Marine ecosystem models for earth systems applications: The MarQUEST experience

The MarQUEST (Marine Biogeochemistry and Ecosystem Modelling Initiative in QUEST) project was established to develop improved descriptions of marine biogeochemistry, suited for the next generation of Earth system models. We review progress in these areas providing insight on the advances that have been made as well as identifying remaining key outstanding gaps for the development of the marine component of next generation Earth system models. The following issues are discussed and where appropriate results are presented; the choice of model structure, scaling processes from physiology to functional types, the ecosystem model sensitivity to changes in the physical environment, the role of the coastal ocean and new methods for the evaluation and comparison of ecosystem and biogeochemistry models. We make recommendations as to where future investment in marine ecosystem modelling should be focused, highlighting a generic software framework for model development, improved hydrodynamic models, and better parameterisation of new and existing models, reanalysis tools and ensemble simulations. The final challenge is to ensure that experimental/observational scientists are stakeholders in the models and vice versa.

[1]  M. Pascual,et al.  Ecological networks : Linking structure to dynamics in food webs , 2006 .

[2]  S. Doney,et al.  An intermediate complexity marine ecosystem model for the global domain , 2001 .

[3]  Thomas R. Anderson,et al.  Parameter optimisation techniques and the problem of underdetermination in marine biogeochemical models , 2010 .

[4]  J. Berry,et al.  A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species , 1980, Planta.

[5]  Mike Ashworth,et al.  Modelling the global coastal ocean , 2009, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[6]  S. Levin,et al.  Optimal nitrogen-to-phosphorus stoichiometry of phytoplankton , 2004, Nature.

[7]  Jason S. Link,et al.  Does food web theory work for marine ecosystems , 2002 .

[8]  Kevin J. Flynn,et al.  A mechanistic model for describing dynamic multi-nutrient, light, temperature interactions in phytoplankton , 2001 .

[9]  Nicholas R. Bates,et al.  Pelagic functional group modeling: Progress, challenges and prospects , 2006 .

[10]  Stéphane Blain,et al.  An ecosystem model of the global ocean including Fe, Si, P colimitations , 2003 .

[11]  C.R.E. de Oliveira,et al.  Three-dimensional unstructured mesh ocean modelling , 2005 .

[12]  Hugh L. MacIntyre,et al.  A dynamic model of photoadaptation in phytoplankton , 1996 .

[13]  Sebastiaan A.L.M. Kooijman,et al.  A biodiversity‐inspired approach to aquatic ecosystem modeling , 2007 .

[14]  Scott C. Doney,et al.  Assessment of skill and portability in regional marine biogeochemical models : Role of multiple planktonic groups , 2007 .

[15]  J. Ras,et al.  Validation of MERIS reflectance and chlorophyll during the BENCAL cruise October 2002: preliminary validation of new demonstration products for phytoplankton functional types and photosynthetic parameters , 2007 .

[16]  Jonathan A. Warrick,et al.  Dispersal scaling from the world's rivers , 2004 .

[17]  Trevor Platt,et al.  Remote sensing of phytoplankton functional types , 2008 .

[18]  M. Follows,et al.  Modeling and Prediction of Marine Microbial Populations in the Genomic era , 2007 .

[19]  Paul J. Somerfield,et al.  A multivariate approach to model skill assessment , 2009 .

[20]  B. Delille,et al.  Budgeting sinks and sources of CO2 in the coastal ocean: Diversity of ecosystems counts , 2005 .

[21]  Jennifer A. Dunne,et al.  The Network Structure of Food Webs , 2005 .

[22]  Scott C. Doney,et al.  Impact of circulation on export production, dissolved organic matter, and dissolved oxygen in the ocean: Results from Phase II of the Ocean Carbon‐cycle Model Intercomparison Project (OCMIP‐2) , 2007 .

[23]  R. Levins.  The strategy of model building in population biology , 1966 .

[24]  Daniele Iudicone,et al.  Mixed layer depth over the global ocean: An examination of profile data and a profile-based climatology , 2004 .

[25]  E. Fulton,et al.  Effect of complexity on marine ecosystem models , 2003 .

[26]  O. Francis,et al.  Modelling the global ocean tides: modern insights from FES2004 , 2006 .

[27]  I. Joint,et al.  Phytoplankton biomass and production in the southern North Sea , 1993 .

[28]  M. Pahlow.  Linking chlorophyll-nutrient dynamics to the Redfield N:C ratio with a model of optimal phytoplankton growth , 2005 .

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

[30]  John J. Walsh,et al.  Importance of continental margins in the marine biogeochemical cycling of carbon and nitrogen , 1991, Nature.

