Modeling Atlantic menhaden in support of nutrient and multispecies management in Chesapeake Bay

1. Modeling Atlantic menhaden in support of nutrient and multispecies management in Chesapeake Bay Mark J. Brush Robert J. Latour Elizabeth A. Canuel LivRaw Meeting Feb 19, 2008

2. Project components 1. Stock assessment • Generate bay-specific estimates of abundance? 2. Feeding ecology • Characterize ingestion, selectivity, functional response, and excretion ? 3. Multilayered modeling • Multispecies bioenergetics modeling Photo: Hall Waters

3. What is an Atlantic menhaden? • Brevoortia tyrannus (Family: Clupeidae) • - Estuarine-dependent, marine migratory • - Range: northern FL to Gulf of Maine • - Chesapeake Bay is center of range • - Pelagic, forms large near-surface schools

4. 10-14 months Maturity at Age 2-3 Slide: D. Vaughan, NOAA

5. Movement patterns of Atlantic menhaden Over 1,000,000 Atlantic menhaden were tagged from 1967 to 1969 Recoveries of these tagged fish showed: the population moves northward in spring and summer… Data: Nicholson (1978), Slide: E. Williams, NOAA

6. Movement patterns of Atlantic menhaden …and the population moves southward in late fall, and overwinters in offshore waters off the southeastern coast Data: Nicholson (1978), Slide: E. Williams, NOAA

7. Jul- Sep Oct Jun May Nov Apr Dec Mar Jan / Feb Spawning Pattern based on egg and larval surveys influenced by temperature Spawning Pattern based on egg and larval surveys influenced by temperature Slide: E. Williams, NOAA

8. Summer 2003 Port Samples Mid-Atlantic 47% age-2 285 mm FL 53% age-3+ 302 mm FL Chesapeake Bay 20% age-1 199 mm FL 70% age-2 242 mm FL 10% age-3+ 291 mm FL South of Hatteras 15% age-1 176 mm FL 85% age-2 187 mm FL During summer, menhaden stratify by size/age along the east coast Older fish occur farther north Slide: E. Williams, NOAA

9. The Fisheries • Atlantic menhaden commercial fisheries • 4th - U.S. landings (lbs.): 6% • Bait fishery (21% of landings) • - Virtually all coastal states • Reduction fishery (79% of landings) • - All coastal states historically • - Currently: VA, NC, coastally • Chesapeake Bay ~ 58.5% reduction • landings (1996 – 2004) Photo: Hall Waters; Data: ASMFC 2006

10. Menhaden landings

11. 1957 25 menhaden factories ~144 vessels 2 2 2 5 4 2 3 Factory locations Reduction fishery Since 2005 1 menhaden factory ~11 vessels Reedville, VA Factory closures largely do to banned/restricted purse seining in coastal states

12. Current ASMFC stock assessment • Statistical catch-at-age model, 1955 - 2005 • Assumes entire coastal population represents unit stock • Suggests population is not overfished and overfishing is not occurring on a coastwide basis

13. Modeling approach, current assessment • Data: seine survey indices many states (juvs), Potomac river poundnet survey (adults), catch-at-age matrix, age-specific M values (MSVPA) Fig: Steven J.D. Martell

14. Bay-specific assessment • Bay-specific questions (e.g., localized depletion and impacts therein) require a more spatially structured model 1. Spatially-explicit model – too many parameters, too little data – virtually no chance of yielding reliable information 2. Spatially-implicit model – modest increases in parameters and data - potential exists to obtain reliable information • Collaborators - Line B. Christensen and Steven J.D. Martell of UBC to develop option 2 for Atlantic menhaden

15. Evidence of sub-stock structure? • Is there a Chesapeake Bay sub-population? • Although many Clupeids exhibit homing abilities, little evidence to date for this in Atlantic menhaden • Eggs are spawned generally offshore • Spawning occurs over many months and may occur year-round • Larvae depend on environmentally driven advective processes for entering estuarine areas • Tagging study shows that adults migrate and stratify by size and age coastwide • Question is just now being formally studied……

16. “Metapopulation” model • Note, we are adding spatial structure with no additional data available – particularly on adults Fig: Steven J.D. Martell

17. “Metapopulation” model • Approach: develop a simulation model that follows an assumed spatially overlapping metapopulation structure 1. Based on values of leading parameters, simulate observation errors and model input data 2. Fit estimation model to simulated data to investigate model capability in terms of parameter estimation 3. Pending outcome of step 2, apply to estimation model to true menhaden data

18. Simulation model • Separated coastwide stock into 3 sub-stocks based on areas of recruitment: • North • Middle • South • For example, menhaden recruited from North Atlantic will form part of the Northern stock, even though they may be offspring of fish from other areas Hypothesized winter (blue), summer (cyan) and spring/fall (red) transition distributions for the aggregate stock

19. Components of model GUI interface • RUN button • Relative habitat parameters: • relative proportion of unfished • recruits to each area • Stock parameters: • Ro=unfished recruits • recK=Goodyear’s compensation • ratio • Egg proportion vectors: • describes how eggs are allocated • among areas by age-group

20. Components of model GUI interface • SAVE options: • allows user to set up scenarios to • be recalled later (i.e., different • parameter combinations) • Constant model parameters: • many parameters kept constant • Relative abundance surveys: • LIDAR, otolith microchemistry • Stock proportion matrices: • annual spatially integrated • menhaden distribution

21. Components of model GUI interface • Estimation model • Runs and assessment model: • -3 sub-stocks • -estimates leading parameters • including stock prop. matrices • with input data: • -catch-at-age • -juv, adult CPUE • -possibly LIDAR and/or • otolith microchemistry

22. Model Description • Simulation, estimation models are structured identically: • – time 1940 – 2005 • – simulation model: simulates population given sub-stock structure and can generate relative abundance indices • – estimation model: uses generated relative abundance indices to estimate leading parameters Leading parameters State variables Habitat Stock Nos. in stock s by year, age Biomass in stock s by year Ro, recK, mort-at-age, age-vul. by fishery (w/ errors), growth parameters (von Bert, power funcs). Area, egg & stock proportions

23. Simulation model results • Simulated abundance data by stock – population originates from Middle region (68.8%), based on weights used by ASFMC for juvenile indices

24. Estimation model results • Model is able to estimate Ro and recK fairly well

25. Estimation model results • Model is not able to estimate stock proportion matrices because, i.e., cannot resolve numbers of fish in each area • No information about stock proportions are contained in the observation indices

26. Estimation model results

27. Estimation model results

28. Some conclusions • The spatially-implicit menhaden model allows for exploration of sub-stock structure • Effects of known removals for each region can be quantified for stock within-areas and the aggregate stock • Indices from LIDAR and otolith microchemistry did not help with estimation of stock proportion matrices • – suggests studies may only help with estimates of absolute population size and seasonal localized depletion in Chesapeake Bay