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TRAIT TRADE OFFS AND CELL SIZE FOR OCEAN ECOSYSTEM MODELING Stephanie Dutkiewicz and Mick Follows Massachusetts Institut PowerPoint Presentation
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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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slide1

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

slide2

genetics

community

structure

physics,

nutrient

“Everything is everywhere, but, the environment selects”

Lourens Baas-Becking

slide3

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 …
slide4

TRAIT-BASED APPROACH TO ECOLOGY

(from Litchman+Klausmeier, 2008)

slide5

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)

slide6

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)

slide7

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 …
slide8

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

slide9

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)

slide10

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)

slide11

Oliver

Jahn

ECCO2 MODEL WITH ECOSYSTEM: DOMINANT FUNCTIONAL TYPE

red/yellow=opportunists, green/blue=gleaners; opacity=total biomass

slide12

ECCO2 MODEL WITH ECOSYSTEM: DOMINANT FUNCTIONAL TYPE

red/yellow=opportunists, green/blue=gleaners; opacity=total biomass

slide13

Trade-offs are the key!

(from Litchman+Klausmeier, 2008)

slide14

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)

slide15

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
slide16

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 …
slide17

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:

slide18

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

slide19

data from

Chrisholm et al (1992)

theoretical

curve (m-1/4)

Kempes et al

(in prep)

Chris’s work

slide20

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

slide21

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

slide22

CELL SIZE INFLUENCES:

  • Sinking speeds

Stokes Law suggest b=2

(from Smayda,1970)

Bigger phytoplankton sink quicker

slide23

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
slide24

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

slide25

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)

slide26

SO WHY ARE THERE ANY BIG CELLS:

  • Taxonomically related advantage

(from Irwin et al, 2006)

slide27

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)

slide28

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 …
slide29

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)
slide30

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

slide31

Maury et al, Prog. Ocean, 2007

Size-dependent physiology and metabolism, using the Dynamic Energy Budget theory (Kooijman, 2001)

slide32

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

slide34

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 …
slide35

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

slide36

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

slide37

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)

slide38

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)

slide39

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

slide40

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)

slide41

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

slide42

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)

slide43

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
slide46

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
slide47

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