alaska marine sciences symposium gulf of alaska – wednesday, january 24th, 2007 session 2: lower...

Alaska Marine Sciences SymposiumGulf of Alaska – Wednesday, January 24th, 2007

Session 2: Lower Trophic LevelsPoster Presentations

Intertidal and subtidal

2) Temporal and Spatial Variability of Nearshore Crab LarvaeBen Daly* School of Fisheries and Ocean Sciences, University of Alaska Fairbanks, 245 O'Neill Bldg. P.O. Box 757220 Fairbanks, Alaska 99775-7220, (907)474-7074 daly@sfos.uaf.eduBrenda Konar. Global Undersea Research Unit, University of Alaska Fairbanks, 217 O'Neill Bldg. P.O. Box 757220 Fairbanks, AK 99775-7220 (907)474-5028 bkonar@guru.uaf.edu

Compare temporal variability between species in the zoeal and megalopa stages and compare habitat use between species over time regardless of larval stage in Kachemak Bay.

3) Remote Sensing of Seagrass Resources in Kachemak Bay, AlaskaDon, Field, NOAA Center for Coastal Fisheries and Habitat Research, Don.Field@noaa.gov; *Kris, Holderied, NOAA Kasitsna Bay Lab, Kris.Holderied@noaa.gov; Mark, Fonseca, NOAA Center for Coastal Fisheries and Habitat Research, Mark.Fonseca@noaa.gov

Seagrass beds were mapped in Kachemak Bay in 2005 using aerial photographs.

4) Development and Testing of a Probability-based Intertidal Monitoring Scheme for Sitka National Historic Park, AlaskaGail V. Irvine*, USGS-Alaska Science Center, gail_irvine@usgs.gov

Presents an intertidal monitoring program at the Sitka National Historic Park

5) www.seaweedsofalaska.com - a photo-rich portal to the taxonomy of Alaskan seaweeds and their habitatsMandy Lindeberg, Auke Bay Laboratories Alaska Fisheries Science Center NOAA/NMFS, Mandy.Lindeberg@noaa.gov*Sandra Lindstrom, University of British Columbia, sandracl@interchange.ubc.caSusan Saupe, Cook Inlet RCAC, Saupe@circac.org

Information on a website to aid in taxonomic classification and mapping of seaweeds

6) Community structuring impacts of Enteroctopus dofleini in Prince William Sound, AlaskaCourtney Lyons*, Alaska Pacific University, courtney.lyons@gmail.comDavid Scheel, Alaska Pacific University, dscheel@alaskapacific.eduLeslie Cornick, Alaska Pacific University, lcornick@alaskapacific.eduRoman Dial, Alaska Pacific University, roman@alaskapacific.edu

Role of an octopus in structuring intertidal communities in Prince William Sound.

Plankton

1) Zooplankton populations on the Alaskan Shelf and northern Gulf of AlaskaSonia Batten, Sir Alister Hardy Foundation for Ocean Science, soba@sahfos.ac.uk

Examines continuous plankton recorder data from the northern Gulf of Alaska collected from 2000 to present.

Autonomous Zooplankton Sampling for Ocean Observing Systems

J.M. Napp1, D.V. Holliday2, C.F. Greenlaw2, P.J. Stabeno3, and A.J. Jenkins3

1NOAA – Alaska Fisheries Science Center2BAE Systems

3NOAA – Pacific Marine Environmental Laboratory

1) Calibration of a nutrient - phytoplankton - zooplankton model for use with a three dimensional physical model to simulate ecological mechanisms on the northern Gulf of Alaska shelfK. O. Coyle, Institute of Marine Science, University of Alaska, coyle@ims.uaf.eduS. Hinckley, Alaska Fisheries Science Center/NMFS, Sarah.Hinckley@noaa.govA. J. Hermann, Joint Institute for the Study of the Atmosphere and Ocean,University of Washington, Albert.J.Hermann@noaa.gov

2) Rocky Intertidal Benthos in Iniskin/Iliamna Bay: A 28-Year Baseline and Hints of Climate Change?Jon Houghton, Pentec Environmental/Hart Crowser, Inc., jon@pentecenv.com Dennis Lees, Littoral Environmental and Ecological Services, dennislees@earthlink.netSandra Lindstrom, University of British Columbia sandrcl@telus.net, andJason Stutes, Pentec Environmental/Hart Crowser, Inc. jason.stutes@pentecenv.com

