The Atlantis Ecosystem Modeling Framework

The Atlantis Ecosystem Modeling Framework

Isaac Kaplan, Chris Harvey, Phil Levin, Jason Link, Howard Townsend

NOAA NMFSBeth Fulton CSIRO Australia

Ecosystem models can improve our understanding of interactions between species, climate, fishing, and habitat.

The Atlantis ecosystem model (Fulton et al. 2004) is a strategic tool used to:

1. synthesize this information; 2. simulate possible ecosystem responses;3. identify key processes that govern ecosystem condition

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3-dimensional structure of model

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Daily oceanographic fluxes(water, heat, salt)

into and out of each box arecontrolled by a ROMSoceanographic modelBiogeochemistry

Hydrographicsubmodel

Communitysubmodel

Habitat

Fisheriessubmodel

Climate and oceanography

Managementsubmodel

Assessment and policy decisions

Atlantis ModelsFully Developed• SE Australia• Port Phillip Bay, Aus.

Mostly CompletedWesternport, Australia

• Northeast US• California Current

Early Stages• Torres Strait• Coastal NSW• Clarence River NSW• SW Australia• Ningaloo Marine Park• SE Tasmania• Central California

Beth

Tasmania

S.E. Australia

Santa Cruz

Long Island

N.E. U.S.

Cal. Current

What are the key features/equations/functions/ assumptions of the model?

Grazer B

lineargrazers

grazingspacenutlight MMPdt

dP

Nutrients

Space

Disease, Lysis,Stress, Fouling

Grazer A

DetritusLight

Grazer C

Primaryproducer

Primary producers

Disease, Oxygen limitation

linearpreds

predprey

spaceoxygenassimprey MMABdt

dB

Detritus

Prey C

Prey B

Prey A

Food availability

Nutrients

Predator B

Predator A

Predator C

Invertebrate

Invertebrate consumers

preds

quadlinearpredprey

spaceoxygenassimprey MMMABdt

dB

Prey availability

Reproduction

Disease, Oxygen limitation

DetritusNutrients

VertebrateiReserve ║ Structure

Vertebrate consumers (age-structured)

Prey C

Prey B

Prey A

Gape limitation

Predator B

Predator A

Predator C

Vertebrate predation and reproduction

AdultsPrey abundance

Pre

y C

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mpt

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per

Pre

dato

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ruits

Holling type II Beverton Holt

ORHolling type I, Holling type III,

Ecosim, Size specific Holling type III, min-max

ORRicker, condition-dependent Beverton Holt,

constant, lognormal, dependent on prim producers (Chla), dependent on all plankton, Bev-Holt with lognormal variation added, Bev-

Holt with prescribed recovery, linearly dependent on maternal condition, pupping/calving a fixed

number per adult spawning, or forced timeseries of recruitment

Small flatfish

(Pleuronectids: Dover sole, rex sole, sanddab)

(mg N/m3)

Spatially Explicit OutputSpatially Explicit Output

Year 1 Year 40

Washington

Oregon

Cape Mendocino

Santa Cruz

Santa Barbara

Spatially Aggregated OutputSpatially Aggregated Output

What are the data requirements?

Atlantis biological parametersFor each species• Abundance per area• Individual growth rates, length-weight conversions• Max age, and age-at-maturity• General habitat preferences• Dispersal and/or migratory characteristics, within and outside model• Diets• Recruitment parameters (e.g. Beverton Holt, Ricker)For ecosystem map• Habitat distribution (bottom type + biogenic habitat)For calibration• Historical catch and abundance data

What key data gaps have been identified? Are these data gaps informing monitoring

efforts?

•Biomass estimates: nearshore and pelagic species, lower trophic levels (jellyfish, benthos, etc.)

•Diets

•Bycatch rates

•Fleet costs (US) and social factors governing fleet behavior

What is the model being used for?Is it used for management?

Management Strategy Evaluation

Ecology and

Fishing Simulator(Atlantis)

Monitoring and Indicators

Assessments and Parameter Estimation

Implementation

Observations

1 year cycle

Observations

1 year cycle1 yr

cycle


Management policies: quotas,

effort limits, MPAs

S.E. Australia-Fleet Restructuring

•Ecosystem-scale MSE

•Pros and cons of 5 kinds of management strategies

• Results = balanced use of levers is most effective

•Led to refinement of questions (incentive systems, size of spatial management zones etc)

S.E. Australia- Indicators

•MSE tested hundreds proposed indicators (with fisheries dependent and independent "data")

•Results=need a suite, cover range of species with different characteristics

•Will shape reporting and decision rules (in tiered harvest strategies)

Central California – Considering interactions between state and

Sanctuary management

What are the strengths and weaknesses of the model?

Atlantis

Pros• Flexible options for predation, reproduction, growth, gape limitation

• MSE (monitoring, assessments, indicators, economics, management)

• Nutrient handling, and interfaces with ROMS oceanography output

•Migrations out of region

Cons•Build time (6 months)

•Run time (hours- days)

•Lacks balancing routines

•Cumbersome parameterization

Model development and improvement

• Output graphics code for total biomass time series, biomass per region, and weight-at-age

• Diet handling

• Improved user interface and parameter input

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Funding• NOAA NMFS• NOAA Fisheries and the Environment (FATE)• NOAA NMFS Economics Program • Moore Foundation• Packard Foundation

Contacts

Beth Fulton [email protected] Kaplan [email protected] Link [email protected]

mailto:[email protected]



Weight-at-age

Weight-at-age relative to

expectation from von Bertalanffy

Age class 1

Age class 10

Atlantis publications are peer reviewedJournal Articles• Fulton, E. A. 2004. Biogeochemical marine ecosystem models II: the effect of physiological detail on model performance. Ecological Modelling

