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A Synthesis of Models to Simulate Benthic-Pelagic Coupling in Florida Bay: Examination of
Ecosystem Restoration and Climate ChangeChristopher J. Madden1, Amanda McDonald1, Marguerite Koch2, Patricia Glibert3,
Cynthia Heil4, Bernard Cosby5
SFWMD Everglades Division, Univ. MD HPL, FL Atl. Univ., FL FWCC, Univ. VAFlorida Bay Science Conference
Naples, FLDecember 2008
Christopher J. Madden1, Amanda McDonald1, Marguerite Koch2, Patricia Glibert3, Cynthia Heil4, Bernard Cosby5
SFWMD Everglades Division, Univ. MD HPL, FL Atl. Univ., FL FWCC, Univ. VAFlorida Bay Science Conference
Naples, FLDecember 2008
22
Florida Bay and the Everglades Watershed:SFWMM, TIME, SICS Model Domains
Florida Bay and the Everglades Watershed:SFWMM, TIME, SICS Model Domains
33
Integration of Watershed Hydrologic Models
Integration of Watershed Hydrologic Models
Langevin et al. (2004)
44
Grid Mesh for Florida Bay Environmental Fluid Dynamics Code (EFDC) & Water Quality ModelGrid Mesh for Florida Bay Environmental Fluid Dynamics Code (EFDC) & Water Quality Model
Hamrick (2006)
55Hunt et al. (2006)
FATHOM (Flux Accounting and Tidal Hydrology Ocean Model)
FATHOM (Flux Accounting and Tidal Hydrology Ocean Model)
Cosby et al. (2005)
66
Florida Bay SAV Numerical Ecological Model Calibration Sites
Nuttle et al. (2005) EvergladesNational
Park TaylorSlough
Florida Bay N
Florida Keys
Madden et al. (2007)
77
Seagrass Community Ecological Model
Madden et al. (2007)
88
Environmental Effects on Plant Growth
(PAR)0 1000 2000
1
15 25 35Temperature (°C)
0
1
Temperature Effect
Salinity Effect
1
0 10 20 30 40 50 60
Phosphorus Concentration (uM)0 1 2
1
Phosphorus Uptake
1
0 5 10 15Nitrogen Concentration (uM)
0 1 2
1
Nitrogen Uptake
Halodule
ThalassiaR
elat
ive
Gro
wth
P vs I
Sulfide Toxicity
Madden et al. (2005)
Halodule
Thalassia
Halodule
Thalassia
Halodule
Thalassia
Halodule
Thalassia
99
Little Madeira Bay (Inner Site)
High Salinity
Salinity output from FATHOM Cosby et al. (2005)
SAV from Madden et al. (2006)
Sal
inity
SA
V
Integrating FATHOM and SAV Models for MFL: Reconstruction of SAV Community: 1970-2002
HaloduleThalassia
1010
Integrating the FATHOM and SAV Models for MFL:Halodule Model Response to Salinity
1111
Eastern Florida Bay Algal BloomChlorophyll a (μg/l)2006-2007 average
Chlorophyll a (μg/l)Jan 8-10, 2008
1212
NewP
Recycled N&P
Variable C:PVariable C:chla
Net Settling 1-15%
Grazing 0-20%
Advection
SAV
Epiphytes
Phytopl
Sediment P
Below ground
Sediment OM
Seagrass Community Phytoplankton Module
Seagrass Community Phytoplankton Module
ResuspensionRemin P
40%~100%
Bound P Available P
Advection (TT=10-120 d)
Geochemical Sequestration
N Substrate
NH4 NO3 urea
1313
Characteristics of the Phytoplankton Module
Characteristics of the Phytoplankton Module
Dependency on RecyclingDependency on Retention TimeDependency on Grazing RateP Limitation/Injection and BloomN Substrate PreferenceMechanistically Incorporates Variables Linked to Climate Change: depth, light, temperature, salinity response
1414
Basin Turnover Time and P Recycling EfficiencyBasin Turnover Time and P Recycling Efficiency
5 YR
Chl
a ug
/L
6
12Turnover= 20d
10 YR
6
6
6
12
6
12
6
12
5 YR 10 YR
Recycling= 0.4
Recycling= 0.6
Recycling= 0.8
Chl
a ug
/L
12
Turnover= 60d
12 Turnover= 40d
1515
Grazing (Sponges)Grazing (Sponges)
Chl
a ug
/L
5
10
10
5
Filtration= 10% d-1
Filtration= 15% d-1
1616
Model SensitivityModel Sensitivity
Least Sensitive to Turnover Time<< Nutrient Competition (epiphytes)<< Recycling Efficiency<< GrazingMost Sensitive to New Nutrient Inputs (in sufficient quantity)
1717
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0.00 912.50 1825.00 2737.50 3650.00
Days
1:
1:
1:
0
10
20
1: chla conc
Untitled
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Days
1:
1:
1:
0
25000
50000
1: TAG
Thalassia
SAV
mg
C/m
2 25000
5 YR
Chl
a ug
/L 10
20Phytoplankton
Untitled
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Days
1:
1:
1:
0
1000
2000
1: PAR @ SAV leaf
PAR
PAR
5 YR 10 YR
1000
2000
50000
Barnes Sound Algal Bloom Simulation: P injection(Road? C111? Other?)
5 YR
15% (high) settling; 85% recycling
10 YR
10 YR
P injection
1818
SAV Decline in Barnes Sound
Frequency of quadrats with high density and sparse vegetation
dense cover
sparse cover
Oct 05 Jan 06
(DERM data; Rudnick et al. 2008)
Begin increase in freq. of sparse cover Oct. 2005-Jan 2006
00.10.20.30.40.50.60.70.80.9
1
Freq
uenc
y
01/2
001
01/2
003
01/2
005
01/2
007
Y Freq(Bare+Sparse Tot) Freq(Dense Tot)
01/2
006
1919
ConclusionsConclusions
Due to shallow, highly coupled nature, bay is poised
Model can identify inflection or “tipping” points where system has a potential to undergo state changeSometimes small change = Big ChangeWe are somewhere between a Box of Models and a Real Model Synthesis
We can use simple transport and heuristic models to understand ecological responses
Models are now being used in synthetically in developing statutory freshwater requirements and in evaluating restoration designs in the context of climate change
SAV Model Fortran algorithms are incorporated in EFDC and
Model links to FATHOM, therefore SAV and WC/WQ module interacts with 2x2, RSM, SICS, PHAST and the HYCOM boundaryUpwardly linked to GAM Higher Trophic Models and HSMsWill be linked to the mangrove transition zone model