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Fire Ecology

by Ryan Kelly (Submitted: 06/01/2009)

[screen shot]

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WHAT IS IT?

This is a simplified but reasonable model of wildfire occurrence intended for use as an educational tool. It has specific applications to wildfire ecology and management, but primarily serves as an example of the complex effects possible when many variables interact to produce a result, and the important role models can play in experimenting with such a system.

HOW IT WORKS

The model calculates the number of lightning strikes occurring on dry days, based on the length of the fire season, the number of days it rains, the time it takes for the landscape to dry after a rain, and the number of lightning strikes per season.

Each lightning strike occurring on a dry day then has a certain probability of igniting a fire, which is based on the age of the patch of forest struck, and the flamability (Fm) of the forest type. Ignited fires spread from patch to patch based on the same parameters.

As in a real forest, a patch can't burn for a certain amount of time after it's burned already (set by variable Lag). In addition, forests become more flammable as they age, modeled by the Mature_Age variable; the longer it takes to reach Mature_Age, the slower the flammability of the forest increases.

Finally, the model includes an approximation of (human) fire suppression effort. The higher the value of the Suppression variable, the more burning pixels will be targeted for suppression (whether suppression is successful is random). As a result of this design, even a small amount of suppression will likely be effective as long as there are only a few burning pixels. If a fire chances to get rather large, however, the suppression effort quickly becomes ineffective.

HOW TO USE IT

"Setup" and "Go" buttons work as usual, and "Reset Parameters" returns all parameters to their default values.

All parameters can be modified in real time. A message in the command center lets you know how many dry-day lightning strikes are occurring each year (one time step), and alerts you if your parameters are such that fire is impossible.

The plots keep track of the number of individual fires per year, as well as the area burned each year.

THINGS TO NOTICE

Notice that the different variables all affect fire occurrence in their own way, and that different ones may enhance or negate each other. There are many ways to produce huge or very frequent fires, or to stop fire occurrence altogether. Most natural ecosystems fall somewhere in between, highlighting their delicate balance of vegetation species, climate, and fire occurrence.

THINGS TO TRY

Model the effects of intense fire suppression: A potential concern of fire managers arises from the increasing flamability of forests the longer they go without burning (this arises from accumulation of dead plant fuels). If parameters are adjusted such that suppression makes a large fire extremely unlikely, but not impossible, eventually a fire will get out of hand...

Model scenarios in which multiple parameters change: What happens if a new climate system arises that increases both the amount of lightning and the number of rainy days? And what if the temperature (Dry_time) is changing too? To what extent do these different parameters outwheigh one another? Arrival or evolution of new vegetation could have similar effects, changing Fm, Mature_Age, and Lag variables simultaneously.
In nature, such situations often arise, in which the obvious effects of one variable are confounded by (sometimes surprising) influence of another.

EXTENDING THE MODEL

The mechanisms of the model were written to produce "reasonable" results, but don't really reflect the current understanding of mechanisms which really drive wildfire ignition and spread. One might want to try implementing the same parameters (and perhaps others) with more mechanistically accurate mathematical models.

Specific scenarios could be designed for use in a classroom setting, and then the output data (# and area of fires) could be used in a quantitative assessment of the effects of certain parameter combinations.

RELATED MODELS

Fire, Percolation, Rumor Mill

CITING THIS MODEL

To refer to this model in academic publications, please use: Kelly, R. (2009). NetLogo Fire Ecology model. Department of Plant Biology, University of Illinois, Urbana, IL.

In other publications, please use: Copyright 2009 Ryan Kelly. All rights reserved.

ACKNOWLEDGEMENTS

The visual technique for representing fire was borrowed from an existing NetLogo model:

"Fire" Copyright 1997 Uri Wilensky. All rights reserved. See http://ccl.northwestern.edu/netlogo/models/Fire for terms of use.

This model was designed and as part of a National Science Foundation GK-12 fellowship.

Special thanks to Susan Camasta and the 2008-09 Hinsdale South AP Environmental Science classes for testing and evaluation of this model as a teaching aid.

QUESTIONS AND COMMENTS

Please send questions and comments to: rkelly AT life DOT illinois DOT edu

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