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TRAIT TRADE OFFS AND CELL SIZE FOR OCEAN ECOSYSTEM MODELING Stephanie Dutkiewicz and Mick Follows Massachusetts Institut

TRAIT TRADE OFFS AND CELL SIZE FOR OCEAN ECOSYSTEM MODELING Stephanie Dutkiewicz and Mick Follows Massachusetts Institute of Technology. Darwin Project People: Oliver Jahn Jason Bragg Fanny Monteiro Anna Hickman Ben Ward. Penny Chisholm Andrew Barton Chris Kempes Sophie Clayton

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TRAIT TRADE OFFS AND CELL SIZE FOR OCEAN ECOSYSTEM MODELING Stephanie Dutkiewicz and Mick Follows Massachusetts Institut

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  1. TRAIT TRADE OFFS AND CELL SIZE FOR OCEAN ECOSYSTEM MODELING Stephanie Dutkiewicz and Mick Follows Massachusetts Institute of Technology Darwin Project People: Oliver Jahn Jason Bragg Fanny Monteiro Anna Hickman Ben Ward Penny Chisholm Andrew Barton Chris Kempes Sophie Clayton Chris Hill

  2. genetics community structure physics, nutrient “Everything is everywhere, but, the environment selects” Lourens Baas-Becking

  3. TRAIT TRADE OFFS AND CELL SIZE FOR OCEAN ECOSYSTEM MODELING • OUTLINE OF TALK: • Trait-based ecology framework • Example from our ecosystem model: • Trade-offs are key! • Size as “master” trait – a brief review • Models with explicit size spectrum – a brief review • Preliminary results from MIT • self-organizing ecosystem model • Where next …

  4. TRAIT-BASED APPROACH TO ECOLOGY (from Litchman+Klausmeier, 2008)

  5. HOW DO THESE TRAITS TRADE OFF AGAINST EACH OTHER? • Competitive ability for different resources • - diatoms (Fe versus light) • - diazotrophs (N versus Fe) • Grazer resistance and nutrient acquisition • Maximum growth rate and nutrient acquisition: • - K versus r strategy (gleaners/opportunists) (from Litchman and Klausmeier)

  6. HOW DO THESE TRAITS TRADE OFF AGAINST EACH OTHER? • Maximum growth rate and nutrient acquisition: • - K versus r strategy (gleaners/opportunists) • K strategy (gleaner): optimize for low nutrient requirements • r strategy (opportunist): optimize for fast growth rate • Test this is a numerical simulation (see: MacArthur+Wilson, 1967 Kilham+Kilham, 1980)

  7. TRAIT TRADE OFFS AND CELL SIZE FOR OCEAN ECOSYSTEM MODELING • OUTLINE OF TALK: • Trait-based ecology framework • Example from our ecosystem model: • Trade-offs are key! • Size as “master” trait – a brief review • Models with explicit size spectrum – a brief review • Preliminary results from MIT • self-organizing ecosystem model • Where next …

  8. SELF ORGANIZING ECOSYSTEM MODEL (Follows et al, 2007) • initialize with many potentially viable organism types and interactions • parameters (rates) are chosen randomly within a reasonable range • allow the system to self-organize … genetics and physiology P1 Pi P P P Pj Pn Z2 Z2 Z1 Z1 N N competition predation selection D D physical and chemical environment

  9. SELF ORGANIZING ECOSYSTEM MODEL (Follows et al, 2007) • biogeochemical cycling of N, P, Si, Fe • 78 phytoplankton • 2 zooplankton classes choices and trade-offs on growth parameters low nutrient half saturation high max growth rate opportunists (r-strategy) gleaners (K-strategy) (Dutkiewicz et al, GBC – submitted http://ocean.mit.edu/~stephd)

  10. RESULTS FROM NUMERICAL SIMULATION: IMPORTANCEOR BIOGEOGRAPHY biomass of opportunists/total biomass 10th year annual 0-50m mean opportunists (fast growth matters) gleaner (low nutrient requirements matter) (from Dutkiewicz et al, GBC – submitted http://ocean.mit.edu/~stephd)

  11. Oliver Jahn ECCO2 MODEL WITH ECOSYSTEM: DOMINANT FUNCTIONAL TYPE red/yellow=opportunists, green/blue=gleaners; opacity=total biomass

  12. ECCO2 MODEL WITH ECOSYSTEM: DOMINANT FUNCTIONAL TYPE red/yellow=opportunists, green/blue=gleaners; opacity=total biomass

  13. Trade-offs are the key! (from Litchman+Klausmeier, 2008)

  14. How to model these in a consistent manner? Trade-offs are the key! (from Litchman+ Klausmeier, 2008) “Size is the most structuring dimension of ecological systems” (Maury et al, 2007)

