Accuracy Assessment of Primary Production Models with and without Photoinhibition Using Ocean-Colour Climate Change Initiative Data in the North East Atlantic Ocean

The accuracy of three satellite models of primary production (PP) of varying complexity was assessed against 95 in situ 14C uptake measurements from the North East Atlantic Ocean (NEA). The models were run using the European Space Agency (ESA), Ocean Colour Climate Change Initiative (OC-CCI) version 3.0 data. The objectives of the study were to determine which is the most accurate PP model for the region in different provinces and seasons, what is the accuracy of the models using both high (daily) and low (eight day) temporal resolution OC-CCI data, and whether the performance of the models is improved by implementing a photoinhibition function? The Platt-Sathyendranath primary production model (PPPSM) was the most accurate over all NEA provinces and, specifically, in the Atlantic Arctic province (ARCT) and North Atlantic Drift (NADR) provinces. The implementation of a photoinhibition function in the PPPSM reduced its accuracy, especially at lower range PP. The Vertical Generalized Production Model-VGPM (PPVGPM) tended to over-estimate PP, especially in summer and in the NADR. The accuracy of PPVGPM improved with the implementation of a photoinhibition function in summer. The absorption model of primary production (PPAph), with and without photoinhibition, was the least accurate model for the NEA. Mapped images of each model showed that the PPVGPM was 150% higher in the NADR compared to PPPSM. In the North Atlantic Subtropical Gyre (NAST) province, PPAph was 355% higher than PPPSM, whereas PPVGPM was 215% higher. A sensitivity analysis indicated that chlorophyll-a (Chl a), or the absorption of phytoplankton, at 443 nm (aph (443)) caused the largest error in the estimation of PP, followed by the photosynthetic rate terms and then the irradiance functions used for each model.

[1]  T. Platt,et al.  Basin-scale estimates of oceanic primary production by remote sensing - The North Atlantic , 1991 .

[2]  E. Steemann Nielsen,et al.  The Use of Radio-active Carbon (C14) for Measuring Organic Production in the Sea , 1952 .

[3]  T. Smyth,et al.  Integration of radiative transfer into satellite models of ocean primary production , 2005 .

[4]  T. Smyth,et al.  Measured and remotely sensed estimates of primary production in the Atlantic Ocean from 1998 to 2005 , 2009 .

[5]  E. Laws,et al.  Nutrient‐ and light‐limited growth of Thalassiosira fluviatilis in continuous culture, with implications for phytoplankton growth in the ocean , 1980 .

[6]  André Morel,et al.  Validation of a spectral light‐photosynthesis model and use of the model in conjunction with remotely sensed pigment observations , 1992 .

[7]  Trevor Platt,et al.  Remote sensing of assimilation number for marine phytoplankton , 2014 .

[8]  F. D’Ortenzio,et al.  The colour of the Mediterranean Sea: Global versus regional bio-optical algorithms evaluation and implication for satellite chlorophyll estimates , 2007 .

[9]  A. Longhurst Seasonal cycles of pelagic production and consumption , 1995 .

[10]  Margareth N. Kyewalyanga,et al.  Seasonal variations in physiological parameters of phytoplankton across the North Atlantic , 1998 .

[11]  Paul G. Falkowski,et al.  A consumer's guide to phytoplankton primary productivity models , 1997 .

[12]  Michele Scardi,et al.  Challenges of modeling depth‐integrated marine primary productivity over multiple decades: A case study at BATS and HOT , 2010 .

[13]  Ankita Misra,et al.  Micro-phytoplankton photosynthesis, primary production and potential export production in the Atlantic Ocean , 2017 .

[14]  M. Perry,et al.  Estimating primary production at depth from remote sensing. , 1996, Applied optics.

[15]  Sang Heon Lee,et al.  Long-Term Pattern of Primary Productivity in the East/Japan Sea Based on Ocean Color Data Derived from MODIS-Aqua , 2015, Remote. Sens..

[16]  J. Ryther,et al.  Light Adaptation by Marine Phytoplankton1 , 1959 .

[17]  P. Pepin,et al.  Photosynthesis–irradiance parameters of marine phytoplankton: synthesis of a global data set , 2017 .

[18]  Laurent Bertino,et al.  Assessment and propagation of uncertainties in input terms through an ocean-color-based model of primary productivity , 2011 .

[19]  T Platt,et al.  Photo inhibition of photosynthesis in natural assemblages of marine phyto plankton , 1980 .

[20]  T. Smyth,et al.  Absorption-based algorithm of primary production for total and size-fractionated phytoplankton in coastal waters , 2014 .

[21]  Dale A. Kiefer,et al.  A simple, steady state description of phytoplankton growth based on absorption cross section and quantum efficiency1 , 1983 .

[22]  B. Franz,et al.  Examining the consistency of products derived from various ocean color sensors in open ocean (Case 1) waters in the perspective of a multi-sensor approach , 2007 .

[23]  B. Osborne,et al.  Light and Photosynthesis in Aquatic Ecosystems. , 1985 .

[24]  Marcel Babin,et al.  Relating phytoplankton photophysiological properties to community structure on large scales , 2008 .

[25]  T. T. Bannister Production equations in terms of chlorophyll concentration, quantum yield, and upper limit to production , 1974 .

[26]  Scott A. Freeman,et al.  An assessment of optical properties and primary production derived from remote sensing in the Southern Ocean (SO GasEx) , 2011 .

