U.S. Department of the Interior

U.S. Geological Survey

Fact Sheet 2004-3110

October 2004

Modeling the Effects of Hydrology on Fire, Vegetation

Dynamics, and their Interaction in the Florida Everglades

Printed on recycled paper

Plant communities are key components of the Greater 

Everglades. In addition to providing food and shelter to higher 

trophic level species, plants influence abiotic ecosystem processes such as fires. The hydrologic modifications, proposed as 

part of the Comprehensive Everglades Restoration Plan (CERP), 

will affect both the spatial distribution of plants through time 

and the fire regime. Changes in the local complement of plants 

can influence the frequency and intensity of fires in a given area 

through consequent changes in flammability and rates of fuel 

production. Hydrologic restoration may, therefore, contribute to 

the restoration of more natural fire patterns by altering the local 

risk of fire in different areas. Fires also play an important role 

in shaping the floral landscape. For example, some fires burn 

soils, lowering local topography and changing local hydrologic 

patterns. Fires also can result in the establishment of fire-climax 

communities, and therefore, are capable of altering the local 

plant community structure and composition.

Understanding the complex interrelationships among these components and processes 

is an important part of evaluating hydrologic 

restoration efforts. Under the Across Trophic 

Level System Simulation (ATLSS) Program, 

models have been developed for vegetation succession and fire that incorporate the 

effects of hydrology. These models examine 

relative differences under proposed hydrologic changes in the: (1) number, diversity, 

and spatial configuration of Everglades 

plant communities; and (2) number, size, 

frequency, and distribution of fires in the 

Everglades.

The Shared Model Environment 

The ATLSS vegetation succession and 

fire models are designed to share a common 

model area, spatial configuration, land cover 

map, and hydrologic input. The model area 

covers most of the natural areas of southern 

Florida, including the water-conservation 

areas, Everglades National Park, and Big 

Cypress National Preserve (fig. 1). Modeling over this entire area presents substantial 

computational challenges, but is necessary in 

order to capture the dynamics of an interconnected system and provide an assessment tool 

in which relations between subregions can be 

evaluated. 

The model grid is spatially divided into cells representing 

500 x 500 m (meter) plots. At this scale of resolution, about 

73,000 grid cells are required to cover the ATLSS model area. 

The vegetation succession model classifies each plot as containing a single vegetation type. Currently, the vegetation types 

are based on those used by the Florida Gap Analysis Project 

(FGAP) for the FGAP map (Pearlstine and others, 2002). FGAP 

is used to initialize the spatial distributions of vegetation in the 

vegetation succession model.

Hydrologic input for the models is based on the output of 

the South Florida Water Management Model (SFWMM), which 

is the standard tool for projecting hydrologic patterns resulting 

from changes in water management in southern Florida. ATLSS 

High Resolution Hydrology (HRH) interpolates SFWMM 

output, provided at a 2-mi (mile) scale of resolution, over a 

high-resolution topography map to create water depths at a 

500-m scale over the model area. 

Figure 1. Boundary of ATLSS modeling region in southern Florida. BCNP is Big Cypress National 

Preserve, ENP is Everglades National Park, and WCA is Water Conservation Area.

MONROE COUNTY

COLLIER COUNTY

COLLIER COUNTY

HENDRY COUNTY

PALM BEACH COUNTY

MIAMI-DADE CO

BROW

BROWARD CO

25°

26°

27°

83° 82° 81° 80°

KEYS

TAMIAMI CANAL

GULF OF MEXICO

Everglades Agricultural Area

Big Cypress National Preserve

Biscayne National Park

Fakahatchee Strand State Preserve

Everglades National Park

Water-conservation area and number

Indian Reservation Lands

Canal or levee

EXPLANATION

Boundary of ATLSS modeling region TLSS modeling region Florida Bay

0

25

25 50 KILOMETERS

50 MILES
The ATLSS Vegetation Succession Model 

The ATLSS Vegetation Succession Model (VSMod) simulates the pattern of spatial and temporal changes in the distribution of vegetation in the Greater Everglades landscape as a 

function of the hydrologic regime, patterns of fire disturbance, 

and nutrients. A primary goal is to quantify the relative differences between various hydrologic scenarios as reflected in their 

impacts on vegetation succession.

VSMod incorporates a spatially explicit, stochastic cellular 

automata model to simulate vegetation succession. At any 

given time, each 500 x 500-meter plot is in one of a finite 

number of states. The transition between states occurs with 

a probability that varies in both space and time, dependent 

on local hydrologic and fire history as well as on the current 

vegetation. The model runs on a yearly time step, synchronized 

with the fire model, and produces annual maps of vegetation 

over the model area.

VSMod rules are based on reports by Wetzel (2001a; 2001b). 

