1. with contributions from:
An innovative modeling approach for simulating hypoxia/anoxia in estuarine ecosystems
Mark J. Brush
James N. Kremer
Scott W. Nixon
with contributions from:
John Brawley
Nicole Goebel
Jamie Vaudrey

2. USE OF MODELS IN MANAGEMENT
Chesapeake Bay Model
Baretta & Ruardij
(1988)
ERSEM I
(1995)
ERSEM II
(1997)
Odum
(1983)
(1994)
Riley
(1946, 1947)
Steele
(1974)
Kremer
& Nixon
(1978)
Rigler & Peters
Also:
Reckhow (1994 & others)
Håkanson (1995, 2004)
Hofmann & Lascara (1998)
Pace (2001)
Duarte et al. (2003)
Fulton et al. (2003)
NUMBER OF PUBLICATIONS
USE OF MODELS IN MANAGEMENT

3. Trade-off between realism & predictability:
Increasing complexity / realism
# of parameters
predictability
Loss of
utility at
lowest
complexity?
Generality
Precision
Realism
Because this is certainly one of the more challenging topics I’ve had to talk about, I’ve sketched roadmap to help us all navigate these tricky waters.
R. Levins (1966, 1968)

4. Published Gmax Functions
Phytoplankton
Primary
Production
Published Gmax Functions
Brush et al.
(2002)
elevated
Eppley
Gmax , d-1
Eppley
Curve
TEMPERATURE, oC

5. Duarte et al. (2003)
“The Limits to Models
in Ecology”

6. Can we find a middle ground?
Empirical
“Stressor-Response”
Models
Can we find a middle ground?
Generality
Precision
Question:
Can a simplified eutrophication model be useful as a heuristic and management tool?
R. Levins
(1966, 1968)
Parsimony Principle
Ockam's Razor
Realism
Complex,
Mechanistic
Systems
Models

7. Estuarine Eutrophication Model

8. * Need to accurately model
Estuarine Eutrophication Model
* Need to accurately model
both states and rates
Phyto
Production
Pelagic
Respiration
C flux to sediments
Macro
Metabolism
Denitrification

9. Light x Biomass (“BZI”) Models … capped by available nutrients
Phytoplankton
Primary
Production
Light x Biomass (“BZI”) Models
Pd = *Chl*Zp*PAR + 
… capped by available nutrients
Cole & Cloern (1987) MEPS v. 36
Brush et al. (2002) MEPS v. 238

10. Water Column
Respiration
Rd = *e kT*Chl10

11. Estuaries and Nutrients
Carbon Flux to
Sediments &
Benthic Respiration
Nixon (1981)
Estuaries and Nutrients
The Humana Press
Csed = 0.25*Pd
Rsed = *e kT

12. Denitrification DENIT = Nload*f(RT) Nixon et al. (1996)
Biogeochemistry 35(1)
DENIT = Nload*f(RT)

13. … a hybrid, empirical-mechanistic
Empirical Functions
Robust, data-driven, & apply across several systems - ideal when
mechanistic formulations are insufficient or poorly constrained.
Reduce model complexity by integrating multiple processes
(which are often poorly constrained) into simplified, bulk functions.
Produce output we can measure and test.
Excellent tools for model validation.
… a hybrid, empirical-mechanistic
approach

14. Greenwich Bay Eutrophication Model
Greenwich Bay, RI
(Avg Z = 3 m)

15. Surface Phytoplankton
Lower West
Passage Chl-a

16. Surface DIN

17. Bottom O2

18. Bottom O2 with Forced Maximum Chlorophyll a
original run
max chl

19. * Need to accurately model Annual Primary Production
both states and rates
Rate Processes
In the absence of flux measurements 
model
MERL fcn of T, Chl, NPP
Annual Primary Production
g C m-2 y-1
Observed: 281 – 326
Modeled:

20. System-Level Validation: Nutrient Reduction Scenarios
Keller (1988)
Nixon et al. (2001)
Nixon et al. (1996)

21. Empirical-Mechanistic
Empirical Models
Complex,
Mechanistic
Systems
Models
A Simplified, Hybrid
Empirical-Mechanistic
Systems Model
Generality
Precision
R. Levins
(1966, 1968)
Realism
Multiple, parallel modeling
approaches, e.g.:
Latour, Brush & Bonzek (2003)
Scavia et al. (2003)
Borsuk et al. (2002, 2004)

22. Models for Hypoxia Applied in Narragansett Bay
Oviatt et al.
Models for Hypoxia Applied in Narragansett Bay
NOAA Coastal Hypoxia
Research Program
Because this is certainly one of the more challenging topics I’ve had to talk about, I’ve sketched roadmap to help us all navigate these tricky waters.

23. Full 3D resolution in ROMS:
Because this is certainly one of the more challenging topics I’ve had to talk about, I’ve sketched roadmap to help us all navigate these tricky waters.

24. Nutrient Reduction Scenarios
Bottom O2, mg/L
0% watershed N,P
0% Narr. Bay N,P
0% Narr. Bay N,P
& saturating O2

25. LOWER
NARRAGANSETT
BAY
PROVIDENCE
RIVER

26. Scope for Improvement: Pre-Colonial Inputs
Bottom O2
Nixon (1997)
Estuaries 20(2)

27. Effect of Macroalgal Decomposition
Bottom O2
Bottom O2

28. Effect of Macroalgal Decomposition

29. Stochastic Simulation
Kremer (1983)
Bottom O2

30. Dr. Brush’s wardrobe provided by:
Acknowledgements
James N. Kremer
Scott W. Nixon
John Brawley
Nicole Goebel
Jamie Vaudrey
Dr. Brush’s wardrobe provided by:
Bay St. Louis Kmart