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Role of zooplankton in marine ecosystemsand modelling perspectivesg p p

Tom AndersonNational Oceanography Centre, Southampton, UK

ASP Researcher Workshop NCARASP Researcher Workshop, NCARAug 6-10th 2013

Role of zooplankton in marine ecosystemsp yand modelling perspectives

Introduction: bottom up (BU) vs top down (TD) control of marine ecosystems

Zooplankton control of phytoplankton blooms Zooplankton control of phytoplankton blooms

Zooplankton control of plankton community structure

Modelling zooplankton: state-of-the-art

Role of zooplankton in marine ecosystemsRole of zooplankton in marine ecosystemsand modelling perspectives





evapotranspiration

NPPtree PFT2

fluxesCH2O

NPPtree PFT1

grasses

NPP

soilrespirationdecomposition

precipitation

soil

pp

uptakeuptake

Sea surface temperature Chlorophyllp p y

http://earthobservatory.nasa.gov

16 most abundant organized by “functional group”

Prochlorococcus Prochlorococcus analogsanalogs

SynechococcusSynechococcus & small eukaryotes& small eukaryotes

DiatomsDiatoms.

Other large eukaryotesOther large eukaryotes

Plant animal warsPlant-animal wars

spinesspinescoloniestoxinstoxins

Daksalov (2002): “Overfishing drives a trophic cascade in the Black sea”( ) g p

Change in dominance across the pelagic food chain since the depletion oftop-predators after 1970: model results

trophic level before 1970 after 1970

top predators

planktivores

resource limited

consumer controlled

-

resource limitedp

zooplankton

phytoplankton

resource limited

consumer controlled

consumer controlled

resource limitedphytoplankton consumer controlled resource limited

Mar. Ecol. Prog. Ser. 225, 53-63

Green world hypothesis

The “Biological Pump”The “Biological Pump”The Biological PumpThe Biological Pump

Export

No simple relationship with primary production

Much export occurs during bloom events

Is related to ecosystem structure

Active flux

Bianchi et al. (2013)

Detritus turnover

A d d T (2010)Anderson and Tang (2010)

Plankton stocks are a balance of opposing forces :accumulation and degradation, consumption and regenerationaccumulation and degradation, consumption and regeneration

(Riley, 1941)

Pgrowth grazing Gordon Riley

Ph (1 k z )L LpI0

= (Ph – R – G)PdPdt

Ph = (1-e-k.zeu)LNLVpI0kzeu

TR = R0erT

photosynthesis grazingG = gZ

Riley (1946)

respiration

Riley (1946)

Georges Bank simulationg

P ZP, Z

monthmonth

maximum growth and grazing rates

MEDUSA

0.5 d-1

2.0 d-1

1 7 d 11.7 d-11.6 d-1

Yool et al. (2010, 2013)

Annual cycle of mixed layer depthAnnual cycle of mixed layer depth

India 60N 20W

KERFIX 50S 68E

60N 20W planktondiatoms mesozooplankton

60N 20W planktonnon-diatoms microzooplankton

plankton biomassl N

m-3

mm

ol

growth60N 20W plankton

g

grazingd-1

non-diatoms diatoms

60N 20W planktondiatoms mesozooplankton

no grazing planktonnon-diatoms microzooplankton

plankton biomassl N

m-3

mm

ol

India 60N 20W

KERFIX 50S 68E

Kerfix planktondiatoms mesozooplankton

Kerfix planktonnon-diatoms microzooplankton

plankton biomassl N

m-3

mm

ol

growth

Kerfix planktong

grazingd-1

non-diatoms diatoms

Kerfix planktondiatoms mesozooplankton

Kerfix,no grazing

planktonnon-diatoms microzooplankton

plankton biomassl N

m-3

mm

ol

grazingplankton

no grazing

grazing

non diatoms it tnon-diatoms nitrate

ol N

m-3

mm

o

PlankTOM5

li h hmixed

coccolithophores diatomsphytoplankton

dissolveddissolvedorganic matter PO4 Fe SiO3

microzooplankton mesozooplanktonsmalldetritus

largedetritus

1 0

0.8

1.0 BS

IvMM

ntak

e, d

-1

0 4

0.6MM

in

0.2

0.4

0 1 2 3 40.0

prey densityprey density

diatoms mg chl m-3diatoms, mg chl m

March MayMM March-May B

0 60.6

0

S IV

(Anderson at al., 2010)