Three modeled factors influence the succession of one plant 

association to another: fire, nutrient change, and prolonged 

change in hydrologic conditions. When hydroperiods increase 

for 2 consecutive years or decrease for 3 consecutive years, 

change occurs with a probability between 0 and 1 for each 

year of continued hydroperiod change. Any interruption in the 

hydroperiod trend resets the consecutive year count.

The type of vegetation in a plot affects succession by determining hydroperiod ranges for persistence, rate of transition to 

a new type, fire frequency required for persistence, maximum 

probability of burning, and time to recover following a fire. 

Hydroperiod and fire frequency ranges for most herbaceous 

and forested vegetation types in the model area are presented in 

table 1 ordered horizontally by the range of hydroperiods and 

vertically by the range of fire frequencies. Each color represents 

similar or identical groups of vegetation types. When more than 

one plant community can occur within a given hydroperiod and 

fire interval, transitional probabilities are computed based on the 

proportional aerial representation of plant associations within 

the model area. Succession can move forward or backward 

within the scale of possible transitions. 

Pending availability of output from more complex nutrient models, the nutrient component of VSMod is based on an 

empirical relation (Reddy and others, 1993; 1998) that estimates 

nutrient concentration as a function of distance from watercontrol structures.

The ATLSS Fire Model 

The purpose of the ATLSS fire model is to provide annual 

estimates of the spatial distribution of areas burned by naturally 

occurring fires in the Florida Everglades (fig. 2). The ATLSS 

fire model provides input for the ATLSS vegetation succession 

model (VSMod), whereas VSMod provides local vegetation 

information for the fire model, simulating the effects of feedback between fire history and vegetation (fig. 3). The yearly 

time step of the model ends on May 31, the end of the natural 

fire season.

The ability to input yearly map layers of historical fire distribution has also been incorporated into VSMod to investigate 

historical patterns of vegetation change. The available data are 

incomplete, however, lacking information for some regions and 

time periods, and historical data do not permit projecting fire 

distributions under alternative hydrologic management 

scenarios. Historical data can be leveraged to parameterize 

the fire model, which will be used to estimate the annual area 

burned across the entire landscape. The model allows future fire 

conditions to be estimated and the effects 

incorporated into Everglades restoration 

planning. 

Vegetation information is provided 

by VSMod, which classifies each plot as 

containing 1 of 25 natural vegetation types. 

In the fire model, the 25 FGAP vegetation 

types are aggregated into five more general 

groups: grasses, pines, hardwoods, flooded 

vegetation, and shrubs. All types within a 

group are assumed to have similar probabilities of burning and are assigned a single 

group-level maximum and minimum burn 

probability. 

Table 1. Hydroperiod and fire 

frequency ranges for most 

vegetation types in the model area

[The horizontal axis is the range of 

hydroperiods (days); the vertical axis is 

the range of fire frequencies. Numbers 

in brackets are the FGAP v. 6.6 plant 

class numbers. Colors indicate similar 

or identical groups of vegetation types]
The ATLSS fire model provides estimates of the spatial 

distribution of both hot and cool fires. Hot fires are those that 

result in the death of trees and/or the burning of soils and peat 

material. These fires reset the successional process to “early” 

vegetation types. Cool fires are those that do not kill trees or 

burn soils. These fires burn only above-ground portions of 

plants and arrest succession at different stages of development 

depending on fire frequency. 

Fire Ignition and Spread 

The model simulates landscape-scale fire patterns by modeling fire spread as a collection of local stochastic processes. 

Each plot is represented by a stochastic cellular automata model 

and is in one of three states: unburned, burned by cool fire, or 

burned by hot fire. Transitions between these states are stochastic and dependent on local environmental conditions and the 

presence or absence of fire in the adjacent plots. 

The model assumes that all natural fires are caused by 

lightning strikes. The spatial distribution of area burned for each 

year is estimated by computing for each plot in the landscape 

the number of lightning strikes, the probability of burning, and 

the number of resulting fires. Finally, fire spread is simulated, 

incorporating a locally determined conditional probability of 

burning given that a neighboring plot is burning. 

We estimate the number of lightning strikes each year during 

the natural fire season using annual rainfall data based on two 

empirical relations (Beckage and others, 2003). The first of 

these relates El Nino Southern-Oscillation (ENSO) to annual 

winter rainfall in southern Florida, and the other relates ENSO 

to the annual number of lightning strikes in southern Florida. 

We then distribute the lightning strikes randomly across the 

landscape. Each plot that is struck by lightning has a probability 

of igniting. 

