Jo King:Jo King:

Mechanisms relating the ocean-scale distribution of Calanus finmarchicus to

environmental heterogeneity

Douglas Speirs

Acknowledgments: Bill Gurney (Strathclyde)

Mike Heath (FRS Aberdeen)

Simon Wood (Glasgow University)

SOC, PML, SAHFOS

Why Calanus finmarchicus ?

2 mm•Widespread & Abundant

•Links to Fish Stocks

•Extensively studied

Continuous Plankton Recorder Surveys

Calanus abundance and Circulation

The life-cycle of Calanus finmarchicus

• Omnivorous, but feeds mainly on phytoplankton.

• x1000 difference in body weight between eggs and adults.

• Stage duration strongly dependent on temperature

• Naupliar survival strongly dependent on food.

• Reproduction & growth in upper layers (<200m).

• Overwinters in a resting state at depths of 500-2000m.

Coupling Life-Cycle to Physical Oceanography

NORTH ATLANTIC OCEAN SHELF SEAS

Overwintering at depth

Export to shelf seas

Growth and reproductionin the upper ocean

In the ocean, Calanus switchesbetween surface and deepcirculation regimes during eachannual cycle.

Each spring, the shelf seas arere-colonised with Calanus fromthe ocean.

The modelling challenge

The Challenge• Physiologically and spatially explicit demographic model

• Ocean-basin scale – advection plus diffusion

• Hypothesis tests require wide parameter exploration

• Need exceptional computational efficiency

The Solution• Focus on Calanus (physical and biotic environment as given)

• Separate computation of physical and biological components

• Discrete-time approach ( 104 speed-up relative to Lagrangian ensemble)

A Calanus-focussed model

Representing Physical Transport

Update at regularly spaced times: Ti

y

TyqTyx iiiTxq CC ,,,,,,

iTxqC ,,

iTxqC ,,

iTyx ,,

Class abundance just before update

Class abundance just after update

Transfer matrix element from y to x for period to Ti. Determine by particle tracking in flow fields from GCM plus random (diffusive) component.

The Biological Model

• Uniform ‘physiological age’ for each group of stages

• Development rate a function of temp. and food

• Diapause entry from start of C5 stage – cued by low food

Updating the Biological Model

1,

,

)(ix

ix

U

U

dttgq

Update all classes in given group at given location at times {Ux,i} such that

uxquxquxqq CC ,,,,,,

according to

xq,

where

Survival of individual in q at x over increment up to u

Updating the system state

• Collect all un-processed updates from the adult, surface developer and diapauser groups

• Form the union of the subsets of each sequence which fall before the next transport update

• Process the new sequence in time order, updating all classes in that group at that location at each operation.

For each cell, in turn:

Do next transport update, Output state variables.

Produces model realisations in good agreement with PDE and Lagrangian ensemble solutions, but MUCH faster.

Prototype - Environment

Flow(HAMSOM)

Temp.(HAMSOM)

Food(SeaWiFS)

Winter (day 42)

Spring(day 133)

Summer(day 217)

Autumn(day 308)

Prototype – diapause control hypotheses

Entry Exit

H1 low food development at depth

H2 photoperiod development at depth

H3 low food photoperiod

H4 photoperiod photoperiod

-25 -20 -15 -10 -5 0 5 10 15 2056

58

60

62

64

66

68

70

StonehavenFoinaven

Murchison

Ocean Weathership M

Faroe shelf

Saltenfjorden

Westmann Islands

N.E. Atlantic - test data

• Overall plausibility test

• Continuous Plankton Recorder surveys (SAHFOS)

• Winter surveys of resting stages

•

Hypothesis Testing - OWS Mike

Surface Copepodites

Diapausers

Newly surfaced overwinterers

No diapausers in spring

Sharp drop at awakening

H1 H1

H3H3

Plausibility test – Diapausers

H1:

H3:

Winter (day 28)

Spring (day 154)

Summer (day 224)

Autumn (day 336)

Plausibility test – Surface Copepodites

H1:

H3:

Winter (day 28)

Spring (day 154)

Summer (day 224)

Autumn (day 336)

Prototype - Conclusions

• Spatially and physiologically resolved model on an ocean basin scale can be made fast enough for wide-ranging parameter exploration

• Current data on C. finmarchicus abundance in the N.E. Atlantic is best fitted by a model which assumes diapause is initiated by low food conditions.

• Models which assume diapause duration is determined by development are invariably falsified

• Awakening must be conditioned on a highly spatially correlated cue – such as photoperiod.

Test Data – Time Series & CPR

Prototype Model - Time Series Test

Gulf of Maine

OWS Mike

surfaceC5-C6

diapauseC5

Prototype Model – CPR Test

observed

Jan./Feb.

May/Jun.

Jul./Aug.

observed predicted

C5’s & phytoplankton carbon at OWSM

•Diapause occurs at end of C5 stage

•Fixed fraction of each generation

Annual Mean Temperature & Food

Labrador Sea is cold => temperature-dependent background mortality

Revised Model - Time Series Test

Gulf of Maine

OWS Mike

surfaceC5-C6

diapauseC5

Revised Model – CPR Test

Jan./Feb.

May/Jun.

Jul./Aug.

observed predicted

Yearly Population Cycle

The Impact of Transport

Domain Connectivity

Year 1

Year 3

Year 6

Conclusions

•Fractional diapause entry

•Diapause entry late in C5

•Photoperiod-cued diapause exit

•Temperature-dependent mortality

•Limited impact of transport

•High domain connectivity

Matching Calanus demography =>

Fitted model =>

•Ocean-scale population model feasible•Numerical efficiency is key