by 51 publications

(39 citation statements)

References 33 publications

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“…Comparisons of different models of primary production based on different assumptions regarding their spectral resolution have shown that the broad-band model of photosynthesis irradiance (P-E) gives realistic estimates of production (Kyewalyanga et al 1992, Campbell et al 2002. This model has a theoretically null bias for values of chl a around 2 mg m -3 , which is close to the average value found in the region.…”

Section: Methodssupporting

confidence: 49%

Generalised model of primary production in the southern Benguela upwelling system

Demarcq¹,

Richardson²,

Field³

2008

Mar. Ecol. Prog. Ser.

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We provide a proof-of-concept demonstration using a novel method for estimating depth-integrated distributions of chlorophyll from archives of data from ships, buoys or gliders combined with remotely sensed data of sea surface temperature (SST) and surface chlorophyll a (chl a) from satellites. Our area of application has contrasting hydrographic regimes, which include the dynamic southern Benguela upwelling system and the stratified waters of the Agulhas Bank, South Africa. The method involves using self-organising maps (SOMs), a type of artificial neural network, to identify 'typical' chl a profiles regardless of their statistical form, provided several of a similar shape have been found in the training set. These are arranged in a linear array, ranging from uniform profiles low in chl a to profiles with high surface or subsurface peaks. We then use generalised modelling to relate these characteristic profiles to remotely sensed surface features, viz. surface chl a and SST, as well as area, season, and water depth (a proxy for distance offshore). The model accounts for 87% of the variability in chl a profile and is used to predict the type of profile likely for each pixel in monthly remote sensing composites of SST and surface chl a and then to estimate integrated chl a and primary production with the aid of a light model. Primary production peaks in mid-summer, reaching 5 mgC m -2 d -1 locally, with an average over the whole area and all seasons of 1.4 mg C m -2 d -1. Seasonal variation is greatest in the southern part of the west coast, and lowest in the stratified southeast. Annual primary production for the southern Benguela region including the Agulhas Bank is ca. 156 million tC yr -1 . This is the most robust estimate of primary production in the Benguela system to date because it combines the spatial and temporal coverage provided by remote sensing with realistic vertical chl a profiles.KEY WORDS: Remote sensing · SeaWiFS · Ocean colour · Primary production · Self-organising maps · SOM · Generalised additive model · SOM · Vertical chlorophyll a profile Resale or republication not permitted without written consent of the publisherMar Ecol Prog Ser 354: [59][60][61][62][63][64][65][66][67][68][69][70][71][72][73][74] 2008 related to their intrinsic complexity (Campbell et al. 2002), few of them directly incorporate information on the vertical distribution of phytoplankton.Sensitivity analyses of primary production models show that the error in estimates of photosynthesis can be considerable when the chlorophyll maximum is near the surface. This is generally the case in coastal upwelling areas, where profiles are variable due to the wide range of oceanic conditions from active upwelling cells and filaments inshore to stratified waters offshore.Several methods have been developed for describing non-uniform biomass profiles in the oceans. However, these methods tend to produce profile categories that are fixed for large spatial and temporal scales and may not be representative of the smaller...

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Section: Methodssupporting

confidence: 49%

Generalised model of primary production in the southern Benguela upwelling system

Demarcq¹,

Richardson²,

Field³

2008

Mar. Ecol. Prog. Ser.

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“…This is the preferred calculation, and its reliability has been demonstrated . Applications of the various models have been compared Kyewalyanga et al, 1992). In the most detailed models, the angular distribution of the irradiance is included , the light field being separated into its direct and diffuse components.…”

Section: Estimating Daily Water-column Productionmentioning

confidence: 99%

Primary Production: Sensitivity to Surface Irradiance and Implications for Archiving Data

et al. 2017

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An equation is derived to express the sensitivity of daily, watercolumn production by phytoplankton in the ocean to variations in irradiance at the sea surface. Assuming no spectral effects, and a vertically uniform chlorophyll profile, the sensitivity is a function only of the dimensionless irradiance. Spectral effects can be accounted for as a function of the chlorophyll concentration. At the global scale, the relative reduction in daily production consequent on halving the surface irradiance (representing the expected scope for variation in surface irradiance under natural conditions) is found to be from 30 to 40%. Choice of data source for irradiance may incur a further systematic error of up to 15%. Given that local irradiance (the principal forcing for primary production) may vary from day to day, the issue of how to archive production data for the most generality is discussed and recommendations made in this regard.

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“…Thus, high ratios of a ph (440)/a ph (676) in the ocean might be due to absorption by PP pigments not contributing to photosynthesis. This will in turn influence the estimation of primary production by spectral models , Kyewalyanga et al 1992, and could also affect the estimation of chl a by remote sensing (based on an empirical relationship between chl a concentration and the ratio of reflectance in the blue and green regions of the spectrum). Morel (1997) showed that during a bloom of Synechococcus, chl a concentration calculated from reflectance values would have been overestimated by a factor of 3 if the usual algorithms for Case 1 waters were used.…”

Section: Effect Of Group Composition and Photoacclimation On The Optimentioning

confidence: 99%

Variability in pigment composition and optical characteristics of phytoplankton in the Labrador Sea and the Central North Atlantic

Lutz¹,

Sathyendranath²,

Head³

et al. 2003

Mar. Ecol. Prog. Ser.

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The relationships between photoadaptation, photoacclimation, cell size and the optical characteristics of the phytoplankton community were studied in 2 areas of the Atlantic Ocean. Pigment composition, absorption and fluorescence excitation spectra were analyzed for samples collected during 2 spring cruises: one in the Labrador Sea and the other in the Central North Atlantic. Photoadaptation (i.e. evolutionary adaptation of different species leading to acquisition of different pigment composition) was evident in the distribution of the main phytoplankton pigments in the area. Photoacclimation (i.e. temporary changes in pigment concentrations in a given species) was also noticeable in the changes in pigment composition and optical characteristics of phytoplankton with changes in depth. Size fractionation of samples from the depth of the chlorophyll a (chl a) maximum showed that, on average, chl a concentration and the values of absorption and fluorescence were dominated by the > 2 µm fraction of phytoplankton. Spectral variations in absorption and fluorescence excitation were, however, similar for the small and for the large size fractions. A distinct regional distribution of algal groups was observed, in which prokaryotic picophytoplankton (size class < 2 µm) dominated in oligotrophic subtropical regions and larger cells (size class > 2 µm) dominated in coastal areas and at higher latitudes. Some significant relationships were observed between the relative abundances of pigments characteristic of certain algal groups and optical properties of the sample. For example, the ratio of absorption at 440 nm to that at 676 nm was positively correlated with the ratio of zeaxanthin to chl a, indicating high abundance of picophytoplankton, especially the cyanobacteria Synechococcus and Prochlorococcus. The ratio of absorption at 555 nm to that at 623 nm was positively correlated with the abundance of phycoerythrin-containing Synechococcus. These results show that useful information about phytoplankton group composition and photoacclimation state can be retrieved from optical properties at a regional scale.

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Ocean primary production calculated by spectral and broad-band models

Cited by 51 publications

References 33 publications

Generalised model of primary production in the southern Benguela upwelling system

Generalised model of primary production in the southern Benguela upwelling system

Primary Production: Sensitivity to Surface Irradiance and Implications for Archiving Data

Variability in pigment composition and optical characteristics of phytoplankton in the Labrador Sea and the Central North Atlantic

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