The local burn probabilities are determined for each plot 

based on local environmental conditions including vegetation 

type, fire history, and hydrology which interact and change 

through time. Although the range of burn probabilities is 

determined by vegetation type, the local fire history and hydrologic conditions determine the specific value within the range. 

The probability of burning is low in the year following a fire, 

increasing each subsequent year without fire until the maximum 

burn probability is reached. Within this chronology, fire probabilities tend to vary inversely with hydroperiod length (fig. 4). 

The highest probability is associated with short hydroperiods 

and follows a smooth decrease as the hydroperiod increases. A 

directional bias incorporates the effect of prevailing winds by 

modifying local burn probabilities of neighboring plots based on 

their position relative to a burning plot.

Model Parameterization 

The parameters for: (1) maximum and minimum hydroperiod 

preference for each vegetation type, and (2) the time required 

to return to maximum burn probability after a fire are assigned 

values provided by Wetzel and others (2001b). The remaining 

parameter values for burn probabilities of the five vegetation 

groups are estimated based on data from Everglades National 

Park fire records of the date, source of ignition, and area burned 

by documented historical fires. From these data, we create 

distributions of fire sizes and frequencies for use in estimating 

model parameter values.

Figure 2. Fire in the pinelands of Everglades National Park, 1974. 

Photo by Dale Wade, U.S. Department of Agriculture Forest Service, Invasive.

org. Used with permission. 

Figure 3. Proposed relation 

between time since last fire and 

probability of burning. In this 

function the probability is at pmin,v

in the first year following a fire, 

where pmin,v is the minimum probability of burning for vegetation 

type v. The probability of burning increases yearly until pmax,v is 

reached, which is the maximum 

probability of burning for vegetation type v. The parameter TR,v

represents the time required 

to return to the maximum burn 

probability.

TIME SINCE LAST FIRE (YEARS)

PROBABILITY OF FIRE (p ) fire

0

0 1

pmin,v

pmax,v

TR,v
Future Work 

The current effort has focused on modeling natural fires. 

However, later versions of the model could incorporate several 

anthropogenic aspects of fire dynamics, including: (1) managed 

burns and their effects on succession, and (2) manmade fire 

breaks, such as airboat trails, which retard fire spread.

References Cited

Beckage, B.W., Platt, W. J., and others, 2003, Influence of the 

El Nino southern oscillation on fire regimes in the Florida 

Everglades: Ecology, v. 84, no. 12, p. 3124-3130.

Pearlstine, L.S., Smith, S., and others, 2002, Assessing statewide biodiversity in the Florida Gap Analysis Project: Journal 

of Environmental Management, v. 66, p. 127-144. 

Reddy, K.R., DeLaune, R.D., and others, 1993, Long-term 

nutrient accumulation rates in the Everglades: Soil Science 

Society of America Journal, v. 57, p. 1147-1155. 

Reddy, K. R., Wang, W., and others, 1998, Forms of soil phosphorus in selected hydrologic units of the Florida Everglades: 

Soil Science Society of America Journal, v. 62, p. 1134-1147. 

Wetzel, P., 2001a, Plant community parameter estimates and 

documentation for the Across Trophic Level System Simulation (ATLSS): Accessed at http://www.tiem.utk.edu/~sylv/ http://www.tiem.utk.edu/~sylv/

HTML/Everglades/VSMod-HTML/index.html 

Wetzel, P., 2001b, Nutrient and fire disturbance and model 

evaluation documentation for the Across Trophic Level System Simulation (ATLSS): Accessed at http://www.tiem.utk.

edu/~sylv/HTML/Everglades/VSMod-HTML/index.html 

For further information contact: 

Donald L. DeAngelis 

U.S. Geological Survey

Florida Integrated Science Center

Water and Restoration Studies

University of Miami 

Coral Gables, FL 33124 

ddeangelis@umiami.ir.miami.edu

Scott M. Duke-Sylvester, Louis J. Gross 

The Institute for Environmental Modeling 

University of Tennessee 

Knoxville, Tennessee 37996 

sylv@tiem.utk.edu 

gross@tiem.utk.edu

Figure 4. Proposed relation between 

hydroperiod (hp) and probability of 

burning. In this relation, the highest 

probability is given by pfire,v(t) as 

obtained from the relation shown in 

figure 3 and is associated with short 

hydroperiods. The value pmin,v is the 

minimum probability of burning for 

vegetation type v. The values hpmax,v

and hpmin,v provide a maximum and 

minimum hydroperiod preference for 

vegetation type v. The form of the 

relation is given by one minus the 

cumulative distribution function for a 

normal distribution where 95 percent 

of the normal distribution is between 

hpmax,v and hpmin,v.

hp hpmax,v min,v

pmin,v

pfire,v

HYDROPERIOD (DAYS)

PROBABILITY OF FIRE (p )b