[27]  P. Falkowski,et al.  Nitrogen- and irradiance-dependent variations of the maximum quantum yield of carbon fixation in eutrophic, mesotrophic and oligotrophic marine systems , 1996 .

[28]  W. Balch,et al.  Factors affecting the estimate of primary production from space , 1994 .

[29]  H. Sosik Bio-optical modeling of primary production: consequences of variability in quantum yield and specific absorption , 1996 .

[30]  H. Dierssen,et al.  Bio‐optical properties and remote sensing ocean color algorithms for Antarctic Peninsula waters , 2000 .

[31]  Walker O. Smith,et al.  An evaluation of ocean color model estimates of marine primary productivity in coastal and pelagic regions across the globe , 2010 .

[32]  K. Baker,et al.  Correlation of primary production as measured aboard ship in Southern California Coastal waters and as estimated from satellite chlorophyll images , 1982 .

[33]  James B. Brown,et al.  The Remote Sensing of Ocean Primary Productivity: Use of a New Data Compilation to Test Satellite Algorithms , 1992 .

[34]  M. Kahru,et al.  Ocean Color Chlorophyll Algorithms for SEAWIFS , 1998 .

[35]  J. Aiken,et al.  Assessment of photosynthesis in a spring cyanobacterial bloom by use of a fast repetition rate fluorometer , 2001 .

[36]  K. Bencala,et al.  Phytoplankton productivity in relation to light intensity: A simple equation , 1987 .

[37]  Janet W. Campbell,et al.  Role of satellites in estimating primary productivity on the northwest Atlantic continental shelf , 1988 .

[38]  J.H.S. Blaxter,et al.  Biological oceanography , 1980, Nature.

[39]  Michele Scardi,et al.  A comparison of global estimates of marine primary production from ocean color , 2006 .

[40]  R. Kudela,et al.  Optimized multi-satellite merger of primary production estimates in the California Current using inherent optical properties , 2015 .

[41]  B. Kok,et al.  On the inhibition of photosynthesis by intense light. , 1956, Biochimica et biophysica acta.

[42]  John Marra,et al.  An Alternative Algorithm for the Calculation of Primary Productivity from Remote Sensing Data , 2003 .

[43]  T. Platt,et al.  Oceanic Primary Production: Estimation by Remote Sensing at Local and Regional Scales , 1988, Science.

[44]  Timothy J. Smyth,et al.  Inherent optical properties of the Irish Sea and their effect on satellite primary production algorithms , 2005 .

[45]  A. Dogliotti,et al.  Estimation of primary production in the southern Argentine continental shelf and shelf-break regions using field and remote sensing data , 2014 .

[46]  L. Seuront,et al.  Photoadaptation and primary production study in tidally mixed coastal waters using a Lagrangian model , 1998 .

[47]  M. Conkright,et al.  Global seasonal climatologies of ocean chlorophyll: Blending in situ and satellite data for the Coastal Zone Color Scanner era , 2001 .

[48]  P. Falkowski,et al.  Photosynthetic rates derived from satellite‐based chlorophyll concentration , 1997 .

[49]  R. Owen,et al.  Estimating ocean production from satellite-derived chlorophyll - Insights from the EASTROPAC data set , 1985 .

[50]  Trevor Platt,et al.  Photoinhibition of photosynthesis in natural assemblages of marine phytoplankton , 1980 .

[51]  K. Taylor Summarizing multiple aspects of model performance in a single diagram , 2001 .

[52]  V. I. Burenkov,et al.  Primary production and chlorophyll distributions in the subtropical and tropical waters of the Atlantic Ocean in the autumn of 2002 , 2007 .

[53]  Janet W. Campbell,et al.  Comparison of algorithms for estimating ocean primary production from surface chlorophyll, temperature, and irradiance , 2002 .

[54]  D. Antoine,et al.  Oceanic primary production: 2. Estimation at global scale from satellite (Coastal Zone Color Scanner) chlorophyll , 1996 .

[55]  P. Falkowski Ocean productivity from space , 1988, Nature.

[56]  L. Small,et al.  VARIATIONS IN PHOTOSYNTHETIC ASSIMILATION RATIOS IN NATURAL, MARINE PHYTOPLANKTON COMMUNITIES1 , 1965 .

[57]  M. Perry,et al.  Estimating oceanic primary productivity from ocean color remote sensing: A strategic assessment , 2015 .

[58]  D. Blondeau-Patissier,et al.  Comparison of new and primary production models using SeaWiFS data in contrasting hydrographic zones of the northern North Atlantic , 2015 .

[59]  André Morel,et al.  Available, usable, and stored radiant energy in relation to marine photosynthesis , 1978 .

[60]  Marcel Babin,et al.  Measured and modeled primary production in the northeast Atlantic (EUMELI JGOFS program): the impact of natural variations in photosynthetic parameters on model predictive skill , 1996 .

[61]  L. Prieur,et al.  Analysis of variations in ocean color1 , 1977 .

[62]  John H. Steele,et al.  ENVIRONMENTAL CONTROL OF PHOTOSYNTHESIS IN THE SEA , 1962 .

[63]  J. Johannessen,et al.  Satellite-derived multi-year trend in primary production in the Arctic Ocean , 2013 .

[64]  William J. Emery,et al.  Data Analysis Methods in Physical Oceanography , 1998 .

[65]  Michele Scardi,et al.  Assessing the Uncertainties of Model Estimates of Primary Productivity in the Tropical Pacific Ocean Revised , 2008 .