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Physics to Fish: Two Examples and Issues with End-to-End models Kenneth Rose Dept. Oceanography and Coastal Sciences Louisiana State University Baton Rouge,

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Presentation on theme: "Physics to Fish: Two Examples and Issues with End-to-End models Kenneth Rose Dept. Oceanography and Coastal Sciences Louisiana State University Baton Rouge,"— Presentation transcript:

1 Physics to Fish: Two Examples and Issues with End-to-End models Kenneth Rose Dept. Oceanography and Coastal Sciences Louisiana State University Baton Rouge, LA, USA

2 Today Example of an “ESAM” –Full disclosure (added last night) –hypocrisy Why physics to fishers or end-to-end models now Issues and challenges –Recent workshop Ongoing case study –Sardine and anchovy in California Current

3 Egg Yolk-sac Ocean larva Estuary larva Early juvenile Late juvenile Adult

4 t+1 E gg A1 A2 A3 A4 A5 A6 A7 t Matrix Projection Model Matrix Projection Model E gg A1 A2 A3 A4 A5 A6 A7 Stage duration and mortality are used to calculate P and G Classic formulation:

5 Age 12 11 10 9 8 7 6 5 4 3 2 1 Egg Yolk-sac Atlantic Bight P G P North Carolina Estuary LarvaEarly JuvenileLate Juvenile Transition Virginia Ocean Larva G Transition Estuary LarvaEarly JuvenileLate Juvenile Estuary LarvaEarly JuvenileLate Juvenile Estuary LarvaEarly JuvenileLate Juvenile Daily Biweekly Monthly July Dec Annual Mid-Atlantic Bight (MAB)

6 Diamond, Murphy, and Rose (in prep)

7 CGCM2 – VA and NC



10 140 0 Baseline versus Global Scenario 2020 matrix in year 50, 2050 in 80 and 2080 in 110


12 Physics to Fishers (Now back to my original talk) Physics-NPZ and fish population models were developed separately Meet at zooplankton –Density-dependent closure term for NPZ –B 2 is not acceptable –Assumed available for fish by fisheries people Advances in each seemed out-of-phase

13 Physics to Fishers: Why now Advances in data collection –Spatially-detailed data –Behavioral measurements Continued increases in computing power Advances in modeling –Physics: meso-scale features in decadal runs –Fish: individual-based, fine-scale observations

14 Why now

15 1996! Data from 1994

16 Preparation documents sent to review panel members for the Gulf of Mexico Red Snapper stock assessment

17 One Long-Term Solution Coupled models that can address bottom-up, top-down, and side-ways issues Climate change effects on fish Perceived fisheries management crisis due to simple single-species approach Ecosystem-based management (whatever that means)

18 How to do it How to combine models with different temporal and spatial scales No general theory Options: –Run models separately and average or disaggregate outputs to be inputs to the next model –Solve pairs or all models simultaneously –All models use the same temporal and spatial scales (“single code”) Super-individuals for self-regeneration

19 Individual-Based Approach Very, very smart particles Allows for local interactions Unique time histories Adaptation and acclimation Individual variability – full distribution Easier movement Compatible with complex systems theory

20 Individual-Based Approach Tedious coding Complicated bookkeeping –Especially full life cycle Data hungry Mixing Eulerian and Lagrangian Difficult to validate details Could be fooling oneself

21 Recent Workshop Abut 50 people meet in Plymouth "Bridging the gap between lower and higher trophic levels" Resulted in Rose et al. (in review) 9 general issues identified

22 Workshop - Issues Zooplankton as the link –E2e shifts from cycling to energy flows –NPZ may need re-vamping –Functional groups and revised processes New organisms –Macroinvertebrates (e.g., jellyfish) –Demersal fish and thus benthos –Very HTL organisms, such as humans

23 Workshop - Issues Acclimation and adaptation –Phenotypic plasticity –Genotypic changes of rapid turnover (plankton) and “evolution” effects on fish Scaling –Fundamental to all ecological modeling –E2e further increases diversity of scales –Fine-scale dynamics (e.g., feeding) over broad space (allow for migration shifts) for multiple decades (long-lived HTL organisms)