[31]  T. R. Anderson.  Progress in marine ecosystem modelling and the “unreasonable effectiveness of mathematics” , 2010 .

[32]  H. Claustre,et al.  Vertical distribution of phytoplankton communities in open ocean: An assessment based on surface chlorophyll , 2006 .

[33]  T. Platt,et al.  Discrimination of diatoms from other phytoplankton using ocean-colour data , 2004 .

[34]  Keith Haines,et al.  Salinity Assimilation Using S(T): Covariance Relationships , 2006 .

[35]  Thomas R. Anderson,et al.  Mechanisms controlling primary and new production in a global ecosystem model – Part I: Validation of the biological simulation , 2006 .

[36]  Richard J. Geider,et al.  A dynamic regulatory model of phytoplanktonic acclimation to light, nutrients, and temperature , 1998 .

[37]  Robert A. Armstrong,et al.  Optimality-based modeling of nitrogen allocation and photoacclimation in photosynthesis , 2006 .

[38]  Timothy P. Boyer,et al.  World Ocean Atlas 2005 Volume 1: Temperature [+DVD] , 2006 .

[39]  J. Aiken,et al.  Semianalytical model for the derivation of ocean color inherent optical properties: description, implementation, and performance assessment. , 2006, Applied optics.

[40]  Tsutomu Ikeda,et al.  Biogeochemical fluxes through mesozooplankton , 2006 .

[41]  T. Platt,et al.  An estimate of global primary production in the ocean from satellite radiometer data , 1995 .

[42]  Julian Icarus Allen,et al.  Quantifying uncertainty in high-resolution coupled hydrodynamic-ecosystem models , 2007 .

[43]  Richard J. Geider,et al.  New cell-based model of photosynthesis and photo-acclimation: accumulation and mobilisation of energy reserves in phytoplankton , 2009 .

[44]  J. Gattuso,et al.  CARBON AND CARBONATE METABOLISM IN COASTAL AQUATIC ECOSYSTEMS , 1998 .

[45]  D. Siegel,et al.  Inherent optical property inversion of ocean color spectra and its biogeochemical interpretation: 1. Time series from the Sargasso Sea , 1997 .

[46]  J. Kindle,et al.  Summary diagrams for coupled hydrodynamic-ecosystem model skill assessment , 2009 .

[47]  B. Shuter,et al.  A model of physiological adaptation in unicellular algae. , 1979, Journal of theoretical biology.

[48]  J. Milliman,et al.  Land-Ocean Interactions in the Coastal Zone: implementation plan , 1995 .

[49]  Robert V. O'Neill,et al.  IS IT TIME TO BURY THE ECOSYSTEM CONCEPT? (WITH FULL MILITARY HONORS, OF COURSE!)1 , 2001 .

[50]  M. Fasham,et al.  Modelling the interactions between ammonium and nitrate uptake in marine phytoplankton , 1997 .

[51]  K. McCann.  The diversity–stability debate , 2000, Nature.

[52]  Joanna Isobel House,et al.  Biosphere dynamics: challenges for Earth System Models. In C. J. Hawkesworth and R. S. J. Sparks (eds), The State of the Planet: Frontiers and Challenges in Geophysics. , 2004 .

[53]  S. Doney.  Major challenges confronting marine biogeochemical modeling , 1999 .

[54]  François-Marie Bréon,et al.  Remote sensing of phytoplankton groups in case 1 waters from global SeaWiFS imagery , 2005 .

[55]  Changsheng Chen,et al.  A model‐dye comparison experiment in the tidal mixing front zone on the southern flank of Georges Bank , 2008 .

[56]  K. Haines,et al.  Evaluation of the S(T) assimilation method with the Argo dataset , 2009 .

[57]  D. Chapman,et al.  A Simple Theory for the Fate of Buoyant Coastal Discharges , 1997 .

[58]  L. A. Anderson,et al.  Title Assessment of skill and portability in regional marine biogeochemical models : Role of multiple planktonic groups Permalink , 2007 .

[59]  R. Wollast,et al.  Ocean margin processes in global change. , 1991 .

[60]  J. Walsh,et al.  The 1983-1984 Shelf Edge Exchange Processes (SEEP)--I experiment: hypotheses and highlights , 1988 .

[61]  D. Noble,et al.  The future: putting Humpty-Dumpty together again. , 2001, Biochemical Society transactions.

[62]  H. Ducklow,et al.  A nitrogen-based model of plankton dynamics in the oceanic mixed layer , 1990 .

[63]  D. J. Franklin,et al.  Growth rates of six coccolithophorid strains as a function of temperature , 2008 .

