fountain darter model
DESCRIPTION
Fountain Darter Model. Bill Grant Hsiao- Hsuan Wang (Dr. Rose) University of Texas Texas A&M University May 12, 2014. Outline (Plan A). I. A bit of modeling philosophy II. The current model Model input / output Model structure Model function Model programming III. The future model - PowerPoint PPT PresentationTRANSCRIPT
Fountain Darter Model
Bill GrantHsiao-Hsuan Wang
(Dr. Rose)University of Texas
Texas A&M UniversityMay 12, 2014
Outline (Plan A)I. A bit of modeling philosophyII. The current model
• Model input / output• Model structure• Model function• Model programming
III. The future model• Available data• UseS of data in model• Hypothesized relationships
IV. Predicting the future? (Embracing uncertainty)• Parametric uncertainty• Structural uncertainty
Outline (Plan A)I. A bit of modeling philosophyII. The current model
• Model input / output• Model structure• Model function• Model programming
III. The future model• Available data• UseS of data in model• Hypothesized relationships
IV. Predicting the future? (Embracing uncertainty)• Parametric uncertainty• Structural uncertainty
Rosen (1991) in Saltelli et al. (2008)
Naturalsystem
Formalsystem
Entailment
Entailment
EncodingDecoding
Modeling
Outline (Plan A)I. A bit of modeling philosophyII. The current model
• Model input / output• Model structure• Model function• Model programming
III. The future model• Available data• UseS of data in model• Hypothesized relationships
IV. Predicting the future? (Embracing uncertainty)• Parametric uncertainty• Structural uncertainty
Model Input
Water flow
Aquatic Habitat
Fountain DarterPopulation Structure and Dynamics
Model Output
Veg. type
Time
Egg
Larv
a
Juve
nile
Adul
t Aquatic vegetation typeWater depth
Water velocity
Water temperature
Life cycle HabitatMovement
Model Structure
Egg laying = f (month)Schenck and Whiteside (1977)
Egg mort. = f (temp.)Larva mort. = f (temp.)Juvenile mort. = f (temp.)Adult mort. = f (temp.)
Picher and Hart (1982)Brandt et al. (1993)Bonner et al. (1998)
Density-dependent mort. = f (# veg. patches)
Movement= f (veg. type)
Stay in habitat patch with vegetation
Move toward habitat patch with vegetation
Aquatic veg. type = f (season)Jan. 2003Dec. 2008
Bio-West annual reports
Water depth = f (flow)Old Channel
10 - 80 cfsHardy et al. (2010)
Water velocity = f (flow)Old Channel
10 - 80 cfsHardy et al. (2010)
Water temp. = f (hour)Jan. 2003Dec. 2008
Bio-West annual reports
Model Function
Life cycle Movement Habitat
1 Initialization
2 Input2.1 Input vegetation types
2.2 Input water temperatures
2.3 Input water depths and water velocities
3 Submodels3.1 Adjust vegetation types (seasonally)
3.2 Adjust water depths and water velocities (daily)
3.3 Adjust water temperatures (hourly)
3.4 Adjust fountain darter ages and developmental stages (daily)
3.7 Calculate fountain darter egg laying (recruitment) (daily)
3.5 Calculate fountain darter mortalities (daily)
3.6 Calculate fountain darter movements (hourly)
3.8 Update aggregated (output) variables (hourly)
Model Programming
Outline (Plan A)I. A bit of modeling philosophyII. The current model
• Model input / output• Model structure• Model function• Model programming
III. The future model• Available data• UseS of data in model• Hypothesized relationships
IV. Predicting the future? (Embracing uncertainty)• Parametric uncertainty• Structural uncertainty
Available Data
Driving Variables (Input) Data
Process Data (Functional Relationships for Model Equations)
Evaluation (of Output) Data
Aquatic Vegetation Datamapping of vegetation typesplant growth = f (temp.)plant biomass = f (% veg. cover)
(2014) plant growth rate and dispersal= f (substrate, depth, velocity)
Fountain Darter Datadensity = f (veg. type)
(Drop nets)Size class distribution
(Dip nets)
mortality = f (temp.)fecundity = f (habitat quality)predation = f (veg. density)movement = f (habitat
preference, dispersal)
(2014)
UseS of Data in Model
E L J A
Depth
VelocityRecr. &
DOMort. = f
Temp.
FoodCover/Pred.
f (veg.)
Veg.
Flow
f (flow)
Movement = f (veg., flow)
Veg. =
f ( flow, veg. restoration, recreation, substrate, light)
Substrate Light
Veg. restoration Recreation
Hypothesized Relationships
Model Input
Water Flow
Aquatic Habitat
Fountain DarterDynamics
Model Output
Outline (Plan A)I. A bit of modeling philosophyII. The current model
• Model input / output• Model structure• Model function• Model programming
III. The future model• Available data• UseS of data in model• Hypothesized relationships
IV. Predicting the future? (Embracing uncertainty)• Parametric uncertainty• Structural uncertainty
Predicting the future?(Embracing uncertainty)
“Oye filósofo ¿va a llover por la noche?”“Te digo mañana.”
(El Filósofo de Guemes)
Naturalsystem
Formalsystem
Entailment
Entailment
EncodingDecoding
Estimated parameters
Uncertainty and sensitivity
analysis
Model Input data
Inference
Saltelli et al. (2008)
Estimation
Parametric bootstrap version of uncertainty and sensitivity analyses
Estimated parameters
ModelLoop on boot-replica of the
input data
Inference
Chatfield (1993) in Saltelli et al. (2008)
Estimation
Bootstrapping of the modeling process (Structural uncertainty)
Modelidentification
Bootstrap of theModeling process
Bayesian model averaging
Data
Prior of model(s)
Prior of parameters
Inference
Posterior of model(s)
Posterior of parameters
Sampling
Saltelli et al. (2008)
The End