3) Role of Grazers in the Recolonization of Hard Bottom Communities in Kachemak Bay, AlaskaNick Harman, University of Alaska Fairbanks, ftnwh@sfos.uaf.edu

4) Clams and Armor: Were They Casualties of the War on the Beaches?Dennis Lees, Littoral Ecological & Environmental Services, dennislees@earthlink.netWilliam Driskell, bdriskell@comcast.net

Calibration of a nutrient - phytoplankton - zooplankton model for use with a three dimensional physical model to simulate ecological mechanisms on the northern

Gulf of Alaska shelfK. Coyle, Institute of Marine Science, University of Alaska

S. Hinckley, Alaska Fisheries Science Center, 7600 Sand Point Way NE, Seattle, WA 98115.

A.J. Hermann, Pacific Marine Environmental Laboratory, 7600 Sand Point Way NE, Seattle, WA 98115.

Funding Agency: North Pacific Research Board

Understand the mechanistic links between physical forcing and the ecosystem response.

Major Goal of Biological Oceanographic Programs

1) To accomplish this goal we aim to develop and verify the quantitative relationships between the physical and biological data collected during field observations.

2) The quantitative relationships between physical and biological observations are expressed by equations in mathematical models.

3) The simulations generated by the mathematical models must be compared with actual measurements to insure that the model output is an accurate reflection of actual conditions in the environment.

1) Site description

2) Brief description of the model.

3) Comparison of model output with GLOBEC results

4) The model as a research tool.

Description of how the model is used to generate data sets permitting direct comparison of simulated results with field measurements.

1. Site Description

May 26, 20000 5 0 1 0 0 1 5 0 2 0 0

D ista n ce (k m )

-1 0 0

-8 0

-6 0

-4 0

-2 0

0

Dep

th (

m)

T em p eratu re ( o

C )

3.8

4.3

4.8

5.3

5.8

6.3

6.8

7.3

0 5 0 1 0 0 1 5 0 2 0 0

D ista n ce (k m )

-1 0 0

-8 0

-6 0

-4 0

-2 0

0

Dep

th (

m)

S a lin ity (P S U )

30.4

30.8

31.1

31.5

31.8

32.2

32.6

32.9

33.3

33.6

0 5 0 1 0 0 1 5 0 2 0 0

D ista n ce (k m )

-1 0 0

-8 0

-6 0

-4 0

-2 0

0

F lu orescen ce

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

Any attempt to understand the potential influence of climate on the Gulf of Alaska shelf ecology must consider the highly complex physical regime shown above.

The physical model which drives the biological simulation must be capable of reproducing the physical environment, at least in the statistical sense: density distribution, flow patterns and eddies.

1. Model Description

Physical Model:1)Regional Ocean Modeling System (ROMS)2)Northeast Pacific (NEP) Component has 11 km

resolution3)Coastal Gulf of Alaska (CGOA) component has

3 km resolution4)Ocean boundaries of the CGOA open allowing

entry and exit of Alaska Stream waters5)Bathymetry was derived from ETOPO5 and

finer-scale bathymetric data. 6)The model has 30 layers, layers are

concentrated near the surface (surface layer thickness varies from 0.3 to 15 m depth).

7)Physical model is driven by MM5 climatology.

11 Component ModelSlide by G. Gibson

Iron

Is this level of model complexity necessary?

For optimal utility, the complexity of mathematical models should not exceed that required to address the problem under consideration.

Highly complex models can:1) Be difficult to parameterize because of the large number of potentially unconstrained variables.2) Require unreasonably long times to run because of the additional algorithms which must be executed to generate model output.

0

10

20

30

40

50

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Fraction of total chl >20 µm

0.0

0.2

0.4

0.6

0.8

1.0

0.1 1.0 10.0 100.0

Total chlorophyll (µg/liter)

ISMSOS

large (>20 µm)small (<20 µm)

Neocalanus

other mesozoo

microzoo

2.62.6

20.1

1.6

1.6

sinking?advection?

67

41.7

A. Spring large-cell dominated food web

microzoo

other mesozoo

13

?

larvaceans

4

13

B. Summer small-cell dominated food web (dashed line = episodic event)

Units: µgC liter-1 d-1

pink salmon?

?