24 Dickey 1991, 2003

25 Workshop - Issues Behavioral movement –Particle tracking for eggs and larvae –Adults are not passive particles –Daily movement versus migrations –Promising approaches but none vetted and little evaluation Software and technology –E2e will use extensive code in sequential languages –Several independent efforts making inter-comparison difficult –Opportunity for common standards and a community effort

26 Workshop - Issues Model confidence and forecasting –Physics and NPZ can use short-term data –Severe challenges for fish and other HTL organisms –Physics people need to loosen up Solution techniques –One-way versus two-way coupling –Tradeoff between ease and speed versus dynamic feedbacks –Feedbacks allow for density-dependence –Meshing of Lagrandian and Eulerian –Numerics for full life cycle, multispecies, fully coupled are tricky –Large number, high mortality - super-individuals can cause artifacts

27 Houde (1987)) Full Life Cycle with Complex Life History (needed to see full effects and sustainability)

28 Technical: Computing Computing power is constantly surprising us (especially older scientists) Super-computers, OPENMP

29 Institutional Silo approach to organizations True collaboration –Not mean joint projects with annual meetings, or email and web meetings –Requires frequent “eye-to-eye” contact Resource managers, especially fisheries, resistant to new models

30 Galileo Newton Darwin Einstein Crick and WatsonInternational Human Genome Sequencing Consortium Barabasi 2005 People

31 Case Study Outgrowth from NEMURO efforts - PICES Initially unfunded and now CAMEO Combining: –ROMS –NEMURO NPZ –individual-based, full life cycle, multi-species (5) fish in any food web plus fishing vessels

32 Kishi et al., in review

33 Original Tokyo Workshop

34 Most Recent Team Enrique Curchitser (Rutgers University) Kate Hedstrom (ARSC – UAF) Jerome Fiechter (UC – Santa Cruz) Shin-ichi Ito (Fisheries Research Agency, JP) Salvador E. Lluch-Cota (CIBNOR, MX) Bernie Megrey (NMFS – Seattle)

35 Provided by: Salvador E. Lluch-Cota Source: Schwartzlose et al., 1999

36 Sardine Anchovy 1971 2004 Provided by: Carl van der Lingen Sources: King, 1997; E. Stenevik, pers com

37 2 – 10km 3 – 3km 4 – 300m Model 1: ROMS

38 Model 2: NEMURO NPZ

39 Model 3: Fish IBM Multi-species Full life cycle Daily processes: –Reproduction –Growth –Mortality –Movement

40 Fish IBM: Reproduction Each female spawns using temperature Fecundity is weight-dependent Add new model individuals using a complicated algorithm for allocating a fixed number to daily spawning in space

41 Fish IBM: Growth W = weight (g ww) C = consumption (1/day) R = respiration S = SDA F = egestion E = excretion H = reproduction Depend on W and temperature PD = prey density (1=ZS; 2=ZL; 3=ZP) V = vulnerability K = feeding efficiency Zoop from NEMURO Mortality to NEMURO

42 FISH IBM: Mortality Natural –Stage or size-dependent –Option: Predators as biomass chasing individuals –Option: full species that eat individuals and reproduce, grow, die, and move Fishing –Option: age-specific –Option: one of the full species is fishing fleets, like predators chasing individuals but based on distance from port and fuel prices

43 FISH IBM: Movement Physics for very young Behavior for older –Fitness –Kinesis –ANN with GA


45 Provided by Jerome Fiechter

46 Provided by Jerome Fiechter

47 Conclusions ESAM approach can be useful –Perhaps I overstated my objection on Monday Ecosystem does not stop at zooplankton, nor can fish be modeled without considering what happens below Physics-to-fishers modeling can, and should, be done –Ingredients are available –Decisions are being made, without the best information –Long-term solution

48 Conclusions Physics, zooplankton, and fisheries together is needed, would benefit all, although full life cycle is very challenging Proof of principle and then say what data are needed Modeling lead the way so get data in 5-10 years Based on need and computers, we are already about 10 years behind


50 Individual Fish (Initial simple coupling)

51 Large Zooplankton (Initial simple coupling)

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