[64]  C. Stow,et al.  Skill Assessment for Coupled Biological/Physical Models of Marine Systems. , 2009, Journal of marine systems : journal of the European Association of Marine Sciences and Techniques.

[65]  David Atkinson,et al.  Predicting marine phytoplankton maximum growth rates from temperature: Improving on the Eppley curve using quantile regression , 2008 .

[66]  Jonathan Sharples,et al.  Recipe for 1‐D Lagrangian particle tracking models in space‐varying diffusivity , 2004 .

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

[68]  J. Aiken,et al.  An inherent optical property approach to the estimation of size-specific photosynthetic rates in eastern boundary upwelling zones from satellite ocean colour: An initial assessment , 2009 .

[69]  G. Evensen,et al.  An Ensemble Kalman Filter with a complex marine ecosystem model: hindcasting phytoplankton in the Cretan Sea , 2003 .

[70]  G. Madec.  NEMO ocean engine , 2008 .

[71]  Jerry Blackford,et al.  Ecosystem dynamics at six contrasting sites: a generic modelling study , 2004 .

[72]  S. Watanabe,et al.  Is there a “continental shelf pump” for the absorption of atmospheric CO2? , 1999 .

[73]  J. G. Baretta-Bekker,et al.  An improved model of carbon and nutrient dynamics in the microbial food web in marine enclosures , 1998 .

[74]  Patrick M. Holligan,et al.  Phytoplankton distribution and survival in the thermocline , 2001 .

[75]  I. C. Prentice,et al.  Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model , 2003 .

[76]  Jim Aiken,et al.  An absorption model to determine phytoplankton size classes from satellite ocean colour , 2008 .

[77]  Thomas R. Anderson,et al.  Plankton functional type modelling : running before we can walk? , 2005 .

[78]  Taro Takahashi,et al.  Skill metrics for confronting global upper ocean ecosystem-biogeochemistry models against field and remote sensing data , 2009 .

[79]  H. Bryden,et al.  Thermohaline circulation at three key sections in the North Atlantic over 1985–2002 , 2005 .

[80]  E. Odum.  Fundamentals of ecology , 1972 .

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

[82]  Andrew J. Watson,et al.  Ecosystem dynamics based on plankton functional types for global ocean biogeochemistry models , 2005 .

[83]  Rosa Barciela,et al.  Ocean color data assimilation with material conservation forimproving model estimates of air-sea CO2 flux , 2008 .

[84]  Ricardo Torres,et al.  Sequential data assimilation in an upwelling influenced estuary , 2006 .

[85]  M. Huddleston,et al.  Quality control of ocean temperature and salinity profiles — Historical and real-time data , 2007 .

[86]  Hugh L. MacIntyre,et al.  A model of photosynthesis and photo‐protection based on reaction center damage and repair , 2008 .

[87]  Jim Aiken,et al.  An objective methodology for the classification of ecological pattern into biomes and provinces for the pelagic ocean , 2008 .

[88]  R. Arnone,et al.  Deriving inherent optical properties from water color: a multiband quasi-analytical algorithm for optically deep waters. , 2002, Applied optics.

[89]  Jonathan Sharples,et al.  Investigating the seasonal vertical structure of phytoplankton in shelf seas , 1999 .

[90]  Robert M May,et al.  Network structure and the biology of populations. , 2006, Trends in ecology & evolution.

[91]  L. Prieur,et al.  A three-component model of ocean colour and its application to remote sensing of phytoplankton pigments in coastal waters , 1989 .

[92]  G. Cadée,et al.  Phytoplankton in the Marsdiep at the end of the 20th century; 30 years monitoring biomass, primary production, and Phaeocystis blooms , 2002 .

[93]  Michael R. Landry,et al.  Phytoplankton growth, microzooplankton grazing, and carbon cycling in marine systems , 2004 .

[94]  Gurvan Madec,et al.  Definition of the interannual experiment ORCA025-B83, 1958-2007 , 2009 .

[95]  Thomas R. Anderson,et al.  Comparison of the emergent behavior of a complex ecosystem model in two ocean general circulation models , 2010 .

[96]  T. Kuroiwa,et al.  Genome analysis and its significance in four unicellular algae, Cyanidioshyzon merolae, Ostreococcus tauri, Chlamydomonas reinhardtii, and Thalassiosira pseudonana , 2008, Journal of Plant Research.

[97]  Kevin J. Flynn,et al.  Castles built on sand : dysfunctionality in plankton models and the inadequacy of dialogue between biologists and modellers , 2005 .

[98]  P. Ruardij,et al.  The European regional seas ecosystem model, a complex marine ecosystem model , 1995 .