Zooplankton Population Dynamics on Georges Bank:

Model and Data Synthesis

PIs: P.J.S. Franks, C.S. Chen, E.G. Durbin, W. Gentleman,

J.M. Pringle and J. Runge

With important contributions from students, postdocs,

technicians

Goals• To improve our mechanistic understanding

of the possible influences of climate variation on the population dynamics and production of the target zooplankton species through its effects on advective transport, temperature, food availability, and predator fields

Questions and Hypotheses• The role of advection

• Advective supply of Calanus finmarchicus and Pseudocalanus spp. copepodites to GB during January-April and the role of winds

• Advective supply and loss of Calanus finmarchicus to GOM basin diapausing populations during June-January

• Role of advection for copepod populations on GB

• Population dynamics of zooplankton on GB and the GOM

• Stratification and variability in food supply: the role of food limitation

• Mortality and invertebrate predation

The role of advection

Advective supply and loss to GOM basin diapausing populations during June-

January

Deep density field mattersFVCOM surface currents and depth of =26.97 isopycnal

Deep density field changes

Note change in cross-gulf density gradientThis will change flow towards Georges Bank

Calculate Geostrophic Cross Gulf Currents (200m reference level)

1) Calculate average density in boxes over one year period from BIO data.

2) Vertically integrate density difference from “level of no motion.”

3) Produce estimate of cross-gulf transport to Georges Bank.

This does not estimate coastal boundary current transport, but it may be related.

Time series of cross-Gulf transport(missing years have too little data)

Mean 0.6Sv

Std. Deviation 0.22Sv

Variability of GOM Transport

Sources of variability: (standard deviation)/(6 month mean) for transport along Pen Bay/Georges Bank axis, not including coastal current.

•Hydrographic variability, 30 to 40%

•Scotian Shelf inflow variability, about 20%

•Winter winds, about 10%.

Open questions? (one of many!)

•What is timescale of hydrographic variability?

What we know best is not what is important on 6 month or longer timescales

GOM subregions

Passive behavior

Density-seeking behavior

Retention in basins

Transport among GOM sub-regions (passive behavior)P

erce

nt r

etai

ned

in s

ub-r

egio

n

Time (first of month)

75 m

100 m

150 m

200 m

250 m

Georges Basin Jordan Wilkinson

Georges Basin

Jordan Basin

Wilkinson Basin

Upstream

Georges Bank

Downstream

Retention Summary:

• Retention in deep GOM is high.

• Retention increases with depth.

• Wilkinson Basin is most retentive, Georges is least.

• Retention is greater for density-seeking particles than passive particles.

• Vertical distribution and diapause behavior drives more uncertainty than winds and inflow, and is poorly understood.

Advective supply to GB during January-April and the role of winds

The role of advection

Day 66 Day 76 Day 81Subtidal currents

surface

20 m

FVCOM: 1999 MM5 wind forcing

Scotian Shelf crossover event Day 78

Lagrangian particles (advected, not mixed)

Passive tracer

(vertically mixed)

• Surface particles released in the Browns Bank area “crossed-over" the NEC, reached NEP of the bank in less than 10 days and followed a clockwise circulation path over the southern Flank of GB.

• The tracer experiment indicates that vertical mixing prevents a significant amount of blooming biomass from being advected to the southern flank.

Population dynamics

Stratification and variability in food supply

1

2

3

1-D 2-D 3-D

• Stratification• Frontal structure• Cross-section variation

ECOM-si ECOM-si FVCOM

A

B

Three zones:

• The central bank in which water is shallow, vertically well-mixed, and relatively self-contained;

• The mid-bank region characterized by a seasonal tidal mixing front;

• The outer-flank between the seasonal tidal mixing front and the permanent shelf break front.

• Seasonal dynamics• Sensitivity• Model behavior

• Advection• Event level

Stratification and the spring bloom

Ammonia Silicate

SmallPhytoplankton

LargePhytoplankton

SmallZooplankton

LargeZooplankton

DetritusNitrogen

DetritusSilica

Predation

Mortality

Remineralization

UptakeUptake Uptake

Dissolution

Fecal

Mortality

Grazing Grazing

Mortality

Mortality

Nitrate

Grazing

Mortality

Site A Site B

Model-Data Comparison 1-D Model

2-D Model

Sensitivity to heat flux

Less heat

Large P Large P

Time Time

dT/dz dT/dz

Stratification summary

• The light environment controls the onset of the bloom in the shallow region, while stratification plays a more significant role in the deep region.

• The magnitude of bloom is modified by both light and nutrients.

• N/Si ratio is an important parameter for the nutrients limitation process and succession of phytoplankton community.

• The basic pattern of lower-level trophic food-web dynamics in shallow and deeper area mirrors the sites A and B in the 1D model. A unique pattern develops in the tidal mixing frontal zone.

• If no impact from advection, the development of weak stratification is critical for the springtime bloom; wind and heat flux can regulate this process.

• The frontal zone is a possible area for the “second” diatom bloom.

• Advection may be critical in determining changes in stratification and thus bloom formation, particularly in deeper waters

Population dynamics

Variability in food supply

Individual-based models

Regression line used to evaluate:MDTi = time when 50% of cohort reached stage i (e.g. MDTC3 = 21.8 days)DTVi = reciprocal of slope = measure of variability (e.g. DTVC3 = 2.7 days)

Campbell et al., 2001 IBM

Food limitation

Durbin et al. 2003: Gulf of Maine Runge et al. (in prep.): Georges Bank

All temperatures, food levels, and stages

IBM with food and temperature effects: comparison with data

Diapause duration model

0 2 4 6 81.8

2

2.2

2.4

2.6

2.8

3Maximum Diapause Duration

T

Length

6060

9090

90

90

120

120

120

120

120

150

150

150

150

180

180

180

180

210

210

210

240

240

240

270

270

300

1.8 2 2.2 2.4 2.6 2.8 30

2500

5000

7500

10000

12500

15000June to August - Jordan Basin

Length (mm)

#C5s/m

2

Month 1Month 2Predicted Month 2

1.8 2 2.2 2.4 2.6 2.8 30

2500

5000

7500

10000

12500

15000August to November - Jordan Basin

Length (mm)

#C5s/m

2

Month 1Month 2Predicted Month 2

Still to come:Further testing, simulation with FVCOM

Detailed exploration of transport pathways, influence of behavior

Develop offline code for tracers, biology

Couple 3D physical model with ecosystem model for annual cycle

Further develop and constrain IBM

Model diapause behavior

Couple ecosystem model with IBM

Workshop Objectives

Coordinate efforts

Work on offline code

Outline papers

Plan research efforts for the next year