173:371-406.• Fulton, E. A., and A. D. M. Smith. 2004. Lessons learnt from a comparison of three ecosystem models for Port Phillip Bay, Australia. South

African Journal of Marine Science 26:219-243.• Fulton, E. A., A. D. M. Smith, and C. R. Johnson. 2003a. Effect of complexity on marine ecosystem models. Marine Ecology Progress Series

253:1-16.• Fulton, E. A., A. D. M. Smith, and C. R. Johnson. 2003b. Mortality and predation in ecosystem models: is it important how these are

expressed? Ecological Modelling 169:157-178.• Fulton, E. A., A. D. M. Smith, and C. R. Johnson. 2004. Effects of spatial resolution on the performance and interpretation of marine ecosystem

models. Ecological Modelling 176:27-42.• Fulton, E. A., Smith, A. D. M., and Punt, A. E. 2005. Which ecological indicators can robustly detect effects of fishing? ICES Journal of Marine

Science, 62: 540-551.Technical Documents• Brand, E. J., I. C. Kaplan, C. J. Harvey, E. A. Fulton, A. J. Hermann, J. C. Field and P.S. Levin. In press. A Spatially Explicit Ecosystem Model of the California Current’s Food Web and

Oceanography. NOAA Tech Memo. NMFS-NWFSC.• Fulton, E.A., Fuller, M., Smith, A.D.M. and Punt, A., 2005. Ecological Indicators of the Ecosystem Effects of Fishing: Final Report. Australian Fisheries Management Authority Report, R99/1546.• Fulton, E.A., Slater J., Smith, A.D.M. and Webb, H., 2005. Ecological Indicators for the Impacts of Fishing on Non-Target Species, Communities and Ecosystems: Review of Potential Indicators.

Australian Fisheries Management Authority Report, R99/1546-A. • Fulton, E. A., Smith, A. D. M., and Punt, A. E. 2003. Indicators of the Ecosystem Effects of Fishing: Case-Study 1 – Temperate Bay Ecosystem. Milestone Project Report, CSIRO Marine

Research, Hobart.

The code base is not (but is the product of 10+ years of work by many at CSIRO)

yselectivitiavailitycatchabiliiiii effortBF

Catch

Carrion

Catchability

Availability

Selectivity

Fisheries: age-specific catch

Fish, age i

Effort

Fleet B

Fleet A

Fleet C

• Key elements for each presentation: What is/has/will the model be used for? What are the data requirements? What key data gaps have been identified? Are these data gaps informing monitoring efforts? What are the key features/equations/functions/assumptions of the model? What are the strengths of this model? What are the weaknesses of this model? Has the model been published in the peer reviewed literature? Has the model & software been through a formal peer review? Have the model outputs been through a formal peer review? How portable is the model software package? What remains for model development/improvement/enhancement? Has/is/will the model outputs be used in LMR management?

Improved Diet Handling(Jason Link and Robert Gamble)

Atlantis Model of the California Current

Model food web has 56 functional groups, including: • 3 primary producer groups• 2 bacteria groups• 3 infaunal invertebrate groups• 9 epifaunal invertebrate groups• 5 pelagic invertebrate groups• 21 fish groups• 3 seabird groups• 6 marine mammal groups• 2 detritus pools

California Current Ecosim model

Field (2004, 2006)

To date:PacFIN catch per region, 1981-2004

Future work:Fleet dynamics calibrated to historical catches, and limited by spatial or seasonal closures, quotas or effort limits

Fisheries

Groundfish trawling effort offcentral Oregon Coast, 2003

Model Dynamics

Outputs with No FishingOutputs with No Fishing

Chloro- phyll a

(mg N/m3) Cape Mendocino

Monterey Bay

Cape Blanco

Cape Flattery

Columbia River

Point Conception

Year 1 Year 40

Deep corals and

anemones

(mg N/m3)


Year 1 Year 40

Small flatfish

(Pleuronectids: Dover sole, rex sole, sanddab)

(mg N/m3)


Year 1 Year 40

ScopingIdentify goals of EBM andthreats to achieving goals

Develop ecosystem indicatorsand targets

Risk Analysis

Characterization of susceptibility to

perturbation

Characterization of resiliency to perturbation

Assessment of ecosystem status relative to EBM goals

Management Actions

Data Acquisition

Monitoring of Ecosystem Indicators

Testing Ecosystem Indicators

– Changes in ecosystem pressure (e.g., temperature) or ecosystem attribute of interest (trophic structure)

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Project 1: Indicators of Fishing Impacts

• A first cut…– For fished species, remove a fixed

amount of biomass annually from standing stock• We show removals as a % of baseline

biomass

– After 25 years, examine changes in ecosystem structure

– What indicators reveal this change?

Piscivore : Planktivore

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target species

Real World

Ecology

Decision Rule

Stock Synthesis II


Implementation

+ error

2 yr

cycle

Observations of Stock

Project 2: English Sole and Canary Rockfish

Current Management

Atlantis Ecology

and Fishing Simulator

Decision Rule

Stock Synthesis II


Implementation

+ error

Ecological Indicators

2 yr

cycle

Observations of Stock

Management Strategy EvaluationClimate Indicators in Assessments and

Management Decisions (w/ Ian Stewart, NWFSC)

Atlantis

• Management Strategy Evaluation Test monitoring, indicators, assessments and regulations

• Integrating ecosystem information

• Strategic planning for fisheries management

Contacts:

• Phil Levin [email protected]

(206)860-3473

• Isaac Kaplan [email protected]

(206)302-2446

