Modeling aquatic vegetation for Comal and San Marcos river systems

Todd M. Swannack, Ph.D.US Army Engineer Research and Development CenterEnvironmental LaboratoryVicksburg, MS

Vegetation in the River systems• Comal and San Marcos vegetation is incredibly dynamic

(influenced by physical environment, existing distributions, and human-driven factors)

• Major species for each system

• Models need to capture dynamism of the system

Comal• Hygrophila• Ludwigia• Sagittaria• Vallisneria• Bryophytes• Cabomba

San Marcos• Wild Rice• Hydrilla• Hygrophila• Potamogeton• Sagittaria• Vallisneria• Ludwigia

Vegetation Changes 2003 – 2005

Summer 2003 Fall 2003 Spring 2004 Fall 2004 Spring 2005 Fall 2005

Model structure• Spatially-explicit, agent-based model, programmed in

Netlogo

• Prototype: Old Channel, Comal River• Spatial domain and scale: same as fountain darter

model, cell size of 0.25m2 (can upscale if needed)

• Temporal scale: varying, depending on the process within the model. Also scalable (e.g., darter-plant interactions may occur on a time scale that we haven’t considered yet)

Major Processes• Growth/Senescence (intra-cell dynamics)

• Dispersal (inter-cell dynamics)

• Recolonization after disturbance event (inter-cell dynamics)

Growth Modeling• ERDC/MEGAPLANT• Mass-balance, carbon flow, biomass

model (100+ parameters)• Simulates above & belowground biomass

for single species

• Designed to simulate conditions in which plants can persist or when plants produce excessive biomass

• Inputs: temperature, irradiance, water depth & transparency

• Outputs: biomass in various states (tubers, roots, leaves & shoots)

Growth Modeling• Cons of these models• Spatially-implicit

• Dispersal is not in the model

• Single species (no competition)

• No current links b/w biomass and existing data (spatial coverage)

• As they currently exist, ERDC models do not address ecosystem-level questions being asked for this project, and are over parameterized for those questions

• Computationally intractable at fine spatial scale of fountain darter model

Current Growth Modeling• Simplify growth models to

capture critical components

• Add characteristics for structure, native/non-native to agent-class

• Current data indicate darters are more often found in native species (e.g., Vallsneria vs Hygrophilia, which are structurally similar)

• Simulate intracell growth• N = biomass in cell i• r = intrinsic growth rate• κ = carrying capacity for each

cell (going to try to link this to percent cover)

𝑵 𝒊 , 𝒕+𝟏=𝑵 𝒊 , 𝒕+𝒓 𝒊 ∙𝑵 𝒊 ,𝒕 ∙ [𝟏−𝑵 𝒊 , 𝒕 ∙𝜿−𝟏 ]

Dispersal Modeling• What’s the probability that a plant

in cell j is colonized by plants from cell i?

• Following Wang et al 2010, 2012• Calculates dispersal based on

lognormal dispersal kernal(kji) • D = Euclidian distance b/w j & I • S = constant (shape parameter,

assumed 1)• L = dispersal velocity (scale

parameter)

• Recolonization will be treated the same way

:

Conceptual Model

: :

𝑁 𝑖 ,𝑡+1=𝑁 𝑖 , 𝑡+𝑟 𝑖∙𝑁 𝑖 ,𝑡 ∙ [1−𝑁 𝑖 ,𝑡 ∙ κ− 1 ]+ ∑

𝑗=1, 𝑗≠ 𝑖

𝑞

𝑘 𝑗𝑖 ∙𝑁 𝑗 ,𝑡

Intracell growth Intercell dispersal

Integrated System

1 Initialization

2 Input2.1 Input vegetation maps

2.2 Input physical parameters

2.3 Input water depths and water velocities

3 Submodels3.1 Update physical parameters (daily)

3.2 Calculate growth and senescence

3.3 Calculate dispersal

3.4 Update aggregated variable (output)

Model Programing

Model evaluation

• Submodels will be evaluated for ability to simulate field dynamics within reasonable range of error

• System model will be evaluated using pattern-oriented modeling (following work of Grimm, Railsback, Topping, and colleagues)

• Basic principle is to identify emergent patterns that result from interactions of model components and compare those patterns to patterns in the real system

Questions?• Contact information:• Todd.m.swannack@usace.army.mil• 601-415-3509