Rosie Fisher (yesterday):

“The juxtaposition of numerous complex models createsTh i l f h l i l b h i ”The potential for pathological behaviour”

coccolithophores mg chl m-3coccolithophores, mg chl m


0.4

0

S IV


microzooplankton mmol C m-3microzooplankton, mmol C m


0.8

0

S IV


mesozooplankton mmol C m-3mesozooplankton, mmol C m


5

0

S IV


Primary production g C m-2 d-1Primary production, g C m d


0.5

0

S IV


export g C m -2 d-1export g C m d


0.2

0

S IV


Trophic transferingested

substrates

assimilationcosts

pelletsassimilation CO2

assimilated digestionsubstrates

moultmaintenance CO2 PO4

basal metabolism

maintenance

remainingsubstrates

protein turnover

t f

newbiomassproduction CO2

release

costs ofgrowth

growth (incl. reproduction)

excess C,P CO2 orDOC

PO4 orDOP

Nit C b

pelletsCO2,NH4

Anderson & Hessen 95 ERSEM Anderson & Hessen 95 ERSEM

Nitrogen Carbon growth

1

0

frac

tion

Pahlow 03 Pahlow 03

0

1

n

0

frac

tion

Anderson et al. 05 HadOCC Anderson et al. 05 HadOCC1

on

food C/N4 20 food C/N4 20 food C/N4 20 food C/N4 200

frac

tio

food C/N4 20 food C/N4 20 food C/N4 20 food C/N4 20

Anderson et al. (in press)

Anderson et al. (in press)

1.0 B

-1

0.8

BS

IvMM

inta

ke, d

-

0.4

0.6i

0.2

0 1 2 3 40.0

prey density

Loss terms and closure

Complex models

ocean surface

Complex models

zooplanktongrazing

phytoplankton

ocean surface

euphotic zone NPP

microzooplankton mesozooplankton

g g

defecation

coccolithophores diatomsmixed

phytoplankton

“messy isinking

nutrients non-living organic matter

excretiondefecation,mortalityuptake

remineralisation

messyfeeding” grazing

mortality

sinking

PO4 Fe SiO3dissolved

organic mattersmall

detrituslarge

detritus

deep ocean mixing mixing sinking

Poorly understood ecology

ingestedsubstrates

assimilation

pelletsassimilation CO2

costsassimilatedsubstrates

digestion

basal metabolism

moultmaintenance CO2

remaining

PO4

protein turnovergsubstrates

p

newbiomassproduction CO2

costs ofgrowth

biomassproduction

growth (incl reproduction)release

excess C,P CO2 orDOC

PO4 orDOP

growth (incl. reproduction)

Aggregation

Simplification

Calanus finmarchicus life history

All in the interactions

coccolithophores mg chl m-3coccolithophores, mg chl m

MM March-May B

S IVV

Lack of validation

Insufficient data

Too many free parameters

“What little validation is undertaken will always tend to overstate the case for belief in the model results”

(Wainwright, 2003)

Conclusions

BU and TD combine to determine ecosystem structure andassociated fluxes such as export

The key is to understand the coupling of phytoplankton andl k di d b h i l izooplankton as mediated by physical environment

M d l k bl i i h i i f Models are remarkably sensitive to the parameterisation of zooplankton

The parameterisation of zooplankton in models is fraught withdifficulty, especially in complex models

role of zooplankton in marine ecosystems and modellinggp p ...ncar).pdf · role of zooplankton in...

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