  15. BENEFITS OF USING CELL SIZE AS A “MASTER” TRAIT: • consistent regulation of trade-offs (hopefully) • closer interface with spectral resolution of • remotely-sensed data • - e.g. particle back-scattering

  16. TRAIT TRADE OFFS AND CELL SIZE FOR OCEAN ECOSYSTEM MODELING • OUTLINE OF TALK: • Trait-based ecology framework • Example from our ecosystem model: • Trade-offs are key! • Size as “master” trait – a brief review • Models with explicit size spectrum – a brief review • Preliminary results from MIT • self-organizing ecosystem model • Where next …

  17. CELL SIZE INFLUENCES: • Metabolic rates and Maximum growth rates • Nutrient acquisition • Chl content and Light absorption • Sinking speeds • Maximum and minimum cell quota • and …. many of the above are related to cell size by, where S can be V,C,r:

  18. CELL SIZE INFLUENCES: • Metabolic rates and Maximum growth rates growth rate versus cell size • b=-0.25 appears to work • over very large range of • scales (Platt and Silvert, 1981; • West et al 2002) • but b has been found between • -0.15 and -0.3 but various studies • (Chisholm 1992) (from Tang 1995) Bigger phytoplankton grow slower

  19. data from Chrisholm et al (1992) theoretical curve (m-1/4) Kempes et al (in prep) Chris’s work

  20. CELL SIZE INFLUENCES: • Nutrient acquisition (from Chisholm, 1992) half saturation for nitrate versus cell volume (from Litchman et al, 2007) rate at which molecular diffusion supplies nutrients to the surface of the cell (Aksnes+Egge, 1991; Munk+Riley, 1952 ) Bigger phytoplankton require more nutrients

  21. CELL SIZE INFLUENCES: • Chl content and Light absorption “packaging effect” intercellular Chl a versus cell diameter absorption spectra normalized by Chl-a and phaeopigments (from Finkel et al, 2004) (from Ciotti et al, 2002) Bigger phytoplankton absorb light less efficiently

  22. CELL SIZE INFLUENCES: • Sinking speeds Stokes Law suggest b=2 (from Smayda,1970) Bigger phytoplankton sink quicker

  23. SO WHY ARE THERE ANY BIG CELLS: • Grazing Pressure - e.g. Thingstad et al 2005 • Susceptibility to Viruses - e.g. Raven et al 2006 • Respiration/Loses - e.g. Laws 1975 • Photo-inhibition – e.g. Raven et al 2006 • “Luxury quota” • Taxonomically related advantage

  24. SO WHY ARE THERE ANY BIG CELLS: • “Luxury quota” ANALYTICAL MODEL OFVERDY ET AL, MEPS, 2009 growth rate Scaling of size dependent parameters: X=aSb size

  25. SO WHY ARE THERE ANY BIG CELLS: • Taxonomically related advantage SIZE RELATIONSHIP NOT SO GROWTH CLEAR: (e.g. Chisholm 1992, Raven et al, 2006) especially for picoplankton e.g. (<1um) Prochloroccus 1 d-1 (4um) Thalassiosira spp. 3 d-1 (from Chisholm 1992)

  26. SO WHY ARE THERE ANY BIG CELLS: • Taxonomically related advantage (from Irwin et al, 2006)

  27. SO WHY ARE THERE ANY BIG CELLS: • Taxonomically related advantage Baird, 2008 b=-0.15 Irwin et al, 2006 b=-0.25 (from Irwin et al, 2006)

  28. TRAIT TRADE OFFS AND CELL SIZE FOR OCEAN ECOSYSTEM MODELING • OUTLINE OF TALK: • Trait-based ecology framework • Example from our ecosystem model: • Trade-offs are key! • Size as “master” trait – a brief review • Models with explicit size spectrum – a brief review • Preliminary results from MIT • self-organizing ecosystem model • Where next …

  29. NUMERICAL MODELING WITH SIZE AS TRAIT: • some examples • Baird and Sutherland (2007) • Maury et al. (2007) • Stock et al (2007) • Mei, Finkel and Irwin (in prep)

  30. Baird+Sutherland, J. Plankton Res (2007) Schematic of size-resolved biology model <1um 78mm (from Baird+Sutherland, 2007) Phytoplankton size determines: carbon content/growth/sinking/half saturation/swimming/predation

  31. Maury et al, Prog. Ocean, 2007 Size-dependent physiology and metabolism, using the Dynamic Energy Budget theory (Kooijman, 2001)

  32. Based on Droop’s Growth Model, 3 classes of plankton run in global 3-D MITgcm setup Phytoplankton size determines: cell quota/growth/uptake/half saturation/mortality