Data from Dagg and Strom

Month

March April May June July August Sept October

Me

an B

iom

ass

(g

m-3

)

0.0

0.1

0.2

0.3

0.4

0.5

OthersSalpidaeChaetognathaLarvaceansEuphausiidsCnidariaPteropodsCalanoida

Mean Zooplankton Biomass: 1998 to 2003GLOBEC Seward Line Data

Month

March April May June July August Sept October

Mea

n B

iom

ass

(g m

-3)

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

Calanus marshallaeEucalanus bungiiMetridia spp.Neocalanus cristatusN. plumchrus & N. flemingeriPseudocalanus spp.Oithona similis

Mean copepod biomass: 1998 to 2003GLOBEC Seward Line Data

Complexity of the 11 box model is probably the minimum required to accurately simulate observed conditions in the northern Gulf of Alaska

Model Validation Using One Dimension Model Output

Model validation and parameterization requires direct comparison of simulated values with actual measurements generated from field collections.

The fully three dimensional model with embedded biological component requires about three and a half weeks for a single simulation for the northern Gulf of Alaska.

Model output for direct comparison of simulated biological variables with field data are generated using a one – dimensional model forced with physical results for any selected location from the three dimensional simulations for the entire Gulf of Alaska grid.

PrinceWilliamSound

ResurrectionBay

Knight Island Passage

Middleton Island

Station locations for biological data from the northern Gulf of Alaska.

GAK6 2001 Model Simulation

Model Simulation: May 2001

Distance (km)

0 50 100 150 200

Bio

mas

s (m

g C

m-3

)

10

15

20

25

30

35

Large PhytoplanktonSmall Phytoplankton

Average in upper 50 m

0

20

40

60

80Measured Biomass

Measured and simulated biomass of phytoplankton along the Seward Line in May Measured values from a poster by Lessard and Foy

Station Numbers

Model Simulation: Jun 2001

Distance (km)

0 50 100 150 200

Bio

mas

s (m

g C

m-3

)

0

20

40

60

80

100

Large PhytoplanktonSmall Phytoplankton

Average in upper 50 m

0

20

40

60

80

Measured and simulated biomass of phytoplankton along the Seward Line in June - July

Measured values from a poster by Lessard and Foy

Measured Biomass

Station Numbers

GAK6 2001 Model Simulation

Model Simulation: 2001; Gak6

Time (days)

Mar Apr May Jun Jul Aug Sep Oct

Bio

mas

s (m

g C

m-3

)

0

5

10

15

20

25

Neocalanus spp.Small Copepods

Average in upper 100 m

Month

March April May June July August Sept October

Mea

n B

iom

ass

(mg

C m

-3)

0

5

10

15

20

25

N. plumchrus & N. flemingeriPseudocalanus spp.

Mean (1998 – 2003) Copepod Carbon Biomass Measured Values

Model as a research tool

How does a regime shift impact the shelf ecosystem?Strong

Southerly

MarineWet

Weak

Northerly

ContinentalDry

Elevated freshwater input from runoff and glacial melt

Low freshwater input; less precipitation and runoff; glacial growth rather than retreat

Modified from Gargett (1997)

What might the model tell us about climate influences on the shelf

1) Will declines or increases in freshwater input to the shelf result in increases or declines in lower trophic – level production? What is the potential magnitude of the response?

2) Are specific regions more sensitive to shifts in freshwater input than others? If so, where and by what magnitude?

3) What sample density and frequency would be required to detect a climate – related change in lower trophic level production? What would be the optimal station distribution?

4) Will a shift in freshwater input lead to higher or lower cross – shelf transport? What regions will be most impacted?

5) What is the potential effect of elevated temperatures on lower trophic level production?

Questions (Conclusions) that the fully implemented 3 – dimensional model with

embedded biological model might address

Most of the data for model calibration were collected by Global Ocean Ecosystem Dynamics (GLOBEC) program for the northern Gulf of Alaska. Participants included: Tom Weingartner, Tom Royer, Evelyn Lessard, Suzanne Strom, Terry Whitledge, Dean Stockwell, Jeff Napp, Phyllis Stabeno, Lew Haldarson, Jennifer Bolt, Russell Hopcroft, Alexei Pinchuk, Mike Foy, Hue Liu, Michael Dagg, Seth Danielson.

The ROMS model was implemented for the Gulf of Alaska by Elizabeth Dobbs, Al Hermann and Kate Hedstrom. The biological model was originally developed by Sarah Hinckley.

The GLOBEC program was jointly funded by the National Science Foundation and NOAA. Additional data for model calibration was provided by the North Pacific Research Board monitoring project along the Seward Line.

Acknowledgments