the atlantis ecosystem modeling framework isaac kaplan, chris harvey, phil levin, jason link, howard...
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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
ab
cd
efg
3-dimensional structure of model
abcdefg0 m50
100150
550
1200
2400
200
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
onsu
mpt
ion
per
Pre
dato
r
Rec
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
Assessments and Parameter Estimation
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
We
igh
t-a
t-a
ge
Funding• NOAA NMFS• NOAA Fisheries and the Environment (FATE)• NOAA NMFS Economics Program • Moore Foundation• Packard Foundation
Contacts
Beth Fulton Beth.Fulton@csiro.auIsaac Kaplan Isaac.Kaplan@noaa.govJason Link Jason.Link@noaa.gov
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)
Outputs with No FishingOutputs with No Fishing
Year 1 Year 40
Small flatfish
(Pleuronectids: Dover sole, rex sole, sanddab)
(mg N/m3)
Outputs with No FishingOutputs with No Fishing
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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Removal scenario
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Mea
n t
rop
hic
lev
elall
target species
Real World
Ecology
Decision Rule
Stock Synthesis II
Assessments and Parameter Estimation
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
Assessments and Parameter Estimation
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 phil.levin@noaa.gov
(206)860-3473
• Isaac Kaplan isaac.kaplan@noaa.gov
(206)302-2446
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