  33. currently adding size-dependent grazing

  34. TRAIT TRADE OFFS AND CELL SIZE FOR OCEAN ECOSYSTEM MODELING • OUTLINE OF TALK: • Trait-based ecology framework • Example from our ecosystem model: • Trade-offs are key! • Size as “master” trait – a brief review • Models with explicit size spectrum – a brief review • Preliminary results from MIT • self-organizing ecosystem model • Where next …

  35. SELF ORGANIZING ECOSYSTEM MODEL (Follows et al, 2007) modified Dutkiewicz et al 2009, Monteiro et al, Hickman et al decision tree on initialized phytoplankton 10’s to 1000’s phytoplankton “types”: choices and trade-offs on growth parameters T, I, nutrients opportunists gleaners

  36. SELF ORGANIZING ECOSYSTEM MODEL SIZE SPECTRUM VERSION decision tree on initialized phytoplankton SIZE SPECTRUM bigger smaller • 10’s to 1000’s phytoplankton “types”: • choices and trade-offs • size: • growth parameters, • nutrient half-saturation, • sinking rates • grazing • T, I, types of nutrients NH4, NO2, NO3 NH4, NO2, NO3 NH4, NO2 NH4 Si No-Si Pico-Eukaryote analogues Synechococcus analogues HL Prochl. analogues LL Prochl. analogues Diatom analogues Non-diatom eukaryote analogues

  37. SELF ORGANIZING ECOSYSTEM MODEL SIZE SPECTRUM VERSION “a” has taxanomic differences (following Irwin et al, 2006) (Irwin et al, 2006) P – Prochloroccus S – Synochcoccus A – diazotroph C – coccolithophers F - dinoflagellates D – diatoms (Smayda, 1970) cell diameter (um)

  38. SELF ORGANIZING ECOSYSTEM MODEL SIZE SPECTRUM VERSION SIZE DEPENDENT GRAZING (following Baird+Sutherland 2007) grazing rate min predator-prey ratio: 3.0 max predator-prey ratio: 22.6 (parameters from Hansen et al 1994,1997)

  39. SELF ORGANIZING ECOSYSTEM MODEL SIZE SPECTRUM VERSION 1-D SIMULATION (S. Atlantic subtropical gyre) green: <1micon cyan: 1-2 microns blue: 2-3 microns depth(m) (100 plankton types, no temp, light or grazing differences in this version) phytoplankton biomass nitrate

  40. SELF ORGANIZING ECOSYSTEM MODEL SIZE SPECTRUM VERSION 1-D SIMULATION (S. Atlantic subtropical gyre) green: <1micon cyan: 1-2 microns blue: 2-3 microns (100 plankton types, no temp, light or grazing differences in this version)

  41. SELF ORGANIZING ECOSYSTEM MODEL SIZE SPECTRUM VERSION 1-D SIMULATION (S. Atlantic subtropical gyre) green: <1micon cyan: 1-2 microns blue: 2-3 microns depth(m) (100 plankton types, no temp, light or grazing differences in this version) phytoplankton biomass nitrate

  42. SELF ORGANIZING ECOSYSTEM MODEL SIZE SPECTRUM VERSION 3-D SIMULATION: PRELIMINARY RESULTS total biomass (uM) (78 plankton types, no temp, light in this version) biomass weighted cell diameter (um) growth rate (1/d) nitrate (uM) cell diameter (um)

  43. WHERE WE ARE GOING: • continuous size spectrum determining • many of the rates/parameters • quota based • pigment specific light absorption • (with Anna Hickman, see poster) • explicit radiative transfer model • (with Watson Gregg) • run in the eddy-permitting ECCO2 framework

  44. ECCO2 with 78-phytoplankton self-organizing model Oliver Jahn

  45. ECCO2 with 78-phytoplankton self-organizing model Oliver Jahn

  46. WHERE WE ARE GOING: • continuous size spectrum determining • many of the rates/parameters • quota based • pigment specific light absorption (see poster) • explicit radiative transfer model • run in the eddy-permitting ECCO2 framework

  47. ADDITIONAL OF PIGMENT SPECIFIC ABSORPTION SPECTRA SELF ORGANIZING ECOSYSTEM MODEL modified Hickman et al decision tree on initialized phytoplankton Large Small from absorption spectra a(l)* = m . a(l)* NH4, NO2, NO3 NH4, NO2, NO3 NH4, NO2 NH4 10’s to 1000’s phytoplankton “types”: choices and trade-offs on growth parameters T, I, nutrients Si No-Si Pico-Eukaryote analogues Synechococcus analogues HL Prochl. analogues LL Prochl. analogues Diatom analogues Non-diatom eukaryote analogues see poster

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